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All Journal Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
Beng, Jap Tji
Universitas Tarumanagara, Jakarta
Computer Science & IT

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Design of a Data Mart for Optimizing Product Sales Analysis at PT. X Samantha, Velline; Beng, Jap Tji; Trisnawarman, Dedi; Tiatri, Sri; Salsabila, Tasya Mulia; Sefira, Fasia Meta; Zahro, Tiara; Latupono, Sania Alikha Rahmadira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3158

Abstract

With the advancement of technology, companies can now efficiently manage and analyze their data, providing valuable insights that support better business decisions. PT. X is one such company that wants to leverage this capability to optimize its sales data analysis. Therefore, the goal of this study is to design an effective data mart. During the development process, we used Kimbal's Nine-Step Methodology alongside the ETL (extract, transform, load) process to ensure the data was accurately extracted, transformed, and loaded into the data mart. The outcome of this research is a data mart and star schema tailored to PT. X specific needs. Testing results showed that query execution time increased by 40% and data accuracy improved by 80%. Report generation time was also optimized, resulting in a process that was 83% faster. These results demonstrate how a well-structured data mart can improve decision-making efficiency and data reliability. 
Analytical Hierarchy Process Method of Prosthetic and Orthotic Materials for Patient Needs Nurkholiza, Rahmiyana; Beng, Jap Tji; Wasino, Wasino; Tiatri, Sri; Sam, Toong Hai; Anolin, Ann G.; Castillo, Sheryll Ann M.; Dinatha, Vienchenzia Oeyta Dwitama
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3159

Abstract

This study highlights the importance of optimising assistive devices for people with disability, as the law says in Law No. 8 of 2016. Ligar Mandiri Prosthetics and Orthopaedics Clinic offer related services, where choosing the right materials is getting more complicated because of fast tech advances and lots of options like carbon fibre, plastic, and titanium. This study aims to develop a Decision Support System (DSS) to assist practitioners in selecting materials based on quality, cost, and production time criteria. The alternatives evaluated include local, semi-imported, and imported materials. Using the Analytic Hierarchy Process (AHP) method, the analysis shows that imported materials received the highest ranking (0.54708), followed by local materials (0.24157) and semi-imported materials (0.21155). The DSS developed in this study has enhanced the accuracy, efficiency, and transparency of decision-making, thereby supporting practitioners in providing effective and reliable prosthetic and orthotic solutions. 
Designing a Data Mart at the Indonesian Psychological Healthcare Center Using Pentaho Angela, Octarifa; Beng, Jap Tji; Trisnawarman, Dedi; Tiatri, Sri; Sam, Toong Hai; Guanco, Rhalf Jayson F.; Nurkholiza, Rahmiyana; Dinatha, Vienchenzia Oeyta Dwitama
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3153

Abstract

Critical data is essential for organisational success, providing essential information for decision-making. This study focuses on the Indonesian Mental Health Centre (IndoPsyCare), which utilises data to improve service performance. The research aims to design a data mart to support analytical needs by transforming the Online Transaction Processing (OLTP) database into Online Analytical Processing (OLAP). This design follows Kimball's Nine-Step Approach and integrates the Extract, Transform, Load (ETL) process. Data was collected from August 2023 to August 2024 through interviews and electronic documentation. The system was implemented using Microsoft SQL Server Management Studio 18 and Pentaho Data Integration. The resulting data mart uses a star schema with fact and dimension tables tailored to stakeholder needs, particularly in appointment analysis. Findings indicate that the data mart facilitates efficient access, targeted analysis, and improved query performance, thereby supporting IndoPsyCare's decision-making and overall service optimisation. 
Co-Authors Angela, Octarifa Anolin, Ann G. Castillo, Sheryll Ann M. Dinatha, Vienchenzia Oeyta Dwitama Guanco, Rhalf Jayson F. Latupono, Sania Alikha Rahmadira Nurkholiza, Rahmiyana Salsabila, Tasya Mulia Sam, Toong Hai Samantha, Velline Sefira, Fasia Meta Tiatri, Sri Trisnawarman, Dedi Wasino, Wasino Zahro, Tiara