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All Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Ilmiah Sinus Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Innovative: Journal Of Social Science Research TOFEDU: The Future of Education Journal The Eastasouth Journal of Information System and Computer Science Journal Emerging Technologies in Education
Iwan Ady Prabowo
STMIK Sinar Nusantara
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Implementation of the Promethee Algorithm to Improve Data Accuracy in a Scholarship Selection Information System Halimah, Diana Nur; Hasbi, Muhammad; Prabowo, Iwan Ady
Jurnal Ilmiah SINUS Vol 22, No 2 (2024): Vol. 22 No. 2, Juli 2024
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v22i2.815

Abstract

The scholarship selection process at X University has traditionally relied on manual methods, primarily focusing on the highest GPA, which often leads to financial constraints and potential biases. This research aims to address these issues by improving the selection process for scholarship admissions using the Promethee method. By introducing new criteria such as residence status, parental education, employment status, income, home ownership, number of dependents, and life score, the study seeks to provide a more comprehensive and fair assessment. Data collection methods include observation, interviews, and literature study to understand the concept of scholarship selection. The research applied the Promethee algorithm to 20 students who received scholarships from Panasonic in 2023. Confusion matrix analysis showed an accuracy level of 50%, with a precision value of 100% and a recall value of 50%. Despite the need for improved accuracy, it is hoped that the Promethee method can help the X University Student Agency determine fairer and more efficient scholarship selections. This research is expected to contribute positively to improving the scholarship selection process at X University with a focus on efficiency and fairness.
Trends in Digital Twin Technology for Industry 4.0: A Bibliometric Study Judijanto, Loso; Qadriah, Laila; Prabowo, Iwan Ady; Widyatmoko, Widyatmoko; Sabila, Puji Chairu
The Eastasouth Journal of Information System and Computer Science Vol. 2 No. 02 (2024): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v2i02.382

Abstract

Digital Twin (DT) technology has emerged as a critical enabler of Industry 4.0, bridging the physical and digital worlds through real-time data integration, simulation, and optimization. This study conducts a comprehensive bibliometric analysis to explore the research trends, key contributors, and thematic clusters in DT research over the past decade. The analysis reveals China's leading role in DT research, supported by strong international collaborations with the United States, Germany, and other countries. Key themes include technological enablers such as IoT, sensors, and infrastructure, as well as emerging applications in sustainability, smart cities, and energy systems. Challenges such as risks, uncertainties, and feasibility constraints remain significant barriers to DT adoption, highlighting the need for interdisciplinary collaboration and standardization efforts. The study identifies opportunities for integrating DT with technologies like blockchain and AI, as well as expanding applications in healthcare and agriculture. These findings provide valuable insights for researchers, practitioners, and policymakers to advance DT technology and its transformative potential in Industry 4.0.
Physical Education in the Era of Artificial Intelligence: The Impact of AI Technology on Enhancing Sports Learning in Schools Fauzi, Muhammad Sukron; Yantiningsih, Erna; Judijanto, Loso; Prabowo, Iwan Ady
The Future of Education Journal Vol 4 No 4 (2025)
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v4i4.487

Abstract

This study aims to examine the impact of Artificial Intelligence (AI) technology in enhancing physical education learning in schools, with a focus on the application of AI in physical education. AI technology has begun to be implemented in various aspects of sports education, ranging from tracking students' physical activities to providing more personalized feedback. The literature review reveals that this technology can assist in monitoring students' performance more thoroughly and offer training programs tailored to individual physical abilities. Several studies reviewed, such as by Smith et al. (2020), show that the use of AI can improve students' physical skills by providing real-time feedback and more accurate training personalization. However, the implementation of AI technology also faces several challenges, such as inadequate technological infrastructure, limited training for teachers, and concerns related to student data privacy. Nonetheless, this study emphasizes that with proper support, AI technology can become a highly effective tool to enhance sports education in schools. Recommendations are made to strengthen teacher training, improve technological infrastructure in schools, and ensure appropriate policies for student data usage.
Pemanfaatan Media Youtube Channel Untuk Mendukung Pembelajaran Elektronik Learning pada Mata Kuliah Teknologi Pendidikan Vanchapo, Antonius Rino; Halik, Abdul; Arifin, Nofri Yudi; Pahmi, Pahmi; Prabowo, Iwan Ady
Innovative: Journal Of Social Science Research Vol. 3 No. 5 (2023): Innovative: Journal of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

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Abstract

Penelitian ini memiliki tujuan untuk menjelaskan cara memanfaatkan media YouTube Channel sebagai sarana pendukung dalam pembelajaran elektronik (e-learning) di mata kuliah Teknologi Pendidikan. YouTube Channel sudah menjadi salah satu platform yang populer dipergunakan dalam pendidikan online. Kajian ini menginvestigasi efektivitas penggunaan YouTube Channel dalam konteks pembelajaran Teknologi Pendidikan. Metode penelitian yang dipergunakan ialah analisa literatur dan konten. Hasil penelitian memperlihatkan jika YouTube Channel bisa menjadi alat yang sangat efektif dalam mendukung pembelajaran Teknologi Pendidikan. Kelebihannya mencakup aksesibilitas yang luas, fleksibilitas dalam penyampaian materi, serta kemampuan untuk menggabungkan berbagai jenis media seperti video, presentasi, serta diskusi interaktif. Mahamahasiswa melaporkan jika mereka merasa pembelajaran melalui YouTube Channel lebih menarik dan mudah dipahami dibandingkan dengan metode tradisional. Penggunaan media YouTube Channel bisa menjadi aset berharga dalam konteks pembelajaran Teknologi Pendidikan. Namun, perlu ada upaya berkelanjutan untuk mengembangkan serta meningkatkan penggunaan YouTube Channel supaya bisa mendukung pembelajaran yang lebih efektif dan bermanfaat.
Penerapan Teknologi QR Code untuk Penguatan Identitas Desa Wisata Sidowayah melalui Sistem Navigasi Jalan dan Pelestarian Informasi Budaya dan Potensi Alam Prabowo, Iwan Ady; Utami, Yustina Retno Wahyu; Prihanto, Prihanto; Qoriah, Annisa Nur; Berlian, Zam Zam; Dianita, Ardhia Dwi Ari; Muhariya, Ahmad
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 17, No 1 (2026): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v17i1.25011

Abstract

Desa Wisata Sidowayah menghadapi kendala signifikan dalam navigasi wisatawan dan promosi digital, yang menghambat potensi ekonomi dan budayanya. Sebanyak 85% wisatawan kesulitan menemukan objek wisata karena minimnya petunjuk arah, dan 70% narasi sejarah lokal berisiko punah karena belum terdokumentasi secara digital. UMKM lokal juga belum memiliki kemampuan pemasaran digital. Program pengabdian masyarakat ini bertujuan untuk menerapkan sistem navigasi berbasis QR Code terintegrasi dan website untuk memperkuat identitas desa dan mendukung UMKM. Metode pelaksanaan meliputi pengembangan kolaboratif: pengumpulan data sejarah lokal, pembuatan QR Code spesifik lokasi, pembangunan website komprehensif (sidowayah.smarttourism.id), pemasangan 75 papan fisik, serta pelatihan partisipatif untuk Kelompok Sadar Wisata (Pokdarwis) dan UMKM. Hasil kuantitatif dari 116 responden menunjukkan kepuasan pengguna yang tinggi (skor komposit 4,06/5), dengan skor tertinggi pada kelengkapan informasi sejarah (4,32) dan peningkatan pengalaman wisata (4,24). Program berhasil mentransformasi akses digital terhadap warisan budaya dan navigasi. Rekomendasi utama adalah pembentukan tim digital khusus untuk keberlanjutan dan penambahan fitur seperti audio guide untuk pengembangan ke depan.
A COMPUTER VISION APPROACH FOR CLASSIFYING CALIFORNIA PAPAYA RIPENESS USING K-NEAREST NEIGHBOR Wulandari, Tyas; Prabowo, Iwan Ady; Utami, Yustina Retno Wahyu; Raharja, Bayu Dwi; Wijayanto, Hendro
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 14, No 1 (2026): Jurnal Tikomsin, Vol 14, No.1, April 2026
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v14i1.1091

Abstract

Determining the ripeness level of California papaya is important for harvest decisions, sorting, distribution, and spoilage control. In practice, ripeness identification is still commonly performed visually and is therefore subjective. This study aims to develop a digital image-based classification system for California papaya ripeness using the K-Nearest Neighbor (K-NN) algorithm with Hue and Saturation features in the Hue Saturation Value (HSV) color space. The dataset consists of 90 primary images, divided into 60 training images and 30 testing images, with four ripeness classes: unripe, half-ripe, ripe, and rotten. All images were captured using a Xiaomi Mi A2 Lite smartphone and cropped to 1436 × 1000 pixels. Classification was conducted using Euclidean distance. The value of k was selected empirically through trial and error in the original study, and k = 9 was retained because it produced the most stable result on the available data while reducing the potential for class ties. The evaluation produced 22 correct predictions out of 30 test images, resulting in an accuracy of 73.33%. This revised manuscript strengthens the methodological reporting by clarifying parameter selection, documenting the data distribution and providing a literature-based comparison with alternative methods, such as Support Vector Machine (SVM) and Convolutional Neural Network (CNN). The findings suggest that K-NN with HSV features remains a feasible, low-cost baseline, although its performance should be improved through larger datasets, per-class evaluation reporting, and head-to-head comparisons on the same dataset.
Co-Authors Abdul Halik Agus Budhi Marendra Aji Pratama Wisnu Wardana Arief Gilang Ramadhan Arifin, Nofri Yudi Bela Septiana Berlian, Zam Zam Dianita, Ardhia Dwi Ari Didik Nugroho Dwi Remawati Fauzi, Muhammad Sukron Fryda Fatmayati Halimah, Diana Nur Hamsiah, Andi Hendro Wijayanto Hendro Wijayanto Heradi, Ade Miraldha Judijanto, Loso Kumarahadi, Yofita Kinanti Lilis Wulandari Mas'ud Muhammadiah Muhammad Hasbi MUHAMMAD HASBI Muhariya, Ahmad Nungky Kurnia Candra Pahmi Pahmi paulus harsadi Prihanto Prihanto, Prihanto Qadriah, Laila Qoriah, Annisa Nur Raharja, Bayu Dwi Riski Lunika Parmawati Riza Riza Sabila, Puji Chairu Saptomo, Wawan Laksito Yuly Setiyowati Sri Siswanti Sujud Aji Wantoro Teguh Susyanto Tulus Wahyuno Tyas Wulandari Vanchapo, Antonius Rino Wahyudi Wahyudi Wawan Laksito YS Widyatmoko Widyatmoko Wijayanto, Hendro Yantiningsih, erna Yohan Alief Rizaldy Yustina Retno Wahyu Utami