Article Per Year (5 Year)
p-Index From 2021 - 2026
4.187
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JTT (Jurnal Teknologi Terpadu) Paradigma Journal of Sustainable Engineering: Proceedings Series Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Jurnal Ilmiah Intech : Information Technology Journal of UMUS Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Sains Indonesia DEVICE Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Informatika Teknologi dan Sains (Jinteks) Journal of Artificial Intelligence and Digital Business Jurnal Lentera Pengabdian Proceeding International Pelita Bangsa Jurnal Pelita Pengabdian SAINTEK
Aswan Supriyadi Sunge
Informatics Engineering Department, Faculty Of Engineering, Pelita Bangsa University, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
The Use of K-Means Algorithm Clustering in Grouping Life Expectancy (Case Study: Provinces in Indonesia) Nugraha, Dimas Reza; Zy, Ahmad Turmudi; Sunge, Aswan Supriyadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4171

Abstract

Life expectancy is defined as information that illustrates the age of the death of a population. Life expectancy is a general picture of the state of a region. If the infant mortality rate is high, then the life expectancy in the area is low. And vice versa, if the infant mortality rate is low, the life expectancy in the region is high. Life expectancy is also a benchmark for government actions in improving the welfare of society and the human development index. For this reason, it is necessary to group life expectancy data to make it easier to determine the provinces with high, middle, and low life expectancy. The results of cluster testing using the silhouette score method showed that two subjects had a low silhouette score level, which caused the cluster value to be less than optimal, namely East Java  & Gorontalo. The clustering results found that the cluster was divided into 3, namely cluster 1, with a high level of life expectancy consisting of 10 provinces, namely East Java, Riau, North Sulawesi, Bali, North Kalimantan, DKI Jakarta, West Java, Central Java, East Kalimantan and Special Region of Yogyakarta. Cluster 2 has a level of middle-life expectancy consisting of 18 provinces, namely Gorontalo, North Maluku, Central Sulawesi, South Kalimantan, North Sumatra, Bengkulu, West Sumatra, Central Kalimantan, Aceh, South Sumatra, Banten, Kep. Riau, South Sulawesi, Kep. Bangka Belitung, Lampung, West Kalimantan, Southeast Sulawesi and Jambi. Cluster 3, with a low level of life expectancy, consists of 6 provinces, namely West Sulawesi, Papua, Maluku, West Papua, West Nusa Tenggara, and East Nusa Tenggara.
Comparative Analysis of Earthquake Prediction with SVM, Naïve Bayes, and K-Means Models: Comparative Analysis of Earthquake Prediction with SVM, Naïve Bayes, and K-Means Models Muttaqin, Ahmad Fadhiil; Sunge, Aswan Supriyadi; Zy, Ahmad Turmudi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5085

Abstract

Earthquakes are natural disasters with significant impacts on people and the environment, so effective methods for prediction are needed to improve preparedness and risk mitigation. This study analyzes the performance of three algorithms Support Vector Machine (SVM), Naïve Bayes, and K-Means in predicting earthquakes in Indonesia using a dataset containing 4,645 historical data from BMKG processed through preprocessing, data separation, analysis, and performance evaluation with RapidMiner tools. The results show that SVM has the best performance with 99.87% accuracy, 99.83% precision, and 95.61% recall, making it highly relevant for earthquake prediction. Naïve Bayes achieved 90.31% accuracy and 95.08% recall, but the low precision (57.24%) shows the limitations of this model. K-Means successfully clusters earthquakes into two categories: small (3,661 data) and large (55 data) earthquakes, with a Davies-Bouldin Index value of 0.579, reflecting good clustering quality. Based on these results, SVM is recommended as a superior earthquake prediction model, while Naïve Bayes and K-Means are more suitable for additional analysis. This approach confirms the potential of machine learning algorithms in supporting future earthquake risk mitigation.
Dampak Pelatihan Pembuatan Toko Online Berbasis E-Commerce Dengan Metode Rapid Prototyping Bagi Siswa Sekolah Menengah Kejuruan Sunge, Aswan Supriyadi; Pramudito, Dendy K. Pramudito; Prasetyo, Sutrisno Aji Prasetyo
JPM: Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v5i4.2326

Abstract

Learning in e-commerce development is vital in helping understand digital business concepts, especially in overcoming the limitations of conventional learning methods, such as listening, observing, and taking notes. By using the ADDIE model, which includes analysis, design, development, implementation, and evaluation, this learning process provides a systematic and comprehensive approach. In this training, you will not only gain theoretical knowledge but also practical skills in modifying and managing e-commerce platforms. This learning aims to be able to understand and carry out the process of creating and managing an online business while stimulating creativity and enthusiasm for entrepreneurship. The results of this learning show that e-commerce development is very effective in facilitating the understanding of concepts and helping link theory to the world of work. Apart from that, the level of satisfaction of the female students was very significant, and they felt more prepared to apply the knowledge they had gained. This training proves that e-commerce development not only provides a better understanding of business but also prepares you with relevant skills to face the challenges of an ever-evolving digital world.
Co-Authors Abdul Halim Anshor Afriantoro, Irfan Agung Nugroho Agus Supriyadi Agus Suwarno, Agus Ahmad Turmudi Zy Aji, Prasetyo Wicaksono Amali, Amali Anggara, Bangkit Akbar Anshor, Abdulhalim Antika Zahrotul Kamalia Aprilia Nur Sa'adah Budiarto, Eko Dendy K. Pramudito Dendy K. Pramudito Dodit Ardiatma Edora, Edora Edy Widodo Edy Widodo Fatchan , Muhammad Febyan Sulastri Hamdani Hamdani Hamzah Muhammad Mardi Putra Juan Fakhri Khalis Sofi Kurniasih, Nabila Listian Indriyani Achmad Miftahuljannah Muttaqin, Ahmad Fadhiil Nanang Tedi Kurniadi Naya, Candra Nugraha, Dimas Reza Pramudito, Dendy K. Pramudito, Dendy K. Pramudito Prasetyo, Sutrisno Aji Prasetyo, Sutrisno Aji Prasetyo Pratama, Nur Priyo, Basuki Edi R. R. Wening Ken Widodasih Riady, Sasmitoh Rahmad Sari, Putri Anggun Septiawan Dwi Pramukti Suprapto Suprapto Suzanna, Suzanna Tedi Kurniadi, Nanang Tedi, Nanang Tyas Ismi Trialfhianty Warnars, Harco Leslie Hendric Spits Wiyanto, Tri Ngudi Wulandari, Anna Zahrotul Kamalia, Antika Zy, Ahmad Turmudi