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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF SCIENCE AND SOCIAL RESEARCH International Journal of Advances in Data and Information Systems INFOKUM Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Jurnal Minfo Polgan (JMP) Journal of Science Technology (JoSTec) Jurnal Pengabdian Masyarakat Nusantara Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Pengabdian kepada Masyarakat Jurnal Pustaka Dianmas Journal of Technology and Computer (JOTECHCOM) LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics JIPITI: Jurnal Pengabdian kepada Masyarakat International Journal of Applied Mathematics and Computing. International Journal of Educational Insights and Innovations (IJEDINS) Outline Journal of Community Development Proceeding of The International Conference on Electrical Engineering and Informatics Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia Jurnal Pengabdian Masyarakat Variasi
M. Rhifky Wayahdi
Universitas Battuta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Mathematics Nursing Public Health Social Sciences Veterinary Other

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AI APPROACH TO PREDICT STUDENT PERFORMANCE (CASE STUDY: BATTUTA UNIVERSITY) Wayahdi, M. Rhifky; Ruziq, Fahmi; Ginting, Subhan Hafiz Nanda
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2332

Abstract

Penelitian yang dilakukan menggunakan pendekatan kecerdasan buatan (AI) pada proses prediksi kinerja mahasiswa Universitas Battuta. Model kecerdasan buatan yang digunakan adalah model Random Forest. Penulis menggunakan tiga dataset berbeda dengan 300 pohon keputusan untuk proses pelatihan dan pengujian dengan model Random Forest dan melakukan uji coba dengan tiga variasi model. Model pertama (RF-1) menunjukkan akurasi yang tinggi yaitu sebesar 90%, sedangkan model kedua (RF-2) dan ketiga (RF-3) masing-masing memperoleh akurasi sebesar 89%. Matriks konfusi dan laporan klasifikasi (presisi, perolehan, dan skor f1) digunakan untuk mengevaluasi kinerja model kecerdasan buatan yang digunakan. Pada kategori “lulus”, ketiga model memiliki performa yang baik dengan presisi dan perolehan 90–95%. Pada kategori “distinction”, model pertama (RF-1) dan ketiga (RF-3) memiliki presisi dan recall yang lebih baik dibandingkan model kedua (RF-2). Sedangkan pada kategori “gagal”, model kedua (RF-2) menunjukkan performa yang sedikit lebih unggul dibandingkan model lainnya. Hasil penelitian ini menunjukkan bahwa model Random Forest mampu menghasilkan akurasi yang cukup tinggi dalam memprediksi kinerja siswa, yaitu berkisar 80–90%. Dengan demikian, model Random Forest merupakan metode yang cukup efektif untuk memprediksi kinerja siswa. Hasil ini diharapkan dapat digunakan oleh universitas untuk mengidentifikasi mahasiswa yang memerlukan intervensi dini dan meningkatkan strategi pembelajaran yang lebih efektif.
Expert System untuk Rekomendasi Pemilihan Bahasa Pemrograman bagi Pemula Menggunakan Algoritma Decision Tree Manza, Yuke; Wayahdi, M. Rhifky
LogicLink Vol. 2 No. 1, Juni 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i1.10924

Abstract

This study develops an expert system based on the Decision Tree algorithm to recommend suitable programming languages for beginners, addressing the challenge of selecting the right language amid the abundance of options and diverse learning goals. This topic is significant because choosing the appropriate language can accelerate the learning process and improve the effectiveness of programming education. The research methodology includes the creation of a synthetic dataset comprising 1,500 entries, with the addition of 5% noise. This noise is introduced to simulate real-world data imperfections and to test the model's robustness against unclean or imperfect data. The next stages involve data preprocessing through encoding and normalization, followed by modeling using the Decision Tree algorithm with hyperparameter optimization to enhance model performance. Evaluation results show an accuracy of 95%, with learning goals (38% contribution) and platform preference (35%) emerging as the most influential factors in decision-making. A 10-fold cross-validation produced an average error of 0.046, indicating model stability across various data subsets. Feature importance analysis revealed that the model logically prioritizes technical relevance, for example, by ranking learning goals and platform preference above demographic features, as these are more directly related to the context and practical use of programming languages. The implemented system successfully provided relevant recommendations, such as Python for Data Science and JavaScript for Web Development. This study concludes that the Decision Tree algorithm is effective for recommendation systems based on user profiles, although data enhancement is needed for minority classes such as Java. These findings contribute to the development of more personalized and adaptive programming learning support tools.
EDUKASI BAHAYA GADGET DAN FESTIVAL KEBAIKAN: WUJUD PENGABDIAN UKM PRO.ASTA UNIVERSITAS BATTUTA Ruziq, Fahmi; Wayahdi, M. Rhifky; Nanda Ginting, Subhan Hafiz; Wahyuni, Dewi; Sridewi, Nurmala
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3393

Abstract

Abstract: The development of digital technology brings both conveniences and challenges for children. Excessive gadget use can negatively impact children’s physical, psychological, and social well-being. The community service programme "Education on the Dangers of Gadgets and Kindness Festival" aims to provide education about the dangers of excessive gadget use while introducing various healthy and enjoyable alternative activities. The method applied was participatory and educational through counselling, educational games, traditional games, and a kindness festival. The results showed an increase in children’s awareness of the negative impacts of gadgets and their interest in engaging in beneficial non-gadget activities. This activity is expected to become a preventive effort to reduce children's dependence on gadgets in the digital era.            Keywords: children's activities; educational gadgets; kindness festival; educational games; community service.  Abstrak: Perkembangan teknologi digital membawa kemudahan sekaligus tantangan bagi anak-anak. Penggunaan gadget yang berlebihan dapat berdampak negatif terhadap kesehatan fisik, psikologis, dan sosial anak. Kegiatan pengabdian kepada masyarakat “Edukasi Bahaya Gadget dan Festival Kebaikan” bertujuan untuk memberikan edukasi tentang bahaya penggunaan gadget berlebihan sekaligus mengenalkan berbagai aktivitas alternatif yang sehat dan menyenangkan. Metode yang digunakan bersifat partisipatif dan edukatif melalui penyuluhan, permainan edukatif, permainan tradisional, dan festival kebaikan. Hasil kegiatan menunjukkan peningkatan kesadaran anak-anak tentang dampak negatif gadget serta tumbuhnya ketertarikan terhadap aktivitas non-gadget yang bermanfaat. Kegiatan ini diharapkan dapat menjadi salah satu solusi preventif dalam menekan ketergantungan anak terhadap gadget di era digital. Kata kunci: aktivitas anak; edukasi gadget; festival kebaikan; permainan edukatif; pengabdian masyarakat 
LENSA TEKNOLOGI: MENGABADIKAN SEMANGAT ANAK-ANAK DI SANGGAR KEADILAN SMH INDONESIA Wayahdi, M Rhifky; Ruziq, Fahmi; Ginting, Subhan Hafiz Nanda
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3357

Abstract

 Abstract: This community service initiative addresses the lack of documentation at Sanggar Keadilan SMH Indonesia, which limits evaluation and promotional materials. The participatory video documentation method engaged 20 children aged 7-15 years using DSLR and smartphone devices with passive observational techniques during a one-day activity. The outputs include a 15-minute documentary and short content that enhanced the sanggar's visibility while shifting children's perception of gadgets from entertainment to creative tools. The project demonstrates the efficacy of low-tech approaches in community documentation and its potential adaptability for various empowerment contexts.            Keywords: video documentation; community empowerment; literacy media; simple technology; sanggar  Abstrak: Kegiatan pengabdian ini dilatarbelakangi oleh minimnya dokumentasi kegiatan di Sanggar Keadilan SMH Indonesia yang berdampak pada terbatasnya bahan evaluasi dan promosi. Metode yang digunakan adalah dokumentasi video partisipatif selama satu hari dengan melibatkan 20 anak usia 7-15 tahun, menggunakan perangkat DSLR dan smartphone, serta teknik pengambilan gambar observasional pasif. Hasilnya berupa video dokumenter 15 menit dan konten pendek yang tidak hanya meningkatkan visibilitas sanggar, tetapi juga mengubah persepsi anak tentang gadget sebagai alat kreasi. Kegiatan ini membuktikan efektivitas pendekatan low-tech dalam pendokumentasian komunitas serta potensi adaptasinya untuk berbagai konteks pemberdayaan. Kata kunci: dokumentasi video; literasi media; pemberdayaan komunitas; sanggar; teknologi sederhana
WORKSHOP GAMES EDUKASI UNTUK ORANG TUA: PENDAMPINGAN BELAJAR MENYENANGKAN ERA DIGITAL DI SANGGAR KEADILAN SMH INDONESIA Ginting, Subhan Hafiz Nanda; Ruziq, Fahmi; Wayahdi, M Rhifky
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3358

Abstract

Abstract: The role of parents in assisting children to learn in the digital era is increasingly crucial, especially in fostering an interest in learning that is fun and meaningful. However, not all parents have adequate knowledge and skills in utilizing digital technology as an educational tool. This community service activity aims to increase the capacity of parents in assisting children's learning process through educational games that are in accordance with current technological developments. The workshop was held at Sanggar Keadilan SMH Indonesia located in Medan, with the main target of parents from the assisted community. The implementation method included a participatory approach through socialization, hands-on training, simulation of the use of educational games based on applications and web, and reflective discussion sessions. The results of the activity showed an increase in parents' understanding and skills in selecting, using and integrating educational games as learning tools for children. In addition, participants showed high enthusiasm in trying out various educational game platforms and stated that this approach helped create a more interactive and fun learning atmosphere at home.            Keywords: Educational Games, Learning Assistance, Digital Age, Sanggar Keadilan SMH Indonesia.  Abstrak: Peran orang tua dalam mendampingi anak belajar di era digital semakin krusial, terutama dalam menumbuhkan minat belajar yang menyenangkan dan bermakna. Namun, tidak semua orang tua memiliki pengetahuan dan keterampilan yang memadai dalam memanfaatkan teknologi digital sebagai sarana edukatif. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kapasitas orang tua dalam mendampingi proses belajar anak melalui media permainan edukatif (games edukasi) yang sesuai dengan perkembangan teknologi saat ini. Workshop dilaksanakan di Sanggar Keadilan SMH Indonesia yang berlokasi di Medan, dengan sasaran utama para orang tua dari komunitas dampingan. Metode pelaksanaan meliputi pendekatan partisipatif melalui sosialisasi, pelatihan langsung, simulasi penggunaan games edukasi berbasis aplikasi maupun web, serta sesi diskusi reflektif. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan orang tua dalam memilih, menggunakan, dan mengintegrasikan games edukasi sebagai alat bantu belajar anak. Selain itu, para peserta menunjukkan antusiasme tinggi dalam mencoba berbagai platform permainan edukatif dan menyatakan bahwa pendekatan ini membantu menciptakan suasana belajar yang lebih interaktif dan menyenangkan di rumah. Kata kunci: Games Edukasi, Pendampingan Belajar, Era Digital, Sanggar Keadilan SMH Indonesia. 
DIABETES PREDICTION BASED ON MEDICAL RECORDS (PIMA INDIANS DIABETES DATASET) USING K-NN Ruziq, Fahmi; Wayahdi, M. Rhifky; Ginting, Subhan Hafiz Nanda
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.2981

Abstract

Abstract: The development of predictive technologies, especially artificial intelligence (AI) and machine learning, has opened up great opportunities in the health sector, including early detection of chronic diseases such as diabetes. This study aims to implement the K-Nearest Neighbors (KNN) algorithm in predicting the likelihood of a person having diabetes based on medical record data from the Pima Indians Diabetes Dataset. The dataset consists of 768 samples with eight key health features. The analysis process includes data cleaning, data distribution exploration, and data preparation for the modelling process. The distance between data is calculated using the Euclidean formula, and normalization is performed so that all features have equal weight. The data was then divided into training and test data with a ratio of 80:20. The analysis results showed an unbalanced class distribution, with more non-diabetic patients than those with diabetes. The age group of 21-30 years dominates in the dataset. The implementation of KNN in this study shows that the method is effective for medical classification based on numerical data. This research demonstrates the potential of KNN as a practical and easy-to-implement early diagnosis tool in data-driven health systems. Keyword: K-Nearest Neighbors, diabetes prediction, machine learning, medical data, classification. Abstrak: Perkembangan teknologi prediktif, khususnya kecerdasan buatan (AI) dan pembelajaran mesin (machine learning), telah membuka peluang besar dalam bidang kesehatan, termasuk deteksi dini penyakit kronis seperti diabetes. Penelitian ini bertujuan untuk mengimplementasikan algoritma K-Nearest Neighbors (KNN) dalam memprediksi kemungkinan seseorang menderita diabetes berdasarkan data rekam medis dari Pima Indians Diabetes Dataset. Dataset terdiri dari 768 sampel dengan delapan fitur kesehatan utama. Proses analisis meliputi pembersihan data, eksplorasi distribusi data, serta persiapan data untuk proses modeling. Jarak antar data dihitung menggunakan rumus Euclidean, dan dilakukan normalisasi agar seluruh fitur memiliki bobot yang seimbang. Data kemudian dibagi menjadi data latih dan uji dengan rasio 80:20. Hasil analisis menunjukkan distribusi kelas yang tidak seimbang, dengan jumlah pasien non-diabetes lebih banyak dibandingkan yang menderita diabetes. Kelompok usia 21–30 tahun mendominasi dalam dataset. Implementasi KNN dalam studi ini menunjukkan bahwa metode ini efektif digunakan untuk klasifikasi medis berbasis data numerik. Penelitian ini mendemonstrasikan potensi KNN sebagai alat bantu diagnosis awal yang praktis dan mudah diimplementasikan dalam sistem kesehatan berbasis data. Kata kunci: K-Nearest Neighbors, prediksi diabetes, machine learning, data medis,                     klasifikasi.
Penerapan Ilmu Sistem Informasi untuk Efisiensi Manajemen Kearsipan di Universitas Battuta Davita, Davita; Wayahdi, M. Rhifky
JIPITI: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 3 (2025): Agustus 2025 - JIPITI: Jurnal Pengabdian kepada Masyarakat
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Kegiatan pengabdian kepada masyarakat ini berfokus pada penerapan praktis ilmu sistem informasi dalam lingkungan kerja nyata, khususnya pada sistem persuratan dan kearsipan di Universitas Battuta. Pentingnya kegiatan ini adalah untuk menjembatani kesenjangan antara teori akademis dengan praktik profesional yang dihadapi mahasiswa. Metode yang digunakan dalam pengabdian ini adalah partisipasi aktif yang meliputi observasi alur kerja, wawancara dengan staf, pencatatan data kinerja sistem, serta dokumentasi proses bisnis di bagian persuratan. Hasil dari kegiatan ini menunjukkan bahwa mahasiswa mampu mengaplikasikan konsep-konsep dari mata kuliah seperti Manajemen Data dan Informasi, Analisis Sistem, dan Etika Profesi secara langsung untuk membantu operasional institusi. Selain itu, kegiatan ini berhasil meningkatkan keterampilan teknis dan soft skills yang esensial bagi mahasiswa sebagai persiapan memasuki dunia kerja. Kesimpulannya, program ini terbukti efektif sebagai sarana hilirisasi ilmu pengetahuan yang memberikan nilai tambah bagi institusi mitra serta meningkatkan kompetensi mahasiswa secara signifikan.
Predicting Smartphone Addiction Levels with K-Nearest Neighbors Using User Behavior Patterns Wayahdi, M. Rhifky; Ruziq, Fahmi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4905

Abstract

Smartphones have become an integral part of everyday life, but their ever-increasing popularity has raised growing global concerns about excessive use (nomophobia), which impacts quality of life, mental health, and academic performance. Existing research often relies on subjective questionnaires, limiting scalability and objectivity. This study addresses this gap by developing a machine learning model to predict smartphone addiction levels through an objective analysis of user behavior patterns. This research evaluates the effectiveness of the K-Nearest Neighbor (KNN) algorithm, identifies the most influential behavioral features, and assesses the model's classification performance. Using a dataset of 3,300 user behavior entries with 11 features, a waterfall-based framework was employed for data preprocessing, model design, and evaluation. The KNN model achieved 95% accuracy in classifying addiction levels. Permutation Feature Importance analysis confirmed ‘App Usage Time’ and ‘Battery Drain’ as the two most influential predictive features. This study demonstrates that KNN is a powerful and viable method for objectively classifying smartphone addiction. The findings provide a strong foundation for developing scalable, AI-driven early detection and intervention systems, offering significant contributions to the fields of computer science and digital well-being.
Web-Based Diabetes Risk Prediction System Using K-NN on Kaggle Early Stage Diabetes Dataset Ruziq, Fahmi; Wayahdi, M. Rhifky
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5277

Abstract

Diabetes mellitus affects approximately 537 million adults globally, and its rising prevalence poses serious health and economic burdens. Early detection is crucial to reduce risks of complications and improve patient outcomes. This study aims to design and implement a web-based diabetes risk prediction system using the K-Nearest Neighbors (K-NN) algorithm to support early detection based on symptoms. The system utilizes the Kaggle Early Stage Diabetes Risk Prediction Dataset containing 520 records with 17 symptom attributes and one class label. Data preprocessing includes converting categorical data into numerical values, discretizing age into predefined ranges, and applying min-max scaling to normalize feature values. K-NN classification was conducted with K values of 1, 3, and 5, using the PHP Machine Learning (PHP-ML) library and MySQL database integration. The system achieved its highest accuracy of 93.46% at K = 1. Manual testing confirmed that the system processes symptom inputs correctly and provides predictions consistent with training data. This web-based tool offers an accessible platform for early diabetes risk screening, supporting self-assessment and triage. It demonstrates that PHP-ML can effectively implement machine learning in a web environment and can be further enhanced through parameter optimization and integration with larger, more diverse datasets to strengthen generalization.
Decision Support System for Students Final Project Title Acceptance at Ganesha Polytechnic Medan using Analytical Hierarchy Process (AHP) Method Ramadhan, Wisnu; Wayahdi, M. Rhifky; Hasibuan, Eka Hayana
Journal of Technology and Computer Vol. 1 No. 3 (2024): August 2024 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Many students are confused about determining the title that has been standardized by the head of study program. Is the title they are proposing relatively easy and in accordance with what is standardized by the head of study program or could it actually make things difficult for the student? The decision making system method used is Analytical Hierarchy Process (AHP) with the criteria of level of difficulty, reference source, number of similar titles and reference accreditation. The manufacturing stages carried out in this research used the waterfall and web-based method. Making this application uses data processing procedures, Data Flow Diagrams and MySQL DBMS. The output of the research I have made is that it can make it easier for students to submit the title of their final assignment, making it easier for the head of study program to sort out whether the title that will be submitted by the student is in accordance with the standards set by the head of study program and can also assess at the same time whether the title is easy and suitable for use as a final assignment.
Co-Authors Anzani, Nurul Baginda Harahap Davita, Davita Dewi Wahyuni Dewi Wahyuni Dinur Syahputra Dinur Syahputra Dinur Syahputra Ellanda Purwawijaya Fatahul Ahmad Dzikri Ginting, Subhan Hafiz Nanda Guntur, Surya Hasibuan, Eka Hayana Hutasoit, Rutmian Mariama Ihsan Primas Danu John John M. Arya Wardana Manza, Yuke Mughnyanti, Mayang Nanda Ginting, Subhan Hafiz Nasution, Auliana Nur Alisya, Siti Nurhajijah, Nurhajijah Ramadhan, Wisnu Rutmian Mariama Rutmian Mariama Hutasoit ruziq, fahmi Sheila Try Thania Sridewi, Nurmala Subhan Hafiz Nanda Ginting Subhan Hafiz Nanda Ginting Subhan Hafiz Nanda Ginting Surya Darma Surya Darma Surya Guntur Syafitri Ramadhani Syed Hassan Ali Thania, Sheila Try Zaki, Mohammed