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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen Jurnal Komtika (Komputasi dan Informatika)
Achmad, Refi Riduan
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisis Perbandingan Performa Algoritma Asimetris Elgamal Dan Merkle-Hellman-Knapsack Pada Pesan Teks Rahmadani, Nurika; Arifin, Zainal; Achmad, Refi Riduan; Hamdani, Hamdani
Jurnal Informatika Komputer, Bisnis dan Manajemen Vol 23 No 1 (2025): Januari 2025
Publisher : LPPM STMIK El Rahma Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61805/fahma.v23i1.158

Abstract

Perkembangan algoritma kriptografi ditandai dengan beragamnya jenis-jenis algoritma kriptografi  yang dapat digunakan dalam enkripsi dan dekripsi, seperti algoritma Elgamal dan Merkle-Hellman-Knapsack. Algoritma Elgamal didasarkan pada logaritma diskrit, sedangkan algoritma Merkle-Hellman-Knapsack didasarkan pada kurva aljabar eliptik. Penelitian ini bertujuan untuk mengetahui perbandingan performa algoritma Elgamal dan Merkle-Hellman-Knapsack dalam melakukan enkripsi dan dekripsi pesan teks. Analisis perbandingan dalam penelitian ini dilakukan dengan mengukur beberapa parameter, yaitu penggunaan memori Resident Set Size (RSS), penggunaan Central Processing Unit (CPU), ukuran ciphertext hasil enkripsi, dan waktu eksekusi. Penelitian dilakukan menggunakan 11 data plaintext dengan ukuran beragam. Hasil pengujian menggunakan ukuran plaintext 10.000 bytes pada metode Elgamal sebesar 51.114 bytes, sedangkan menggunakan metode Merkle Hellman Knapsack hanya sebesar 34.982 bytes.  Sementara itu, plaintext 100.000 bytes menggunakan metode Elgamal menghasilkan ciphertext sebesar 511.216 bytes dan Merkle Hellman Knapsack menghasilkan ciphertext sebesar 348.138 bytes. Hasil penelitian menunjukkan bahwa kedua algoritma dapat digunakan untuk mengamankan pesan teks, namun algoritma Elgamal lebih sesuai digunakan untuk sistem dengan keterbatasan memori dan CPU.
Kuliah kerja nyata sebagai katalis peningkatan budaya Keselamatan dan Kesehatan Kerja (K3) di Perusahaan Achmad, Refi Riduan; Supratman, Agus Ahmad; Hidayatullah, Hidayatullah; De Jesus, Maria Martina; Walhidayat, Mohammad Taufik; Nurhasanah, Nurhasanah; Hadi, Nur
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 6 (2025): November (In Progress)
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i6.34251

Abstract

Abstrak Program Kuliah Kerja Nyata di PT. Karunia Armada Indonesia, Kecamatan Tabang, Kabupaten Kutai Kartanegara, dilaksanakan untuk meningkatkan kesadaran dan kepatuhan karyawan terhadap aspek keselamatan dan kesehatan kerja. Kegiatan dilakukan melalui sosialisasi K3LH dan pendampingan praktik penerapan Lock Out Tag Out (LOTO) di area workshop. Metode pelaksanaan meliputi pelatihan interaktif, demonstrasi penggunaan APD, dan observasi perilaku keselamatan sebelum dan sesudah kegiatan. Program diikuti oleh 22 karyawan, dengan 14 orang diantaranya mengikuti pendampingan praktik LOTO secara langsung. Hasil evaluasi menunjukkan peningkatan kepatuhan penggunaan APD dari sekitar 60% menjadi 85%, serta peningkatan penerapan prosedur LOTO dari 30% menjadi 70% pada aktivitas perawatan alat. Perubahan ini mengindikasikan bahwa program KKN efektif dalam memperkuat pemahaman dan budaya keselamatan kerja karyawan, serta berkontribusi terhadap penerapan standar K3LH yang lebih konsisten di lingkungan industri. Kata kunci: Kuliah Kerja Nyata; K3LH; LOTO; keselamatan kerja; pengabdian masyarakat. AbstractThe Community Service Program (Kuliah Kerja Nyata—KKN) conducted at PT. Karunia Armada Indonesia, located in Tabang District, Kutai Kartanegara Regency, aimed to enhance workers’ awareness and compliance with occupational health and safety practices. The program was implemented through K3LH (Occupational Health, Safety, and Environment) socialization and hands-on mentoring on the application of Lock Out Tag Out (LOTO) procedures in the workshop area. The activities involved interactive training sessions, demonstrations of proper personal protective equipment (PPE) usage, and observational assessments conducted before and after the intervention. A total of 22 employees participated in the program, with 14 individuals taking part in direct LOTO practice mentoring. The evaluation results indicated an increase in PPE compliance from approximately 60% to 85%, as well as an improvement in LOTO implementation from 30% to 70% across maintenance activities. These findings demonstrate that the KKN program effectively strengthened workers’ understanding and safety culture, contributing to more consistent adherence to K3LH standards within the industrial environment. Keywords: community service program; K3LH; LOTO; workplace safety; industrial engagement.
Bridging academia and industry: model kolaborasi KKN mandiri dalam pemberdayaan masyarakat dan dunia kerja Achmad, Refi Riduan; Anggalo, Aditya Ramadan; Cahyo, Didik Dwi; Rahmasari, Fenni; Mursalim, Mursalim; Rahayu, Sinta Tri; Chadiq, Tommy Mohammad
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 6 (2025): November (In Progress)
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i6.34252

Abstract

Abstrak Program Kuliah Kerja Nyata (KKN) skema mandiri Unit 14 UNU Kalimantan Timur dilaksanakan melalui kolaborasi dengan mitra industri dan masyarakat sebagai upaya memperkuat hubungan antara perguruan tinggi dan dunia kerja. Kegiatan mencakup program sosial kemasyarakatan yang melibatkan 35 peserta, serta pelatihan teknis dan keselamatan kerja (K3) yang diikuti oleh 18 karyawan mitra industri. Metode pelaksanaan meliputi pengabdian langsung, sosialisasi, dan pelatihan berbasis praktik. Evaluasi kegiatan menunjukkan adanya peningkatan pemahaman peserta terhadap materi K3, tingginya partisipasi masyarakat, serta peningkatan kompetensi sosial dan teknis mahasiswa. Kolaborasi ini berdampak positif bagi mitra melalui peningkatan kesadaran K3 dan penguatan hubungan kemitraan. Temuan ini menegaskan bahwa skema KKN mandiri efektif dalam menjembatani dunia akademik dengan kebutuhan nyata industri dan masyarakat. Kata kunci: kuliah kerja nyata; pengabdian masyarakat; kolaborasi; industri; K3. AbstractThe independent Kuliah Kerja Nyata (KKN) program of Unit 14 at UNU Kalimantan Timur was implemented through collaboration with industrial partners and local communities as an effort to strengthen the linkage between higher education and the world of work. The activities included community social programs involving 35 participants, as well as technical and occupational safety (K3) training attended by 18 employees from partner companies. The implementation methods consisted of direct community engagement, socialization, and practice-based training. Evaluation results indicate an improvement in participants’ understanding of K3 materials, strong community participation, and enhanced social and technical competence among students. This collaboration has provided positive benefits for partner industries through increased K3 awareness and strengthened partnership relations. These findings affirm that the independent KKN scheme is effective in bridging academic knowledge with the practical needs of industry and society. Keywords: community service; community engagement; collaboration; industry; K3.
Optimasi Gradient Boosted Trees dalam Memprediksi Minat Nasabah untuk Berlangganan Pinjaman Berjangka Achmad, Refi Riduan; Zulfariansyah, Muhammad
Jurnal Komtika (Komputasi dan Informatika) Vol 9 No 2 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v9i2.15259

Abstract

This research focuses on optimizing the design parameters of Gradient Boosted Trees (GBT) to predict customer interest in subscribing to term loans. The study highlights the importance of tuning parameters such as the number of trees, tree depth, and learning rate to enhance the predictive accuracy of GBT. Through this optimization, the model aims to provide more precise insights into customer behavior, aiding financial institutions in making informed decisions and improving operational efficiency. The research compares GBT with other algorithms like Decision Trees and Random Forests, utilizing metrics such as accuracy, precision, recall, and AUC. The results indicate that GBT, with optimal parameter settings, outperforms the other models in predicting customer interest. The study concludes that GBT is an effective tool for market segmentation and can significantly contribute to more accurate predictions in financial services, ultimately helping companies develop better-targeted marketing strategies.
Co-Authors Anggalo, Aditya Ramadan Cahyo, Didik Dwi Chadiq, Tommy Mohammad De Jesus, Maria Martina Hamdani Hamdani Hidayatullah Hidayatullah Mursalim Mursalim Nur Hadi Nurhasanah Nurhasanah Rahayu, Sinta Tri Rahmadani, Nurika Rahmasari, Fenni Supratman, Agus Ahmad Walhidayat, Mohammad Taufik Zainal Arifin Zulfariansyah, Muhammad