Penerapan Logika Fuzzy dalam Mengoptimalkan Penjadwalan Aktivitas Stripping pada Gudang PT. Bulog

Abstract

PT. BULOG is a company that distributes and stores national rice stocks. Inside there is a stripping process during the rice distribution process. Demolition activity at PT. BULOG has not fulfilled the available working hours, meaning that 8 hours of working hours is not enough to complete the unloading activity at BULOG's rice warehouse. This is caused by the determination of the number of workers in the field with a non-scientific approach from the field coordinator. Actually, this method results in additional hours of overtime for demolition activities which can last until 21.00-22.00. Fuzzy logic is an appropriate way to map an input space into an output space. Fuzzy logic can be applied in various fields of life including dismantling activities in warehouses. There are 3 fuzzy input variables, namely payload, number of workers, and displacement, while the fuzzy output variables are unloading time. This study aims to predict the time of demolition as a basis for planning the daily number of workers in the demolition process. The number of demolition activities in January will be used as the formation of a fuzzy set of 105 historical data. Fuzzy logic uses 3 inference systems namely Mamdani, Sugeno and Tsukamoto. Determination of the selected fuzzy logic is determined by two parameters, namely Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Sugeno's logic became the chosen fuzzy logic with an MSE value of 33.930 and a MAPE of 8.873%. The results of the scheduling planning show that the time spent outside the demolition activity is 180 minutes, while the demolition activity with Sugeno's fuzzy logic is 291 minutes out of 300 minutes, so the idle time is 9 minutes. Rated idle time 3%. So with Sugeno's fuzzy logic approach theoretically it can solve scheduling problems and can also determine the most optimal number of workers available, namely as many as 20 workers.