Nadya Nurasia Koimah, . (2026) PENERAPAN SISTEM PREDIKSI STOK BARANG BERBASIS WEB PADA TOKO SRC SAIFUL. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
SRC Saiful Store requires more structured inventory data management and sales transaction recording since the previous recording process was still performed manually. This condition may cause several problems, such as inaccurate stock information, difficulties in checking product availability, and ineffective determination of restock requirements. Therefore, this research develops a web-based system to support inventory management through transaction recording, product data storage, stock monitoring, and prediction of required inventory levels based on sales data. The application development process applies the Waterfall approach, which includes several stages from requirement analysis to system evaluation. In addition to system development, this study evaluates Linear Regression and Random Forest algorithms using R-Squared (R²) and Mean Absolute Error (MAE) as performance metrics. Based on the testing results, Random Forest achieved the best performance with an R² value of 0.9885 and an MAE of 2 units, making it the prediction model implemented in the application. User evaluation through User Acceptance Testing (UAT) obtained a score of 93.5%, which is categorized as very good. These results indicate that the system successfully supports inventory management and assists the decision-making process more effectively compared to manual methods.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2210511034] [Pembimbing 1: Musthofa Galih Pradana] [Pembimbing 2: Nurul Afifah Arifuddin] [Penguji 1: Neny Rosmawarni] [Penguji 2: Kharisma Wiati Gusti] |
| Uncontrolled Keywords: | web-based system, inventory stock prediction, inventory management, Linear Regression, Random Forest |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | NADYA NURASIA KOIMAH |
| Date Deposited: | 15 Jul 2026 09:15 |
| Last Modified: | 25 Aug 2026 15:23 |
| URI: | http://repository.upnvj.ac.id/id/eprint/50753 |
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