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Abstrak :
[ABSTRAK
Prediksi pasar saham adalah penting dan sangat menarik karena prediksi return saham dapat menjanjikan keuntungan yang menarik. Dalam karya akhir ini, penulis menyelidiki prediktabilitas return pasar saham dengan Adaptive NetworkFuzzy Inference System (ANFIS). Tujuan dari penelitian ini adalah untuk menentukan apakah suatu algoritma ANFIS mampu secara akurat memprediksi return pasar saham dibandingkan dengan model Time Series ARIMA (Automatic Regression Integrated Moving Average). Penulis mencoba untuk membuat model dan memprediksi return saham ? saham dari Indeks LQ 45 di Bursa Efek Indonesia (BEI) menggunaka metode ANFIS. Penulis menggunakan empat variabel makroekonomi dan tiga indeks sebagai variabel input. Hasil eksperimen karya akhir ini menunjukkan bahwa model forecasting return saham harian LQ 45 dengan ANFIS memiliki tingkat error lebih kecil bila dbandingkan dengan metode ARIMA (Automatic Regression Integrated Moving Average). Metode ANFIS ini diharapkan dapat menjadi pendekatan alternatif yang menjanjikan untuk prediksi return saham. Sehingga ANFIS dapat menjadi alat yang berguna untuk ahli ekonomi dan praktisi yang berurusan dengan prediksi return dari saham.

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ABSTRACT
Stock market prediction is important and of great interest because successful prediction of stock return may promise attractive benefits. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm is capable of accurately predicting stock market return than Time Series Model Automatic Regression Integrated Moving Average (ARIMA). We attempt to model and predict the return on stock of the LQ 45 Index in Indonesia Stock Exchange (JSE) with ANFIS. We use four macroeconomic variables and three indices as input variables. The experimental results reveal that the model forecasts the daily return of LQ 45 stocks with ANFIS have less error than Auto Regressive Integrated Moving Average Method. ANFIS provides a promising alternative for stock market return prediction. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of stock return, Stock market prediction is important and of great interest because successful prediction of stock return may promise attractive benefits. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm is capable of accurately predicting stock market return than Time Series Model Automatic Regression Integrated Moving Average (ARIMA). We attempt to model and predict the return on stock of the LQ 45 Index in Indonesia Stock Exchange (JSE) with ANFIS. We use four macroeconomic variables and three indices as input variables. The experimental results reveal that the model forecasts the daily return of LQ 45 stocks with ANFIS have less error than Auto Regressive Integrated Moving Average Method. ANFIS provides a promising alternative for stock market return prediction. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of stock return]