ANT-WUM: ALGORITMA BERBASIS ANT COLONY OPTIMIZATION UNTUK WEB USAGE MINING - Abdurrahman -; Bambang Riyanto Trilaksono; Rila Mandala; Rajesri Govindaraju (JURNAL TEKNOLOGI TECHNOSCIENTIA, 2009)
This paper is continuity research from our previous work in Ant-Miner implementation for web user classification. In our previous work, we implemented Ant-Miner algorithm for web user classification same with Ant-Miner for classification task in data mining domain. In this paper, we propose modification of heuristic function of Ant-Miner based on web usage mining (WUM) problem, that we name Ant-WUM. The heuristic function ACO is based on local problem domain. Information theory is common heuristic function used in classification task, such as implemented in C4.5 algorithm and ant-miner algorithm. Ant-WUM uses heuristic function based on closeness principle that implemented in clustering problem in WUM. We propose to use data from web access log, profile user, and transaction data to provide some attributes as term candidate of classification rule by Ant-WUM algorithm. We compared Ant-WUM algorithm with Ant-Miner algorithm. The result indicates that Ant-WUM has competitive result in term of accuracy rate, amount of rules, and computation time.