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All Journal INTECOMS: Journal of Information Technology and Computer Science
Nurkholiza, Rahmiyana
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Computer Science & IT

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Rancang Bangun Dashboard Appointment Pada Layanan Kesehatan Mental X Dengan Metode Prototyping Angela, Octarifa; Nurkholiza, Rahmiyana; Lawrence, Valerie; 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.v7i6.12873

Abstract

Data berkontribusi secara signifikan dalam kesinambungan suatu perusahaan. Data berpengaruh besar melaluiinformasi yang disediakannya. Untuk itu penting bagi suatu perusahaan dapat mengelola serta memanfaatkandata yang tersedia. Demikian pula pada layanan kesehatan mental X yang mengoptimalkan layanannya melaluipemanfaatan data secara efektif. Maka dari itu, penelitian ini bertujuan untuk merancang sebuah dashboardsehingga dapat digunakan dalam memahami, monitoring, menganalisis data, dan mendukung pengambilankeputusan. Perancangan dashboard dilaksanakan dengan menggunakan metode prototyping yang terdiri dariempat tahapan yaitu communication, quick plan and modeling quick design, construction of prototype, dandeployment delivery and feedback. Data divisualisasikan sehingga menghasilkan sebuah dashboard denganmenggunakan tools Microsoft Power BI. Dengan dashboard yang dirancang, data dapat lebih mudah dipahamisehingga mendukung dalam pengambilan keputusan untuk meningkatkan kinerja layanan. Pengambilankeputusan dilakukan berdasarkan Key Performance Indicator (KPI). Adanya dashboard juga menghasilkansuatu informasi yang berguna bagi proses bisnis melalui data yang ada.Kata Kunci: Dashboard, Data, Key Performance Indicator (KPI), Metode Prototyping, Microsoft Power BI
Analisis Pemilihan Material Prosthetic Dan Orthotic Menggunakan Metode Simple Additive Weighting Pada Klinik X Nurkholiza, Rahmiyana; Lawrence, Valerie; Limbor, Ellen Gabriel; Wasino, Wasino; 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.v7i6.13139

Abstract

Pemilihan material dalam bidang prostetik dan ortotik sangat penting untuk memastikan kenyamanan dan efektivitas alat bantu medis bagi pasien. Penelitian ini mengusulkan penggunaan metode Simple Additive Weighting (SAW) untuk mendukung pengambilan keputusan dalam pemilihan material. Metode ini memungkinkan evaluasi berbagai kriteria yang relevan, termasuk kebutuhan pasien, aktivitas fisik, kondisi medis, serta preferensi individu. Dengan merancang sebuah sistem pendukung keputusan berbasis pembelajaran mesin, proses seleksi material dapat dioptimalkan sehingga lebih responsif terhadap parameter individual pasien. Studi ini menganalisis beberapa jenis material prosthetic dan orthotic serta bagaimana metode SAW dapat membantu dalam menyusun peringkat material terbaik. Hasil penelitian menunjukkan bahwa material import memiliki peringkat pertama dalam material terbaik serta integrasi teknologi ini dapat meningkatkan akurasi dan efisiensi dalam pengambilan keputusan, memberikan solusi yang lebih dipersonalisasi, dan memperbaiki kualitas hidup pasien. Kata Kunci: Disabilitas, Simple Additive Weighting, Prosthetic, Orthotic
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.
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.
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 Angela, Octarifa Dedi Trisnawarman Desi Arisandi Dinatha, Vienchenzia Oeyta Dwitama Hutagaol, Alice Shizuka Jap Tji Beng Lawrence, Valerie Limbor, Ellen Gabriel Lunzaga, Ele Salsabila, Tasya Mulia Sefira, Fasia Meta Sri Tiatri Wasino Wasino Wijaya, Angeline Carolina