Penerapan Fuzzy Inference System Metode Sugeno untuk Menetapkan Rekomendasi Memilih Kendaraan Roda Empat Tipe SUV

Abstract

The selection of sport utility vehicles (SUVs) has become increasingly complex due to the growing variety of options available in the market. In this context, consumers tend to prefer vehicles that offer optimal performance at efficient prices. This study aims to develop an SUV recommendation system based on buyer preferences using the Fuzzy Inference System (FIS) with a Sugeno approach. The input variables include power, torque, engine capacity, and price, each categorized into three levels: low, medium, and high. The system produces an output in the form of a defuzzification value, where values greater than 0.5 indicate a recommended vehicle. This study processes data from 30 SUV models using both manual calculations and MATLAB implementation. The results show that both methods produce identical or very close values, confirming the effectiveness of the system. Six vehicles are identified as recommended, as they have defuzzification values above 0.5, indicating alignment with most buyer preferences. This system is expected to assist prospective buyers in making more objective and needsbased decisions.