Informatics graduate from Telkom University focused on database-driven web architecture and tabular deep learning. I build full-stack applications with Next.js, TypeScript, and PostgreSQL, paired with explainable clinical prediction research using TabNet.
I am an Informatics graduate from Telkom University (GPA 3.71 / 4.00) with a dual focus on full-stack web engineering and applied machine learning research. My work centers on turning administrative and analytical requirements into maintainable, production-ready software systems.
During my internship at the Ministry of Marine Affairs and Fisheries (Kementerian Kelautan dan Perikanan / KKP), I engineered the Dashboard Kepegawaian P3K, an internal personnel management platform built with Next.js, TypeScript, Prisma, and PostgreSQL. In research, I authored an experimental study on heart failure mortality prediction applying TabNet, transfer learning, and SHAP, published in IEEE ICIMCIS 2025.
I prioritize structural discipline, database integrity, and practical machine learning models that provide actionable interpretability. Whether building administrative web tools with Role-Based Access Control or training neural architectures on imbalanced clinical records, the objective is always system reliability and real-world utility.
Architecting type-safe web applications with Next.js, React, TypeScript, Prisma ORM, and PostgreSQL. Focused on relational schema design, role-based workflows, and server-side data fetching.
Developing tabular deep learning pipelines using TabNet, transfer learning architectures, and SMOTE for severe clinical class imbalance, evaluated with SHAP explainability.
Building administrative management platforms with granular Role-Based Access Control (RBAC), multi-criteria filtering, geospatial verification, and structured data reporting.
Internal personnel management dashboard developed during my internship at the Ministry of Marine Affairs and Fisheries (KKP) to centralize employee administration, promotion tracking, and geospatial attendance monitoring.
Full-stack attendance platform with GPS validation, attendance workflows, leave management, document uploads, and bilingual support.
Mortality risk prediction in heart failure patients using transfer learning-based TabNet architectures and explainable AI with SHAP, published in IEEE ICIMCIS 2025.
Academic task management and reminder system built with a decoupled FastAPI backend, SQLAlchemy ORM, Pydantic schema validation, and JWT authentication, paired with a React and Next.js frontend.
End-to-end web application engineering with strict TypeScript type safety, relational schema modeling in PostgreSQL, and server-side data workflows.
Tabular deep learning pipelines, transfer learning architectures, medical class imbalance mitigation with SMOTE, and explainable AI with SHAP.
Decoupled backend API development with FastAPI, token-based authentication protocols, schema validation, and version-controlled environments.
I am available for full-stack software engineering roles, applied machine learning projects, and technical research collaborations. Feel free to get in touch directly via email or connect through my profiles.