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Bappenas Visits UGM to Learn About Digital Transformation and AI for Its Macro Intelligence Hub

Yogyakarta, September 4, 2026 — The Ministry of National Development Planning/National Development Planning Agency (Ministry of PPN/Bappenas) conducted a working visit and benchmarking session at Universitas Gadjah Mada (UGM) to learn about the use of Artificial Intelligence (AI), as well as the development and management of dashboards.

The activity, themed “Strengthening Knowledge Management, Digital Technology Utilization, and Dashboard Development,” took place at Multimedia Room 1, 3rd Floor, North Wing of UGM’s Central Building, Bulaksumur.

The visit forms part of preparations by the Deputy for Macro Development Planning at Bappenas to develop the Macro Intelligence Hub (MIH) and an internal dashboard for the Deputy’s Office. The Bappenas delegation, consisting of staff from work units responsible for knowledge and data management as well as dashboard development, was welcomed by UGM’s Digital Transformation Bureau (Biro Transformasi Digital/BTD).

In an official request letter sent by the Secretary of the Deputy for Macro Development Planning, Ewin Sofian Winata, the visit was intended to enable Bappenas to learn directly from an institution with experience in digital technology and data management, making UGM an important reference for its digital transformation efforts.

Four Years of UGM’s Digital Transformation Journey

During the discussion, the UGM team, led by the Head of the Digital Transformation Bureau, presented the university’s digital transformation journey over the past four years. The presentation covered the development and structuring of enterprise architecture, the development of data dashboards, the adoption of AI and agentic AI, as well as flagship research initiatives with direct impact on society.

One of the key insights shared with the Bappenas delegation was that the core challenge in developing dashboards and AI systems lies not simply in the data or technology, but in business processes.

For this reason, UGM did not move directly into developing AI systems. Instead, the university began by structuring its Enterprise Architecture during the first 1.5 to 2 years of its transformation journey.

“One hundred motorcycles are not simply one hundred motorcycles; they represent one hundred instances of the process of parking a motorcycle,”

the UGM team explained, illustrating why business processes must be properly understood before digital systems are built.

This early investment resulted in four major components: business processes, data, applications, and technology. Thousands of business processes across UGM have since been mapped, providing a foundation for the development and integration of subsequent digital systems.

From Intelligent Dashboards to Agentic AI

Building on this foundation, UGM presented a range of systems that have already been developed and are currently in operation, including:

  • Intelligent Dashboard, developed in collaboration with the Ministry of Communication and Digital Affairs (Komdigi). The system crawls social media and mass media content and applies AI-based sentiment analysis to help detect emerging issues at an early stage.
  • Service Queue System, developed by UGM’s internal team with the assistance of AI for technical development and now operating as part of UGM’s service delivery.
  • AgenDKI, an agentic AI platform that provides shared access to AI tokens and subscriptions, enabling staff to build their own AI agents or dashboards without having to wait for the IT team’s development ticket queue.
  • Hermes, a general-purpose AI agent platform that supports a range of activities, including coding assistance, research, and server management.
  • Agentic Visual Applications, covering applications such as CCTV-based people counting and anomaly detection, library document digitization—from scanning and conversion to AI-based querying—and automated meeting minute-taking.
  • Automated SDG and Key Performance Indicator (IKU) Reporting, in which AI automatically maps campus news and activities to relevant SDG indicators and IKU, reducing the need for previously manual reporting processes.
  • Indonesian-Language AI Models, with further development toward regional languages. These models are designed to better address Indonesian and local contexts than general-purpose global AI models.

Throughout the development of these systems, the UGM team emphasized a key principle: AI is intended to reduce technical and repetitive workloads, not to replace people.

Flagship Research with Real Societal Impact

Beyond internal digital systems, UGM also presented several flagship research initiatives that have delivered tangible benefits to society.

In the area of disaster management, UGM has developed spatial data analysis capabilities covering disaster-point mapping, identification of passable and impassable routes, evacuation locations, and support for automated emergency response.

UGM also showcased its smart agriculture initiatives, including agricultural monitoring and automation systems that have been implemented in several regions.

In the health sector, UGM presented a health screening device developed as a continuation of technology originally developed during the COVID-19 pandemic. The technology has begun to be deployed in remote and outermost regions of Indonesia.

Data generated from health examinations is planned to be transmitted to UGM’s data center, enabling the university to establish regional data records and gain a broader picture of health conditions across different areas.

The UGM team noted that one of the main challenges in implementing this system is internet connectivity in remote areas. To address this challenge, UGM is exploring partnerships with industry players that have extensive network coverage to support data transmission from these regions.

Governance Principles: Unified Reporting and Dashboards That Tell a Story

The discussion also highlighted several data and system governance principles implemented at UGM, including single source of truth and unified reporting.

Under the single-source-of-truth principle, trusted and validated data is established as primary data and serves as a reference for other units. This approach helps reduce duplication and discrepancies across different systems and reporting processes.

The principle of unified reporting means that reporting is managed through a single platform and channel, while thematic dashboards can still be developed according to the specific needs of individual units.

Responding to a question from Bappenas leadership about whether dashboards merely display data or also support decision-making, the UGM team emphasized that a good dashboard should generate insights that drive decisions and action, rather than simply displaying figures without providing meaningful context for decision-makers.

Visualization design, they explained, should be developed to “tell a story”—helping users understand not only what has changed in the data, but also the factors behind those changes.

Regarding regulation, the UGM team shared that discussions with Komdigi over the past semester indicate that there are no major obstacles to the use of AI within government institutions. This is supported by an existing legal framework, alongside ongoing efforts to develop AI-related codes of ethics and regulations.

Another principle emphasized by the UGM team when presenting innovations to partners and university leadership was that “there must be something tangible to demonstrate first.” Working prototypes or tangible results should be presented before moving into deeper discussions about broader implementation and collaboration.

Follow-Up: Bappenas to Develop Its Own Prototype Within a Month

At the end of the visit, the head of the Bappenas delegation expressed appreciation to the Head of UGM’s Digital Transformation Bureau and the UGM team for the presentation and insights, which were considered relevant for the development of the Macro Intelligence Hub and the data management ecosystem within the Deputy for Macro Development Planning.

As a follow-up, Bappenas plans to develop its own dashboard and AI utilization prototype, with a target of presenting the initial results at a subsequent meeting approximately one month later.

The UGM team has also been invited to return and present a more mature version of its systems while continuing knowledge sharing and collaboration between the two institutions.

“We start from ourselves, and we have to start,”

Bappenas representatives said, reflecting on the growing importance and inevitability of AI adoption within government institutions.

The visit underscores UGM’s role not only as an educational institution, but also as a learning and collaboration partner for government institutions in developing data governance, digital transformation, dashboards, and artificial intelligence that genuinely support evidence-based decision-making.

Tags: SDG 9: Industry, Innovation and Infrastructure · SDG 16: Peace, Justice and Strong Institutions · SDG 17: Partnerships for the Goals

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September 7, 2026 No Comments
AI Joint Center UGM-IOH-NVIDIA
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UGM, Indosat, and NVIDIA Officially Launch AI Technology Center to Advance Indonesia’s AI Innovation

Yogyakarta, August 13, 2026 — Universitas Gadjah Mada (UGM), Indosat Ooredoo Hutchison (Indosat/IOH), and NVIDIA, together with the Ministry of Communication and Digital Affairs (Komdigi), officially launched the UGM Indosat NVIDIA AI Technology Center (NVAITC) at the Gelanggang Inovasi dan Kreativitas (GIK) UGM on Thursday (13/8).

The launch marks the establishment of Indonesia’s first university-based AI technology center, dedicated to advancing artificial intelligence research, innovation, and digital talent development. The center is part of the broader Indonesia AI Center of Excellence (AI CoE) initiative and brings together government, academia, industry, and global technology partners to accelerate applied AI research and develop solutions for Indonesia’s most pressing challenges.

The establishment of NVAITC represents a strategic step in Indonesia’s efforts to move beyond being an AI technology consumer and toward becoming a country that develops, creates, and contributes AI innovations with both national and global impact.

Strengthening UGM’s AI Ecosystem

UGM Rector, Prof. dr. Ova Emilia, Ph.D., said UGM has been committed since 2023 to optimizing the use of AI across education, research, and community engagement. One of the initiatives supporting this commitment is the development of UGM AI Society, which serves as a platform for interdisciplinary collaboration, research, innovation, and knowledge exchange in AI.

“Since 2023, UGM has been committed to realizing a smart university through the optimization of AI in education, research, and community engagement. One of these efforts is the initiation of UGM AI Society,” Ova explained.

According to Ova, AI research at UGM has continued to grow across a wide range of disciplines, including healthcare, agriculture, engineering, social sciences, and the humanities. These efforts include the use of AI in pandemic response, AI ethics, tuberculosis screening and diagnosis support, and smart agriculture.

The multidisciplinary nature of AI research at UGM is also reflected in the involvement of 18 faculties and two schools, with AI research being developed across different academic fields. Ova noted that more than half of student research at UGM is now related to AI in various applications.

Through NVAITC, UGM aims to expand access to advanced AI infrastructure and global expertise while strengthening interdisciplinary research in strategic areas such as healthcare, agriculture, and disaster resilience. The center is also expected to serve as a collaborative space that can be accessed by researchers and talents beyond UGM.

“This is not only for UGM. Universities across Indonesia can use the facilities, collaborate, and participate in these research activities,” Ova said.

From Indonesian Talent to Global AI Innovation

President Director and CEO of Indosat Ooredoo Hutchison, Vikram Sinha, emphasized that Indonesia has significant potential to become a creator of AI innovation.

He said Indonesia’s challenge is not a lack of talent, but unequal access to opportunities, infrastructure, and capabilities needed to develop that talent. For this reason, investment in people, research, and innovation must go hand in hand with investment in technology.

“80% is about people, then comes the platform and technology. Ultimately, people must lead and technology must remain human-centered,” Vikram said following the launch.

He stressed that AI development must ultimately translate into tangible benefits for society, particularly in sectors such as agriculture, healthcare, and education.

“Indonesia cannot remain a country that only consumes. We have to shift,” he said.

For Indosat, the partnership with UGM is therefore not simply about establishing an AI facility, but about creating a long-term ecosystem where research, infrastructure, and talent development reinforce one another.

The collaboration itself has evolved over several stages, beginning with the initiation of organizational governance in July 2025, followed by the signing of a Letter of Intent in early 2026, and culminating in the official inauguration of NVAITC on August 13, 2026.

Indosat has also set an ambitious target to support the development of up to two million AI-ready talents by 2030 through collaborations with UGM and other universities.

Bringing World-Class AI Infrastructure to Indonesian Researchers

Vice President of Solutions Architecture and Engineering at NVIDIA, Marc Hamilton, highlighted the critical role of computing infrastructure in enabling AI research and innovation.

He described an AI Factory as an infrastructure ecosystem that takes data as raw material, processes it using accelerated computing and AI technologies, and turns it into models and applications that generate value.

Indonesia already has a large base of developers and researchers. Hamilton noted that more than 500,000 Indonesian software developers are registered on GitHub, representing significant potential for AI development. However, realizing this potential requires access to high-performance computing, AI models, software, and technical expertise.

Through NVAITC, researchers and students will gain access to NVIDIA’s full-stack AI platform and Indosat’s GPU Merdeka sovereign GPU-as-a-Service platform. The center provides access to enterprise-grade accelerated computing, AI software, pretrained and open models, development frameworks, technical mentorship, training, and opportunities for industry collaboration.

NVIDIA is also making its open AI models and expertise available to Indonesian researchers and institutions, enabling them to build and adapt AI systems for their own needs.

Hamilton emphasized that this approach can help universities and companies develop their own AI capabilities without having to build every component of the AI stack from scratch.

Three Initial AI Projects for Indonesia

NVAITC will initially focus on applied AI research aligned with Indonesia’s strategic priorities. Three projects have been identified as the center’s initial flagship initiatives: eNose-TB, SmartAgri, and Tech4Disaster.

eNose-TB: AI for Accessible Tuberculosis Screening

Developed by researchers at UGM’s Faculty of Medicine, Public Health, and Nursing, eNose-TB is an AI-powered electronic screening technology designed to support tuberculosis detection through breath analysis.

The technology aims to make TB screening more affordable, rapid, and accessible, particularly for communities in remote and underserved areas where specialist expertise and advanced laboratory equipment may not always be available.

Dr. Dian Kesumapramudya Nurputra, M.Sc., Ph.D., Sp.A., lead researcher of the eNose-TB team, said the technology reflects a fundamental principle behind the center: solutions developed in Indonesia should be capable of addressing Indonesian challenges.

“Technology developed in Indonesia can solve Indonesian challenges,” Dian said, adding that access to world-class AI infrastructure and expertise would help accelerate the research toward affordable and accessible healthcare technologies.

SmartAgri: AI for Tropical Agriculture

The second initiative, SmartAgri, combines multimodal AI, edge computing, satellite imagery, sensor data, and local agricultural knowledge to support precision farming.

The system is designed to generate practical recommendations for farmers, including decisions related to irrigation and crop management, with the broader goal of improving agricultural productivity and resilience in Indonesia’s tropical environment.

Tech4Disaster: AI for Disaster Resilience

The third initiative, Tech4Disaster, focuses on disaster preparedness and response through geospatial AI.

The platform is designed to process satellite and sensor data using accelerated computing to improve situational awareness, disaster prediction, preparedness, and emergency response. The technology is particularly relevant to Indonesia, which faces significant risks from earthquakes, volcanic activity, floods, landslides, and other natural hazards.

Together, the three projects demonstrate the intended direction of NVAITC: using AI not simply as a technological experiment, but as a tool to address concrete challenges in healthcare, agriculture, and disaster resilience.

AI Sovereignty and Data Governance

Deputy Minister of Higher Education, Science, and Technology, Prof. Stella Christie, emphasized that AI development must be accompanied by strong data sovereignty.

She warned that Indonesia must ensure its data remains strategically valuable to the country rather than being given away without appropriate consideration of its economic and technological value.

“We may trade our data. We may sell our data in exchange for returns, but we must not simply give that data away”

She also called on NVAITC to establish clear targets and remain focused on solving real problems in Indonesia. In her view, AI centers should not stop at training activities or prototype development, but must anticipate future challenges and produce solutions that can be meaningfully adopted.

“The primary task of an AI center today, above all else, is to anticipate — to anticipate what will happen and when it will happen,” she said.

Stella further emphasized that AI adoption must begin with a clear understanding of the problem being addressed, the appropriate timing for adopting the technology, and the people responsible for operating it, while ensuring that humans remain in control.

AI Sovereignty Does Not Mean Isolation

Minister of Communication and Digital Affairs Meutya Hafid said UGM was selected as a partner after the government explored collaboration with several universities.

UGM ultimately stood out because of its commitment to research, the quality of its scientific work, and its strong track record in innovation.

According to Meutya, NVAITC is an important component of the Indonesia AI Center of Excellence, an initiative led by Komdigi with support from the Ministry of Higher Education, Science, and Technology.

The initiative reflects a broader national strategy to bring together government, universities, industry, and global technology companies to strengthen Indonesia’s AI capabilities.

Meutya also encouraged the use of sovereign cloud approaches, ensuring that critical data and infrastructure remain within Indonesian jurisdiction and meet the country’s security requirements.

However, she stressed that AI sovereignty should not be interpreted as technological isolation.

“AI sovereignty does not mean that Indonesia isolates itself or has to develop all technologies entirely on its own. Collaboration and sovereignty can go hand in hand,” Meutya said.

From Research Center to Long-Term AI Ecosystem

The establishment of NVAITC is also part of a much broader expansion of AI infrastructure in Indonesia.

Indosat is developing a large-scale AI Factory through Zankore, a joint venture involving Indosat, Ooredoo Group, Nokia, and NVIDIA. The project is planned to reach up to 1 gigawatt of AI Factory capacity, with the full-scale development potentially requiring investment of more than US$50 billion. This is a broader infrastructure initiative and is distinct from the NVAITC investment itself.

For NVAITC specifically, Katadata reported that the collaboration involves an initial investment of approximately Rp105 billion, comprising GPU credits and human-capital development. Indosat has also indicated its intention to expand its GPU-credit investment following the development of the center’s initial research outputs.

The broader strategy reflects a shift in how AI infrastructure is being developed in Indonesia: combining sovereign computing capacity, global AI technologies, local datasets, research institutions, and human talent into a connected ecosystem.

Measuring Success by Impact

For Meutya,

the success of NVAITC should not be measured simply by the number of training programs conducted or prototypes developed.

Instead, success should be reflected in the growth of AI talent and competencies, the adoption of research outcomes by society and industry, and the creation of intellectual property and innovations developed in Indonesia.

This perspective aligns with UGM’s ambition for NVAITC to become more than an infrastructure facility. The center is intended to serve as a bridge between research and real-world implementation, connecting Indonesian researchers and students with global expertise, advanced computing infrastructure, industry partners, and opportunities to scale their innovations.

As Ova emphasized, UGM hopes the collaboration will continue to generate innovative AI solutions that benefit Indonesia while contributing to the advancement of global science and technology.

The launch of UGM Indosat NVIDIA AI Technology Center therefore marks not simply the opening of a new facility, but the beginning of a longer-term collaboration to build Indonesia’s capacity to research, develop, deploy, and contribute AI technologies to the world.

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August 18, 2026 No Comments
AI4Disaster
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UGM AI Tech4Disaster Dorong Pemetaan Kondisi dan Kebutuhan Lapangan Pascagempa NTT

Gempa bumi berkekuatan magnitudo 7,7 yang mengguncang wilayah Flores, Nusa Tenggara Timur (NTT), pada Sabtu (15/8) menimbulkan dampak di sejumlah wilayah dan mendorong masyarakat untuk melakukan evakuasi. Gempa yang berpusat di laut sekitar 38 kilometer timur laut Mbay, Kabupaten Nagekeo, tersebut juga sempat memicu peringatan dini tsunami.

Di tengah proses penanganan darurat dan pendataan dampak bencana yang masih berlangsung, UGM AI Tech4Disaster mengajak masyarakat, relawan, dan pihak-pihak yang berada di wilayah terdampak untuk membantu menyediakan informasi kondisi lapangan secara cepat dan terpetakan.

Inisiatif ini merupakan bagian dari UGM Indosat NVIDIA AI Technology Center, yang mengembangkan pemanfaatan kecerdasan buatan, data spasial, dan teknologi digital untuk mendukung ketahanan serta penanganan bencana.

Memetakan Kondisi Nyata di Lapangan

Dalam situasi pascabencana, ketersediaan informasi yang cepat, akurat, dan terlokalisasi menjadi salah satu kebutuhan penting untuk mendukung pengambilan keputusan. Informasi mengenai wilayah yang terdampak, akses yang terputus, lokasi pengungsian, hingga kebutuhan logistik dapat membantu pihak terkait menentukan prioritas penanganan.

Melalui UGM Geoportal, masyarakat yang berada di wilayah terdampak dapat membantu melaporkan kondisi di lapangan, antara lain:

  • Kondisi lapangan, meliputi lokasi terdampak, tingkat kerusakan, akses jalan yang terputus atau sulit dilalui, serta lokasi pengungsian.
  • Kebutuhan logistik, seperti jenis kebutuhan, perkiraan jumlah yang diperlukan, dan lokasi masyarakat atau posko yang membutuhkan.
  • Bukti dan informasi lapangan, berupa foto atau dokumentasi kondisi terkini yang dapat membantu proses verifikasi.

Informasi tersebut dapat disampaikan melalui UGM Geoportal:
UGM Geoportal

Data spasial menjadi penting karena memungkinkan informasi lapangan tidak hanya dikumpulkan sebagai laporan tekstual, tetapi juga ditempatkan berdasarkan lokasi sehingga dapat memberikan gambaran kondisi wilayah secara lebih menyeluruh.

Terhubung dengan Informasi Kebencanaan BNPB

UGM AI Tech4Disaster juga mendorong pemanfaatan informasi kebencanaan secara terintegrasi dengan data dan informasi resmi pemerintah. Salah satu rujukannya adalah sistem informasi kebencanaan BNPB melalui InaRISK, yang menyediakan informasi geospasial terkait risiko dan penanganan kebencanaan.

Dashboard BNPB – Informasi Penanganan Bencana

Integrasi dan keterhubungan informasi tersebut diharapkan dapat membantu membangun gambaran situasi (situational awareness) yang lebih baik, sehingga kebutuhan di lapangan dapat diidentifikasi dan menjadi bahan pendukung dalam koordinasi penyaluran bantuan.

Data dari Masyarakat, Tetap Harus Terverifikasi

UGM AI Tech4Disaster menekankan bahwa setiap informasi yang disampaikan masyarakat perlu mengutamakan akurasi, verifikasi, dan koordinasi dengan pihak berwenang.

Masyarakat yang memberikan laporan diimbau untuk:

  1. Menyampaikan lokasi dan kondisi secara jelas.
  2. Memberikan informasi berdasarkan kondisi yang benar-benar ditemukan di lapangan.
  3. Menyertakan dokumentasi apabila memungkinkan dan aman untuk dilakukan.
  4. Menghindari penyebaran informasi yang belum dapat diverifikasi.
  5. Tetap berkoordinasi dengan BPBD, BNPB, pemerintah daerah, serta posko resmi setempat.

Langkah tersebut penting agar teknologi tidak hanya menghasilkan lebih banyak data, tetapi juga menghasilkan informasi yang dapat dipercaya dan bermanfaat untuk mendukung respons bencana.

AI untuk Memperkuat Ketahanan Bencana

Pemanfaatan data spasial dan kecerdasan buatan dalam penanganan bencana merupakan salah satu fokus Tech4Disaster, sebagai bagian dari pengembangan riset dan inovasi dalam ekosistem UGM Indosat NVIDIA AI Technology Center.

Sebelumnya, Tech4Disaster UGM telah dikembangkan melalui berbagai teknologi, termasuk jaringan sensor dan analitik berbasis AI untuk mendukung pemantauan kondisi bencana. Kolaborasi UGM dengan Indosat Ooredoo Hutchison dan NVIDIA juga diarahkan untuk memperkuat pemanfaatan edge AI, konektivitas, serta teknologi AI dalam menghadapi tantangan kebencanaan.

Dalam konteks gempa NTT, pendekatan tersebut diarahkan untuk memperkuat ketersediaan data lapangan sebagai dasar pengambilan keputusan, khususnya ketika kondisi di lapangan berubah dengan cepat dan akses informasi dapat menjadi terbatas.

Jika Anda berada di wilayah terdampak gempa NTT, bantu kami memetakan kondisi dan kebutuhan di lapangan.

Laporkan kondisi yang Anda temukan melalui UGM Geoportal, sertakan lokasi, kebutuhan, dan dokumentasi apabila memungkinkan.

Satu laporan yang akurat dapat membantu menghadirkan informasi yang lebih jelas tentang kondisi di lapangan.

UGM AI Tech4Disaster
AI for Disaster Resilience
A flagship initiative of the UGM–Indosat–NVIDIA AI Technology Center

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August 16, 2026 No Comments
AI Joint Center UGM-IOH-NVIDIA
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UGM Strengthens Its Artificial Intelligence Ecosystem Through Strategic Collaboration with Indosat and NVIDIA

Yogyakarta, July 27, 2026 – Universitas Gadjah Mada (UGM) continues to strengthen its Artificial Intelligence (AI) ecosystem by fostering multidisciplinary collaboration that connects research, innovation, and technology development to address real-world challenges. This commitment was demonstrated through the UGM AI Seminar 2026, themed “Research with Artificial Intelligence (AI),” held at the Multimedia Hall, UGM Central Office Building, on Monday (July 27).

The seminar brought together researchers, faculty members, students, industry partners, and government representatives to share experiences in applying AI across diverse disciplines while showcasing innovative AI-powered solutions developed by UGM researchers. The presentations demonstrated how AI has evolved beyond a research support tool into practical solutions for law, energy, agriculture, healthcare, and disaster management.

Opening the seminar, Dr. Mardhani Riasetiawan, S.E., Ak., M.T., Head of UGM’s Bureau of Digital Transformation, emphasized that developing a robust AI ecosystem has become one of the university’s strategic priorities to strengthen research capacity, promote multidisciplinary collaboration, and accelerate digital transformation in higher education.

“Last year, we achieved an important milestone with the establishment of the UGM AI Center of Excellence. We were also honored to initiate a strategic collaboration with Indosat Ooredoo Hutchison,” he said.

Dr. Mardhani explained that before the partnership was formalized, teams from Indosat Ooredoo Hutchison and NVIDIA conducted several site visits and comprehensive assessments of UGM’s research infrastructure and institutional readiness. Following these evaluations, UGM was selected to become part of the NVIDIA AI Technology Center (NVAITC) network.

According to him, one of the biggest challenges in AI research is the limited availability of high-performance computing resources required to train and deploy advanced AI models.

“The greatest challenge in AI development has always been computational resources. Through this collaboration, we hope UGM researchers will gain access to significantly greater computing capacity than ever before,” he explained.

Beyond strengthening computational infrastructure, UGM has also launched several strategic initiatives to cultivate its AI ecosystem, including the Artificial Intelligence Talent Factory (AITF) and the establishment of the UGM AI Faculty Members Network, which brings together researchers from various faculties to encourage interdisciplinary collaboration.

Dr. Mardhani highlighted that UGM’s greatest strength lies in its multidisciplinary nature.

“What we value most in this collaboration with NVIDIA is UGM’s multidisciplinary character. Our approach goes beyond technical aspects by actively involving researchers from social sciences, humanities, health sciences, agriculture, engineering, and many other disciplines.”

He added that the university aims to develop an AI ecosystem collaboratively.

“We want to build this ecosystem together because no significant achievement can ever be accomplished alone.”

One of the key outcomes of the collaboration with Indosat Ooredoo Hutchison and NVIDIA is the provision of Artificial Intelligence Infrastructure as a Service (AI Infrastructure as a Service – AIaaS). Through this initiative, researchers gain free access to enterprise-grade GPU computing infrastructure for developing, training, and deploying AI models without the need to invest in their own high-performance computing facilities.

This shared infrastructure has significantly accelerated experimentation, model development, and multidisciplinary AI research across the university.

The seminar featured numerous research projects that have benefited from this AI infrastructure.

From the Faculty of Law, Dr. Rimawati, S.H., M.Hum., demonstrated how Artificial Intelligence is transforming legal research by assisting researchers in searching legal regulations, analyzing court decisions, and organizing legal references. Tasks that previously required weeks of manual work can now be completed within hours. Nevertheless, she emphasized that AI should remain a research assistant rather than replacing legal scholars, as every AI-generated output must still be verified against authoritative legal sources.

Another presentation by Prof. Dr. Ir. Ferian Anggara, S.T., M.Eng., IPM., from the Faculty of Engineering, showcased the application of machine learning in mineral and energy exploration. By integrating geological datasets with AI-based predictive modeling, researchers can identify mineral potential more efficiently, reducing both exploration time and operational costs.

One of the seminar’s major highlights was presented by Dr. Andri Prima Nugroho from the Faculty of Agricultural Technology, who introduced UGM’s AI-driven Smart Agriculture initiatives.

His research integrates machine learning, computer vision, Internet of Things (IoT) technologies, environmental sensors, drones, multispectral imagery, and weather data to transform agricultural data into intelligent recommendations that support precision farming.

The technologies showcased include the SIPASI Smart Irrigation System, AI-powered greenhouses, plant factory technologies, crop health monitoring using unmanned aerial vehicles, fertilizer decision-support systems, and AI-based knowledge management platforms. According to Dr. Andri, AI in agriculture must be developed based on local conditions and through close collaboration among researchers, farmers, government agencies, and industry partners to produce solutions that are both scientifically sound and practically applicable.

The seminar also presented the development of an AI-powered electronic nose (e-Nose) platform, which combines advanced sensor technologies with artificial intelligence algorithms to recognize complex odor patterns automatically. Supported by the AI infrastructure provided through the collaboration with Indosat Ooredoo Hutchison and NVIDIA, this technology has the potential to support rapid disease screening, healthcare diagnostics, food quality assessment, and industrial monitoring.

Another research showcase came from Dr. Nur Mohammad Farda of the Faculty of Geography, who introduced Tech4Disaster, a GeoAI platform integrating geospatial technologies, IoT, satellite imagery, drones, big data, and artificial intelligence into a comprehensive disaster management ecosystem.

The platform supports the entire disaster management cycle—from mitigation and preparedness to emergency response and post-disaster recovery—by transforming large volumes of spatial data into actionable real-time intelligence. Applications demonstrated during the seminar included rapid disaster mapping, AI-based damaged-building detection using deep learning, participatory needs mapping, and geospatial disaster information portals that assist emergency response agencies in making faster and more informed decisions.

The seminar clearly illustrated that Artificial Intelligence at UGM has progressed far beyond being merely a research tool. Across multiple disciplines—including law, engineering, agriculture, healthcare, and disaster management—AI is now enabling innovative solutions with tangible societal impact.

Through its strategic collaboration with Indosat Ooredoo Hutchison and NVIDIA, UGM is not only strengthening its computational capabilities but also accelerating the development of impactful AI research. The availability of AI Infrastructure as a Service (AIaaS) has become a critical foundation for enabling multidisciplinary AI innovation while reinforcing UGM’s commitment to building a collaborative, sustainable, and globally competitive AI ecosystem that contributes to Indonesia’s digital transformation.

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July 27, 2026 No Comments
AITF KOMDIGI dan UGM
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UGM Students Develop an AI Platform to Monitor Public Issues and Viral Content

A team of students from Universitas Gadjah Mada (UGM) participating in the Artificial Intelligence Talent Factory (AITF) Batch 1 2026, a collaborative program between Indonesia’s Ministry of Communication and Digital Affairs (Komdigi) and Universitas Gadjah Mada, has successfully developed an artificial intelligence (AI)-powered platform for monitoring public issues and digital conversations.

The platform automatically monitors online news and social media through data crawling, classifies emerging issues, analyzes public sentiment, maps media narratives, and generates daily briefs to support data-driven decision-making. Beyond processing text, the system is also capable of analyzing images and audio, presenting insights through an interactive dashboard, and providing an AI-powered chatbot to assist users in interpreting the collected information.

One of the student developers, Gevan, explained that the idea originated from the growing challenges of the digital economy, where the volume, diversity, and speed of information shared across social media have made manual monitoring and analysis increasingly difficult.

“Through this platform, monitoring public conversations, analyzing issues, and developing communication strategies can be carried out more quickly, systematically, and based on data,” he said during the Demo Day and Graduation of the Artificial Intelligence Talent Factory 2026 Batch 1, held at the Multimedia Room, UGM Central Building, on Wednesday (June 24).

According to Gevan, the platform follows an integrated workflow. It begins by identifying trending topics through Google Trends and Trends24 while also allowing users to input custom keywords based on specific monitoring needs. A keyword generation module then expands these keywords to drive the crawling engine, which collects multimodal content—including text, images, and audio—from online news portals and social media platforms.

The collected data is subsequently enriched using AI technologies. Images are processed through image captioning, while audio content is automatically converted into text using speech-to-text technology. The system then performs automatic labeling, sub-issue categorization, and sentiment analysis before storing the processed data in a centralized database and presenting it through an interactive monitoring dashboard.

Beyond monitoring, the dashboard groups related articles, generates concise summaries using the 5W+1H framework, identifies key stakeholders and their statements, and automatically produces daily briefing documents summarizing the most viral issues from the previous day.

“The platform provides decision-makers with a comprehensive overview of emerging public issues, enabling faster and more informed responses,” Gevan added.

The system is also equipped with an Early Warning System (EWS) that detects sudden spikes in online conversations or issues with the potential to go viral. Leveraging Large Language Models (LLMs), the platform analyzes digital narratives in real time and provides recommendations for proactive communication strategies based on the latest available information.

Meanwhile, Dr. Said Mirza Pahlevi, M.Eng., Head of the Digital Talent Development Center at the Ministry of Communication and Digital Affairs, praised the innovative solutions developed by the AITF participants. He noted that the projects reflect the outcomes of four months of intensive hands-on learning fostered through collaboration among universities, government, and industry.

He expressed his hope that the Demo Day and Graduation would serve not only as a showcase for students’ achievements but also as a forum for constructive discussions on advancing AI adoption in Indonesia.

“The AI solutions presented today demonstrate how artificial intelligence can be leveraged to understand the dynamics of public opinion and support faster, more accurate, and data-driven decision-making,” he concluded.

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June 28, 2026 No Comments
AI Joint Center UGM-IOH-NVIDIA
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Forging Global AI Ties: Strategic Move by UGM, Indosat, and NVIDIA to Build an Applied Research Ecosystem at SNAIC Singapore

SINGAPORE – The Digital Transformation Office (BTD) team of Universitas Gadjah Mada (UGM) recently concluded a strategic mission during an observational study visit to the Singapore Institute of Technology (SIT) from June 10 to 12, 2026. This cross-disciplinary delegation’s visit is part of a strategic initiative under the direction of the Vice Rector for Research, Business Development, and Collaboration of UGM, with the primary mission of following up on the collaborative plans between UGM, Indosat, and NVIDIA to establish a tangible Artificial Intelligence (AI) ecosystem for both industry and society.

The main focus of this observational study was to delve into the operations of the NVIDIA Joint Center at SIT, professionally known as SNAIC (SIT-NVIDIA Artificial Intelligence Centre). Through this visit, the UGM team explored the operational practices of a world-class AI research center, future-ready technological infrastructure management, and implementation strategies for innovation programs that bridge academia with global industry leaders.

Welcomed by Key Figures in Singapore’s AI Ecosystem

Throughout the observational series at the SIT campus, the UGM delegation was welcomed by and engaged in intensive discussions with leading figures and principal researchers driving Singapore’s AI ecosystem. The strategic meeting was directly accompanied by A/Prof. Daniel Wang, Co-director of SNAIC and Director of the SIT Data Science & AI Lab, alongside Ng Aik Beng, Ph.D., Senior Regional Manager at NVIDIA AI Technology Center Asia Pacific South, who brings over two decades of industry expertise.

Also present to enrich the cross-disciplinary technical exchange were top-tier researchers from SNAIC, including Dr. Timothy, a Natural Language Processing (NLP) expert and SUTD alumnus; Dr. Akshita Abrol, a Post-Doctoral Fellow focusing on AI-based speech analysis for diagnostic healthcare; and Isfaque, a Research Engineer specializing in security data analytics, Graph Neural Networks, and Machine Learning.

A Cross-Disciplinary Approach for Real-World Solutions

The quality of the discussions became highly focused on actionable solutions, thanks to the multidisciplinary composition of the UGM delegation. Led by experts in their respective fields, the UGM team comprised Ir. Andri Prima Nugroho, S.T.P., M.Sc., Ph.D. (agricultural informatics expert), Dr. Nur Mohammad Farda, S.Si., M.Cs. (remote sensing expert), dr. Dian Kesumapramudya Nurputra, Sp.A., Ph.D. (pediatric neurology expert), and Muhammad Alif Taufiqurrahman, S.Kom. (Systems Analyst).

The inclusion of experts from diverse backgrounds breaks the traditional stereotype that AI development belongs solely to pure computer scientists. A fascinating synergy emerged during the discussions; for instance, the AI research for medical devices presented by dr. Dian (UGM) found a strong common ground with the diagnostic healthcare research focus of Dr. Akshita (SNAIC). AI applications at UGM are specifically designed to solve concrete problems—ranging from optimizing cutting-edge agriculture, extracting satellite imagery for disaster management and mitigation, to innovating intelligent algorithms to support the precision of pediatric medical devices in hospitals.

Bridging Academia and Global Industry

Through deep observation alongside SNAIC leadership, the UGM delegation studied the three-prong governance model driving the AI center: Industry Enablement (accelerating AI adoption in business), Applied Research & Development (industry-scale applied research), and Talent Development (cultivating job-ready digital talent).

SNAIC demonstrated how a higher education institution transforms from a purely academic approach toward creating direct impact. One prominent example studied was the implementation of the Industrial Doctorate program, where doctoral-level research is fully aligned with industry projects to solve real challenges within the business and operational sectors.

Becoming a Beacon of AI Innovation in Indonesia

The insights gathered from this visit with SNAIC’s leadership and researchers will serve as a vital foundation for UGM in formulating an academic-industry collaboration model with Indosat and NVIDIA in Indonesia. This strategic partnership aims to build a center of excellence in AI that functions as a national beacon of innovation. This upcoming AI center will not only coordinate scattered internal research across the university but also foster solid trust from both industry and government to accelerate technological leaps in the country.

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June 14, 2026 No Comments
AITF KOMDIGI dan UGM
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AI Talent Factory Workshop 3 Strengthens AI Solution Development for Public Communication and Media

YOGYAKARTA – The Ministry of Communication and Digital Affairs (Komdigi), through the Human Resources Development Agency for Communication and Digital Affairs, in collaboration with Universitas Gadjah Mada (UGM), organized the third Artificial Intelligence Talent Factory (AITF) Workshop on 2–3 June 2026 at the Multimedia Room 1, UGM Central Building, Yogyakarta.

The workshop is part of the broader AI Talent Factory program, which aims to strengthen Indonesia’s digital talent ecosystem by enhancing competencies in Artificial Intelligence (AI). The program serves as a collaborative learning platform that encourages participants to develop innovative AI solutions relevant to industry and public sector needs.

During the third workshop, participants presented the progress of their Phase 3 projects and received feedback from mentors, technical tutors, and subject-matter experts. The event also focused on Demo Day preparation, participant performance evaluation, and refinement of solution development strategies.

Over the course of two days, participants engaged in intensive discussions and project presentations centered on public communication and media use cases. The showcased solutions included a Monitoring and Evaluation Dashboard, an Issue Narrative Model, a Communication Strategy Model, and an AI solution based on Retrieval-Augmented Generation (RAG) and a Minimum Viable Product (MVP).

The workshop provided participants with opportunities to assess the maturity of their projects, identify technical and implementation challenges, and formulate action plans for the final demonstration stage.

The collaboration between Komdigi and UGM is expected to cultivate adaptive, critical, and solution-oriented AI talents while fostering innovations that support public communication needs and strengthen information resilience in Indonesia.

Workshop 3 marks an important milestone in ensuring that each team develops AI solutions that are not only technically robust but also capable of delivering tangible impact for society and Indonesia’s ongoing digital transformation.

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June 7, 2026 No Comments
AITF KOMDIGI dan UGM
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Komdigi x UGM – AI Talent Factory (AITF) Batch 2 — 2026

Program intensif kecerdasan artifisial oleh Kementerian Komunikasi dan Digital, resmi berkolaborasi dengan Universitas Gadjah Mada.

Tentang Program AITF adalah program pelatihan AI intensif yang diselenggarakan oleh Pusat Pengembangan Talenta Digital Komdigi bersama Universitas Gadjah Mada. Program ini mencakup tiga Learning Path: Data Science, Deep Learning, dan LLM Practitioner — diakhiri dengan Demo Day dan Graduation.

Surat resmi dan panduan lengkap dapat diakses melalui: surat-resmi-aitf-komdigi-batch-2

Konversi SKS: 6 – 20 SKS (menyesuaikan kebijakan)
Durasi: ±4–6 bulan (Agustus – Desember 2026)

Link Pendaftaran: ugm.id/daftaraitf2

Link Learning Path: digitalent.komdigi.go.id atau klik disini

MAHASISWA

  • S1 tahun ke-3/4 atau Mahasiswa Magister
  • Prodi: AI, Data Science, Informatika, Teknik Komputer, Statistik, atau sejenisnya
  • Menguasai Python & Machine Learning dasar
  • Berpengalaman dengan Git, GPU/Cloud
  • Komitmen penuh ±4–6 bulan
  • Portofolio AI/Data Science (diutamakan)

DOSEN

  • Dosen/Tutor Teknis di UGM
  • Wajib menyelesaikan LP3: LLM Practitioner
  • Ikuti seleksi internal UGM

Timeline Lengkap

Seleksi Mahasiswa

  • 25 Mei 2026 – Pembukaan pendaftaran
  • 25 Mei – 6 Jul – Pendaftaran & pengerjaan LP1: Data Science
  • 13 – 17 Jul – Ujian Seleksi (Proctoring)
  • 27 – 31 Jul – Interview peserta
  • 5 Agustus – Pengumuman hasil seleksi
  • 10 Agustus – Konfirmasi peserta/kampus

Seleksi Dosen

  • 25 Mei – 6 Jul – Pendaftaran & pengerjaan LP3: LLM Practitioner
  • 13 – 31 Jul – Seleksi internal UGM
  • 5 Agustus – Pengumuman hasil seleksi

Pelaksanaan Program

  • 14 Agustus – Kick-off AITF UGM Batch 2
  • 14 Agt – 4 Des – Pelaksanaan program penuh
  • 24 Agt – 24 Sep – Belajar mandiri LP2: Deep Learning + Workshop 1
  • 29 Sep – 29 Okt – Belajar mandiri LP3: LLM Practitioner + Workshop 2
  • Week 1 November – Workshop 3
  • Week 4 November – Demo Day
  • Week 1 Desember – Graduation/Kelulusan
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June 4, 2026 No Comments
AITF KOMDIGI dan UGM
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Indonesia Launches AI Talent Factory Workshop to Build the Next Generation of AI Developers

Mastery of Artificial Intelligence (AI) is no longer merely a technological matter — it has become a defining factor in global geopolitics. Nations that lead in AI development hold significant influence over the shape of the world order. Recognizing this, the Indonesian Government is actively cultivating digital talent among the younger generation, steering them toward building AI technologies that serve both industry and national development.

“Going forward, the workforce will be a combination of humans and digital humans. This is both a challenge and an opportunity for us to prepare talents who are not only capable of using technology, but developing it,” said Deputy Minister of Communication and Digital Affairs Nezar Patria at the opening of the Artificial Intelligence Talent Factory (AITF) Workshop, held on Friday, April 17.

PROBLEM-FIRST APPROACH

Nezar emphasized the importance of a problem-first mindset in AI development — prioritizing solutions to real-world challenges. He identified sectors such as healthcare, food, energy, and fisheries as strategic fields ripe for AI-driven innovation. Beyond technical skills, he also stressed the value of non-technical competencies including critical thinking, ethical judgment, and human-AI interaction design. “AI development must remain human-centered and must not produce negative impacts,” he stated.

AI AS A TOOL, NOT A SHORTCUT

Arief Setiawan Budi Nugroho, Vice Rector for Planning, Assets, and Information Systems, underscored that AI’s value depends entirely on the human operating it. “AI is a tool. How beneficial it is depends on the person behind it. Without a strong foundational understanding, AI use can actually lead to misinterpretation,” he explained.

He called on students to serve as agents of change — not passive consumers of technology. “Students must be agents of change, not just technology users. The use of AI must always be accompanied by critical thinking,” he affirmed.

INTO THE AGE OF AGENTIC AI

The workshop featured expert Prof. Dr. Ir. Esther Irawati Setiawan, a Google Developer Expert in AI and Cloud Computing, who discussed the rapid evolution from conventional machine learning toward large language models (LLMs) and the emerging era of Agentic AI. “We have entered the era of Agentic AI, where systems don’t just respond — they reason, plan, and execute tasks,” she explained.

She also cautioned against over-reliance on LLMs, noting that conventional machine learning approaches are often more efficient for specific use cases. “LLMs are trending, but not every solution requires an LLM. We need to match the tool to the need to avoid overkill.”

ABOUT THE WORKSHOP

The AITF Workshop, co-organized by Komdigi and Universitas Gadjah Mada, engaged 98 students and 28 mentors from UGM, Universitas Brawijaya, and Institut Teknologi Sepuluh Nopember (ITS). Sessions included progress discussions, use case mentoring, and expert lectures — all aimed at deepening participants’ understanding of AI and developing practical, AI-based solutions.

The collaboration aims to cultivate adaptive, critical, and solution-oriented digital talent capable of contributing to Indonesia’s digital transformation — particularly in strengthening public communication and information resilience nationwide.

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April 19, 2026 No Comments
Berita terbaru
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The GCI World program from the University of Tokyo

Hello everyone 👋

Here’s an interesting opportunity for those interested in Data Science & AI.

The GCI World (April 2026) program from the University of Tokyo (in collaboration with the Matsuo–Iwasawa Lab) is now open and available to students worldwide 🌏

✨ Highlights:

  • 💻 Online (conducted in English)
  • 💰 FREE for the basic course
  • 🎓 Open to active university students

📅 Application deadline: April 2, 2026 (14:00 UTC)
📚 Classes begin: April 8, 2026

This program is shared by JICA Indonesia

🔗 More information & registration:
https://weblab.t.u-tokyo.ac.jp/en/lecture/gci/

If you’re interested in AI/Data Science, this is a great opportunity 🙌

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March 31, 2026 No Comments
AI Joint Center UGM-IOH-NVIDIA
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UGM Develops AI Solutions for Disaster Mitigation through the Tech4Disaster Program

Yogyakarta – Universitas Gadjah Mada (UGM), through its Faculty of Geography team, has introduced an artificial intelligence (AI)-based innovation under the AI for Climate program through the Tech4Disaster use case—an integrated solution for disaster and landslide mitigation.

This program is driven by Indonesia’s high vulnerability to various natural disasters, which necessitates a transformation from reactive disaster response approaches to more proactive, integrated, and data-driven systems.

Technology-Based Disaster Management Transformation

Through the Integrated Smart Disaster Management approach, the Tech4Disaster solution integrates several advanced technologies, including:

  • Geospatial Technology (GIS)
  • Internet of Things (IoT)
  • Big Data
  • Artificial Intelligence (AI)

This integration enables environmental signals to be processed into real-time spatial information that supports fast and accurate decision-making.

The Tech4Disaster solution is built on a system architecture consisting of four main components:

  1. Sense (IoT)
    Real-time data collection through field sensors, drones, and community reports.
  2. Store (GeoBigData)
    Centralized storage for large-scale spatial, historical, and demographic data.
  3. Think (GeoAI)
    Utilization of machine learning for:
    • Disaster risk prediction
    • Automated damage classification
  4. Act (Geospatial/GIS)
    Visualization through dynamic maps, decision-making dashboards, and evacuation route optimization.

This approach enables faster response times while supporting long-term, data-driven planning.

Participatory Mapping and Rapid Response

One of the key innovations in this program is participatory mapping (needs mapping), which allows communities to directly report field conditions through digital platforms.

Additionally, the system supports:

  • Rapid mapping based on satellite imagery
  • Mapping of flood- and landslide-affected areas
  • Real-time monitoring dashboards

As a result, aid distribution and evacuation processes can be carried out more accurately and effectively.

Advanced Analytics with AI

In terms of analytics, Tech4Disaster leverages deep learning models such as Prithvi-EO-2.0, which is based on the Vision Transformer architecture, to detect potential landslides from satellite imagery.

This model is trained using thousands of polygon datasets derived from manual interpretation, enabling it to:

  • Identify landslide-prone areas
  • Detect environmental changes
  • Support post-disaster analysis

Case Study and Implementation

The implementation of this solution has been carried out in several regions across Indonesia, including Aceh (Bener Meriah Regency) as a case study area.

Through the use of satellite data and AI, the team successfully:

  • Mapped affected areas
  • Identified building damage
  • Compared pre- and post-disaster conditions

Towards Climate-Resilient Communities

The Tech4Disaster program aims to:

  • Reduce disaster risks and casualties
  • Accelerate rehabilitation processes
  • Support sustainable spatial planning
  • Build climate-resilient communities

This initiative also aligns with the achievement of the Sustainable Development Goals (SDGs), particularly in disaster resilience and sustainable development.

By integrating AI, geospatial technologies, and community participation, UGM—through Tech4Disaster—demonstrates that technology can be a key enabler in addressing the challenges of climate change and future disasters.

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March 24, 2026 No Comments