Sistem Analisis Prediksi Harga Forx Menggunakan Indikator Non Farm Payroll AS
Abstract
Abstrak
Pasar valuta aisng (forex market) adalah pasar terbesar dan memiliki transaksi keuangan terkomplek di dunia. Bermain di pasar ini dapat menghasilkan keuntungan finansil yang sangat besar namun memiliki resiko yang tinggi. Oleh karena itu banyak penelitian telah dilakukan untuk membantu para trader memprediksi harga pergerakan pasar valuta asing agar terhindar dari resiko kerugian, Pada penelitian ini, dibuat suatu aplikasi untuk memprediksi dampak dari suatu berita apakah akan menaikan harga atau sebaliknya. Berita yang diteliti
difokuskan kepada indikator fundamental non form payroll. Penelitian ini menggunakan pre processing POSTagger [1], sedangkan proses prediksi dibuat berdasarkan banyaknya kata yang sesuai pada suatu kelompok menggunakan algoritma brut force string match. Dari hasil penelitian didapati tingkat akurasi sebesar 60%, yaitu dengan menggunakan data latih sebesar 50 berita dan uji coba dengan 10 berita.
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Abstract
The foreign exchange market (forex market) is the largest and complex financial transactions in the world. Involved in this market can generate huge financial profits but also has a high risk. Therefore, research has been done to help traders predict the price movements of the foreign exchange market in order to avoid the risk of loss. In this study, an application has been made to predict the impact of news on whether to raise prices or otherwise . News are focused on fundamental indicators of non farm payroll. This study used a pre-processing POSTagger [1], while the predictions made based on the number of matches in a group using brut force algorithm strings match. The results found an accuracy rate of 60%, by using training data of 50 news and 10 trials of the news.
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