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All Journal Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika METIK JURNAL Jurnal Ilmiah Pengabdian dan Inovasi Jurnal Publikasi Teknik Informatika (JUPTI) Kolaborasi: Jurnal Hasil Kegiatan Kolaborasi Pengabdian Masyarakat
Ahmad Hudawi AS
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika

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Implementasi GridSearch dalam Meningkatkan Kinerja Model Support Vector Regresion (SVR) utuk Prediksi Penjualan Produk (Studi kasus : Meubel Rohman Jaya): Implementation of GridSearch to Improve the Performance of the Support Vector Regression (SVR) Model for Predicting Product Sales at Rohman Jaya Furniture Ahmad Baidowi Eko Fitra Firmanda; Ahmad Hudawi AS; Abu Tholib; Juvinal Ximenes Guterres
EXPLORE IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Vol 16 No 1 (2024): Jurnal Explore IT Edisi June 2024
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v16i1.5042

Abstract

In the era of digitalization, product sales forecasting plays a crucial role for companies in estimating future demand. Meubel Rohman Jaya, a furniture business established since 2010, requires accurate predictions to optimize stock availability with the variety of products they produce. This research aims to forecast furniture product sales using the Support Vector Regression (SVR) algorithm with GridSearch optimization. Sales data of 11 furniture products over 30 months (January 2021 - June 2023) were processed through data collection and preprocessing. Modeling was performed using SVR without optimization and SVR with GridSearch optimization to obtain the best parameters. Predictions were generated and then evaluated using the Mean Absolute Percentage Error (MAPE) metric. The results showed that SVR without optimization achieved a MAPE of 40.39%, while SVR with GridSearch achieved a MAPE of 0.45%, indicating a significant increase in accuracy. GridSearch optimization has proven effective in improving prediction performance and is highly recommended for implementation in forecasting product sales at Meubel Rohman Jaya.
Co-Authors Abdul Karim Abu Tholib Ahmad Baidowi Eko Fitra Firmanda Dimas Ilham Maulana Asmarakandi Juvinal Ximenes Guterres Muhammad Afandi Muhammad Naufal Said Agil Asy’ari Yaqin, Moh. Ainol