Salsabila, Tasya Mulia
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Journal : INTECOMS: Journal of Information Technology and Computer Science

Perancangan Data Mart Untuk Manajemen Data Penjualan Pada Kedai Kopi X Di Jakarta Salsabila, Tasya Mulia; Caroline, Angeline; Marcydiaz, Andrew Haikal; Trisnawarman, Dedi; Beng, Jap Tji
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 6 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i6.12875

Abstract

Data yang kompleks dengan volume besar dan format bervariasi memiliki peran penting bagi suatu perusahaan. Semakin kompleksnya data transaksi penjualan, kebutuhan sistem manajemen data yang efisien untuk memberikan wawasan yang cepat dan akurat. Penelitian ini bertujuan merancang data mart untuk menganalisis data penjualan, mendukung pengambilan keputusan yang lebih baik. Data dari Online Transaction Processing diubah menjadi Online Analytical Processing untuk memudahkan pengolahan, penyimpanan, dan analisis secara efisien. Penelitian ini, menggunakan metode Nine-step Kimball untuk perancangan data mart dan mengimplementasikan dalam star schema dengan melakukan proses Extract, Transform, Load. Pengumpulan data dilakukan melalui wawancara dengan data penjualan dari tahun 2023 hingga 2024, disimpan dalam Database Management System menggunakan Microsoft SQL Server Management Studio 18. Hasil dari penelitian ini, terbentuknya data mart dengan star schema, yang terdiri dari tabel fakta dan tabel dimensi. Perancangan data mart untuk management dapat mengoptimalkan pemrosesan data penjualan pada kedai kopi x dalam pengambilan keputusan. Kata Kunci: Data Mart, Extract Transform Load (ETL), Penjualan, Nine-step Kimball
Proses Desain Pada Perancangan Dashboard Pemantauan Penjualan Produk PT. XYZ Samantha, Velline; Salsabila, Tasya Mulia; Wijaya, Angeline Carolina; Trisnawarman, Dedi; Beng, Jap Tji
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 6 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i6.12917

Abstract

Perancangan desain dashboard penjualan menjadi komponen krusial dalam mendukung efisiensi analisis data dan pengambilan keputusan di perusahaan. Proses ini melibatkan integrasi berbagai elemen visual yang mencakup penggunaan Data Analytics, Decision Support System (DSS), serta desain Human Machine Interface (HMI). Desain dashboard yang efektif tidak hanya mengutamakan penyajian data secara komprehensif, tetapi juga memfokuskan pada aspek visual, seperti pemilihan warna, tata letak, dan format tampilan yang intuitif. Penelitian ini bertujuan untuk merancang dashboard pemantauan penjualan produk di PT. XYZ yang berorientasi pada Key Performance Indicator (KPI) perusahaan, dengan penekanan pada desain user-friendly. Desain yang baik akan memudahkan pengguna dalam memahami data dan meningkatkan efektivitas pemantauan performa penjualan.
DESIGNING A DATA WAREHOUSE TO OPTIMIZE THE HOTEL BOOKING MONITORING DASHBOARD Hutagaol, Alice Shizuka; Beng, Jap Tji; Wasino, Wasino; Tiatri, Sri; Lunzaga, Ele; Salsabila, Tasya Mulia; Nurkholiza, Rahmiyana
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 5 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/rr4rhx45

Abstract

In the rapidly growing tourism industry, efficient data management is crucial for strategic decision-making. This study focuses on the design and implementation of a data warehouse to optimize the monitoring dashboard for hotel bookings on an application X, an online hotel booking platform, a product of PT. XYZ. Along with the increase in volume and complexity of booking transaction data, there is an urgent need for an efficient data management system that can provide insights quickly and accurately. To address this, the study uses Kimball's Nine-Step Methodology and implements a star schema, which simplifies complex data relationships and improves query performance. The ETL (Extract, Transform, Load) process is applied to ensure accurate extraction, transformation, and loading of data from operational systems into the data warehouse, thereby guaranteeing consistency and accuracy for analysis. Tools such as SQL Server Management Studio 2022, Visual Studio 2019, and SQL programming were used to develop the data warehouse and the star schema. The results of the study show that the star schema, with a central fact table and surrounding dimension tables, effectively optimizes data processing and query speed. The system is scalable, allowing for future expansion without significant changes, and provides a robust platform for business intelligence. Recommendations include developing dimension analysis, optimizing the ETL process, and integrating predictive analytics to enhance decision-making. Overall, this study provides a structured data warehouse design that significantly improves PT. XYZ's ability to process, analyze, and visualize hotel booking data for strategic decision-making. Keywords: Data Warehouse, Extract Transform Load (ETL), Dashboard, Nine-Step Kimball, SQL.
DESIGNING A DATA MART FOR OPTIMIZING CLOTHING SALES AT C STORE Limbor, Ellen Gabriel; Beng, Jap Tji; Arisandi, Desi; Tiatri, Sri; Nurkholiza, Rahmiyana; Salsabila, Tasya Mulia; Dinatha, Vienchenzia Oeyta Dwitama
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 5 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/7k3f3443

Abstract

Data plays a crucial role in supporting strategic decision-making, particularly in the retail sector like C Store. To enhance sales performance and understand purchasing trends, an effective system such as a data mart is needed. This study aims to design a data mart that can be used to analyze sales data at C Store to support data-driven decision-making. The methodology used is the nine-step Kimball approach in data mart design. The ETL (Extract, Transform, Load) process is used to manage sales transaction data collected from the period of 2021 to 2024. The result of this study is a data mart with a star schema, consisting of fact and dimension tables, enabling the analysis of sales performance based on product categories and time. The implementation of this data mart is expected to assist C Store in managing data efficiently, supporting strategic decision-making, and improving business operational effectiveness. Keywords: Data Mart, Kimball's Nine-Step Process, Clothing Sales.
DESIGNING A DATA WAREHOUSE FOR AIRLINE TICKET SALES AT PT ABC Qadriah, Sekar Aurannisa Ramdhani; Beng, Jap Tji; Arisandi, Desi; Nagm, Fouad; Salsabila, Tasya Mulia; Zahro, Tiara; Dinatha, Vienchenzia Oeyta Dwitama
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 5 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/hfhqv835

Abstract

The high demand for airline ticket purchases in Indonesia and ticket sales being one of the important assets for companies in the aviation industry. PT ABC requires a system that can effectively manage this data to support business analysis and strategic decision-making. This research aims to design a data warehouse that can integrate airline ticket sales data, enabling more efficient data storage, processing, and analysis. The approach used in the design of this data warehouse is the star schema, which consists of one main fact table and several dimension tables. The fact table contains ticket sales transaction data, while the dimension tables include information about time, flight routes, airlines, and customers. This research provides a primary contribution in the form of a data warehouse design that integrates airline ticket sales data, enabling faster and more accurate analysis. The resulting business impact includes increased operational efficiency, more accurate data-driven decision-making, and the ability to monitor sales trends in real-time through interactive dashboards. With this data warehouse, PT ABC can reduce data analysis time and improve the accuracy of sales trend predictions. Keywords: Data warehouse, Star Schema, PT ABC plane ticket sales, Business Intelligence.
DESIGN OF A DATA WAREHOUSE FOR CUSTOMER SEGMENTATION PREDICTION AT PT X Lawrence, Valerie; Beng, Jap Tji; Wasino, Wasino; Tiatri, Sri; Nurkholiza, Rahmiyana; Salsabila, Tasya Mulia; Sefira, Fasia Meta
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 5 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/he6dx426

Abstract

With the rapid growth of the tourism industry, particularly within the hotel and airline sectors, understanding customer behavior and segmentation has become crucial for driving strategic decisions. However, customer segmentation in these sectors often faces challenges due to the complexity of transactional data and varying service demands. This study addresses these challenges by designing a data warehouse using a Star Schema architecture, aimed at integrating hotel and airline booking data from 2023 to 2024. The methodology follows the Nine-Step Kimball approach, coupled with the Extract, Transform, Load (ETL) process, to transform transactional data from OLTP systems into a format suitable for Online Analytical Processing (OLAP). The data warehouse features fact and dimension tables that support in-depth analysis of customer segments, booking trends, and performance across service categories and time periods. Key findings show that the data warehouse significantly improves the ability to segment customers based on booking behavior, seasonality, and service preferences, leading to more effective decision-making. This integrated system provides a robust foundation for data-driven strategies, allowing businesses in the tourism industry to optimize customer targeting, improve service offerings, and enhance operational efficiency. Keywords: Data Warehouse, Star Schema, ETL, Hotel Booking, Flight