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All Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Electrical Engineering and Computer (JEECOM)
Adhani, Muhammad Azmi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy

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Sistem Inventaris Stok Obat Menggunakan Metode Exponential Moving Average Sukaria, Petra Nugra; Muzakki, Mohammad Haris; Adhani, Muhammad Azmi; Kusrini, K; Agastya, I Made Artha
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.828

Abstract

The management of drug inventory in hospitals is a crucial aspect that affects the quality of healthcare services and patient safety. Uncertain drug demand can lead to overstock, resulting in wastage due to expiration, or understock, endangering patient safety. This study aims to develop a drug inventory system using the Exponential Moving Average (EMA) method to forecast drug sales. Historical sales and purchase data from Betang Pambelum Hospital, Palangka Raya, were used for forecasting. The implementation of the EMA method proved to provide accurate forecasting results, with the Mean Absolute Percentage Error (MAPE) falling into good to very accurate categories. This system not only reduces the risks of drug overstock and understock but also helps hospitals in more efficient inventory management. The adoption of this system is expected to enhance the quality of healthcare services through better drug inventory management
Currency Exchange Rate Prediction Using Gated Recurrent Unit (GRU) with Historical Data and Economic Factor Adhani, Muhammad Azmi; Kusrini, Kusrini
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 2 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i2.12385

Abstract

This study presents a currency exchange rate prediction model using a Gated Recurrent Unit (GRU) with historical price data and selected economic factors. Historical data, including Open, High, Low, and Close (OHLC) prices, were obtained from Yahoo Finance. Economic factor data, including Non-Farm Payrolls (NFP), Gross Domestic Product (GDP), Purchasing Managers Index (PMI), Retail Sales, and Durable Goods Orders, were collected from Trading View. Data preprocessing involved chronological sorting, missing value handling, feature scaling, and sequence generation. Multiple experiment cases were evaluated: historical data alone, historical data combined with all economic factors, and historical data combined with each individual factor. The GRU model achieved its best performance when incorporating historical data with Durable Goods Orders, indicating that this economic indicator provides significant predictive value, as reflected by the lowest RMSE (0.0076) and MAPE (0.0054), and the highest R² (0.9764) indicating that this economic factor provides significant predictive value. These findings highlight the importance of integrating selected economic factors into exchange rate prediction models to enhance forecasting accuracy.
Co-Authors Agastya, I Made Artha Kusrini, K Kusrini, Kusrini Mohammad Haris Muzakki, Mohammad Haris Sukaria, Petra Nugra