PERANCANGAN SISTEM PREDIKSI HARGA BAHAN POKOK DI PASAR ANTAR PROVINSI DI INDONESIA DENGAN MENGGUNAKAN PENDEKATAN MACHINE LEARNING

Keisha Maura Putri, . (2025) PERANCANGAN SISTEM PREDIKSI HARGA BAHAN POKOK DI PASAR ANTAR PROVINSI DI INDONESIA DENGAN MENGGUNAKAN PENDEKATAN MACHINE LEARNING. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

This study aims to design a price prediction system for essential food commodities across Indonesian inter-provincial markets using a machine learning approach. The Random Forest algorithm is used to predict daily prices based on historical data from SP2KP. The system is developed as an interactive web application using Streamlit, displaying price predictions and direction of change (increase, decrease, or stable) through interface elements. The model was tested with several data split scenarios, with the 90:10 split yielding the best results (R² = 97.58%, RMSE = 3062.54, MAE = 1295.34, MAPE = 2.84%). These results indicate that the model has a high level of accuracy and can be relied upon to provide insights into trends in food commodity prices. Although the system still has limitations, it is expected to support decision-making and policy development for distribution planning and food price stabilization in Indonesia.

Item Type:	Thesis (Skripsi)
Additional Information:	[No.Panggil: 2110512112] [Pembimbing 1: Didit Widiyanto] [Pembimbing 2: I Wayan Widi Pradnyana] [Penguji 1: Tjahjanto] [Penguji 2: Ika Nurlaili Isnainiyah]
Uncontrolled Keywords:	system design, essential food price prediction, machine learning, Random Forest
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User:	KEISHA MAURA PUTRI
Date Deposited:	10 Jul 2025 09:26
Last Modified:	03 Sep 2025 08:19
URI:	http://repository.upnvj.ac.id/id/eprint/37521

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