Analisis Prediksi Harga Saham PT. Telekomunikasi Indonesia Menggunakan Metode Support Vector Machine
DOI:
https://doi.org/10.21111/fij.v5i2.4449Abstract
AbstrakSaham merupakan salah satu bentuk investasi yang mana merupakan surat berharga yang menjadi bukti kepemilikan seseorang atas suatu perusahaan. Pergerakan saham dari waktu ke waktu relatif tidak menentu dan tidak pasti, namun masih dapat diprediksi. Prediksi harga saham ini akan sangat berguna bagi investor untuk mengetahui bagaimana alur investasi bekerja pada setiap harga pada masing-masing harga saham yang berubah dari waktu ke waktu. Model prediksi pergerakan harga saham yang akurat dapat membantu para investor dalam pertimbangan pengambilan keputusan transaksi saham karena pergerakan harga saham yang cenderung non linier ini akan menyulitkan investor dalam melakukan prediksi. Dalam penelitian ini dilakukan prediksi harga saham PT. Telekomunikasi Indonesia menggunakan metode algoritma Support Vector Machine yang ditingkatkan kinerjanya menggunakan kernel RBF. Dari hasil pengujian dengan metode Support Vector Machine dihasilkan tingkat akurasi sebesar 0.9641 dan RMSE sebesar 0.0932. Pengujian juga dilakukan menggunakan algoritma k-Nearest Neighbors dengan tingkat akurasi sebesar 0.945 dan RMSE sebesar 0.1162. Dengan itu diketahui bahwa algoritma SVM memiliki tingkat akurasi yang lebih tinggi dan tingkat error yang lebih rendah dibangdingkan metode KNN.Kata kunci: prediksi, harga saham, support vector machine. Abstract[Stock Price Prediction Analysis of PT. Indonesian Telecommunications Using Methods Support Vector Machine] Stock is a form of investment which is a form of securities which is a proof of someone's ownership of a company. The movement of shares from time to time is relatively uncertain, but still predictable. This stock price prediction will be very useful for investors to find out how the flow of investment works at each price on each stock price that changes from time to time. An accurate prediction model of stock price movements can help investors in considering the decision of stock transaction because the stock price movements that tend to be non-linear will make it difficult for investors to make predictions. In this research a prediction of the stock price of PT. Telekomunikasi Indonesia uses the Support Vector Machine algorithm method which is improved in performance using the RBF kernel. From the results of testing with the Support Vector Machine method the accuracy level is 0.9641 and the RMSE is 0.0932. Tests are also carried out using the k-Nearest Neighbors algorithm with an accuracy level of 0.945 and an RMSE of 0.1162. Therefore, it is known that the SVM algorithm has a higher level of accuracy and a lower error rate than the KNN method.Keywords: prediction, stock price, support vector machine.References
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