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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer Seminar Nasional Informatika (SEMNASIF) JOIV : International Journal on Informatics Visualization SENTIA 2016 Jurnal Pengabdian Polinema Kepada Masyarakat International Journal of Multidisciplinary: Applied Business and Education Research JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Ilmiah Edutic : Pendidikan dan Informatika International Journal of Health, Engineering and Technology Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat
Mungki Astiningrum
Politeknik Negeri Malang
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Implementasi Infrastruktur Jaringan Untuk Mendukung Program Sertifikasi SMA Islam Kepanjen Kabupaten Malang Yuri Ariyanto; Yan Watequlis Syaifudin; Budi Harijanto; Dwi Puspitasari; Chandrasena Setiadi; Mungki Astiningrum
Jurnal Pengabdian kepada Masyarakat Vol. 11 No. 2 (2024): JURNAL PENGABDIAN KEPADA MASYARAKAT 2024
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/abdimas.v11i2.6054

Abstract

The Community Service Program intends to support the Empowering School Certification Program by establishing computer network infrastructure at the Islamic High School in Malang's Kepanjen region. According to analysis studies, the current network falls short of the online access criteria for certification tests. This intervention employed two essential approaches. The first option entails installing standard-based computer networks in the school laboratory facilities. The second option gives information technology (IT) educators extensive network management support. The Community Service Program Team of the State Polytechnic of Malang runs the initiative, which focuses on creating a reliable network topology and increasing the skills of the school's IT staff. This intervention is expected to increase overall educational quality and develop network infrastructure that will allow certification programs to be implemented. The accompanying seeks to provide expertise to Kepanjen's Islamic High School Team so that they can manage the network more independently. This community service project is designed to optimize the digital learning ecosystem, improve education and evaluation processes, and prepare students for the complexities of the digital age. This will be accomplished through collaboration between the Community Service Program team and the Islamic High School of Kepanjen District Malang.
Identifikasi Biometrik Dengan Ekstraksi Fitur Telapak Tangan Berbasis Machine Learning Kusumadewa Tutuko, Aryo Bagus; Astiningrum, Mungki; Suarjuna Batubulan, Kadek
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 3: Juni 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026133

Abstract

Perkembangan teknologi memungkinkan akses cepat dan aman ke berbagai layanan dan perangkat melalui identifikasi biometrik yang mengandalkan fitur unik manusia seperti sidik jari, retina, wajah, dan telapak tangan. Penelitian ini bertujuan untuk mengidentifikasi telapak tangan menggunakan metode ekstraksi fitur garis telapak tangan dengan pendekatan ROI (Region of Interest). Ekstraksi fitur garis telapak tangan diharapkan menjadi suatu fitur dari identifikasi telapak tangan sehingga mendapatkan hasil dengan akurasi yang tinggi dengan bantuan pembelajaran mesin. Metode yang digunakan dalam penelitian ini adalah Neural Network. Studi ini membahas bagaimana ROI diterapkan untuk memfokuskan pada area tertentu dari citra telapak tangan yang berisi informasi biometrik relevan seperti garis utama, kerutan, dan punggung bukit. Hasil penelitian menunjukkan banyaknya fitur ekstraksi yang ada dalam telapak tangan dapat meningkatkan akurasi dalam proses identifikasi telapak tangan. Penelitian ini berkontribusi dalam pengembangan sistem identifikasi biometrik dengan memperkenalkan metode ekstraksi fitur garis telapak tangan berbasis ROI yang mampu meningkatkan akurasi identifikasi hingga 80% melalui penerapan Neural Network.   Abstract Technological developments enable quick and secure access to various services and devices through biometric identification that relies on unique human features such as fingerprints, retina, face, and palm. This research uses the palm line feature extraction method with the ROI (Region of Interest) approach to identify palms. Palm line feature extraction is expected to be a feature of palm identification to get results with high accuracy with the help of machine learning. The method used in this research is Neural Network. This study discusses how ROI is applied to focus on specific areas of the palm image that contain relevant biometric information, such as main lines, wrinkles, and ridges. The results show that the number of extracted features present in the palm can increase the accuracy in the palm identification process. This research contributes to the development of biometric identification systems by introducing an ROI-based palm line feature extraction method that is able to increase identification accuracy up to 80% through the application of Neural Network.
Co-Authors Abdul Muhsyi Ade Putra Lesmana Adhitya Bhawiyuga, Adhitya Adittiyaputra, Diva Aldodhery, Zigrozora Krishy Amien, Moch Ma’ruf Amrozi, Aris Nur Annisa Puspa Kirana Ari Zanupratama Arie Rachmad Syulistyo Arif, Rizqya Zakyyatul Asyraq, Farhan Azharuddin Atiqah Nurul Asri Aulia Rachmannisa Diwantari Aura Kanza Caesaria Azkia Nury Farizah Batubulan, Kadek Suarjuna Budi Harijanto, Budi Candra Bella Vista Cecilia, Sintia Dardanela Chandrasena Setiadi Denny Nur Ramadhan Dhebys Suryani Hormansyah, Dhebys Suryani Dhike Almira Ramadiyah Dian Hanifudin Subhi Dika Rizky Yunianto Dinda, Elistya Rahma Diva Adittiyaputra DWI PUSPITASARI Dwi Puspitasari Dyah Ayu Irawati Dyah Ayu Irawati Dyah Ayu Irawati, Dyah Ayu DyahAyu Irawati Elistya Rahma Dinda Elly Fatmawati Elly Fatmawati, Elly Erfan Rohadi Excellina Excellina Excellina, Excellina Faisal Rahutomo Farhan Azharuddin Asyraq Farizah, Azkia Nury Gunawan Budi Prasetyo Ika Dyah Rahmawati Ika Kusumaning Putri Ilmi, Muhammad Fikrul Indra Dharma Wijaya Indra Dharma Wijaya, Indra Dharma Irawati, DyahAyu Kusumadewa Tutuko, Aryo Bagus Lesmana, Ade Putra M. Alfin Zakariya Maya Shoburu Rohmah Moch Ma’ruf Amien Moch Zawaruddin Abdullah Muhammad Fikrul Ilmi Mustika Mentari Nabilla Aqmarina Ariditya Ni’ma Shoumi, Milyun Pambudi, Sandy Priyo Pramana Yoga Saputra Pramudhita, Agung Nugroho Putra Prima Arhandi, Putra Prima Rahmad, Cahya Ramadiyah, Dhike Almira Rawansyah Rawansyah Rawansyah, Rawansyah Rentia Ayu Suprapto Ridwan Rismanto Rifa'i, Bahtiar Rizqya Zakyyatul Arif Rohmah, Maya Shoburu Rokhimatul Wakhidah Rosa Andrie Asmara Sandy Priyo Pambudi Sintia Dardanela Cecilia Siti Nuraisyah Sultan Achmad Qum Masykuro Nur Santiko Suprapto, Rentia Ayu Toga Aldila Cinderatama Ulla Delfana Rosiani Vivi Nur Wijayaningrum Yan Watequlis Syaifudin Yoppy Yunhasnawa Yuri Arianto Yuri Ariyanto Yuri Ariyanto Yuri Ariyanto Yushintia Pramitarini Zakariya, M. Alfin Zanupratama, Ari Zigrozora Krishy Aldodhery