Over the past three years after completing my master’s degree, I have worked on a variety of projects across research, innovation, and competitive initiatives such as hackathons and exploration projects. These projects include completed works and ongoing developments, reflecting my continuous exploration of data integration, knowledge engineering, and AI-enabled information systems.
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🧪 Research Projects
Construction of establishment directory knowledge graph using the Neo4j graph database
This study explores the integration of establishment directory data in Indonesia using a knowledge graph approach implemented in Neo4j. By overcoming the structural limitations of RDBMS-based integration, knowledge graphs enable more flexible representation of entities and relationships, allowing the discovery of meaningful patterns that support industry mapping, regional economic planning, and data-driven decision-making. The study also notes remaining challenges in data collection and transformation, which present opportunities for further research and methodological refinement.
Silver-Dash: The Vulnerability of Indonesia’s Elderly
A comprehensive analysis of the elderly population, presenting current data, future projections, and in-depth insights. It is designed to assist policymakers, researchers, and healthcare professionals in understanding the trends, challenges, and opportunities related to the aging population.
🧩 Innovation Projects
SIGER LAMPUNG: An integrated application platform for BPS
A web-based platform for socio-economic statistics (DTSEN) equipped with an LLM-based question-answering module, individual decile verification tools, and automated news scraping to enrich contextual analysis.
TAPIS: An integrated application platform for BPS
An integrated web application for BPS employees across Lampung Province. The platform consolidates multiple organizational applications into a single access point, including tools for performance reporting, incoming and outgoing correspondence, assignment and travel orders, and other administrative services.
🏆 Competition Projects
SIMPUL: Monitoring and Analytics Development Information System for Local Administrative
Bridge the gap between data and decisions — an intelligent analytics platform specifically designed to accelerate local development in Lampung Province. This platform integrates diverse infrastructure data (including Official Statistics and Big Data) to visualize gaps in basic public services in real time. Powered by Artificial Intelligence, SIMPUL can recommend priority local areas that are most in need of intervention, helping governments design more targeted and measurable development policies and programs. Developed by the SIMPUL Team, participated in the Lampung Province Ideathon, and reached the Top 25 of innovations.
SEHAT: Smart Enabler for Health Assistance and Recommendation
SEHAT is an Agentic AI and Generative AI–based system that serves as a digital assistant for JKN participants to find suitable doctors or hospitals based on their needs, location, and service preferences. It integrates official BPJS data with external big data sources (e.g., Google Maps, Alodokter) and applies Aspect-Based Sentiment Analysis (ABSA) to evaluate service aspects such as cleanliness, friendliness, and waiting time, while allowing users to search and interact naturally through a conversational chatbot. Developed by the MIRAE Team, participated in the BPJS Healthkathon, and reached the Top 50 of innovations.
CERDAS: CASN Expert Recommendation and Decision Assistance System
The CASN recruitment system via SSCASN still faces challenges such as mismatches between applicant profiles and job positions, limited workforce planning analysis, and insufficient adaptation to the characteristics of newer generations of workers. To address these issues, CERDAS, an AI-based system with NLP-driven job recommendation and predictive analytics for workforce demand forecasting, built on a cloud and microservices architecture, enhances CASN recruitment to be more intelligent, efficient, transparent, and data-driven. Developed by the MIRAE Team, participated in the BKN Hackathon, and reached the Top 100 of innovations.
🔀 Exploration Projects
BPJS-QA: AI-Driven knowledge assistant for BPJS to enhance public service information access
BPJS-QA is a system that uses Retrieval-Augmented Generation (RAG) to answer questions about BPJS. It retrieves relevant information from a knowledge base and uses it to generate accurate responses.
🛠️ Ongoing Projects
🛠️ Ongoing Projects
Elevating spice data as a knowledge graph: A pilot study
Onto-KBLI: A semantic ontology for standard classification of Indonesian business fields
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