IMPLEMENTASI METODE WEIGHTED PRODUCT DAN PROFILE MATCHING DALAM SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SEPEDA MOTOR MATIC PADA DEALER LHOKSEUMAWE

Abstract

With the increasing diversity of transportation needs, selecting the most suitable automatic motorcycle (matic) has become a challenge for consumers due to the wide range of available options. This study aims to develop a Decision Support System (DSS) to assist consumers in choosing the best matic motorcycle using the Weighted Product (WP) and Profile Matching (PM) methods. Data were collected through interviews with local motorcycle dealers and official manufacturer websites. The decision-making process focuses on five key criteria: price, engine capacity, safety level, year of release, and the number of available color options. The WP method calculates the preference value of each alternative by multiplying the normalized values with their respective weights. Meanwhile, the PM method compares actual data with an ideal profile and evaluates the resulting gaps. The system was developed using PHP and tested through both manual calculations and application-based validation. Results show that both WP and PM methods consistently recommended the Vario 160 ABS as the top choice. However, the PM method also placed NMAX Neo in an equivalent top position. These findings demonstrate that combining WP and PM methods provides complementary insights. WP offers clearer ranking distinctions, while PM emphasizes alignment with ideal profiles.