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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Infotech Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI International Journal of New Media Technology Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal ULTIMA InfoSys Jurnal ULTIMATICS Jurnal ULTIMA Computing Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Tekno Kompak Jurnal Tekinkom (Teknik Informasi dan Komputer) G-Tech : Jurnal Teknologi Terapan BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi dan Komunikasi Journal of Applied Data Sciences DEDIKASI PKM Prosiding Konferensi Nasional PKM-CSR Indonesian Community Journal Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Journal of Artificial Intelligence and Digital Business
Ni Made Satvika Iswari
Universitas Primakara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Personalized Learning System Based on Artificial Intelligence to Enhance Learning Effectiveness: A Bibliometric Analysis Ni Made Satvika Iswari
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7355

Abstract

The integration of artificial intelligence (AI) in personalized learning systems has emerged as a transformative approach to address diverse educational needs and enhance learning effectiveness. However, comprehensive insights into the research landscape, trends, and challenges remain underexplored. This study aims to systematically map and analyse the development of AI-driven personalized learning systems over the past decade to understand their evolution, thematic focus, and future directions. To achieve this, a bibliometric analysis was conducted on 368 Scopus-indexed publications (2015–2025). Utilizing VOSviewer, the analysis reveals a significant surge in research output post-2021, with conference papers and articles dominating scholarly communication. Key themes include adaptive learning, machine learning algorithms, and educational innovation, while emerging clusters highlight advancements in generative AI (e.g., ChatGPT) and language models. Findings indicate that AI-based systems improve academic performance, engagement, and retention through tailored content and real-time feedback. However, challenges such as data privacy, algorithmic bias, and accessibility disparities persist. This study provides a data-driven synthesis of the field’s intellectual structure, offering actionable insights for educators, policymakers, and researchers to optimize AI’s potential in creating equitable and effective learning environments.
Prediksi Kesehatan Mental Pengguna Berdasarkan Konsumsi Konten Pada Media Sosial Menggunakan Metode Random Forest Putri, Ni Luh Putu Adela Sartian; Iswari, Ni Made Satvika; Juliharta, I Gede Putu Krisna
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5440

Abstract

Penelitian ini bertujuan memprediksi tingkat risiko kesehatan mental pengguna media sosial berdasarkan pola konsumsi konten dan intensitas interaksi di platform digital menggunakan metode Random Forest. Fenomena meningkatnya penggunaan media sosial pada kelompok usia muda membawa dua sisi: manfaat komunikasi dan informasi, namun juga berpotensi memicu kecemasan, stres, gangguan tidur, hingga penurunan produktivitas ketika digunakan berlebihan dan tidak terkontrol. Data penelitian dikumpulkan melalui kuesioner daring (Google Form) pada responden aktif media sosial dengan variabel utama meliputi durasi penggunaan harian, waktu akses (pagi–larut malam), jenis platform yang sering digunakan (Instagram, TikTok, Twitter/X), serta frekuensi interaksi negatif. Data kemudian melalui tahapan pembersihan, transformasi, dan konversi numerik sebelum diproses pada Orange Data Mining. Model Random Forest mengklasifikasikan responden ke dalam tiga kategori risiko, yaitu Tidak Berisiko, Cenderung Berisiko, dan Risiko Tinggi. Hasil menunjukkan bahwa durasi penggunaan yang panjang (≥3,5 jam), akses pada malam hari (terutama setelah pukul 19.00–21.00), serta frekuensi interaksi negatif yang tinggi merupakan faktor paling kuat dalam meningkatkan risiko gangguan mental. Evaluasi model memperlihatkan kinerja yang baik dan stabil, ditunjukkan oleh nilai AUC yang tinggi pada tiap kelas serta akurasi yang konsisten dalam mendeteksi kondisi pengguna. Temuan ini menegaskan pentingnya pemantauan kebiasaan digital sebagai langkah deteksi dini, sekaligus menjadi dasar edukasi penggunaan media sosial yang lebih sehat untuk menjaga keseimbangan psikologis pengguna.
Rancang Bangun Game Edukasi Penyakit Rabies Menggunakan Unity Dengan Metode Game Development Life Cycle Mulyosaputro, Matthew Alden; Iswari, Ni Made Satvika; Wijaya, I Nyoman Yudi Anggara
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.13354

Abstract

Rabies, which is usually transmitted through dog bites, is one of the common diseases in Indonesia. Based on data from Indonesia Ministry of Health, there were 31,113 cases of rabies animal bites and 11 deaths caused by rabies in 2023. Although efforts to eradicate rabies have been made in Indonesia, it has not been carried out completely due to the lack of public awareness about rabies. Therefore, there needs to be a means that can be used to increase public awareness about rabies. In this study, the author designed and created a game that aims to educate the public about rabies and how to prevent it. The rabies educational game was created using the Game Development Life Cycle method and was created using Unity software. The game produced in this study is a rabies education game in the form of a story-based choice game where the player's choice will impact the player's success in preventing or failing to handle rabies. From the test results, it can be concluded that the rabies education game is able to entertain players and educate players about rabies and how to prevent it.
Analyzing Student Sentiments and Insights on Generative AI for Independent Learning in Universities Iswari, Ni Made Satvika; Wijaya, I Nyoman Yudi Anggara; Yuniari, Ni Putu Widya
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1083

Abstract

Transformations in higher education brought about by Generative AI have significantly changed how university students’ access, comprehend, and develop learning materials. This study explores Indonesian university students’ perceptions and experiences regarding the use of Generative AI for independent learning, employing qualitative surveys together with sentiment analysis powered by machine learning. Data were collected from open-ended questionnaires and analyzed using four key algorithms, such as Naive Bayes, Logistic Regression, Random Forest, and Linear SVM, to classify student sentiments towards generative AI technologies. These four classical machine learning models were employed as baseline algorithms commonly used in sentiment analysis to benchmark performance on small, imbalanced educational datasets before applying more complex transformer-based methods. In addition to quantitative analysis, this study also implements thematic analysis of open-ended responses to identify prominent issues, challenges, and student recommendations concerning the use of generative AI in learning. Evaluation results identified Linear SVM as the most consistent model, with the highest weighted F1-score (0.63), although all models showed limitations in detecting negative sentiment due to class imbalance (only three negative samples out of forty responses), which affected model generalization. Key findings indicate that students perceive Generative AI as a supportive tool that accelerates understanding, creativity, and reference searching; however, they remain wary of risks related to dependency, reduced originality, and academic integrity dilemmas. This article recommends the implementation of ethical policy, AI digital literacy training, and enhancement of campus infrastructure to ensure that AI technologies enrich the learning process without compromising student independence and integrity.
PENERAPAN DATA MINING UNTUK MENENTUKAN KELAYAKAN KENDARAAN SEPEDA MOTOR BEKAS MENGGUNAKAN ALGORITMA C4.5 Ni Kadek Juliani; Ni Made Satvika Iswari; Nengah Widya Utami
INFOTECH journal Vol. 11 No. 2 (2025)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v11i2.15338

Abstract

Determining the feasibility of used motorcycles is one of the challenges for companies in selecting attributes that cover various factors, such as physical condition, maintenance history, and reasonable price. In this study, the researcher aims to analyze the existing problems and provide decision results by applying the C4.5 algorithm to determine the feasibility of used motorcycles based on relevant data. The C4.5 algorithm has the capability to build decision trees to automate and improve the accuracy of the feasibility determination process. In this research, attributes such as motorcycle model, year, engine, kilometers, fuel type, modifications, engine overhaul, oil type, transmission, engine type, and displacement are used as determining variables.Furthermore, to avoid overfitting that may occur due to overly complex decision trees, the researcher also applies pruning techniques to the C4.5 algorithm. Pruning functions to trim insignificant branches of the tree so that the model becomes simpler. With pruning, it is expected that the resulting decision tree will be not only accurate but also efficient, enabling the feasibility determination process of used motorcycles to be conducted optimally. Therefore, after applying pruning techniques, the model achieved an accuracy of 72.41%, precision of 68.42%, recall of 86.67%, and F1-score of 76.47%.
RANCANG BANGUN LMS BERBASIS MOODLE UNTUK PENINGKATAN KUALITAS PENDIDIKAN DI SMP GENTA SARASWATI GIANYAR Ni Putu Gunaprya Dharmapatni; Ni Made Satvika Iswari; I Nyoman Yudi Anggara Wijaya
INFOTECH journal Vol. 11 No. 2 (2025)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v11i2.15831

Abstract

Penelitian ini bertujuan untuk merancang dan menerapkan Learning Management System (LMS) berbasis Moodle di SMP Genta Saraswati sebagai upaya mempermudah guru dalam mendistribusikan materi ajar dan mengelola tugas siswa secara daring. Pengembangan sistem dilakukan menggunakan model ADDIE yang mencakup tahap analisis, desain, pengembangan, implementasi, dan evaluasi. Evaluasi sistem dilakukan dengan melibatkan 30 responden yang terdiri atas guru dan siswa melalui kuesioner berbasis teori SEPENTES, yang menilai aspek kemudahan penggunaan, kelengkapan fungsi, aksesibilitas, dan stabilitas sistem. Hasil evaluasi menunjukkan bahwa sekitar 80% pengguna merasa LMS sangat bermanfaat dalam mendukung proses pembelajaran. Skor rata-rata tertinggi diperoleh pada aspek aksesibilitas dengan nilai 4,5 dari 5, sedangkan skor terendah terdapat pada aspek kelengkapan fungsi dengan nilai 3,9, yang menunjukkan perlunya pengembangan fitur tambahan. Selain memberikan manfaat langsung bagi sekolah, penelitian ini juga membantu pengembang memperoleh kompetensi dalam analisis kebutuhan, perancangan sistem e-learning, serta penyusunan dan analisis instrumen evaluasi. Secara keseluruhan, LMS ini diharapkan mampu menjadi solusi untuk mendukung pembelajaran digital yang efektif, interaktif, dan berkelanjutan di sekolah
Co-Authors A. A. Istri Ita Paramitha Adhi Kusnadi Adnyani, Dewa Ayu Anggi Afriliana, Nunik Agustyan Hidayat Andre Rusli Andre Utomo Martliong Anugrah Cahya Dewi, Putri Bagus Nugraha Sindhu, I Gd Putu Bimo Satriantoro David Domarco Dennis Gunawan Dewi, Putri Anugrah Cahya Dharma, Eddy Muntina Dwi Eva Pramesti, Ni Made Dwiyanti Gunaswari, Made Dyah Ayu Anggreini Tuasikal Eddy Muntina Dharma Eko K. Budiardjo Fredlina , Ketut Queena I Gede Juliana Eka Putra I Gede Juliana Eka Putra I Gede Prana Yoga I Gede Putu Krisna Juliharta I Made Surya Kumara I Nyoman Yudi Anggara Wijaya I Nyoman Yudi Anggara Wijaya I Putu Eka Indrayana Juliana Eka Putra, I Gede Kadek Intan Janeta Pratiwi Ketut Queena Fredlina Lin, Lin Andriani Luthfialmas Fakhrizki Malik Abdul Ghani Marlinda Vasty Overbeek MB Nugraha Moeljono Widjaja Mulyosaputro, Matthew Alden Muntina Dharma, Eddy Nengah Widya Utami Ni Kadek Juliani Ni Putu Gunaprya Dharmapatni Ni Putu Noviyanti Kusuma Ni Putu Widya Yuniari Nyoman Purnama, Nyoman PERMANA, LEON FARREL AGUNG Putri, Ni Luh Putu Adela Sartian Putu Krisna Juliharta, I Gede Ranny Ranny Reza Setiabudi Risa Rahayu Setiawati, Ni Wayan Robi Rianto Ryan Adiputra Samuel Christoper Santo Syakh Alam, Helmy Wella Wella Wella Wella Widya Utami, Nengah Winarno Winarno Yaman Khaeruzzaman Zainal Arifin Hasibuan