Indonesian Stock Prediction using Support Vector Machine (SVM)

¹ Electrical Engineering Department, Petra Christian University, Jl. Siwalan Kerto 121-131, Surabaya, Indonesia 60236
² Informatics Department, Institut Informatika Indonesia, Jalan Pattimura No.3, Sonokwijenan, Surabaya, Indonesia 60189

^* Corresponding author: resmana@petra.ac.id; murtis@petra.ac.id

Abstract

This project is part of developing software to provide predictive information technology-based services artificial intelligence (Machine Intelligence) or Machine Learning that will be utilized in the money market community. The prediction method used in this early stages uses the combination of Gaussian Mixture Model and Support Vector Machine with Python programming. The system predicts the price of Astra International (stock code: ASII.JK) stock data. The data used was taken during 17 yr period of January 2000 until September 2017. Some data was used for training/modeling (80 % of data) and the remainder (20 %) was used for testing. An integrated model comprising Gaussian Mixture Model and Support Vector Machine system has been tested to predict stock market of ASII.JK for l d in advance. This model has been compared with the Market Cummulative Return. From the results, it is depicts that the Gaussian Mixture Model-Support Vector Machine based stock predicted model, offers significant improvement over the compared models resulting sharpe ratio of 3.22.