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Journal : INTECOMS: Journal of Information Technology and Computer Science

DATA MART DESIGN FOR Y CLOTHING STORE SALES Wijaya, Angeline Carolina; Beng, Jap Tji; Arisandi, Desi; Tiatri, Sri; Dinatha, Vienchenzia Oeyta Dwitama; Nurkholiza, Rahmiyana; 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/qr7rg481

Abstract

The data mart design for Y Clothing store aims to integrate scattered sales data to simplify analysis and speed up business decision making. Using the Kimball Nine-Step method and ETL process, sales transaction data from 2019 to 2023 is managed in a star schema. As a result, these data marts enable faster and more accurate analysis, identifying customer purchasing patterns, sales trends and promotional effectiveness. Implementation of this data mart increased inventory management efficiency by 15% and reduced sales report generation time from hours to minutes. However, challenges such as significant resource allocation for initial implementation and a learning curve for employees slowed down the maximum benefit gain somewhat. However, overall, these data marts contribute greatly to improved business decisions and more effective sales strategies. Keywords: Data Mart, Y Clothing Store, Kimball Nine-Step Method, ETL Process, Star Schema.
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
Co-Authors Aeda Andianturi Taim Agustin, Dinda Aisya Putri Handayani Alivia Fitriani Amanto Alivia Fitriani Amanto Angela, Octarifa Angelina, Ellen Anisa Husnul Khotimah Arumsari, Chysanti Arvelia Yoshianne Anggie Ayesha Desfitrianie Bianca Debby Bryan Riyanto Calvinus, Yohanes Caroline, Angeline Claudia Fiscarina Claudia Fiscarina Daniel Daniel Davin Sebastian Dedi Trisnawarman Desella Chandra Desella Chandra Desella Chandra Desi Arisandi Desi Arisandi Desi Arisandi Dewi, Ezra Shandra Dinatha, Vienchenzia Oeyta Dwitama Elysia Putri Elysia Putri, Elysia Endah Setyaningsih Eoh, Vivin Bolu Ery Dewayani Eugenius Edsel Barito Fateema, Sabrina Ayesha Febynola Tiara Salsabilla Felicita Mauli Firliana, Dira Fitriya, Febby Nurul Fransisca I. R. Dewi Fransisca Iriani Roesmala Dewi Fransisca Pranata Gregorio, Keanen Han, Hansen Hartinah Dinata Henry Candra Hervanny Zisli Hetty Karunia Tunjungsari Ho, Stevanie Hutagaol, Alice Shizuka Ikishima, Faura I. Ivan Juan Jonathan Jap, Bernard Amadeus Jaya Juliana, Sarah Gracyntia Juniarto Salim Kamila, Nadia N. Kelvin Julian Tannius KENI KENI Larasati, Kirey Latupono, Sania A. R. Lawrence, Valerie Layla Adila Ramadhani Limbor, Ellen Gabriel Lunzaga, Ele Lusiana, Fenny Lygia Teresa Timoria Natan Marcydiaz, Andrew Haikal Margareta Margareth Natalia Marwahdi, Azahra Putri Matondang, Mikhayla Illyna Mei Ie Mei Ie Michelle Friscilia Michelle Friscilia Michellen, Kyren Mira Bella Mirabella Mirabella Mirabella Muhammad Irfan Pradana Muhammad Nashir Mutiara, Maitri Widya Nadya Aliwarga Nadya Aliwarga, Nadya Nagm, Fouad Nina Perlita Nina Perlita Nina Perlita Norita Margareth Berta, Norita Margareth Novario Jaya Perdana Nurkholiza, Rahmiyana Octarifa Angela Oeyta, Vienchenzia Oktovianus Irvan P. Tommy Y. S. Suyasa P. Tommy, Y. S. Suyasa Pandumpi, Shania Krisan Putri, Erika Ardya Mesia Putri, Melzha E. Putri, Tifani Anasya Qadriah, Sekar Aurannisa Ramdhani Rahmiyana Nurkholizah Ramadhan, Asya A. P. Rasji Rasji Riani Riani Ricky Sanjaya Rita Markus Idulfilastri Rita Markus Idulfilastri Rizky Eka Putra Salsabila, Tasya Mulia Samantha, Velline Sania Alikha Rahmadira Latupono Sari, Emilia Sefira, Fasia Meta Setiawati, Winni Shalsa Dea Purnama Sharon Yosephine Sihotang, Fitriana Nursinta Silky Goswara Silky Goswara Solikhah, Nafiah Sri Tiatri Sri Tiatri Sri Tiatri Sri Tiatri Sri Tiatri Stefania Morin Stenly Handy Wijaya Stivanus, Celvin Sugeng Astanggo Sumantri, Paramitha Mudita Tasya Mulia Salsabila Thalia Syahrunia Suci Ardhia Tony Tony Valensia Audrey Rusli Vania Yori Wakano Vincent Suryawidjaja Vivien H. Wangi Wasino Wasino Wasino Wasino Wasino Wijaya, Angeline Carolina Yuniawati, Elisa Ika Zahra Shafira ZAHRO, TIARA Zheng, Margareta