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All Journal International Journal of Electrical and Computer Engineering Jurnal EECCIS Jurnal Terapan Abdimas Fountain of Informatics Journal JTT (Jurnal Teknologi Terpadu) SemanTIK : Teknik Informasi JRSI (Jurnal Rekayasa Sistem dan Industri) JURNAL MEDIA INFORMATIKA BUDIDARMA Langkawi: Journal of The Association for Arabic and English Informatika Pertanian ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar Khadimul Ummah Journal of Social Dedication Agroindustrial Technology Journal Applied Information System and Management Jurnal Teknoinfo Multitek Indonesia : Jurnal Ilmiah ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Repositor International Journal on Teaching and Learning Mathematics Jurnal Pengabdian kepada Masyarakat Jurnal Informatika Polinema (JIP)
Shoffin Nahwa Utama
UIN Maulana Malik Ibrahim Malang
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Klasifikasi Irama Bacaan Al-Qur’an menggunakan Algoritma CNN Utama, Shoffin Nahwa; Prakasa, Johan Ericka Wahyu; Hariyanto, Wahyu
ILKOMNIKA Vol 7 No 1 (2025): Volume 7, Number 1, April 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v7i1.731

Abstract

Klasifikasi nada bacaan Al-Qur’an sangat penting untuk mendukung pembelajaran tajwid, tartil, serta tilawah yang sesuai dengan aturan. Tantangan utama dalam klasifikasi ini terletak pada keberagaman gaya bacaan qari dan kemiripan akustik antar maqam. Penelitian ini bertujuan untuk mengembangkan model klasifikasi otomatis irama bacaan Al-Qur’an menggunakan pendekatan berbasis CNN dengan 8 kelas maqam bacaan. Model CNN dalam penelitian ini memiliki tiga jalur konvolusi dengan ukuran kernel berbeda. Variasi bentuk masukan berupa data audio yang diubah ke dalam representasi spektrogram dan mel-frequency cepstral coefficients (MFCC). Evaluasi kinerja model pada dataset bacaan Al-Qur’an yang terdiri dari 8 kelas tilawah yaitu Ajam, Bayat, Hijaz, Kurd, Nahawand, Rast, Saba, dan Seka. Hasil pelatihan menunjukkan bahwa metode yang diusulkan mencapai akurasi 92,6%, sedangkan pada proses pengujian didapatkan akurasi sebesar 82,04%. Hasil confusion matric didapatkan nilai akurasi yang diperoleh dalam proses validasi mencapai 80,88%. Nilai presisi, recall dan F1-score masing-masing adalah 0,82, 0,80, dan 0,81. Dengan hasil ini, pendekatan CNN yang diusulkan terbukti efektif untuk mendukung otomatisasi dan peningkatan akurasi dalam klasifikasi nada bacaan Al-Qur’an.
Two-step majority voting of convolutional neural networks for brain tumor classification Santoso, Irwan Budi; Utama, Shoffin Nahwa; Supriyono, Supriyono
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp4087-4098

Abstract

Brain tumor type classification is essential for determining further examinations. Convolutional neural network (CNN) model with magnetic resonance imaging (MRI) image input can improve brain tumor classification performance. However, due to the highly variable shape, size, and location of brain tumors, increasing the performance of tumor classification requires consideration of the results of several different CNN models. Therefore, we proposed a two-step majority voting (MV) on the results of several CNN models for tumor classification. The CNN models included InceptionV3, Xception, DensNet201, EfficientNetB3, and ResNet50; each was customized at the classification layer. The initial step of the method is transfer-learning for each CNN model. The next step is to carry out two steps of MV, namely MV on the three CNN model classification results at different training epochs and MV on the results of the first step. The performance evaluation of the proposed method used the Nickparvar dataset, which included MRI images of glioma, pituitary, no tumor, and meningioma. The test results showed that the proposed method obtained an accuracy of 99.69% with a precision and sensitivity average of 99.67% and a specificity of 99.90%. With these results, the proposed method is better than several other methods.
Penerapan Teknologi Augmented Reality pada Media Pembelajaran Bahasa Arab: Durus Al-Lughah Jilid 1 Fauzan, Ady; Muriyatmoko, Dihin; Utama, Shoffin Nahwa
ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar Vol 4 No 1 (2020): FEBRUARI
Publisher : UNIVERSITAS MUHAMMADIYAH SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/else.v4i1.4379

Abstract

Abstrak: Saat ini penggunaan teknologi telah banyak dikembangkan sebagai media pembelajaran diberbagai lembaga pendidikan. Sebagai Universitas berbasis pesantren yang sehari-hari menggunakan Bahasa Arab, Universitas Darussalam Gontor (UNIDA Gontor) telah memiliki media pembelajaran baik dalam bentuk buku bahasa arab (Durusullughah Al-Arabiyah), dan dalam bentuk aplikasi, diantaranya aplikasi android menggunakan metode terjemahan (bit.ly/tamrinlughah) dan metode langsung (http://bit.ly/duruslughah). Seiring berkembangkan teknologi augmented reality (AR) maka diperlukan sebuah trobosan baru pada media pembelajaran. Penelitian ini bertujuan mengembangkan media pembelajaran Bahasa arab dengan memanfaatkan teknologi AR. Konten diambil dari buku Bahasa Arab Durusullughah Al-Arabiyah karya KH. Imam Zarkasyi dan KH. Imam Syubani sebagai trimurti pendiri Pondok Modern Darussalam Gontor. Media ini berbasis Android dan dibuat menggunakan tools seperti Blender 3D, Corel Draw, dan Unity 3D. Aplikasi ini dapat berjalan pada smartphone berspesifikasi minimal android versi OS 4.0 Jelly Bean, ukuran layar 4 inches, RAM 512 MB, ruang kosong memori minimal 200 MB dan kamera belakang 13 MP. Hasil penelitian dengan teknologi AR ini diharapkan dapat memperkaya media pembelajaran Bahasa arab UNIDA Gontor dan dapat bermanfaat untuk pengembangan media pembelajaran Bahasa arab di lingkungan kampus pesantren maupun masyarakat umum. Untuk pengembangan kedepan bisa memanfaatkan teknologi lain misalnya Virtual Reality dan lain sebagainya. Kata Kunci: Media Pembelajaran, Augmented Reality, Bahasa Arab, Android Abstract: Currently, the use of technology has been widely developed as a medium of learning in various educational institutions. As a pesantren-based university that uses arabic language for daily activities, the University of Darussalam Gontor  (UNIDA Gontor) already has a learning medium in the form of Arabic books (Durusullughah Al-Arabiya), and in the form of applications, including Android applications using the translation method (bit.ly/tamrinlughah ) and direct method (bit.ly/duruslughah ). Along with developing augmented reality (AR) technology, a breakthrough in learning media is desired. This research aims to develop Arabic language learning media by utilising AR technology. Content is taken from the Arabic book Durusullughah Al-Arabiyah by KH. Imam Zarkasyi and KH. Imam Syubani as the founding father of Pondok Modern Darussalam Gontor. This media is based on Android and is made using tools such as Blender 3D, Corel Draw, and Unity 3D. This application can run on a minimum android smartphone specification OS 4.0 Jelly Bean, 4 inches screen size, 512 MB RAM, free memory space of at least 200 MB and a 13 MP rear camera. The results of this research with AR technology are expected to be able to enrich UNIDA Gontor's Arabic language learning media and can be useful for the development of Arabic language learning media in the pesantren-based university environment and for pesantren based university specifically and the public generally. For future development, it can utilise other technologies such as Virtual Reality and others. Keywords: Learning Media, Augmented Reality, Arabic, Android
Improving Moodle Performance Using HAProxy and MariaDB Galera Cluster Prakasa, Johan Ericka Wahyu; Hanani, Ajib; Hariri, Fajar Rohman; Utama, Shoffin Nahwa
Applied Information System and Management (AISM) Vol. 7 No. 1 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i1.34871

Abstract

Moodle is a widely used Learning Management System in various educational institutions worldwide. However, frequent reports on internet forums indicate performance degradation when massive simultaneous users access Moodle. One of the most resource-intensive components supporting Moodle is the database, as all user-accessed data is stored in it. This study aims to optimize Moodle’s performance through distributed databases. Distributing the database into multiple database servers allows the database load to be distributed across all the database servers, resulting in an overall improvement in Moodle performance. This study compares the performance of Moodle installed on a single server with that installed on multiple database servers. Various testing parameters are employed to get valid results. Namely, course read, course write, and database performance, utilizing the server performance plugin available in Moodle. This research reveals a performance improvement of 384% in course read, 193% in course write, and 260% in the Moodle database in the multi-server scenario compared to the single-server scenario. This result validates that the database is the most crucial part of Moodle.
Co-Authors Abdul Wahid Abdul Wahid Ahmad Baiquni Fariz Azka Ahmad Fahmi Karami Ajib Hanani azis isrofi Aziz Musthafa Aziz Musthofa Badrus Sholeh Badrus Sholeh Dihin Muriyatmoko Fairoza Arafah, Rosa Faisal Reza Pradhana Fajar Rohman Hariri Fauzan, Ady Feldi Hekmatyar Haris Setyaningrum Hesti Rokhaniyah, Hesti Imron Rosyadi Irwan Budi Santoso Johan Ericka Wahyu Prakasa M. Aziz Muslim Moch Alfi Syahrin Muhammad Nur Kholis Muhammad Nur Kholis Oddy Virgantara Putra Onny Setyawati Rila Setyaningsih Supriyono Supriyono Syamsiar, Syamsiar Triana Harmini Wahyu Hariyanto