Enhancing Software Developer Selection with Integrated F-AHP and F-TOPSIS Techniques

Abstract

This study focuses on enhancing the selection process for software developers by integrating the Fuzzy Analytic Hierarchy Process (F-AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS). The primary objective is to address the uncertainties and ambiguities in determining evaluation criteria and weights, thereby facilitating accurate decision-making when faced with multiple criteria and alternatives. Conducted within a software development company in Bandung, Indonesia, the study involved evaluating ten potential candidates for the software developer position. The methodology employed F-AHP to assess the importance of each criterion through pairwise comparisons, and F-TOPSIS to rank the candidates based on these criteria weights. The results revealed that Candidate CK-7 exhibited the highest closeness coefficient (CC_i), making them the top candidate, while CK-4 ranked the lowest. This integrated approach provided a systematic and transparent framework for decision-making, demonstrating its effectiveness in optimizing recruitment processes. The study contributes to the field by offering a robust decision-making tool that can be adapted to various industries, ensuring the selection of high-quality employees who meet necessary competencies, thereby improving overall productivity and performance.