Farida Sibuea, Head of the Working Group for Strategy, Data Analysis, and Information Utilisation, Data and Information Centre, Ministry of Health, Indonesia

1. How do you use your role to ensure that technology and policy are truly inclusive?  

Inclusivity is measured by how far technology can reach and empower citizens in frontier, outermost, and disadvantaged regions (3T). Our strategy relies on standardisation and mandates.

First, we require the use of a Single Data Standard (FHIR) across all healthcare facilities integrating with SATUSEHAT. This ensures that data from a remote community health centre is valued just as much as data from major hospitals. No more data silos, and no “second-class citizens” in our digital systems. 

Second, we implement an Offline-First policy for Electronic Medical Records (EMR), enabling health workers to record data even in areas with limited or no connectivity. The data synchronises with SATUSEHAT once a connection is available, ensuring digitalisation continues regardless of infrastructure constraints.

2. What’s a moment in your career when you saw firsthand how technology or a new policy changed a citizen’s life for the better? 

The most memorable moment was during the Covid-19 crisis. In a period filled with uncertainty, we built a centralised data system and dashboard to monitor daily cases, transmission trends, mortality, and hospital capacity in real time. 

We displayed these analytics transparently on a national dashboard that guided decision-making for the Task Force, local governments, and the public in determining social distancing measures. 

This technology enabled Indonesia to implement movement restrictions in a measured, adaptive, and evidence-based manner. It was a clear example of how Big Data and technology can directly influence government policy to protect citizens’ lives. 

3. What was the most impactful project you worked on this year, and how did you measure its success in building trust and serving the needs of the public?  

The most impactful project this year is strengthening the National Vital Statistics through the pilot of the Medical Certificate of Cause of Death (MCCD). Indonesia has long struggled with obtaining accurate cause-of-death data, even though it is essential for health policymaking.  

The project aims to build a uniform and centralised reporting system nationwide. We ensure the coding of causes of death is internationally standardised (ICD-10/11) and integrated into the National Vital Statistics System, which will eventually serve as the country’s official vital statistics dataset. 

Accurate data allows us to design precise and predictive policies. For example, determining whether deaths in a region are caused by communicable or non-communicable diseases, and directing budgets accordingly.  

It also strengthens public trust, as the epidemiological data we share is valid, verifiable, and nationally consistent. 

4. What was one unexpected lesson you learned this year about designing for real people? 

Data quality has become the “new bottleneck” in Digital Transformation. We have solved data fragmentation through SATUSEHAT.

Our current challenge is overcoming Garbage In, Garbage Out (GIGO). We realised that AI innovation and precision policymaking will never succeed if data from thousands of health facilities is inconsistent or unclean. 

This requires a renewed focus on Data Quality Assurance and reskilling health workers to become Data Quality Controllers and Data Annotators. Data quality is now a shared responsibility between the Data and Information Centre and clinical staff. 

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5. We hear a lot about AI. What's a practical example of how AI can be used to make government services more inclusive and trustworthy?  

AI makes services more inclusive by addressing human bias and equalising access to specialist expertise.

First, AI can bring specialist capabilities to 3T regions. For example, AI-powered Tuberculosis (TB) screening can read X-rays in remote clinics with speed and accuracy close to that of a radiologist in Jakarta. 

Second, trust is built through transparent and auditable AI models, aligned with our Health AI Committee’s guidelines. Citizens trust the system when diagnosis decisions are supported by valid data and fair algorithms. 

6. How are you preparing for the next wave of change in the public sector? What new skill, approach, or technology are you most excited to explore in the coming year?  

Preparation focuses on strategic talent development and long-term data security. 

In terms of skills, it is important to master Data Governance, the Personal Data Protection Law, FHIR standards, and the fundamentals of Large Language Models (LLM), which will support health workers in the future. 

Technologically, I am looking forward to the adoption of Post-Quantum Cryptography (PQC) in the public sector to safeguard sensitive data for decades to come, and the rise of Indonesian-language LLMs that can serve the public more personally and accountably. 

7. What advice do you have for public sector innovators who want to build a career focused on serving all citizens?  

My advice reflects both mindset and practical approaches. 

Mindset and Vision 

• Understand the problem, not just technology. Do not chase hype or gadgets. Focus on the real issues faced by citizens or inefficiencies within bureaucracy. The most valued innovations in the public sector are those that improve service quality for the people. 
• Have a grit. The public sector moves more slowly than startups. You will face bureaucracy, budget shifts, and mindset change. Success here requires patience, resilience, and negotiation. 

Practical Approaches 

• Master the “plumbing”or the underlying infrastructure. Before creating appealing applications, learn about the data standards and foundational systems of your institution. Build integrated solutions on top of existing foundations, not isolated systems. 
• Prioritise data standardisation so that information can be exchanged nationally and become a valuable asset for broader policymaking. 
• Start responsible pilot projects: small, fast, but compliant with legal and ethical requirements. These builds trust among stakeholders. 

8. Who inspires you to build a more inclusive and trustworthy public sector?  

My inspiration does not come from a single individual, but from the spirit of solidarity and resilience shown by frontline health workers. These include midwives, nurses, and doctors in 3T Puskesmas who continue serving despite fragmented data, limited connectivity, and complex bureaucracy.

Their dedication motivates us at Pusdatin to build SATUSEHAT infrastructure worthy of their service, systems that remove administrative burdens and trust the data they input. 

9. If you had an unlimited budget, what would your dream project be?  

My dream project is achieving quantum-secured data sovereignty and national AI fairness. 

This includes a National PQC Infrastructure to protect SATUSEHAT patient data and ensure confidentiality for the next 100 years, regardless of advances in computing. 

It also includes an Ethical AI Centre to train bias-free AI models that deliver equal, fair, and accurate diagnoses for every ethnic and geographic group in Indonesia. 

10. Outside tech, what excites you the most? 

Outside technology, my focus is on maternal and child health programmes. 

To me, technology is merely a tool. The success of health digital transformation is not measured by how fast an API runs, but by how quickly Indonesia’s stunting rate decreases and how safely mothers can give birth. 

Maternal and child health is a humanitarian barometer. Success in this area is the ultimate proof that our technology has had an inclusive and meaningful impact on human lives.