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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK)
Datin, Maha Valne
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences

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ANALISIS PERBANDINGAN METODE DOUBLE EXPONENTIAL SMOOTHING DAN DOUBLE MOVING AVERAGE PADA KASUS PERAMALAN PENJUALAN KOPI BUBUK DI LOPO MANDHELING COFFEE Siahaan, Andysah Putera Utama; Rabe, Siska Mayasari; Asyifa, Nathania; Datin, Maha Valne; Syahri, Rahma; Rambe, Rezkinah
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4199

Abstract

Abstract: This study aims to compare the accuracy between time series forecasting methods, namely Double Exponential Smoothing (DES) and Double Moving Average (DMA), in forecasting ground coffee sales at Lopo Mandheling Coffee, an MSME in the beverage sector. The sales data used is monthly data from January 2024 to March 2025. The analysis was carried out by calculating the accuracy of each method using the MAPE, MAD, and MSE indicators. The results show that the DMA method provides more accurate forecasting results than the DES method for both types of coffee (Specialty and Premium). DMA has lower MAPE, MAD, and MSE values, so it is more recommended for use in sales forecasting in this MSME. This study provides a practical contribution for MSME actors in improving operational efficiency through a data-driven forecasting approach.Keyword: Sales forecasting; double exponential smoothing; double moving average; ground coffee; MSMEAbstrak: Penelitian ini bertujuan sebagai perbandingan akurasi antara metode peramalan deret waktu, yaitu Dpuble Exponential Smoothing (DES) dan Double Moving Avarega (DMA), dalam meramalkan penjualan kopi bubuk di Lopo Mandheling Coffee, sebuah UMKM di sektor minuman. Data penjulan yang digunakan merupakan data bulanan dari Januari 2024 hingga Maret 2025. Analisis dilakukan dengan menghitung akurasi masing-masing metode menggunakan indikator MAPE, MAD, dan MSE. Hasil penelitian menunjukkan bahwa metode DMA memberikan hasil peramalan yang lebih akurat dibandingkan metode DES untuk kedua jenis kopi (Specialty dan Premium). DMA memiliki nilai MAPE, MAD, dan MSE yang lebih rendah, sehingga lebih direkomendasikan untuk digunakan dalam peramalan penjualan pada UMKM ini. Penelitian ini memberikan kontribusi praktis bagi pelaku UMKM dalam meningkatkan efisiensi operasional melalui pendekatan peramalan berbasis data.Kata kunci: Peralaman penjualan; double exponential smoothing; double moving average; kopi bubuk; UMKM
Analisis Performa Algoritma A* untuk Optimasi Penjadwalan Janji Temu Dokter di Rumah Sakit Harahap, Nur Azizah; Novelan, Muhammad Syahputra; Rambe, Siska Mayasari; Syahri, Rahma; Datin, Maha Valne
Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Vol 4 No 1 (2025): Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK)
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/jumistik.v4i1.157

Abstract

Optimizing scheduling in healthcare systems is crucial for improving operational efficiency and patient satisfaction. This study analyzes the performance of the A* algorithm in optimizing doctor appointment scheduling in hospitals. Using a heuristic-based approach, the proposed solution aims to minimize search time and improve the accuracy of determining optimal appointment slots. The algorithm integrates time penalties to align scheduling outcomes with patient preferences, demonstrating significant improvements compared to traditional linear search methods.A comparative evaluation was conducted with traditional search algorithms using experimental data, showing that A* significantly reduces execution steps (the number of search steps directly impacts energy efficiency) while maintaining high accuracy in slot allocation. The A* algorithm excels in this context by providing consistent solutions with reduced search effort. This study addresses gaps in previous research, particularly in handling large Datasetss and meeting real-time scheduling needs.The results of this research are expected to contribute to the development of efficient hospital reservation systems, thereby enhancing patient experiences and streamlining hospital operations. This study serves as a foundation for further exploration of the application of the A* algorithm in healthcare optimization.
Co-Authors Andysah Putera Utama Siahaan Asyifa, Nathania Harahap, Nur Azizah Muhammad Syahputra Novelan Rabe, Siska Mayasari Rambe, Rezkinah Rambe, Siska Mayasari Syahri, Rahma