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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Teknika Seminar Nasional Informatika (SEMNASIF) Al-Jabar : Jurnal Pendidikan Matematika Emerging Science Journal Jurnal TAM (Technology Acceptance Model) Prosiding Seminar Nasional Darmajaya International Journal on Emerging Mathematics Education International Journal of Supply Chain Management Journal of Robotics and Control (JRC) Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Jurnal PkM: Pemberdayaan Masyarakat Al Irsyad: Jurnal Studi Islam NEAR: Jurnal Pengabdian kepada Masyarakat Pena Dimas: Jurnal Pengabdian Masyarakat Greenation International Journal of Engineering Science SATKRIYA: Jurnal Pengabdian Kepada Masyarakat Siber Journal of Advanced Multidisciplinary Siber Journal of Transportation and Logistics Siber International Journal of Digital Business Siber International Journal of Education Technology Jurnal Greenation Sosial dan Politik Greenation International Journal of Engineering Science Greenation International Journal of Law and Social Sciences Greenation International Journal of Tourism and Management Greenation International Journal of Economics and Accounting Dinasti Information and Technology Dinasti Accounting Review International Journal of Psychology and Health Science Dinasti Health and Pharmacy Science Siber International Journal of Advanced Law Jurnal TAM (Technology Acceptance Model)
Andino Maseleno
Prodi Sistem Informasi, STMIK Pringsewu Lampung
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Journal : Emerging Science Journal

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An Explainable Deep Learning Approach for Classifying Monkeypox Disease by Leveraging Skin Lesion Image Data Maseleno, Andino; Huda, Miftachul; Ratanamahatana, Chotirat Ann
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-013

Abstract

According to the World Health Organization's (WHO) external situation report on the multi-country outbreak of Monkeypox in 2023, from 11 countries in Southeast Asia Regions, Thailand recorded the highest reported cases, totaling 461. The ongoing Monkeypox outbreak has raised significant public health concerns due to its rapid spread across several nations. Early detection and diagnosis are imperative for effectively treating and controlling Monkeypox. Given this context, this study aimed to determine the most efficient model for detecting Monkeypox by employing interpretable deep learning techniques. This study utilizes deep learning techniques to diagnose Monkeypox based on images of skin lesions. We evaluate based on four models—convolutional neural network (CNN), gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short term memory (BiLSTM)—using a publicly available dataset. Additionally, we incorporate Local Interpretable Model-Agnostic Explanations (LIME) and techniques for explainable AI, facilitating visual interpretation of model predictions for healthcare practitioners. The CNN model's performance and LSTM model's performance have an accuracy of 100%, while the GRU model's performance and BiLSTM model's performance have an accuracy of 99.88% and 99.45%. Our findings demonstrate the effectiveness of deep learning models, including the suggested CNN model leveraging the pre-trained MobileNetV2 and LSTM. These models can play a pivotal role in combating the Monkeypox virus. Doi: 10.28991/ESJ-2024-08-05-013 Full Text: PDF
Metaheuristic Hyperparameter Optimization and Explainable Deep Learning for Baggage Threat Detection Maseleno, Andino; Huda, Miftachul; Fudholi, Ahmad; Ratanamahatana, Chotirat Ann
Emerging Science Journal Vol. 10 No. 1 (2026): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2026-010-01-06

Abstract

The American Statistical Association reports that Bangkok, the capital and largest city of Thailand, holds the top spot as the most visited city worldwide in 2023. X-ray imaging for security screening plays a crucial role in upholding transportation security by detecting a diverse range of threats or prohibited items carried by passengers. This study introduces an advanced deep learning model leveraging YOLOv8, renowned for its enhanced efficiency in automating baggage detection processes. To enhance the model's hyperparameters and adjust them finely during the training process using the baggage dataset, the system utilized a metaheuristic optimization algorithm known as Evolutionary Genetic Algorithm, which is based on evolutionary principles. Incorporating explainable artificial intelligence techniques such as Local Interpretable Model-Agnostic Explanations (LIME) and Gradient-weighted Class Activation Mapping (Grad-CAM) allows for visual interpretation of predictions, aiding operators in utilizing the model effectively. We trained and tested the baggage dataset, which included 8,312 images and five classes: gun, knife, pliers, scissors, and wrench. The YOLOv8 model achieved the following metrics for the detection of prohibited objects in baggage inspection: an overall precision of 90.5%, recall of 83.3%, mAP50 of 91.3%, and mAP50-95 of 67%. The proposed method can fully automate the recognition of prohibited objects during baggage inspection. This approach is beneficial for designing an integrated, automatic, and non-destructive X-ray image-based classification system.
Co-Authors -, Nungsiyati Agrawal, Heit Ahmad Fudholi Anggia Sari Ani Choirunnisa Anwar, Muhammad Saidun Apsari, Nur Fitri Artha, Arsya Sinatria Bachani, Jenith Baghadiya, Jenik Baldi, Vansh Barvaliya, Ram Bhatt, Aum Bhutra, Yuvraj Bich Huynh, Vy Dang Bich Vu, Ngoc Bohra, Hussain Budi Satiawan Chahwala, Keshav Chatarina Umbul Wahyuni Chauhan, Rahul Choirudin, Choirudin Choirunnisa, Ani Citra Dewi Citrawati Jatiningrum Damayanti, Alfina Danar Aulia Husnan Dang Vo, Khoa De Brito Silva, Gabriel Deep P, Baraiya Dhaakad, Deepak Dhanak, Jaydev Dhruv, Aryan Dwivedi, Shaurya Eka Fitria Ningsih Eva Yuliana Faozi, Seli Aulia Fauzi Fauzi Fauzi Fauzi Fiqih Satria Gabriel De Brito Silva Gabriel De Brito Silva Gafurjiwala, Moh. Kaif Goyal , Vikas Guha, Tannay Gurjar, Krishna Hamzah Hamzah Hasanah, Khuswatun Hashim, Wahidah Hendra Hendra Hubur, Aa Husnan, Danar Aulia Ipin Prasojo Ipin Prasojo, Ipin Isnaini, Nurlaila Jadhwani, Om Jaju, Pooja Jeprianto, Jeprianto Kacchara, Gul Kachhadiya, Diya Kamya, Bhatt Kataria, Yachi Khakhar, Bhavik Khoa Dang Vo Khubchandani, Sania Khuswatun Hasanah Kotak, Yash Kristina, Marilin Laksono Trisnantoro Le Hoang Thuy To Nguyen, Quyen Loan Phuc Le Machhvara, Jenil Makhija, Hitesh Marselina Jupon, Rara Meet Shah, Meet Meghwal, Mayank Mehta, Hitarth Mehta, Meet Mendpara, Lucky Mian Usman Sattar Miftachul Huda Miswan Gumanti Mohnia, Tiya Monpara, Yesha Muhammad Miftahussurur Muhammad Muslihudin Muhtadin Arrosyid Muhtadin Asnady Murti, Sri Nagani, Purva Nagdevani, Dev Naik, Pratham Ngoc Bich Vu Nishith Shahu Nungsiyati Nungsiyati Nur Aminudin Nur Azizah nurul latifah Omar tanane Omar Tanane Padaliya, Om Padang Tunggal, Tatiya Parchani, Nilesh Patel, Diya Patel, Hetvi Patel, Kavya Patel, Raj Patel, Suhani Patel, Tarang Patel, Vasu Petel, Bhavya Phong Thanh Nguyen Phuc Le, Loan Phuong Thanh Phan Prajapati, Hetal Prisma Megantoro Quyen Le Hoang Thuy To Nguyen R Rizal Isnanto R. Rizal Isnanto Rahul Chauhan Rais Zulkarnain Raisa, Kharchenko Raithatha, Bhavya Rajapara, Monil Rajkotiya, Abhi Rakesh Shah, Arya Ramchandani, Paras Ramrakhya, Divesh Ratanamahatana, Chotirat Ann Rathod, Lakshita Rika Fetricia Rina Wati Rizal Isnanto, R Rizal Isnanto, R. Sah, Aditya Sakaria, Anuchi Samsukha, Akshita Samtani, Heena Sapra, Ruchi Satria Abadi Satria, Fiqih Sattar, Mian Usman Septia Nagara, Erliza Seth, Dhruv Shah, Dhwanit Shah, Fenil Shah, Hitarth Shah, Nirmit Shah, Stuti Shah, Supan Shah, Tanish Shahu, Nishith Sharma, Ansh Sharma, Yajurv Shriyal, Harsh Shubham, Chavda Sigit Soijoyo Silva, Gabriel De Brito Singh, Pushpendra Sinh Zala, Harshvadhan Sodikin Sodikin Sompura, Jayesh Sri Murti Store, Shreyas Suda, Pranjal Sudewi Sudewi Suyono Suyono Tanane, Omar Tatiya Padang Tunggal Thacker, Nevil Thakkar, Krish Thakur, Aryan Thanh Nguyen, Phong Thanh Phan, Phuong Tri Ayu Septiana Tri Susilowati Triana Dewi Triana Dewi Trisnawati Trivedi, Pratham Unaliya, Maitri Vaghela, Sidhraj Vaja, Hitarthsinh Viramgama, Netra Vy Dang Bich Huynh Wahidah Hashim Yash, Panchal Yus, Yumaira Zalariya, Nihal Zaveri, Krish Zulkifli