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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JIEET (Journal of Information Engineering and Educational Technology) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Abdi: Media Pengabdian Kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Abdimas: Papua Journal Of Community Service Journal of Informatics and Computer Science (JINACS)
ANITA QOIRIAH
Jurusan Teknik Informatika, Fakultas Teknik, Universitas Negeri Surabaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Pre-trained convolutional neural network-based algorithms: application for recognizing the age category Yamasari, Yuni; Anggraini, Lusiana; Qoiriah, Anita; Eka Putra, Ricky; Agustin Tjahyaningtijas, Hapsari Peni; Ahmad, Tohari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3576-3587

Abstract

Cybercrime is a major issue in the current digital era, with one of its branches-cyber pornography-notably affecting Indonesia. Various efforts have been made to suppress or prevent this problem. One alternative solution involves using technological advances to recognize age ranges based on facial recognition. This age range recognition can be implemented to prevent users from accessing content that is not appropriate for their age. An optimal age-range recognition system is essential for this purpose. However, limited research has focused on this domain. Therefore, our research aimed to develop the best possible system. The proposed method applies a trained convolutional neural network (CNN) as a feature extractor to the artificial neural network (ANN) and k-nearest neighbor (K-NN) methods for age recognition based on facial images. By incorporating computational learning techniques, the system's performance is significantly enhanced, leveraging advanced algorithms to improve accuracy. The test results show that the performance of the pre-trained CNN-based ANN model is superior. This is indicated by the model's accuracy and F1-score, which were 11% and 0.11 higher, than the pre-trained CNN-based K-NN model. The error rate of the pre-trained CNN-based ANN model was also reduced by 0.11.
PELATIHAN MEDIA PEMBELAJARAN MENGGUNAKAN CANVA UNTUK GURU MI AL AHMAD, KRIAN, SIDOARJO Naim Rochmawati; Yamasari, Yuni; Yustanti, WIyli; Qoiriah, Anita; Aviana, Anisah Nurul
Jurnal ABDI: Media Pengabdian Kepada Masyarakat Vol. 9 No. 1 (2023): JURNAL ABDI : Media Pengabdian Kepada masyarakat
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/abdi.v9i1.19853

Abstract

Dalam proses belajar mengajar, media pembelajaran berperan penting. Media pembelajaran yang interaktif membantu para siswa lebih mudah dalam memahami konten materi yang disampaikan para guru. Dengan kesadaran untuk meningkatkan kemampuan dalam membuat media pembelajaran agar kualitas pembelajaran semakin meningkat, para guru MI Al Ahmad, Krian, Sidoarjo, meminta pelatihan pembuatan media pembelajaran. banyak tool yang bisa digunakan, salah satunya adalah Canva. Dalam Canva, disediakan banyak fasilitas menu untuk membuat media pembelajaran yang interaktif. Untuk itu, pelatihan kali ini adalah memberikan pelatihan Canva bagi para guru MI Al Ahmad untuk meningkatkan kemampuan digital para guru MI Al Ahmad dalam membuat media pembelajaran yang interaktif. Metode kegiatan adalah dengan model ceramah dilanjutkan dengan praktikum menggunakan Canva. Hasil dari pelatihan ini adalah kemampuan para guru MI Al Ahmad dalam membuat media pembelajaran interaktif menggunakan Canva. Dari hasil evaluasi kegiatan disimpulkan bahwa pelatihan ini dapat dikatakan berhasil meskipun masih perlu penyempurnaan dalam kegiatan yang dilakukan. Hal ini diindikasikan dengan respon yang diberikan oleh guru MI Al Ahmad, sebagai peserta pelatihan, pada angket online yang dibagikan setelah selesai pelatihan.
Pelatihan Pemanfaatan Internet untuk Menunjang Kreativitas Guru dalam Penyampaian Materi secara Daring Yamasari, Yuni; Qoiriah, Anita; Yustanti, Wiyli; Rochmawati, Naim; Nurhidayat, Andi Iwan; Kurniawan, Ari
Abdimas: Papua Journal of Community Service Vol. 6 No. 1 (2024): Januari
Publisher : Lembaga Pengembangan dan Pengabdian Masyarakat Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/pjcs.v6i1.2749

Abstract

   
Rule-Based Adaptive Chatbot on WhatsApp for Visual, Auditory, and Kinesthetic Learning Style Detection Rahulil, Muhammad; Yamasari, Yuni; Putra, Ricky Eka; Suartana, I made; Qoiriah, Anita
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.1215

Abstract

Adapting learning methods to individual learning styles remains a major challenge in digital education due to the static nature of traditional questionnaires and the absence of adaptive feedback mechanisms. This study aimed to develop a rule-based adaptive WhatsApp chatbot capable of automatically identifying users’ learning styles, visual, auditory, and kinesthetic, through a weighted questionnaire enhanced with probabilistic refinement. The proposed system introduces an adaptive decision framework that dynamically manages conversation flow using score dominance evaluation, early termination, and selective question expansion. Bayesian posterior probability estimation is employed to strengthen decision confidence in borderline cases, ensuring consistent and interpretable results even when user responses are ambiguous. The chatbot was implemented using WhatsApp-web.js and MongoDB, supported by session validation and activity log monitoring to ensure operational reliability and data integrity. System validation involved white-box testing using Cyclomatic Complexity to verify logical accuracy and 20-fold cross-validation using a Support Vector Machine (SVM) to evaluate classification performance. The adaptive model achieved an accuracy of 80.2% and an AUC of 0.902, supported by a balanced precision (0.738), recall (0.662), and F1-score (0.698). These results demonstrate stable discriminative capability and confirm that the adaptive scoring mechanism effectively reduces redundant questioning, lowers cognitive load, and improves interaction efficiency without compromising reliability. In conclusion, the study successfully achieved its objective of developing an adaptive, efficient, and mathematically transparent learning style detection system. The findings confirm that adaptive rule-based logic reinforced by probabilistic reasoning can significantly enhance the efficiency and reliability of digital learning assessments. Future research will extend this framework by incorporating multimodal behavioral indicators and personalized learning content to further strengthen adaptive learning support
Co-Authors AB Sinaga, Christiano Zetro Aditya Prapanca Agus Prihanto Agustin Tjahyaningtijas, Hapsari Peni Amalia, Rahma Andi Iwan Nurhidayat Anggraini, Lusiana ARI KURNIAWAN Arjunantyo, Algonza Dewangga Asmunin Asmunin Aviana, Anisah Nurul Azam, Hafidh Ismu Azam Bintang, Elroy Chalatha Doa, Udkhul Rogodan Cynthia, Grace Eka Putra, Ricky Farhani, Farih Sartika Febriansyah, Tri Yoga Fresinsya, Vica Gunawan, Duta Alif Hasanah, Wahenda Uswatun Iqbal Zaki, Naufal Istiqomatul Anissa, Amanda Mahfudhoh, Meysa Mirnawati, Nila Naim Rochmawati Napitupulu, Ingwer Ludwig Benjamin Putri, Dian Oktavia Qurrotul Uyun, Qurrotul Rafif Raif, Andi Rhifqy Rahmada, Vita Rahulil, Muhammad Ramadhan, Ahmad Syaifudin Ricky Eka Putra Rina Harimurti Rochmawati, Naim Sadiyah, Siti Halimatus Siska Oktavia Sofi'ie, Farro Axza Febsinatra Suartana, I Made Suyatno, Dwi Fatrianto Tohari Ahmad Wiyli Yustanti YUNI YAMASARI Yusuf, Dhani Ahmad Zulfikar, Mochammad