Perbandingan Algoritma Forward Chaining dalam Sistem Pakar Rekomendasi Peminatan Bidang Teknologi

This research aims to compare the forward chaining algorithm with the Backward Chaining, Breadth-First Search (BFS), and Depth-First Search (DFS) algorithms in the context of an expert system for recommending specialization in the field of technology. The primary focus of this study is to analyze the runtime performance of each algorithm and determine the algorithm that provides the fastest runtime. The research methodology involves implementing the four algorithms in an expert system that provides recommendations for technology field specialization based on rules and user responses. The data used in the study consists of specialization rules in the technology field and user responses related to their interests in those fields. The results of the study demonstrate that the forward chaining algorithm outperforms the Backward Chaining, BFS, and DFS algorithms in terms of runtime performance. This indicates that the forward chaining algorithm is more efficient in generating technology field specialization recommendations. Based on the findings of this research, it is recommended to use the forward chaining algorithm in the development of expert systems for technology field specialization. This algorithm can assist users in obtaining recommendations quickly and efficiently, thereby enhancing user experience and the effectiveness of the expert system in providing suitable technology field specializations based on user interests.