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Anggayana, Denta Pratama
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering

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Price Prediction of Second-Hand Iphones Using Random Forest Regression Based on Unit Conditions Anggayana, Denta Pratama; Taufik, Ichsan; Gerhana, Yana Aditia
ISTEK Vol. 14 No. 1 (2025)
Publisher : Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/istek.v14i1.2154

Abstract

This study presents the development of a price prediction model for second-hand Iphones based on unit conditions using the Random Forest Regression algorithm, implemented in a web-based application. A dataset of 542 records was collected from Facebook Marketplace and iPhone trading groups, with variables including Iphone type, storage capacity, warranty status, Face ID, and Truetone. The research employed the CRISP-DM methodology through the stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The model was tested using data splits of 80%–20%, 70%–30%, and 60%–40%, resulting in MAE values of 8.32%–8.42% and RMSE values of 10.64%–10.88%, indicating good and consistent accuracy. The developed system can automatically provide price recommendations based on unit conditions, assisting both sellers and buyers in determining fair market prices.
Co-Authors Ichsan Taufik, Ichsan Yana Aditia Gerhana, Yana Aditia