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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi CONSEN: Indonesian Journal of Community Services and Engagement
Ibrahim, Deva
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Religion Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Neuroscience Physics Social Sciences Transportation Other

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Analisis Model Sistem Informasi Pembelajaran Adaptif Menggunakan Machine Learning untuk Optimalisasi Hasil Belajar Mahasiswa Andryadi, Ansen; Zulkifli, Ridwan; Ibrahim, Deva; Aulya, Syifa; Puspita, Novia Nurul; Amalia, Dhita Ayu; Agustina, Nadya Sri
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 9, No 1 (2026): Februari 2026
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v9i1.10540

Abstract

Abstrak-Perkembangan teknologi digital dan pembelajaran daring menuntut sistem pembelajaran yang mampu menyesuaikan dengan kebutuhan individual mahasiswa untuk meningkatkan hasil belajar. Namun, banyak institusi pendidikan masih menggunakan pendekatan pembelajaran yang kurang adaptif sehingga efektivitas belajar belum optimal. Penelitian ini mengangkat persoalan tersebut dengan menganalisis model sistem informasi pembelajaran adaptif yang memanfaatkan machine learning untuk mengoptimalisasi hasil belajar mahasiswa. Tujuan penelitian adalah merancang dan mengevaluasi model sistem informasi pembelajaran adaptif yang mampu memberikan rekomendasi pembelajaran personal secara dinamis berdasarkan data performa dan pola belajar mahasiswa. Metode penelitian yang digunakan adalah penelitian dan pengembangan (RD) dengan pendekatan kuantitatif untuk menguji efektivitas model menggunakan data praktikum mahasiswa. Alat utama dalam penelitian ini adalah algoritma machine learning yang diterapkan pada platform pembelajaran berbasis web. Temuan penelitian menunjukkan bahwa penggunaan model adaptif berbasis machine learning secara signifikan meningkatkan ketercapaian hasil belajar mahasiswa dibandingkan metode pembelajaran tradisional. Implikasi penelitian ini dapat menjadi referensi bagi pengembangan sistem pembelajaran modern yang lebih responsif dan personal di perguruan tinggi, serta memperkuat penerapan teknologi kecerdasan buatan dalam pendidikan. Rekomendasi untuk penelitian selanjutnya adalah memperluas aplikasi model ini ke konteks pembelajaran lain dan integrasi dengan fitur pembelajaran yang lebih variatif.Kata Kunci : Sistem Informasi Pembelajaran; Machine Learning; Optimalisasi Hasil Belajar; Personalisasi Pembelajaran; Pendidikan Tinggi; Abstract - The rapid development of digital technology and online learning has driven the need for learning systems that can adapt to individual student needs in order to improve learning outcomes. However, many educational institutions still rely on less adaptive learning approaches, resulting in suboptimal learning effectiveness. This study addresses this issue by analyzing an adaptive learning information system model that utilizes machine learning to optimize student learning outcomes. The purpose of this research is to design and evaluate an adaptive learning information system model capable of providing dynamic, personalized learning recommendations based on students’ performance data and learning behavior patterns. The research employs a Research and Development (RD) methodology with a quantitative approach to test the effectiveness of the model using student practicum data. The main tool in this study is a machine learning algorithm implemented within a web-based learning platform. The findings indicate that the use of a machine learning–based adaptive model significantly improves students’ learning achievement compared to traditional learning methods. The implications of this study suggest that the proposed model can serve as a reference for the development of more responsive and personalized modern learning systems in higher education, as well as strengthen the implementation of artificial intelligence technologies in education. Future research is recommended to expand the application of this model to other learning contexts and to integrate more diverse learning features.Keywords : Learning Information System; Machine Learning; Learning Outcome Optimization; Personalized Learning; Higher Education;
Implementation of Online-Based Marketing for MSMES in Pasirhandap and Pagerwangi Areas: Implementasi Pemasaran UMKM Berbasis Online di Kawasan Pasirhandap, Pagerwangi Ubaidilah, Ardian; Nurmahmudah, Lutfiana; Faizal, Muhamad; Ibrahim, Deva; Salsabila, Salsabila; Apriliani, Diah
CONSEN: Indonesian Journal of Community Services and Engagement Vol. 5 No. 2 (2025): Consen: Indonesian Journal of Community Services and Engagement
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/consen.v5i2.2236

Abstract

This community service program was carried out as an effort to empower Micro, Small, and Medium Enterprises (MSMEs) in the Pasirhandap area, Pagerwangi Village, through digital-based marketing assistance. The main problem faced by MSME actors in this area is limited access to digital technology and a lack of understanding of modern promotional strategies. Therefore, this program was designed to provide practical and applicable training, ranging from brand identity creation, utilization of digital platforms such as Shopee and Grab Merchant, to education on the importance of business legality. The program was implemented in three stages: an initial seminar, technical training, and direct mentoring. The results of the activity showed a significant improvement in participants’ understanding and ability to implement digital marketing strategies, as well as increased awareness of the importance of innovation and technological adaptation in the development of small businesses.
Co-Authors Agustina, Nadya Sri Amalia, Dhita Ayu Andryadi, Ansen Aulya, Syifa Diah Apriliani Faizal, Muhamad Nurmahmudah, Lutfiana Puspita, Novia Nurul Salsabila, Salsabila Ubaidilah, Ardian zulkifli, ridwan