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All Journal Jurnal ICT : Information and Communication Technologies Journal of Education Religion Humanities and Multidiciplinary
Gunawan, Bayu
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Mechanical Engineering Nursing Social Sciences

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Transformasi Ruang Lingkup Dakwah di Media Sosial Gunawan, Bayu; Aryani, Marwa; MG, Nashrillah
Journal of Education Religion Humanities and Multidiciplinary Vol 2, No 2 (2024): Desember 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/jerumi.v2i2.4260

Abstract

Perkembangan teknologi telah mengubah cara penyampaian dakwah melalui media sosial. Dakwah sebagai upaya menyebarkan pesan agama kini memanfaatkan media digital untuk menjangkau audiens lebih luas, khususnya generasi muda. Penelitian ini bertujuan mengkaji perubahan dakwah dari media sosial, khususnya dalam aspek jangkauan, fleksibilitas, dan tantangan yang dihadapi. metode yang digunakan kualitatif melalui studi pustaka, tujuan penelitian ini menemukan bahwa dakwah di media sosial memungkinkan penyampaian pesan yang lebih kreatif dan interaktif. Tantangan utama dalam dakwah digital adalah menjaga relevansi dan etika dalam penyampaian konten, meskipun terdapat potensi besar dalam memperluas audiens dakwah. pemanfaatan media sosial yang bijaksana dalam dakwah dapat meningkatkan keimanan serta mendukung penyebaran nilai-nilai Islam secara global, memberikan dampak positif bagi masyarakat modern.
Determining Sales Based on Goods Data Classification Using the Web-Based C4.5 CRISP-DM Method Gunawan, Bayu; Fahrozi, Wirhan
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i2.278

Abstract

The increasing complexity of product distribution and sales activities at PT Mitra Bersama has created challenges in accurately classifying product performance, particularly due to manual data processing that is inefficient and prone to error. To address this issue, this study aims to develop an intelligent decision-support system capable of classifying best-selling and non-best-selling products using a data-driven approach. The CRISP-DM methodology was applied to guide the overall analytical process, consisting of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The C4.5 algorithm was used to perform the classification through entropy and information gain calculations to determine the most influential attributes. The results show that Type of Food has the highest information gain (0.0113340), followed by Initial Stock, Unit, Month, and Ending Stock, indicating that product characteristics and early inventory levels play a significant role in predicting sales performance. These findings were implemented into a web-based application to facilitate real-time classification and assist decision-makers in optimizing inventory planning, distribution strategies, and sales forecasting. This research contributes to improving organizational efficiency by providing a systematic, accurate, and accessible tool that supports better strategic decision-making in product sales management.
Co-Authors Aryani, Marwa MG, Nashrillah Wirhan Fahrozi, Wirhan