Implementation of Data Warehouse and Business Intelligence for AIDS Cases in West Java

Abstract

This study discusses the design of a data warehouse for analyzing AIDS cases in West Java using the Nine Step Methodology. The background of this research is the high prevalence of AIDS cases in West Java during 2018–2019 and the need for an integrated data management system to support data-driven health policies. The objective of this study is to design and implement a data warehouse capable of integrating data from various dimensions, such as region, age group, gender, and year, to support epidemiological analysis of AIDS. The methodology employed includes stages such as data extraction from various sources, data transformation to enhance quality, and data loading into a PostgreSQL-based data warehouse system. The study also utilizes the ETL (Extract, Transform, Load) process to ensure the integrity of the processed data. The results indicate that the designed data warehouse successfully maps the distribution of AIDS cases based on relevant dimensions. Key findings reveal that the productive age group (25–49 years) and males have the highest number of cases, with Bandung City being the region with the most cases. The contribution of this study is the provision of a data platform that supports evidence-based decision-making while identifying high-risk regions and groups for more effective health interventions. Limitations include the scope of data limited to two years and the absence of predictive analytics features. Future research is recommended to expand the time coverage and integrate predictive analysis to enhance the effectiveness of health policy