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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Query : Jurnal Sistem Informasi JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Pengabdian Masyarakat: Darma Bakti Teuku Umar Jurnal Pengabdian kepada Masyarakat Nusantara Djtechno: Jurnal Teknologi Informasi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) EXPLORER Prosiding Snastikom Jurnal ABDIMAS Budi Darma PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Computer and Technology
Haida Dafitri
Universitas Harapan Medan
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Journal : jurnal computer and technology

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EFEKTIVITAS SEGMENTASI MENGGUNAKAN VLAN DAN INTER VLAN ROUTING PADA JARINGAN KOMPUTER DI PERUSAHAAN Yazid Zaidan; Haida Dafitri
Journal Computer and Technology Vol. 3 No. 2 (2025): Desember 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v3i2.417

Abstract

Jaringan komputer tanpa segmentasi berpotensi menimbulkan permasalahan seperti tingginya trafik broadcast, rendahnya keamanan, dan sulitnya pengelolaan jaringan. Untuk mengatasi hal tersebut, penelitian ini menerapkan Virtual Local Area Network (VLAN) dan Inter-VLAN Routing pada topologi jaringan. VLAN digunakan untuk memisahkan jaringan berdasarkan divisi (Administrasi, Keuangan, IT Support, dan HRD) sehingga komunikasi dalam satu VLAN menjadi lebih efisien dan aman. Agar perangkat dari VLAN yang berbeda tetap dapat berkomunikasi, diterapkan konfigurasi Inter-VLAN Routing dengan metode router multi-interface. Implementasi dilakukan melalui perancangan topologi, konfigurasi switch untuk segmentasi VLAN, serta konfigurasi router sebagai penghubung antar VLAN. Hasil pengujian menunjukkan bahwa jaringan memiliki kualitas sangat baik berdasarkan parameter QoS: delay rendah (0–6 ms), packet loss 0%, dan jitter kecil. Dengan demikian, penerapan VLAN dan Inter-VLAN Routing terbukti meningkatkan efisiensi, keamanan, serta fleksibilitas jaringan, sehingga dapat menjadi solusi tepat bagi organisasi skala menengah hingga besar. Kata kunci: VLAN, Inter-VLAN Routing, Router, Segmentasi Jaringan
Beyond Intensity Gradients: A Lightweight Client-Side Morphological Framework for Robust Binary Image Segmentation Gregorius Ananta Sinaga; Haida Dafitri
Journal Computer and Technology Vol. 4 No. 1 (2026): July 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v4i1.408

Abstract

Edge detection in binary images frequently suffers from contour fragmentation when utilizing conventional gradient operators (e.g., Sobel, Canny), as they inherently rely on continuous intensity variations absent in discrete binary data. To address this, this study proposes a lightweight, client-side morphological gradient framework designed to structurally and topologically extract object boundaries based purely on spatial geometry. A modular web-based computational pipeline was developed using a PHP-JavaScript architecture, integrating adaptive Otsu binarization, dynamic kernel configurations, and core morphological computations. For rigorous algorithmic and engineering validation, the system was benchmarked against the conventional Canny detector using a dataset of 50 botanical images, supplemented by comprehensive white-box and black-box software testing involving 20 participants across 20 distinct test cases. Experimental results demonstrate that the proposed morphological framework achieves superior topological fidelity and boundary continuity. It secured an optimal F1-score of 0.9006 using a 3×3 disk structuring element, significantly outperforming the Canny detector’s F1-score of 0.7761. Furthermore, the method exhibits highly parallelizable efficiency, executing edge extraction at a mean runtime of 18.2 ms, more than twice as fast as the multi-stage Canny operator (42.5 ms). Software evaluations confirmed exceptional system reliability, yielding a 97.4% functional success rate, 95% overall module coverage, and an excellent usability score of 4.58/5.0. Ultimately, this research proves that shifting the paradigm from intensity differentiation to mathematical morphology offers a highly precise, robust, and computationally lightweight solution for real-time, web-native binary image segmentation.
Unlocking Customer Behavior in COD-based E-commerce: An Unsupervised Learning Approach Using Gaussian Mixture Model for Strategic Segmentation Andri Adlian Rangkuti; Haida Dafitri
Journal Computer and Technology Vol. 4 No. 1 (2026): July 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v4i1.409

Abstract

Customer segmentation in Cash on Delivery (COD) logistics is inherently challenging due to highly heterogeneous, skewed transaction data and elevated rejection rates, which frequently limit the efficacy of traditional deterministic clustering models. To address this, this study proposes a robust probabilistic segmentation framework utilizing the Gaussian Mixture Model (GMM) to extract actionable insights from complex COD operations. We analyzed 5,147 raw transaction records, meticulously aggregating them into 2,225 unique customer profiles engineered around three critical logistics-centric features: delivery frequency, total COD value, and average COD value. The model’s optimal configuration was rigorously determined using the Bayesian Information Criterion (BIC) to prevent overfitting, and the entire analytical pipeline was seamlessly integrated into an interactive, web-based Decision Support System (DSS). Empirical results demonstrate that a two-cluster solution optimally balances statistical fit and operational interpretability, clearly delineating "High-Value Active Customers" (68%) from "Low-Value Occasional Customers" (32%). Comparative analysis validates GMM’s superiority over baseline algorithms like K-Means, achieving a significantly higher Silhouette Score (0.64 vs. 0.51) and effectively capturing the non-spherical, overlapping data distributions characteristic of COD behaviors. Crucially, the probabilistic soft-clustering capability of GMM uniquely identified a transitional segment of 15.7% "boundary customers," offering logistics managers a nuanced, early-warning lens for preemptive risk mitigation and targeted interventions. Ultimately, this research bridges the critical gap between advanced probabilistic analytics and operational logistics, providing express delivery enterprises with a scalable, data-driven tool for dynamic route optimization, failed-delivery mitigation, and differentiated service personalization.
Co-Authors Abdul Jabbar Lubis Ade Putri Humaira Alwi Aulia Andi Marwan Elhanafi Andri Adlian Rangkuti Ari Usman Arief Budiman Arif Rahman Lubis Arnes Sembiring Asih, Munjiat Setiani Asri Tamara David David Diana Suita Dodi Siregar Dorlika Safitra Harefa Eddy Eddy Elpridayanti Saragih Erwin Panggabean Fakhrana Nadhila Gregorius Ananta Sinaga Ika Sari Imam Prayoghi Indra Roza Lisa Adriana Liza Fitriana M Rizky Pramana Putra M Tuahoryanda Tarigan Marina Elsera Muhammad Al Hafis Nst Muhammad Fitra Abdillah Muhammad Hafiz Al Hakim Muhammad Ridho Muhammad Yasir Lubis Nur Wulan Rachmat Aulia, Rachmat Rahman, Sayuti Ramli Reza Putra Ramadhan Rini Ida Astuti Risko Liza Rismayanti SAWITRI, DARA Septiana Dewi Andriana, Septiana Dewi Siti Sundari Sumi Khairani Tengku Mhd Diansyah Tri Fuji Mandala Yazid Zaidan Yogi Pratama Yunita Shara Lubis Yussa Ananda