Penerapan TOPSIS Multi-Kriteria untuk Pemilihan Motor Bekas Layak Jual Kembali Berdasarkan Multi-Kriteria

Abstract

Selecting used motorcycles for resale inventory requires an objective assessment because each unit differs in price, age, mileage, engine capacity, type, and transmission. This study applies the multi-criteria Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to prioritize used motorcycles suitable for resale. The dataset comprises 199 sales transactions recorded by Cahaya Emas Motor Showroom in 2025. Six criteria were evaluated: price, production year, odometer, engine capacity, motorcycle type, and transmission. Price and odometer were treated as cost criteria, while the remaining criteria were treated as benefit criteria. Their respective weights were 0.25, 0.20, 0.25, 0.10, 0.10, and 0.10. The calculation covered decision-matrix construction, normalization, weighting, determination of positive and negative ideal solutions, distance calculation, and preference scoring. The results placed a 2017 Honda Supra-X 125 first with a preference value of 0.89310533, followed by a Yamaha Vixion at 0.88259345 and a Honda Revo at 0.87931174. The findings indicate that favorable price and mileage profiles can offset differences in production year, engine capacity, type, and transmission when assessing resale suitability.