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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI) JITK (Jurnal Ilmu Pengetahuan dan Komputer) INTECOMS: Journal of Information Technology and Computer Science Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JSAI (Journal Scientific and Applied Informatics) Jurnal Ilmu Teknik dan Komputer Journal of Computer Science and Engineering (JCSE) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sistem Informasi Dan E-Bisnis Jurnal Ilmu Komputer Dan Informatika Dedikasi Nusantara: Jurnal Pengabdian Masyarakat Pendidikan Dasar Sinergi: Jurnal Pengabdian Kepada Masyarakat JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) JCOSIS (Journal Computer Science and Information Systems) International Journal of Computing Science and Applied Mathematics-IJCSAM
Ayumi, Vina
Universitas Mercu Buana
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Penerapan Optimasi Convolutional Neural Network untuk Klasifikasi Multi-Kelas Tumor Otak pada Citra MRI Ayumi, Vina
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9986

Abstract

Brain tumors are among the most critical neurological diseases and require early and accurate diagnosis to support appropriate medical treatment. Magnetic Resonance Imaging (MRI) is widely used for brain tumor detection due to its high-resolution imaging capability; however, manual analysis of MRI images is time-consuming and highly dependent on the expertise of radiologists. Therefore, this study aims to apply an optimized Convolutional Neural Network (CNN) for multi-class brain tumor classification using MRI images. The dataset used in this study consists of 7,023 MRI images, categorized into four classes: glioma, meningioma, pituitary, and healthy, and divided into training, validation, and testing subsets. The research stages include image preprocessing, CNN architecture design, hyperparameter optimization, model training for 50 epochs, and performance evaluation. The training process achieved an accuracy of 87.44%, while the validation accuracy reached 85%, indicating good model generalization. Model evaluation on the test dataset using a confusion matrix, precision, recall, F1-score, and accuracy resulted in an overall accuracy of 77.8%.
PENGGUNAAN SISTEM EVALUASI PEMBELAJARAN AL QUR’AN BERBASIS GOOGLE FORM PADA SISWA SMA DAARUL FIKRI Hasanah, Uswatun; Ayumi, Vina
JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Vol. 6 No. 1 (2026): April
Publisher : Lembaga Penelitian Pengabdian Masyarakat Penerbitan dan Percetakan Indonesian Scholar Khiar Wafi (LPPMPP IKHAFI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jpmtt.v6i1.658

Abstract

Evaluasi pembelajaran Al-Qur’an di tingkat sekolah menengah masih banyak dilakukan secara manual, sehingga menimbulkan kendala dalam rekapitulasi nilai, risiko kehilangan data, dan keterlambatan pelaporan perkembangan siswa. Digitalisasi sistem penilaian menjadi kebutuhan mendesak untuk meningkatkan efisiensi, akurasi, dan transparansi administrasi pembelajaran keagamaan. Kegiatan pengabdian ini bertujuan mengimplementasikan sistem evaluasi pembelajaran Al-Qur’an berbasis Google Form pada siswa SMA Daarul Fikri. Metode yang digunakan adalah pendekatan service learning, yang mengintegrasikan pemberian solusi teknologi dengan pemberdayaan mitra melalui pelatihan teknis. Tahapan kegiatan meliputi observasi sistem manual, identifikasi kebutuhan penilaian (makhraj, tajwid, dan kelancaran bacaan), perancangan instrumen evaluasi digital, integrasi Google Form dengan Google Sheets, serta sosialisasi dan pelatihan penggunaan sistem melalui perangkat mobile. Program dilaksanakan di Pesantren Terpadu Daarul Fikri, Cikarang Barat, Kabupaten Bekasi, dengan sasaran pengajar Al-Qur’an pada Sub-Unit Kurikulum SMA. Hasil pelatihan menunjukkan bahwa sistem digital mampu mempercepat rekapitulasi nilai secara otomatis dan real-time, meningkatkan keamanan penyimpanan data, serta mempermudah monitoring perkembangan siswa. Implementasi ini juga meningkatkan kompetensi digital guru dan mendukung modernisasi tata kelola evaluasi pembelajaran Al-Qur’an secara berkelanjutan.
Co-Authors Abd Rahman Abrar, Muhammad Fauzan Angga, Tyas Dwi Anita Ratnasari Anzalna, Akbarakah Bagus Priambodo Cahyo Pambudi Darmo Desi Ramayanti Desmon, Johanes Devi Fitrianah Dhamanti, Inge Dianing Asri, Sri ferdi Fitri Dwi Astuti, Fitri Dwi Fitri Yakub Hadiguna Setiawan Handrie Noprison Handrie Noprisson Hong Wei Ida Farida Ida Nurhaida Ida Nurhaida Ida Nurhaida Inge Handriani, Inge Iryani, Lemi Jumaryadi, Yuwan Kananga, Meylani Mentari Laksono Trisnantoro Luhyana, Nahdah Mailana, Siska Mariana Purba Mariana Purba Marissa Utami Naufal, Muhamad Fahri Nengsiana, Nengsiana Noprisson, Handrie Nur Ani Pangrepti, Diah Ayu Purba, Mariana Putra, Erwin Dwika Remmy A. M. Zen Salamah, Umniy Sarwati Rahayu Sri Dianing Asri Syamsiar, Syamsiar Tjahjono, Benny Uswatun Hasanah Uus Rusmawan, Uus Wachyu Hari Haji Wachyu Hari Haji Wahyu Adianto Wina Firly, Tiara Yogga Herlambang, Helwy