Sistem Pelacakan Posisi Aset Laboratorium Melalui Sensor Tanpa Kontak Fisik Menggunakan Metode K – Nearest Neighbor (K- NN) - Atika Nur Rahmawati; Susetyo Bagas Bhaskoro; Siti Aminah (APIC, 2020)
The purpose of this research is to build a laboratory asset position tracking system automatically by utilizing data acquisition from contactless based sensors, namely UHF RFID. In addition, this study also identifies the location of the asset position using the K-Nearest Neighbor method. This case study of tracking the position of assets was conducted at the Manufacturing Automation Engineering Department and Mechatronics, Bandung Manufacturing Polytechnic. The identification of the position of laboratory assets in this study uses the RSSI RFID asset tag as a predictor which will then be compared with 240 training data samples (training data). Testing of the RFID tag position detection system was carried out by means of three RFID readers detecting RFID tags simultaneously and producing an average classification accuracy of 64%.