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All Journal JOIV : International Journal on Informatics Visualization Indonesian Community Journal
Sharef, Nurfadhlina Mohd
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Recent Advances on Meta-heuristic Algorithms for Training Multilayer Perceptron Neural Network Al-Asaady, Maher Talal; Aris, Teh Noranis Mohd; Sharef, Nurfadhlina Mohd; Hamdan, Hazlina
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.3109

Abstract

Artificial Neural Networks (ANNs) have demonstrated applicability and effectiveness in several domains, including classification tasks. Significant emphasis has been given to the training techniques of ANNs in identifying appropriate weights and biases. Conventional training techniques such as Gradient Descent (GD) and Backpropagation (BP), while thorough, have several disadvantages such as early convergence, being highly dependent on the initial parameters, and quickly getting stuck in local optima. Conversely, meta-heuristic algorithms show great potential as effective approaches for training ANNs with high computational efficiency, high quality, and global search capabilities. The literature has proposed several such techniques; hence, this paper offers a thorough examination of current advancements in training a Multilayer Perceptron (MLP) neural network using meta-heuristic algorithms, with a focus on classification benchmark datasets. The study was conducted over a period of ten years, from the year 2014 to 2024. The research papers were specifically chosen from four widely used databases: ScienceDirect, Scopus, Springer, and IEEE Xplore. Through the use of a research methodology that incorporates specific criteria for including and excluding articles, and by thorough examination of more than 53 publications, we present a comprehensive study of meta-heuristic methods for training MLPs. Our main focus is on discovering trends across these tools. The analysis has been conducted utilizing relevant factors such as evaluation metrics for classification models, fitness functions, comparing approaches, datasets, and observed outcomes. The present work serves as a significant asset for researchers, facilitating the identification of suitable optimization methodologies for various application areas. 
Menjembatani Teknologi dan Spiritualitas: Pengenalan Artificial Intelligence di Pondok Pesantren melalui Workshop Kolaboratif Sulistiyo, Mahmud Dwi; Adytia, Didit; Baizal, Z.K. Abdurahman; Mohamed, Raihani; Zamani, Nabila Wardah; Sharef, Nurfadhlina Mohd
I-Com: Indonesian Community Journal Vol 5 No 3 (2025): I-Com: Indonesian Community Journal (September 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i3.7799

Abstract

Pesantren sebagai lembaga pendidikan berbasis keagamaan memiliki tantangan dalam mengakses perkembangan teknologi terbaru seperti Artificial Intelligence (AI). Menjawab kebutuhan ini, tim pengabdian dari Telkom University menyelenggarakan workshop pengenalan AI dan mengundang sivitas Pondok Pesantren Modern Assuruur. Kegiatan ini bertujuan untuk meningkatkan literasi digital para santri melalui pengenalan konsep dasar AI dan pemanfaatannya dalam pembelajaran Al-Qur’an. Workshop dilakukan secara hybrid bersama narasumber dari Telkom University dan Universiti Putra Malaysia (UPM), mencakup pretest, materi inti, praktik aplikasi Tarteel, dan posttest. Hasil evaluasi menunjukkan peningkatan skor pemahaman peserta dari rata-rata 93,97 menjadi 98,10, disertai penurunan standar deviasi dari 14,50 menjadi 5,88. Kegiatan ini membuktikan bahwa pendekatan yang kontekstual dan aplikatif mampu meningkatkan pemahaman santri terhadap teknologi modern serta membuka peluang integrasi AI dalam pendidikan Islam.
Co-Authors Al-Asaady, Maher Talal Aris, Teh Noranis Mohd Didit Adytia Hamdan, Hazlina Mahmud Dwi Sulistiyo Mohamed, Raihani Zamani, Nabila Wardah ZK Abdurahman Baizal