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All Journal Devotion : Jurnal Pengabdian Psikologi JIMKI: Jurnal Ilmiah Mahasiswa Kedokteran Indonesia
Naufal, Muhammad Alif
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Health Professions Medicine & Pharmacology Neuroscience Public Health Social Sciences Other

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Catoe Rimueng: Upaya Meningkatkan Kepercayaan Diri Anak dan Remaja melalui Seni Bertutur di Panti Asuhan Media Kasih Rizki, Aulia Maulana; Zulfikri; Prawita, Tiwidian; Naufal, Muhammad Alif
Devotion : Jurnal Pengabdian Psikologi Vol. 2 No. 01 (2023): Mei
Publisher : Fakultas Psikologi Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/devotion.v2i01.4048

Abstract

Self confidence is considered very important for the development of adolescents and children’s as it is one of the standard criteria for achiving individual social and emotional development. Adolescents and children’s who possess self-confidence will have a positive self-image and self-concept. On the other hand, adolescents and children with low self confidence will show doubtful behavior when completing tasks, do not dare to speak in a group activities without support, tend to withdraw and avoid participating in discussion, isolate themselves from their environment, and tend to be aggressive. Through catoe rimueng training and the art of speech activities, children’s in orphanage can enhance their self confidence. The objective of this community service is to boost the self confidence of the children at Media Kasih Orphanage in Banda Aceh City. The observation instrument used before and after the implementation of this community service is The Lautser Self Confidence Scale (2012). Based on the observation, there is an increase in children’s self confidence before and after the implementation. Thus, there is potential for program sustainability with defined product prototypes.
Development of an Artificial Intelligence–Based Portable Prototype for Early Tuberculosis Detection Using Exhaled Breath Analysis and IoT Integration: A Feasibility Study Naufal, Muhammad Alif; Nusair, Rafie; Duta, Teuku Fais
JIMKI: Jurnal Ilmiah Mahasiswa Kedokteran Indonesia Book of Abstrack RCIMS 2025
Publisher : BAPIN-ISMKI (Badan Analisis Pengembangan Ilmiah Nasional - Ikatan Senat Mahasiswa Kedokteran Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53366/jimki.vi.978

Abstract

Introductions: Tuberculosis (TB) remains a major global health problem and has become one of the world’s leading infectious diseases, particularly affecting populations in low- and middle-income countries. Despite advancements in molecular testing, the accessibility, cost, and time requirements of conventional diagnostics limit early case detection. Exhaled breath analysis provides a promising non-invasive approach through the identification of volatile organic compounds (VOCs) produced during TB infection. This study aimed to develop and evaluate a portable diagnostic system that integrates VOC sensing, Artificial Intelligence (AI), and Internet of Things (IoT) technologies to enhance early TB screening in community and primary healthcare settings. Methods: A metal oxide semiconductor gas sensor array connected to an ESP32-S3 microcontroller was employed to capture VOC profiles from 33 participants (17 TB-confirmed patients and 16 healthy controls). The acquired data were preprocessed, reduced, and classified using Principal Component Analysis. Several machine learning algorithms, including Support Vector Machines (SVM), Random Forest, Gradient Boosting, and Artificial Neural Networks (ANN), were trained and validated to develop a TB recognition model. Results and Discussion: The ANN achieved the best performance, with an accuracy of 79%, sensitivity of 78%, specificity of 80%, and an AUC of 0.84. IoT integration enabled real-time data transfer and cloud-based visualization, demonstrating scalability and potential use in resource-limited settings. Conclusion: This portable AI-based breath analysis system offers a rapid, affordable, and non-invasive approach for early TB detection. With further validation, it might complement existing diagnostics and strengthen global TB elimination efforts.
Co-Authors Duta, Teuku Fais Nusair, Rafie Prawita, Tiwidian Rizki, Aulia Maulana Zulfikri