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All Journal Jurnal Peluang JOURNAL OF HEALTHCARE TECHNOLOGY AND MEDICINE Jurnal Mirai Management Master Bahasa YUME : Journal of Management JURNAL ILKES (Jurnal Ilmu Kesehatan) Serambi Tarbawi JURMA : Jurnal Program Mahasiswa Kreatif Jurnal Manajemen dan Organisasi Review (MANOR) Multica Science and Technology Jurnal Riset sosial humaniora, dan Pendidikan (Soshumdik) Jurnal Penelitian Rumpun Ilmu Teknik Alfihris: Jurnal Inspirasi Pendidikan Jurnal Riset Ilmu Kesehatan Umum dan Farmasi
Muliana Muliana
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Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Journal : Multica Science and Technology

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Prediction of Shrimp Sales Using the ARIMA (AutoRegressive Integrated Moving Average) Method at UD Udang Makmur Peureulak Veri Ilhadi; Muliana Muliana; Zulfia , Anni; Ulya, Athiyatul; Sahputra , Ilham
Multica Science and Technology Vol 4 No 2 (2024): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v4i2.978

Abstract

UD. Udang Makmur is a shrimp farming business that often faces challenges in accurately predicting sales stock due to reliance on manual forecasting methods. This study aims to develop a web-based sales prediction application utilizing the AutoRegressive Integrated Moving Average (ARIMA) method. The application uses daily sales data from January to December 2023 for analysis. The results indicate that the ARIMA (2,1,1) model delivers accurate predictions, achieving a Mean Squared Error (MSE) of 0.264295. Forecasts for the next 24 periods demonstrate a stable projection, with predicted values converging around 2.5 and a narrow 95% confidence interval. These findings highlight the model's reliability and low uncertainty for the forecasted time frame. The application was successfully tested using the Black-Box method, confirming its functionality and effectiveness in supporting sales predictions.
Co-Authors Abu Bakar Ashar Ashar Baharuddin Dammar Budiman Budiman Djalante, Andi Endah Luqmanasari Ichsan Ichsan Islami Fatwa M Ikhsan Marniati Marniati Mashur Razak Mukhlis Hidayat Nina Isywara Kusuma Quratul Aini Rahmayani Rahmayani Regina Sipayung Rohamah Rohamah Roslynrosdiah Roslynrosdiah Sahputra , Ilham Sakinah Mawaddah Salimah Salimah Siraj Siraj Ulya, Athiyatul Usfiah Hamzah Siga Veri Ilhadi Zainal Abidin Zulfia , Anni