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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal ULTIMA InfoSys Jurnal Ilmiah Sistem Informasi
Sari, Muh. Masri
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Computer Science & IT

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Utilizing a Data Warehouse to Analyze the Effects of Sales Type, Product Type, and Price on Net Profit in an F&B Outlet Putri, Allegra Aretha; Aurelia, Nadine; Veronika, Vera; Wiriady, Fransiska Eka Putri; Kurniawan, Rido Dwi; Sari, Muh. Masri
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4513

Abstract

This research aims to investigate how sales type, product type, and price influence net profit in an F&B outlet using a Data Warehouse system. A quantitative method was applied by integrating daily transaction data into a Data Warehouse architecture built through an Extract, Transform, and Load (ETL) process, allowing the data to be more organized and easier to analyze. To address heteroskedasticity and obtain more reliable coefficient estimates, multiple linear regression with HC3 robust standard errors was used. The results show that price and sales type have a significant and positive effect on net profit, while product type shows mixed effects depending on the category. The regression model, with an R² value of 0.994, indicates that these three variables explain most of the variation in net profit. Overall, the findings highlight how structured data processing through a Data Warehouse can support profitability analysis and improve decision-making in F&B operations.
The Influence of Operating Costs on Revenue and Cash Balance: Data Warehouse Analysis Anthony, Revan; Ernesto, Brian; Prasetya, Jonathan Ansell; Subrata, Kenneth Marchelino; Sari, Muh. Masri; Kurniawan, Rido Dwi
Jurnal Ilmiah Sistem Informasi Vol. 5 No. 1 (2026): January: Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/qwahp256

Abstract

Penelitian ini menganalisis pengaruh biaya operasional terhadap omzet dan saldo kas pada sebuah perusahaan Food and Beverage (F&B) sektor minuman dengan memanfaatkan data warehouse sebagai basis integrasi dan pengolahan data keuangan. Permasalahan utama yang diangkat adalah kurangnya pemanfaatan data keuangan bulanan secara analitis sehingga hubungan antara biaya operasional, kinerja penjualan, dan kondisi saldo kas belum terpantau dengan baik. Tujuan penelitian ini adalah menguji pengaruh biaya operasional terhadap omzet dan saldo kas, serta menilai hubungan antara omzet dan saldo kas melalui analisis statistik yang terstruktur. Data penelitian terdiri dari 21 observasi bulanan periode Januari 2024–September 2025, yang diperoleh dari laporan keuangan internal dan diproses ke dalam data warehouse melalui prosedur extract–transform–load (ETL). Analisis dilakukan menggunakan statistik deskriptif, uji asumsi klasik, regresi linier sederhana, dan korelasi Pearson dengan bantuan Microsoft Excel dan IBM SPSS Statistics. Hasil penelitian menunjukkan bahwa biaya operasional berpengaruh positif dan signifikan terhadap omzet, menandakan bahwa pengeluaran operasional yang bersifat produktif masih mampu mendorong peningkatan pendapatan. Sebaliknya, biaya operasional berpengaruh negatif dan signifikan terhadap saldo kas sehingga dapat menurunkan likuiditas bila tidak dikendalikan. Adapun hubungan antara omzet dan saldo kas bersifat positif sedang namun belum signifikan, sehingga peningkatan omzet tidak selalu langsung meningkatkan saldo kas akhir. Penelitian ini menegaskan pentingnya pengendalian biaya operasional dan pemanfaatan data warehouse untuk menghasilkan informasi keuangan yang lebih terstruktur serta mendukung keputusan manajerial pada usaha F&B.
Analisis Faktor Penentu Kategori Harga Rumah di Kota Tangerang Selatan Menggunakan Web Crawling dan Regresi Logistik Multinomial Muhammad Iyad Irviansyah; Claresta, Vanesya; Anabella, Marshanda; Saputra, Muhammad Rifqo; Kurniawan, Rido Dwi; Sari, Muh. Masri
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 9 No. 3 (2025): IKRAITH-INFORMATIKA Vol 9 No 3 November 2025
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to identify factors influencing housing price categories in South Tangerang City using digital data obtained through web crawling from online property platforms. The research addresses how physical attributes, facilities, and location affect the probability of a house belonging to a specific price category. Data were automatically collected via web crawling, and after data cleaning and validation, 1,264 housing records were retained for analysis. Housing prices were classified into four categories—Economical, Standard, Luxury, and Exclusive—using a quartile-based approach. Multinomial Logistic Regression (MLR) was applied to model relative probabilities based on land area, building area, number of bedrooms, number of bathrooms, garage availability, and district location. The results indicate that land area, building area, number of bathrooms, and garage availability significantly influence housing price categories, while the number of bedrooms and district location are not significant after controlling for physical characteristics. The model is statistically significant and achieves a classification accuracy of 64.8%. The main contribution of this study lies in the integration of web crawling and Multinomial Logistic Regression for housing price classification, offering a data-driven framework to support housing market analysis and automated property valuation systems.
Co-Authors Anabella, Marshanda Anthony, Revan Aurelia, Nadine Claresta, Vanesya Ernesto, Brian Muhammad Iyad Irviansyah Prasetya, Jonathan Ansell Putri, Allegra Aretha Rido Dwi Kurniawan Saputra, Muhammad Rifqo Subrata, Kenneth Marchelino Veronika, Vera Wiriady, Fransiska Eka Putri