PENDEKATAN MOVING AVERAGE OF VWAP UNTUK PREDIKSI PERGERAKAN HARGA EMAS MENGGUNAKAN ALGORITMA GRADIENT BOOSTING REGRESSION

ABDILLAH, REZA WAHYU (2024) PENDEKATAN MOVING AVERAGE OF VWAP UNTUK PREDIKSI PERGERAKAN HARGA EMAS MENGGUNAKAN ALGORITMA GRADIENT BOOSTING REGRESSION. S1 thesis, Universitas Mercu Buana Jakarta.

Preview	Text (HAL COVER) 01 COVER.pdf Download (431kB) | Preview
Preview	Text (ABSTRAK) 02 ABSTRAK.pdf Download (27kB) | Preview
	Text (BAB I) 03 BAB 1.pdf Restricted to Registered users only Download (75kB)
	Text (BAB II) 04 BAB 2.pdf Restricted to Registered users only Download (228kB)
	Text (BAB III) 05 BAB 3.pdf Restricted to Registered users only Download (237kB)
	Text (BAB IV) 06 BAB 4.pdf Restricted to Registered users only Download (276kB)
	Text (BAB V) 07 BAB 5.pdf Restricted to Registered users only Download (75kB)
	Text (DAFTAR PUSTAKA) 08 DAFTAR PUSTAKA.pdf Restricted to Registered users only Download (125kB)
	Text (LAMPIRAN) 09 LAMPIRAN.pdf Restricted to Registered users only Download (458kB)

Abstract

Gold price movements are influenced by various economic factors, inflation, supply and demand, and monetary policy, which makes gold price prediction important for investors. This research aims to develop a gold price prediction model using the Moving Average of VWAP approach and the Gradient Boosting Regression algorithm. Data is taken from the website www.investing.com, covering the period January 14, 2016 to April 12, 2024. Research methods include data cleaning. Scaling with StandardScaler, and division of data into training and testing sets, Moving Average of VWAP is used to analyze Price based on trading volume, while Gradient Boosting Regression Algorithm is used to predict the trend of price movement based on the actual prices. The results show a very high level of accuracy with R-Squared (R2) reaching 0.9990 and the model performance evaluation shows MAE of 6.2918, MSE of 77.2228, RMSE of 8.7848. these results indicate that the resulting prediction model can be an effective tool for investors in making more informational and strategic gold investment decisions. Key Words: Gold, Gradient Boosting Regression, Moving Average, VWAP Pergerakan Harga emas dipengaruhi oleh berbagai faktor ekonomi, inflasi, penawaran dan permintaan, serta kebijakan moneter, yang membuat prediksi Harga emas menjadi penting bagi investor. Penelitian ini bertujuan untuk mengembangkan model prediksi Harga emas menggunakan pendekatan Moving Average of VWAP dan Algoritma Gradient Boosting Regression. Data diambil dari situs www.investing.com, mencakup periode 14 Januari 2016 hingga 12 April 2024. Metode penelitian meliputi pembersihan data. Penskalaan dengan StandardScaler, dan pembagian data menjadi set pelatihan dan pengujian, Moving Average of VWAP digunakan untuk menganalisis Harga berdasarkan volume perdagangan, sementara Algoritma Gradient Boosting Regression digunakan untuk memprediksi tren pergerakan harga berdasarkan harga aktual. Hasil penelitian menunjukan Tingkat akurasi yang sangat tinggi dengan R-Squared (R2) mencapai 0.9990 dan evaluasi kinerja model menunjukan MAE sebesar 6.2918, MSE sebesar 77.2228, RMSE sebesar 8.7848. hasil ini menunjukan bahwa model prediksi yang dihasilkan dapat menjadi alat yang efektif bagi investor dalam pengambilan Keputusan investasi emas yang lebih informasional dan strategis. Kata kunci: Emas, Gradient Boosting Regression, Moving Average, VWAP

Actions (login required)

View Item