EVALUATION OF CONTAINER TERMINAL SYSTEM PERFORMANCE IN TANJUNG PERAK SURABAYA PORT IN INCREASING CUSTOMER SATISFACTION USING BINARY LOGISTICS REGRESSION

Abstract

In this sophisticated era, we can do almost anything, and we can get it easily. No exception with the necessities of life that we can get easily from one place and sent to us via transportation services, even goods with a large capacity. One of the transportation services that can efficiently deliver goods in large quantities is sea transportation via ships with a shipping system using containers. Tanjung Perak Port in Surabaya is one of the ports that provides container loading and unloading services. For this reason, in this study an evaluation of the performance of container terminals at the Port of Tanjung Perak Surabaya will be carried out by looking at the factors that influence customer satisfaction (Y), which consist of several predictor variables, namely price of goods (X1), weight of goods (X2) and Travel Time (X3) using the binary logistic regression method, which is a method used to model the response variable consisting of two categories and is appropriate for modeling data consisting of possible events with response variables consisting of two choice categories. Logistic regression will form a predictor/response variable, which is a linear combination of the independent variables. In this study, modeling was carried out to determine the relationship between whether the predictor variable affects the response variable and the extent to which this variable influences it. After knowing the variables that contribute to customer satisfaction, these variables can then be used as evaluation material, whether they need to be increased or reduced. Based on the results of the study, it was found that the variable weight of goods (X2) has a significant influence on customer satisfaction with a classification accuracy of 88.1%, so it must be optimized related to the container capacity that contains customer goods because, if this variable increases by 1 unit, it will increase the probability of customer satisfaction is 1.792 times and this increase is higher than the other variables.