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

---

ABSTRACT
Stock market prediction is important and of great interest because successfulprediction of stock return may promise attractive benefits. In this paper, weinvestigate the predictability of stock market return with Adaptive Network-BasedFuzzy Inference System (ANFIS). The objective of this study is to determinewhether an ANFIS algorithm is capable of accurately predicting stock marketreturn than Time Series Model Automatic Regression Integrated Moving Average(ARIMA). We attempt to model and predict the return on stock of the LQ 45 Indexin Indonesia Stock Exchange (JSE) with ANFIS. We use four macroeconomicvariables and three indices as input variables. The experimental results revealthat the model forecasts the daily return of LQ 45 stocks with ANFIS have lesserror than Auto Regressive Integrated Moving Average Method. ANFIS providesa promising alternative for stock market return prediction. ANFIS can be a usefultool for economists and practitioners dealing with the forecasting of stock return, Stock market prediction is important and of great interest because successfulprediction of stock return may promise attractive benefits. In this paper, weinvestigate the predictability of stock market return with Adaptive Network-BasedFuzzy Inference System (ANFIS). The objective of this study is to determinewhether an ANFIS algorithm is capable of accurately predicting stock marketreturn than Time Series Model Automatic Regression Integrated Moving Average(ARIMA). We attempt to model and predict the return on stock of the LQ 45 Indexin Indonesia Stock Exchange (JSE) with ANFIS. We use four macroeconomicvariables and three indices as input variables. The experimental results revealthat the model forecasts the daily return of LQ 45 stocks with ANFIS have lesserror than Auto Regressive Integrated Moving Average Method. ANFIS providesa promising alternative for stock market return prediction. ANFIS can be a usefultool for economists and practitioners dealing with the forecasting of stock return]