Machine learning classification analysis model community satisfaction with traditional market facilities as public service

Abstrak

Traditional markets are public service facilities that can be utilized by thecommunity. The market function is used place where sellers and buyers meetin conducting transactions. This study aims to build a machine learningclassification analysis model in measuring community satisfaction withtraditional market facilities. The analytical methods used include Fuzzy.multiple linear regression (MRL), artificial neural network (ANN), anddecision tree (DT). Fuzzy is used to generate a pattern of rules in determiningthe level of satisfaction. MRL serves to measure and test the correlation ofrules that have been formed. The ANN method is used to carry out theclassification analysis process based on learning. In the final stage. DT is usedto describe the decision tree of the analysis process. This study presents theresults of machine learning analysis which is very good in determiningsatisfaction with an accuracy rate of 99.99%. This result is influenced by fuzzylogic which can develop a classification rule pattern of 32 patterns. MRL alsoshows a significant correlation level of 81.1% based on the indicator variables.Overall, the machine learning classification analysis model can provideknowledge to be considered in the management of traditional markets aspublic service facilities.