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All Journal JITCoS : Journal of Information Technology and Computer System Jurnal Pengabdian Masyarakat Indonesia
Rusma Riansyah
Universitas Islam Negeri Sumatera Utara
Computer Science & IT Control & Systems Engineering Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Implementasi Program KKN untuk Penguatan Literasi, Digitalisasi UMKM, dan Moderasi Sosial di Desa Ndokum Siroga Rusma Riansyah; Dahri Aziz; Servina Rahayu; Annisa Salsabila; Uqbatul Khoir Rambe
JURNAL PENGABDIAN MASYARAKAT INDONESIA Vol. 4 No. 3 (2025): Oktober : Jurnal Pengabdian Masyarakat Indonesia (JPMI)
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpmi.v4i3.5865

Abstract

Community service through the Kuliah Kerja Nyata (KKN) program in Ndokum Siroga Village aims to strengthen literacy, digitalize micro, small, and medium enterprises (MSMEs), and promote social moderation. This program was carried out over 30 days, involving 29 students from various disciplines. The methods used included literacy training for elementary school students to increase reading interest, digital marketing workshops to optimize MSMEs' market potential, and social dialogue sessions to facilitate communication among community members. The results showed a 60% increase in the reading interest of elementary school students, with activities encouraging reading habits outside school hours. Additionally, digitalization was successfully applied to 12 MSMEs, which are now able to operate their businesses online, expanding market reach and increasing revenue. The application of social moderation also showed positive results, with increased interfaith harmony reflected in joint social activities involving various community elements. This program successfully addressed existing community challenges such as low reading interest, limited access to MSME markets, and potential social tensions. The integrated approach combining education, economic empowerment, and social cohesion made a significant contribution to sustainable village development. This program is not only beneficial to the people of Ndokum Siroga Village but also serves as a model that can be replicated in other villages with similar challenges to achieve inclusive and sustainable development.
Implementation of a Favorite Course Search System Based on Students’ Average Grades Using the A* Algorithm Dwiky Oldi Amsyah; Rusma Riansyah; Dimas Aqila Aptanta; Muhammad Randy Fachrezi; Nasywa Roudhotul Firdaus
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Journal of Information Technology and Computer System
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.50

Abstract

Optimal selection of elective courses plays an important role in supporting students’ academic success and ensuring alignment between learning interests and final project preparation. This study aims to develop a favorite course search system based on the A-Star (A*) algorithm by utilizing students’ average grades as the main evaluation variable. The system was implemented using the Java NetBeans platform, supported by datasets consisting of course names, credit weights (SKS), and grade distributions. The A* algorithm was adapted through the integration of heuristic components, including Standard Deviation and Relative Credit Load, to improve accuracy in identifying optimal course recommendations. Experimental results demonstrate that the system is capable of generating recommendations with an accuracy rate of 95%, verified through comparison between system outputs and manual calculations. The results also show that the Mitigation course ranked highest with a score of 6.1, indicating strong student performance in that subject. Overall, the system provides a practical and efficient solution for academic decision-making, enabling students to select elective courses more strategically based on data-driven insights. This study contributes to the development of computational methods in educational recommendation systems and opens opportunities for further enhancement through integration with real academic databases.
Co-Authors Annisa Salsabila Dahri Aziz Dimas Aqila Aptanta Dwiky Oldi Amsyah Muhammad Randy Fachrezi Nasywa Roudhotul Firdaus Servina Rahayu Uqbatul Khoir Rambe