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All Journal Journal of Innovative and Creativity Subservire: Jurnal Pengabdian kepada Masyarakat
Bella Paramita
Institut Teknologi dan Bisnis Bina Sriwijaya Palembang
Religion Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Sosialisasi Penerapan Sistem Informasi Pendidikan untuk Pengelolaan Data Guru dan Akademik Berbasis Web Akhmad Sayuti; Irwansyah; Abdul Harits M; Serry Davizan; Bella Paramita
Subservire: Jurnal Pengabdian Masyarakat Vol 2 No 1 (2024): Subservire
Publisher : Fakultas Ushuluddin dan Dakwah IAIN Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/subservire.v2i1.2096

Abstract

This article aims to introduce and implement a Web-Based Information System at SMK Bina Sriwijaya, Palembang. Through socialization and training activities, participants from various backgrounds, including teachers, students, operators, administrators, school principals, and parents, were invited to understand and use this system. The implementation method of the activities includes preparation, execution, and evaluation stages. The results showed that participants demonstrated enthusiasm in understanding and using this system. With the presence of a web-based information system, it is expected that the effectiveness and efficiency of academic and administrative data management in schools can be improved, providing faster and more accurate information, and minimizing possible errors. In conclusion, this activity successfully introduced and implemented a Web-Based Information System at SMK Bina Sriwijaya, which is expected to make a positive contribution to the management of academic and administrative data in the school.
Pengembangan Aplikasi Monitoring Jaringan Komputer Berbasis Mobile Bella Paramita; Yuliza Aryani; Indah Rahma Sari
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

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Abstract

Pentingnya monitoring jaringan untuk memastikan kondisi jaringan selalu baik. Tujuan utama adalah mengembangkan aplikasi mobile (Android) untuk membantu teknisi jaringan memonitoring kinerja jaringan secara real-time melalui smartphone. Aplikasi ini memberikan notifikasi saat terjadi masalah jaringan, mempermudah administrator untuk mengelola jaringan di mana saja, serta meningkatkan efisiensi dan keandalan jaringan.Metode yang di pakai dalam penelitian ini adalah Menggambarkan bagaimana aplikasi dikembangkan, termasuk penggunaan bahasa pemrograman (Java), basis data (MySQL), dan UML untuk perancangan sistem.Pengembangan aplikasi monitoring jaringan komputer berbasis mobile menjadi penting dalam era digital untuk memantau kinerja jaringan secara real-time dan meningkatkan keamanan. Aplikasi ini memungkinkan administrator jaringan untuk mengawasi parameter seperti penggunaan bandwidth, status perangkat, dan deteksi anomali dari perangkat mobile. Dengan teknologi mobile, monitoring dapat dilakukan secara fleksibel dan responsif, membantu dalam pengambilan keputusan cepat untuk menjaga stabilitas dan keamanan jaringan.
Sistem Rekomendasi Berbasis Collaborative Filtering Pada E-Commerce Bella Paramita; Muhammad Ridho Ardiansyah
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

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Abstract

The rapid development of e-commerce causes information overload, where users have difficulty finding suitable products amidst the many choices. Recommendation systems are becoming a key component for improving user experience and driving sales. This research aims to design and implement a product recommendation system in e-commerce using the Collaborative Filtering method (both User-based and Item-based). This method works by analyzing user behavior patterns, such as transaction history, ratings, or clicks, to look for similarities between users or between items. The Cosine Similarity technique is used to measure similarity, while k-Nearest Neighbor (KNN) is applied to find the nearest neighbors to produce predictions. This system is designed to overcome the problem of data sparsity and provide personalized recommendations. System evaluation is carried out using the Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE) metric to measure the level of prediction accuracy. The research results show that a recommendation system based on Collaborative Filtering is able to produce relevant product recommendations and increase the effectiveness of marketing strategies on e-commerce platforms.
Co-Authors Abdul Harits M Akhmad Sayuti Indah Rahma Sari Irwansyah Serry Davizan Yuliza Aryani