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All Journal Nusantara Journal of Computers and its Applications Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka
Hafin, Aqid Fahri
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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ENHANCING DIGITAL COMPETENCIES OF STUDENTS AT MUHAMMADIYAH AL MUJAHIDEEN ISLAMIC JUNIOR HIGH SCHOOL THROUGH PYTHON-BASED CODING INSTRUCTION Darmanto, Darmanto; Pratama, Ridho Haikal; Hazar, Siti; Rajunaidi, Rajunaidi; Hafin, Aqid Fahri; Ridwan, Muhammad; Bidinnika, Muhammad Kunta; Murinto, Murinto; Yuliansyah, Herman
Jurnal Pengabdian Masyarakat Sabangka Vol 4 No 02 (2025): Jurnal Pengabdian Masyarakat Sabangka
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/sabangka.v4i02.1425

Abstract

In the digital era, programming has become an essential skill for students. This community service activity aimed to introduce Python-based coding instruction to students at Muhammadiyah Al Mujahideen Islamic Junior High School, combining digital literacy with Islamic character development. The activity followed a three-stage model: planning, implementation, and evaluation. During the two-day training, students were taught basic Python concepts such as syntax, variables, and data types using the W3Schools platform. Tasks were designed to evaluate their understanding, including coding exercises to calculate the area of basic geometric shapes. Results showed high enthusiasm and full task completion by all 20 participants, indicating that junior high school students can grasp foundational programming concepts when supported by clear instruction and engaging materials. This program demonstrates the potential of integrating Python into early education to support national education goals and foster future-ready, ethically grounded digital citizens.
Use of Deep Learning and k-Nearest Neighbor Algorithms for Recognition of Fruit Types Sulthan, M Burhanis; Hartiansyah, Fiqih Rahman; Hafin, Aqid Fahri
NJCA (Nusantara Journal of Computers and Its Applications) Vol 10, No 1 (2025): Edisi Juni 2025
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v10i1.293

Abstract

fruit recognition was done in this research specifically for fruit image. The recognition of fruit in this study can be implemented to know the number of fruits that exist. Fruit image trained into several labels (fruit types) that are classified by data testing. There are several processes and methods undertaken in this research until the classification process, one of this i.e. Gaussian filter to improve the quality of fruit image recognition. Furthermore, the feature extraction process uses Gabor filter and for feature selection, PCA technic is respectively used to select some of the best features. The selected feature will be classified using deep learning and k-nearest neighbor (k-NN) method. Moreover, the results of the processes done carried out in achieving an accuracy of 95.01%.
Co-Authors Bidinnika, Muhammad Kunta Darmanto Darmanto Hartiansyah, Fiqih Rahman Hazar, Siti Herman Yuliansyah, Herman Muhammad Ridwan Murinto Murinto Pratama, Ridho Haikal Rajunaidi, Rajunaidi Sulthan, M Burhanis