Implementasi Fuzzy Tsukamoto dan IoT Pada Sistem Pendukung Keputusan Tingkat Kepadatan Lahan Parkir

Abstract

Parking lots are a common thing in everyday life. The problem of parking lot's density can be a problem for managers of a place. So to overcome the problem that can occur, this study aims to design a decision support system (DSS) to determine the density of parking lots by applying the concept of IoT and Tsukamoto's fuzzy method. IoT is used to automate data retrieval to create fuzzy rule patterns. In the Tsukamoto method, each rule is represented by IF-THEN. The method for system design in this study includes the design of hardware and software. In this design, data retrieval uses an ultrasonic sensor HC-SR04 and is processed with the IoT concept using Arduino UNO and ESP8266 microcontrollers. The sensor is placed on the exit and entry path of the vehicle on the parking lot to detect vehicles entering and exiting. The parking lot used in this study is miniature. Vehicle data is processed using Tsukamoto's fuzzy logic to determine parking density decisions. Data variables used are time, duration, and density of parking lots. DSS is designed using the Laravel framework. Based on the test results, it is known that IoT devices can perform their functions properly. DSS that is made in the form of a website can also function well. The results are based on error testing, obtained error for determining the parking density level is 7,68%.