Purwarupa Sistem Pembuka Pintu Cerdas Menggunakan Perceptron Berdasarkan Prediksi Kedatangan Pemilik - Brisma Meihar Arsandi; Triyogatama Wahyu Widodo; Faizah Faizah (IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., 2017)
Arrival prediction system on smarthome is system that cam estimating time of home owner arrival on smarthome. Prediction system used to reference on smarthome system to preparing electronic devices so at home owner arrive, the devices are already to use. Prediction system made by divide distance of home owner location to home by driving velocity. Prediction also use neural network perceptron to determine travel condition are in traffic or not and correcting to predicting perform. Perceptron use last travel data as reference correction to prediction system. Based on testing on prediction system, accuracy of prediction system reach 74% to 79%. Accuracy reach these values due errors occurred while determining location so predicted route became not match with real condition. Errors occured by GPS usage not on outdoor area and smartphone GPS only detect 6 GPS satellite. Neural network perceptron differ of traffic condition on travel after fourth epoch, with weight value at 11.09 and bias value at 61. And perceptron can correcting prediction system after twelfth epoch with weight values at -0.2778 and 0.2924 also bias value at -0.05.