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All Journal Jurnal Informatika Progres
Teny Handhayani
Fakultas Teknologi Informasi, Universitas Tarumanagara, Jakarta
Computer Science & IT

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PREDIKSI HARGA DAGING SAPI DI KOTA JAKARTA PUSAT MENGGUNAKAN LSTM DAN GRU Farhan Adithya Putra; Teny Handhayani
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

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Abstract

This study analyzes the performance of two algorithms, Long ShortTerm Memory (LSTM) and Gated Recurrent Unit (GRU), in predicting data from the PIHPS website, focusing on beef commodity prices. The dataset was divided into two proportions: 80:20 and 70:30, and evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and coefficient of determination (R²). The experimental results showed that GRU with 128 units and a 70:30 proportion achieved the best performance, with metrics of MAE at 170, RMSE at 390.2889, and R² at 0.902. The goal of this research is to determine the most suitable algorithm and unit configuration for this dataset. Future research is expected to integrate additional data with more complex models to improve prediction accuracy.
Co-Authors Farhan Adithya Putra