Perbandingan Metode Double Exponential Smoothing Holt, Fuzzy Time Series Lee, Dan Fuzzy Time Series Stevenson-Porter Pada Peramalan Harga Penutupan Saham BBRI

Nur Indah Lutfira (Prodi Statistika, Fakultas Farmasi dan Sains, Universitas Islam Bandung, Indonesia)
Teti Sofia Yanti (Prodi Statistika, Fakultas Farmasi dan Sains, Universitas Islam Bandung, Indonesia)

Bandung Conference Series: Statistics
337-346

Abstract. Forecasting is an approach used to estimate future conditions based on historical data patterns. In investment, stock price forecasting provides important information to support decision-making because stock price movements are dynamic and fluctuating. This study aims to compare the performance of the Double Exponential Smoothing Holt, Fuzzy Time Series Lee and, Fuzzy Time Series Stevenson-Porter methods in forecasting BBRI stock closing prices and determining the method with the best accuracy. The research uses quantitative methods with secondary data in the form of daily BBRI stock closing prices from January 2, 2026, to June 30, 2026, obtained from Yahoo Finance. The data processing involves applying three forecasting methods and evaluating their accuracy using the Mean Absolute Percentage Error (MAPE). The results show that the MAPE values of the Double Exponential Smoothing Holt, Fuzzy Time Series Lee, and Fuzzy Time Series Stevenson-Porter methods are 1.65%, 1.78%, and 0.49%, respectively. The Fuzzy Time Series Stevenson-Porter method achieves the best performance with the smallest MAPE value. The forecasting result for the 117th period using this method is Rp2,713.07 per share. Abstrak. Peramalan merupakan pendekatan untuk memperkirakan kondisi masa mendatang berdasarkan pola data historis. Dalam bidang investasi, peramalan harga saham menjadi informasi penting karena pergerakan harga saham bersifat dinamis dan fluktuatif. Penelitian ini bertujuan untuk membandingkan kinerja metode Double Exponential Smoothing Holt, Fuzzy Time Series Lee, dan Fuzzy Time Series Stevenson-Porter dalam meramalkan harga penutupan saham BBRI serta menentukan metode dengan tingkat akurasi terbaik. Data yang digunakan merupakan data sekunder berupa harga penutupan harian saham BBRI periode 2 Januari 2026 hingga 30 Juni 2026 yang diperoleh dari Yahoo Finance. Metode peramalan diterapkan pada data saham yang memiliki pola fluktuatif dengan kecenderungan tren menurun, kemudian tingkat akurasi dievaluasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan nilai MAPE metode Double Exponential Smoothing Holt sebesar 1,65%, Fuzzy Time Series Lee sebesar 1,78%, dan Fuzzy Time Series Stevenson-Porter sebesar 0,49%. Metode Fuzzy Time Series Stevenson-Porter menghasilkan akurasi terbaik dengan nilai MAPE terkecil dan menghasilkan peramalan harga penutupan saham BBRI periode ke-117 sebesar Rp2.713,07 per lembar saham.