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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Hasil Pengabdian Masyarakat (JURIBMAS)
Zarasky, Dzira Faza
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Computer Science & IT Education Electrical & Electronics Engineering Engineering Social Sciences

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Efektivitas Pembelajaran Melalui E-Learning Di Masa Pandemi Covid 19 Pratama, Arya; Zarasky, Dzira Faza; Wardana, Wafiq Hafiz; Al Fahmi, Qori
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 1 No 1 (2022): Juli 2022
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (394.334 KB) | DOI: 10.62712/juribmas.v1i1.7

Abstract

Pada awal tahun 2020 seluruh dunia termasuk Indonesia mengalami situasi di luarkendali yang diakibatkan oleh menyebarnya wabah COVID-19 di hampir seluruhpenjuru dunia. Berbagai aspek kehidupan ikut terkena imbas dari pandemi inidikarenakan diterapkannya berbagai protokol kesehatan yang mengharuskansebagian besar orang harus tetap berada di rumah dan menghentikan sementarakegiatan sosialnya. Di Perguruan Tinggi yang berisikan tentang penghentiansementara kegiatan akademik khususnya modus pembelajaran tatap muka danmenggantikan dengan modus belajar dari rumah atau pembelajaran daring bagimahasiswa. Salah satu media pembelajaran yang paling efektif pada masa pandemiadalah e-learning. Penelitian ini bertujuan untuk mengetahui apakah pembelajaranmelalui e-learning efektif terhadap minat pembelajaran pada perkuliahan saat dalammasa pandemi. Metode penelitian yang digunakan adalah penelitian deskriptif,dengan melakukan survei. Penelitian survey dilaksanakan untuk menggambarkansikap atau pendapat. Instrumen pada penelitian ini menggunakan kuesioner.
Web-Based F&B Lazatto Product Sales and Stock Prediction System with Double Moving Average (DMA) Method Zarasky, Dzira Faza; Alda, Muhamad
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10012

Abstract

This study aims to develop a web-based sales and stock prediction system for Lazatto, a Food and Beverage (F&B) company, using the Double Moving Average (DMA) method. The background of this research is based on issues stock requirement planning is still done conventionally, where the head of the restaurant places stock orders solely based on personal experience and intuition, without utilizing past sales data as a basis for decision-making, which often result in overstocking or stockouts. By implementing a web-based forecasting information system, the company can obtain real-time and structured data. This study uses sales data from April 2024 to March 2025. The prediction results show a downward trend in sales for the "Kentang" (Potato) product, with a forecasted value of 107.33 for April 2025, compared to an actual value of 95. Model evaluation indicates an average MAPE of 21.19%, which is considered a "fair" level of forecasting accuracy. Additionally, the time required for weekly stock planning was reduced, and interviews with staff revealed increased user satisfaction and ease of use. The developed system has proven to support more accurate and efficient decision-making in inventory management.
Co-Authors Al Fahmi, Qori Muhamad Alda Pratama, Arya Wardana, Wafiq Hafiz