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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Information System for Educators and Professionals : Journal of Information System INOVTEK POLBENG INOVTEK Polbeng - Seri Informatika Matrix : Jurnal Manajemen Teknologi dan Informatika JURNAL INSTEK (Informatika Sains dan Teknologi) Batoboh : Jurnal Pengabdian Pada Masyarakat ILKOM Jurnal Ilmiah Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Mantik JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Sistem Informasi dan Sains Teknologi JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Proceeding Applied Business and Engineering Conference Journal of Embedded Systems, Security and Intelligent Systems TANJAK : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika dan Teknologi Informasi
Mansur Mansur
Teknik Informatika, Politeknik Negeri Bengkalis
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RANCANG BANGUN SISTEM PENCATATAN DATA OBAT BERBASIS WEBSITE PADA GUDANG FARMASI PUSKESMAS MESKOM Nauval Fatur Rahman; Mansur Mansur; Pretti Ristra
Jurnal Sistem Informasi dan Sains Teknologi Vol 7, No 2 (2025): Jurnal Sistem Informasi dan Sains Teknologi
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/sistek.v7i2.2414

Abstract

Puskesmas merupakan salah satu fasilitas kesehatan yang sangat penting di Indonesia, berfungsi sebagai pusat pelayanan kesehatan masyarakat tingkat pertama. Salah satu aspek penting dalam operasional Puskesmas adalah pengelolaan obat, yang mencakup seluruh kegiatan dari perencanaan hingga pelaporan. Pengelolaan obat yang baik sangat diperlukan untuk memastikan ketersediaan obat yang tepat dan mendukung tercapainya tujuan kesehatan. Namun, di Puskesmas Meskom, pencatatan dan pelaporan data obat masih dilakukan secara konvensional menggunakan Microsoft Excel dan pencatatan manual, yang mengakibatkan proses pencarian data dan pembuatan laporan menjadi lambat, tidak akurat, dan memakan waktu. Berdasarkan hasil observasi, petugas pengelola obat di Puskesmas Meskom juga mengungkapkan kesulitan dalam menyampaikan laporan stok obat ke Dinas Kesehatan Kabupaten Bengkalis. Untuk mengatasi masalah ini, penelitian ini bertujuan untuk merancang dan membangun sistem pencatatan data obat berbasis website di Gudang Farmasi Puskesmas Meskom. Sistem ini akan menyimpan data dalam bentuk elektronik yang memudahkan pencarian, pengelompokan, dan pembuatan laporan. Diharapkan dengan penerapan sistem ini, proses pengelolaan data obat di Puskesmas Meskom akan menjadi lebih efisien, akurat, dan mempermudah petugas dalam menyampaikan laporan tepat waktu.
Phishing Email Detection Using SVM with RBF Kernel Based on Manhattan Distance Asrianda Asrianda; Sujacka Retno; Beno Jange; Mansur Mansur
ILKOM Jurnal Ilmiah Vol 18, No 2 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i2.2806.268-280

Abstract

This study examines the performance of a Support Vector Machine (SVM) model with a Radial Basis Function (RBF) kernel for phishing email detection using Euclidean and Manhattan distance measures. The dataset consists of 3,600 email samples, including 2,400 legitimate emails and 1,200 phishing instances. The features are designed to capture both linguistic and structural characteristics of emails, including word count, vocabulary diversity, stop word usage, number of links and domains, presence of email addresses, spelling errors, and urgency-related terms. The experiments were conducted using two train-test split ratios, 80:20 and 70:30, combined with hyperparameter tuning of C and gamma across 15 iterations. The findings indicate that the Manhattan distance consistently outperforms the Euclidean distance, particularly in terms of recall and F1-score, which are critical for detecting the minority class. The model achieved a best accuracy of 78.33%, accompanied by noticeable improvements in recall and F1-score. These results suggest that the choice of distance function within the RBF kernel plays a crucial role in enhancing model sensitivity and generalization when dealing with imbalanced data. Furthermore, the iterative hyperparameter tuning process contributes significantly to improving both performance and model stability. Overall, the SVM-RBF approach with Manhattan distance provides an effective and reliable framework for phishing email detection in machine learning applications.
Co-Authors Agus Kusnayat Amy Sahrull Ramadhani Asrillah Asrillah Azzuhra, Nur Aida Beno Jange Daryuni, Mega DIAH ANGRAINA FITRI Diah Angraina Fitri Fazri Nugraha Fitri, Diah Angraina Hidayatur Romadhan Husaini, M. Iqbal Ilman Sholihin Jefry Subastian Juwanda, Farikhin Karisma, Elana Kasmawi Kasmawi Kasmawi Kasmawi Lidya Wati M Iqbal Husaini M. Isma Halil Mansur Mawardah, Dinda Nurul Muhammad Tisna Nugraha, Muhammad Tisna Nauval Fatur Rahman Nuranisa, Putri Nurasmawati, Nurasmawati Nurmi Hidayasari Nurmi Hidayasari Nurmi Hidayasari Nurmi Hidayasari Nurmi Hidayasari Nurmi Hidayasari, Nurmi Hidayasari Pretti Ristra Pretti Ristra Prity Virnanda Rahmah Rahmah Rahmah Rahmah Ramona sari Rapiana Rapiana Rezki Kurniati, Rezki Risma Yani Risma Yani Rusnani Rusnani Sovia Bella Sujacka Retno SYAHPUTRI, WIDYA Taufik Hidayat Toni Prahasto Widya Saputri Zuliar Efendi Zuliar Efendi Zuliar Efendi Zuliar Efendi Zuliar Efendi, Zuliar Efendi