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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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Produksi Video Company Profil Fakultas Teknologi Universitas Battuta Medan dengan Adobe Premier CC 2019 Surya Darma; John John; M. Rhifky Wayahdi; Ihsan Primas Danu
Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia Vol. 3 No. 2 (2025): Komunitas: Hasil Kegiatan Pengabdian Masyarakat Indonesia
Publisher : Asosiasi Riset Ilmu Tanaman Dan Hewani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/komunitas.v3i1.126

Abstract

This study aims to produce a company profile video for the Faculty of Technology, Battuta University, Medan using Adobe Premiere CC 2019 software. This company profile video is designed to provide a clear picture of the vision, mission, organizational structure, facilities, and superior programs at the Faculty of Technology, Battuta University, Medan. The production process of this video goes through several stages, namely planning, shooting, processing visual materials, and editing to produce a video that is in accordance with the communication objectives to be conveyed. Adobe Premiere CC 2019 was chosen as the main tool in video editing because of the ability of this software to provide various professional editing features, such as transition settings, visual effects, color adjustments, and audio processing that supports the quality of the final video results. The results of this study are in the form of a company profile video that can be used as a promotional media, which is expected to improve the image and attractiveness of the Faculty of Technology, Battuta University, Medan in the eyes of prospective students and the general public. With this video, it is hoped that information about the faculty can be conveyed more effectively and attractively.
Pelatihan Pembuatan Game Edukatif untuk Orang Tua dalam Meningkatkan Literasi Digital Anak Usia Dini di Sanggar Keadilan SMH-Indonesia Nurmala Sridewi; M. Rhifki Wayahdi; M. Arya Wardana
Jurnal Pengabdian Masyarakat Variasi Vol. 1 No. 2 (2024)
Publisher : LPPM STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Seiring berkembangnya teknologi, maka literasi digital anak usia dini menjadi semakin penting di era digital saat ini. Hal ini memiliki dampak positif dan negative. Oleh karena itu orang tua wajib membekali anak dengan literasi agar mereka dapat menggunakan teknologi dengan bijak dan aman. Penelitian ini mengkaji peran orang tua dalam memfasilitasi perkembangan literasi digital anak melalui pelatihan pembuatan game edukatif. Kegiatan pelatihan dilaksanakan di Sanggar Keadilan SMH-Indonesia. Hasil penelitian ini menunjukkan bahwa pelatihan ini tidak hanya meningkatkan kemampuan orang tua dalam membuat game edukatif tetapi juga memperkuat hubungan antara orang tua dan anak melalui kegiatan bersama.
Decision Tree-Based Student Graduation Prediction System at the Faculty of Technology, University of Battuta Syafitri Ramadhani; Fahmi Ruziq; M. Rhifky Wayahdi
Journal of Technology and Computer Vol. 3 No. 2 (2026): May 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

On-time graduation is an important indicator of academic quality in higher education. However, the Faculty of Technology at Battuta University still faces the challenge of low on-time graduation rates among students. This study designed a graduation prediction system based on the C4.5 Decision Tree Algorithm by utilizing the academic data of students from the 2022–2024 batch, including GPA, IPS, failed courses, academic leave, status, and attendance. The method used is a quantitative approach with data mining classification techniques, and the system is implemented web-based using PHP and MySQL. The results show that the C4.5 algorithm is capable of accurately predicting student graduation potential and producing classification rules that are easy to understand. This system can help academic advisors and study programs detect students at risk of graduating late at an early stage so that appropriate follow-up actions can be taken.
Implementasi Metode WASPAS pada Sistem Penerimaan Anggota Baru M. Rhifky Wayahdi; Fahmi Ruziq
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13504

Abstract

Sistem pengambilan keputusan banyak membantu kehidupan manusia, seperti untuk mengidentifikasi dan memprediksi kanker, mengklasifikasikan gambar, dan menemukan rute terpendek adalah beberapa masalah yang dapat diselesaikan oleh teknologi pengambilan keputusan. Kasus yang sedang dibahas memiliki banyak pendekatan sistem pengambilan keputusan yang dapat digunakan. WASPAS adalah salah satu metode sistem pendukung keputusan yang paling populer. Ini adalah metode pengambilan keputusan yang efektif untuk memecahkan masalah pemilihan algoritma. Dalam penelitian ini, penulis akan menerapkan dan menganalisis metode WASPAS dalam proses penerimaan anggota baru di UKM Pro.asta. Penulis akan menentukan kriteria-kriteria terkait yang akan dijadikan variabel penilaian pada proses penerimaan anggota baru beserta nilai bobotnya masing-masing. Pemberian bobot pada masing-masing kriteria sangat berpengaruh pada hasil akhir. Penelitian menunjukkan bahwa metode ini sangat bermanfaat bagi semua pihak yang terlibat dalam proses penerimaan anggota baru Pro.asta. Adanya metode pengambilan keputusan ini akan mengurangi kesalahan penilaian dan mempercepat proses pengambilan keputusan.
Sistem Pendukung Keputusan Seleksi Karyawan Baru dengan Simple Additive Weighting pada PT. Technology Laboratories Indonesia Fahmi Ruziq; M. Rhifky Wayahdi
Jurnal Minfo Polgan Vol. 11 No. 2 (2022): Article Research
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v11i2.13506

Abstract

Perkembangan teknologi informasi yang pesat memberikan dampak signifikan dalam berbagai aspek kehidupan, memudahkan pemrosesan data, analisis data, dan menghasilkan informasi relevan. Sistem Pendukung Keputusan (SPK) dengan metode Simple Additive Weighting (SAW) menjadi langkah strategis dalam pengambilan keputusan. Studi ini mengevaluasi aplikasi SAW pada seleksi karyawan baru PT. Technology Laboratories Indonesia dan mengintegrasikannya dengan metode pengumpulan data melalui studi lapangan dan studi pustaka. Hasil normalisasi dan perangkingan memberikan peringkat yang efisien dalam menentukan karyawan terpilih. Kesimpulannya, penerapan SAW pada SPK dapat menyederhanakan proses seleksi, meningkatkan efisiensi, transparansi, dan obyektivitas, memberikan dampak positif bagi pengelolaan organisasi, serta mendukung pengambilan keputusan yang lebih terinformasi.
Optimization of Weighting in the WASPAS Method with Analytic Hierarchy Process (Case Study Selection of New Members at Programmer Association of Battuta) M. Rhifky Wayahdi; Fahmi Ruziq
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13997

Abstract

Penelitian ini bertujuan untuk mengoptimasi metode WASPAS dengan cara menerapkan metode AHP pada proses pembobotan kriteria. Tujuannya adalah untuk meningkatkan kinerja WASPAS dalam pengambilan keputusan. Penelitian ini mengevaluasi metode WASPAS dalam hal pembobotan kriteria yang kurang optimal, sehingga diusulkan penggunaan AHP untuk meningkatkan konsistensi dan akurasi dalam pengambilan keputusan. Analisis menunjukkan bahwa hasil perankingan yang diperoleh yaitu nilai tertinggi 1,83 untuk Person-3 dan nilai terendah 0,769 untuk Person-4. WASPAS memberikan keputusan berdasarkan nilai kriteria input, dan pembobotan setiap kriteria secara signifikan sangat mempengaruhi hasil akhir. Oleh karena itu, optimalisasi WASPAS dengan memasukkan AHP untuk pembobotan menjadi sangat penting. Hasil pembobotan AHP konsisten dan seimbang, karena membandingkan tingkat kepentingan antara satu kriteria dengan kriteria lainnya. Studi ini menyimpulkan dan membuktikan bahwa melakukan optimasi dengan metode AHP pada proses pembobotan di metode WASPAS merupakan langkah yang efektif untuk meningkatkan kualitas dan keandalan keputusan yang dihasilkan.
Implementation of SAW Method in Website-Based Application (Case Study: New Employee Recruitment at PT. Technology Laboratories Indonesia) Fahmi Ruziq; M. Rhifky Wayahdi
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13998

Abstract

Penelitian ini bertujuan untuk mengimplementasikan metode Simple Additive Weighting (SAW) dalam aplikasi berbasis website guna mendukung proses penerimaan karyawan baru di PT. Technology Laboratories Indonesia (PT. Technolabs). Sejak didirikan pada tahun 2022, PT. Technolabs telah menghadapi tantangan signifikan dalam proses seleksi karyawan, yang dilakukan secara manual. Proses manual ini rentan terhadap subyektivitas, ketidakkonsistenan penilaian, dan memakan waktu yang lama, sehingga menghambat efisiensi dan produktivitas perusahaan. Metode SAW dipilih karena kemampuannya yang efektif dalam menangani masalah-masalah tersebut melalui pendekatan penjumlahan tertimbang, yang memberikan bobot pada setiap kriteria penilaian. Dalam penelitian ini, kriteria yang digunakan mencakup pendidikan, pengalaman kerja, keterampilan teknis, dan kemampuan interpersonal. Aplikasi ini dirancang dengan antarmuka yang user-friendly, memudahkan pengguna dalam memasukkan data pelamar, menetapkan bobot kriteria, serta melihat hasil normalisasi dan perangkingan secara real-time. Hasil penelitian menunjukkan bahwa aplikasi berbasis SAW ini mampu meningkatkan efisiensi proses seleksi dengan signifikan. Waktu pemrosesan yang sebelumnya memakan waktu lama dapat dipangkas, dan penilaian menjadi lebih akurat dan objektif. Pelamar dinilai berdasarkan kriteria yang telah ditetapkan, dan hasil perangkingan memberikan panduan yang jelas bagi manajemen dalam membuat keputusan penerimaan karyawan. Selain meningkatkan efisiensi dan akurasi, aplikasi ini juga memberikan kontribusi signifikan dalam bidang pengambilan keputusan berbasis teknologi. Implementasi metode SAW dalam aplikasi berbasis website ini tidak hanya bermanfaat bagi PT. Technolabs, tetapi juga dapat diadaptasi untuk berbagai keperluan seleksi dan penilaian lainnya di berbagai organisasi dan industri. Dengan demikian, penelitian ini memberikan model yang efektif dan efisien dalam seleksi karyawan, yang dapat meningkatkan produktivitas dan kinerja perusahaan secara keseluruhan.
K-Nearest Neighbor and Random Forest Algorithms in Loan Approval Prediction Syafitri Ramadhani; M. Rhifky Wayahdi
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.14345

Abstract

Loan approval prediction is an important task in the financial sector, which helps banking institutions and lenders make informed decisions regarding loan applications. This research compares the performance of two machine learning algorithms, namely K-Nearest Neighbor (KNN) and Random Forest (RF), in the context of loan approval prediction. The research methodology includes data collection, pre-processing, modeling, and evaluation. The analysis results showed that the Random Forest model performed better overall than KNN, with more true positives and true negatives, and fewer false positives and false negatives. In addition, Random Forest recorded higher accuracy, precision, recall, and F1-score values. These findings provide valuable insights for financial institutions in improving credit risk management strategies and decision-making regarding loan applications.
Website-Based Village Information System Design (Case Study: Ujung Batu III Village) M. Rhifky Wayahdi; Surya Guntur
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.14621

Abstract

This research aims to design a website-based village information system in Ujung Batu III Village, Hutaraja Tinggi, Padang Lawas, North Sumatra. With the rapid development of digital technology, websites have become an important tool for increasing information access, transparency and public participation. The research method used is the waterfall model, which includes the stages of communication, planning, modeling, construction and implementation. The research results show that the village information website has succeeded in increasing community access to important information, such as village activities and government programs. In addition, training provided to village officials and community representatives improves their skills in managing content sites, thereby encouraging community empowerment. This website also functions as a promotional tool to introduce the village's potential, including tourist attractions and local products, which can attract the attention of tourists and investors. Increased communication between the village government and the community via the website creates a more open and responsive channel. With a structured system, village information management can continue in a sustainable manner, ensuring the relevance and benefits of information for future generations. This research supports the development vision of Ujung Batu III Village and contributes to the welfare of the village community.
Predictive Modeling of Smartphone Addiction: Performance Evaluation of KNN, XGBoost, and Naive Bayes on Behavioral Patterns M. Rhifky Wayahdi; Fahmi Ruziq; Auliana Nasution; Ellanda Purwawijaya
Jurnal Minfo Polgan Vol. 15 No. 1 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i1.16178

Abstract

Excessive smartphone use has triggered a global crisis in the form of smartphone addiction, which negatively impacts mental health and productivity. Most current detection methods still rely on subjective questionnaires that are prone to bias. Therefore, this study aims to evaluate and compare the performance of machine learning-based predictive models—namely K-Nearest Neighbors (KNN), Naive Bayes, and Extreme Gradient Boosting (XGBoost)—in objectively classifying addiction levels based on user behavioral patterns. The research methodology adopts a standard machine learning workflow encompassing data preprocessing, model training, and performance evaluation using a dataset of 3,300 user activity log entries. Empirical results demonstrate that XGBoost yields superior classification performance, achieving an accuracy of 97.27% and an F1-Score of 96.70%, significantly outperforming the KNN (94.54%) and Naive Bayes (89.09%) algorithms. Further feature importance analysis confirms that App Usage Time is the most crucial predictor in detecting addiction. This study concludes that the XGBoost architecture is highly robust in handling non-linear behavioral feature interactions, enabling high-precision predictions. The implications of these findings provide a solid technical foundation for the development of automated early detection systems. Future research should consider expanding the dataset to include application categorization and integrating XGBoost modeling into real-time digital wellbeing application prototypes.
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