PENERAPAN SUPPORT VECTOR REGRESSION DALAM MEMPREDIKSI KEBUTUHAN BAHAN BAKU PADA CV. XYZ

Nisaul Husna, . (2026) PENERAPAN SUPPORT VECTOR REGRESSION DALAM MEMPREDIKSI KEBUTUHAN BAHAN BAKU PADA CV. XYZ. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

CV. XYZ is a palm oil processing company that uses loose oil palm fruits as its primary raw material. Fluctuations in raw material usage and unintegrated operational records have caused purchasing plans to remain insufficiently supported by data. This study applies Support Vector Regression (SVR) using a multi-output regression approach to predict raw material usage for the next three days and integrate the model into a web-based application. The dataset consists of 394 daily records from June 1, 2025, to June 29, 2026. The model uses 10 input features, namely beginning inventory, incoming raw materials, production output, and raw material usage on the current day and the previous six days. Hyperparameter optimization was performed using grid search with a time-series cross-validation scheme. Based on the lowest cross-validation MAE of 12,228.9836, the best model used the Polynomial kernel with a regularization parameter C of 10, epsilon of 0.05, gamma of 0.01, degree of 3, and coef0 of 1.0. The model achieved MAPE values of 6.6396% for the “H+1” target, 15.3602% for the “H+2” target, and 24.2327% for the “H+3” target. The model was integrated using React.js, FastAPI, and PostgreSQL. All 34 black-box testing scenarios passed, while UAT achieved an average score of 95%. The results indicate that the system can support inventory monitoring and raw material purchasing planning.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2210511055] [Pembimbing 1: Jayanta] [Pembimbing 2: Nur Hafifah Matondang] [Penguji 1: Dr. Noor Falih] [Penguji 2: Kharisma Wiati Gusti]
Uncontrolled Keywords: inventory, multi-output regression, prediction, raw materials, Support Vector Regression.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: NISAUL HUSNA
Date Deposited: 29 Jul 2026 13:54
Last Modified: 29 Jul 2026 13:54
URI: http://repository.upnvj.ac.id/id/eprint/52144

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