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All Journal Indonesian Journal of Informatic Research and Software Engineering Jurnal Masyarakat Religius dan Berwawasan
Iswandi Iswandi
UIN Mahmud Yunus Batusangkar
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Environmental Science Social Sciences

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Excel Application Training for Regional Guardian Equipment and Staff and Management of Bumdes Batujonggi Kumanis Village Khairunnisa Khairunnisa; Iswandi Iswandi; Fitra Kasma Putra; Lidya Rahmi; Abdurrahman Niarman
Jurnal Masyarakat Religius dan Berwawasan Vol 1, No 2 (2022): MASYARAKAT RELIGIUS DAN BERWAWASAN
Publisher : Universitas Islam Negeri Mahmud Yunus Batusangkar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31958/mrw.v1i2.7931

Abstract

The role of technology is urgently needed by society as a precaution in dealing with the changes in the age of Industrial Revolution 4.0 to Industrial Revolution 5.0. Operating a computer, especially the Excel application, is one of the hard skills for the community. Microsoft Excel is usually known as number processing software or it can be referred to as a spreadsheet application that is designed to process data automatically such as arithmetic calculations, formulas, use of functions, tables, charts and data management to create information. This service activity presents issues identified by Kumanis Nagari officials and government, namely the lack of optimal use of computers, particularly the community's use of the Excel application, and the need to improve the community's knowledge and skills to Optimization of use to improve the Excel application. The solution offered is the training of the Excel application for processing simple data such as the data processing of official travel orders and wage data of the employees. The methodology for implementing this non-profit activity uses the Participatory Action Research (PAR) approach. The results of conducting this training are designed to provide an understanding of using the Excel application to create official travel orders and employee payroll data, as well as increase hard skills for the apparatus and staff of the village guard and management of BUMDES Batujonggi Nagari Kumanis.
Pendekatan Analitik Prediktif dan Preskriptif untuk Optimasi Operasional Penjualan Snack di Lingkungan Kampus: Predictive and Prescriptive Analytics Approach for Optimizing Campus Snack Sales Operations Lita Sari Muchlis; Iswandi Iswandi; Zihnil Afif; Adriyendi Adriyendi; Lidya Rahmi; Eva Rahmayanti Br Saragih; Nindya Dwi Putri
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 6 No. 1 (2026): Indonesian Journal of Informatic Research and Software Engineering (IJIRSE)
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v6i1.2741

Abstract

Penelitian ini bertujuan untuk mengoptimalkan penjualan snack mahasiswa di lingkungan kampus menggunakan pendekatan Artificial Intelligence (AI) prediktif dan preskriptif. Metode yang digunakan meliputi pengumpulan data penjualan dari lima kantin fakultas dengan variabel jenis produk, hari transaksi, cuaca, event kampus, dan promo. Model prediktif dalam penelitian ini dibangun menggunakan algoritma Linear Regression, Random Forest, Gradient Boosting, dan XGBoost. Selanjutnya, model preskriptif dikembangkan melalui pendekatan What-If Analysis untuk menghasilkan rekomendasi optimalisasi strategi penjualan dan pengelolaan stok berdasarkan berbagai kondisi penjualan. Hasil evaluasi menunjukkan bahwa seluruh model memiliki performa yang sangat baik dengan nilai koefisien determinasi (R²) dan cross-validation di atas 0,98. Model Gradient Boosting menghasilkan performa terbaik dengan nilai R² sebesar 0,9917, MAE sebesar 0,8872, serta nilai cross-validation R² sebesar 0,9875. Sementara itu, Linear Regression, Random Forest, dan XGBoost juga menunjukkan hasil prediksi yang kompetitif dan stabil. Analisis preskriptif menunjukkan bahwa jenis produk, hari transaksi, dan event kampus merupakan faktor utama yang memengaruhi penjualan, sedangkan promo dan cuaca memiliki pengaruh yang relatif lebih kecil. Penelitian ini menunjukkan bahwa integrasi AI prediktif dan preskriptif mampu membantu pengelola kantin dalam mengoptimalkan strategi penjualan, pengelolaan stok, serta pengambilan keputusan berbasis data secara lebih efektif di lingkungan kampus.
Co-Authors Abdurrahman Niarman Adriyendi Adriyendi Eva Rahmayanti Br Saragih Fitra Kasma Putra Khairunnisa Khairunnisa Lidya Rahmi Lita Sari Muchlis Nindya Dwi Putri Zihnil Afif