Analisis Prediksi Kebangkrutan Perusahaan Menggunakan Artificial Neural Network Pada Sektor Pertambangan Batubara - Nurdini, Rizki Amalia; Priyadi, Yudi; ., Norita (JSINBIS (Jurnal Sistem Informasi Bisnis), 2018)
Indonesia’s coal mining industry has been decreased since the last five years and causing the financial performance of companies in the industry to deteriorate. The aim of this paper is to analyze the bankruptcy prediction on coal mining sector companies listed in Indonesia Stock Exchange (IDX) in 2012 – 2016 using data mining prediction method that is artificial neural network model with three financial ratios as an input parameter. The financial ratios used are shareholder’s equity ratio, current ratio and return on assets. The results indicate that these ratios are very suitable to be used as an input parameter because it shows a quite significant difference in calculation results between bankrupted and non-bankrupted companies.The ANN training model used in the prediction process in this study resulted in the best training performance with the model architecture of 15 neurons on input layer and one hidden layer with 30 neurons in it. The training model produces training performance with the lowest MSE of 0,000000313 and the highest R of 99,9%. Bankruptcy prediction result using ANN showed that 7 (seven) coal mining sector companies are predicted to be bankrupt