Penerapan Logika Fuzzy Tsukamoto Sebagai Sistem Pendukung Keputusan Penentuan Mata Kuliah Pilihan Mahasiswa Ilmu Komputer XYZ - Muhammad Reza Alhafiz; Sriani (JURIKOM (Jurnal Riset Komputer), 2026)
The selection of elective courses poses a challenge for Computer Science students at XYZ University because it influences competency development, while objective decision-making guidance remains limited. This study aims to develop a web-based decision support system to recommend specialization elective courses using the Fuzzy Tsukamoto method. Data were collected through questionnaires from students in semesters five to seven and processed into four input variables: Robotics, Mathematics, Programming, and Analysis. Each variable was modeled into three fuzzy sets (Weak, Moderate, Strong) using trapezoidal membership functions and processed through IF–THEN rule-based inference with a total of 162 rules. Output values were obtained through weighted average defuzzification to generate course recommendations. System testing was conducted by comparing system outputs with manual calculations and evaluated using the Mean Absolute Percentage Error (MAPE). The results showed a MAPE value of approximately ±0.1096%, indicating that the implementation of the Tsukamoto method in the system is consistent with manual calculations. This study contributes to providing a structured and objective decision support system to assist students in determining elective courses based on their competencies.