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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) Abdi Cendekia: Jurnal Pengabdian Masyarakat Komputasi : Jurnal Ilmiah Ilmu Komputer dan Matematika
Fathi Athallah Z
Universitas Islam Negeri Sumatera Utara
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A Analysis and Modeling Simulation King Kuphi Cafe Queuing System With Customer Arrival Variations Using Python Nurul Fikria Nurul_Fikria; Risky Ananta Pradana; Jelita Rahmah Zebua; Fathi Athallah Z
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 23 No. 1 (2026): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika.
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v23i1.78

Abstract

Queueing system modeling and simulation is an effective approach for analyzing service performance in business environments with dynamic customer arrival rates, such as at King Kuphi Cafe. This study aims to model the queueing system at the cafe with various variations in customer arrival rates using the queueing theory approach and simulate it using the Python programming language. The models used are the M/M/1 and M/M/c queueing systems, which allow analysis of changes in waiting time, queue length, server utilization, and service level based on variations in arrival (λ) and service (μ) parameters. The simulation was run using Python packages such as NumPy and SimPy to represent the arrival and service processes realistically. The results of the study show that an increase in the rate of customer arrivals significantly affects system performance, particularly in terms of an increase in average waiting time and queue length. In addition, adding more servers has been proven to reduce queue congestion and improve overall service quality. These findings are expected to serve as a basis for King Kuphi Cafe managers in making strategic decisions regarding the number of baristas and operational optimization to achieve more efficient service.
Classification of Herbal Plants Based on Leaf Images Using Gray Level Co-Occurrence Matrix and K-Nearest Neighbor Fahmi Nur Alimsyah Purba; Fathi Athallah Z; Alfin Alfarizi; Lailan Sofinah Harahap
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2291

Abstract

Herbal plants have long been used as traditional medicine. However, many people struggle to tell different herbal leaves apart because they look quite similar. This study tries to build a system that can recognize two types of herbal leaves, Moringa and Katuk, simply from their photos. We used GLCM to extract texture features from the leaves, then classified them using KNN. The dataset came from Kaggle, with 480 leaf images in total. Before processing, we cropped the images, resized them to 256x256 pixels, and converted them to grayscale. GLCM features were taken from four angles (0°, 45°, 90°, 135°) and then averaged. This gave us four texture values: contrast, correlation, energy, and homogeneity. We tested KNN with k values from 1 to 15 and five different distance metrics. The best result we got was 94% accuracy, using Manhattan distance with k=1. This system could help everyday people identify medicinal plants more easily without needing lab tests.
Penguatan Peran Perguruan Tinggi melalui KKN Berbasis Penelitian Tindakan Partisipatif di Desa Karang Bangun Fathi Athallah Z; M. Fadly Rizky Pratama; Endang Ekowati; Tasya Nabila; Amanda Zahra; Sakya Salsabila; Riska Annisah Ritonga; Alfin Alfarizi; Abdullah Harits Harahap; Rizky Zaidan Ketaren
Abdi Cendekia : Jurnal Pengabdian Masyarakat Vol 5 No 3 (2026): September
Publisher : Yayasan Zia Salsabila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61253/abdicendekia.v5i3.1270

Abstract

Kuliah Kerja Nyata (KKN) merupakan bentuk pengabdian mahasiswa kepada masyarakat yang mengintegrasikan Tri Dharma Perguruan Tinggi. Kegiatan ini bertujuan untuk mendeskripsikan pelaksanaan KKN UIN Sumatera Utara Tahun 2026 di Desa Karang Bangun, Kecamatan Siantar, Kabupaten Simalungun, dengan pendekatan Participatory Action Research (PAR) yang dipadukan dengan Community Based Research (CBR), Asset Based Community Development (ABCD), dan Service Learning (SL). Metode yang digunakan adalah deskriptif kualitatif dengan teknik observasi partisipatif, wawancara, dan dokumentasi selama periode 30 Juli hingga 30 Agustus 2026. Program unggulan yang dilaksanakan adalah upaya pencegahan stunting melalui pendampingan posyandu dan pembagian Makanan Bergizi Gratis (MBG), sedangkan program pendukung meliputi gotong royong kebersihan desa dan kantor desa, penyuluhan anti-bullying, edukasi bermedia sosial, pengenalan cita-cita, serta partisipasi dalam perayaan HUT RI ke-81. Hasil kegiatan menunjukkan bahwa seluruh program tercapai dengan tingkat partisipasi masyarakat yang tinggi, rata-rata 25 orang per kegiatan. Pendekatan PAR terbukti efektif dalam menumbuhkan kesadaran dan kemandirian masyarakat, khususnya dalam bidang kesehatan ibu dan anak, pendidikan karakter, serta kebersihan lingkungan. Kendala utama yang dihadapi adalah keterbatasan waktu dan jarak antar huta. Kegiatan KKN ini memberikan dampak positif yang berkelanjutan bagi masyarakat Desa Karang Bangun serta menjadi sarana pembelajaran kontekstual bagi mahasiswa.
Co-Authors Abdullah Harits Harahap Alfin Alfarizi Amanda Zahra Endang Ekowati Fahmi Nur Alimsyah Purba Jelita Rahmah Zebua Lailan Sofinah Harahap M. Fadly Rizky Pratama Nurul Fikria Nurul_Fikria Riska Annisah Ritonga Risky Ananta Pradana Rizky Zaidan Ketaren Sakya Salsabila Tasya Nabila