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All Journal Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Kesehatan Masyarakat
Syafarina, Inna
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health

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Automated Detection of Porcine Gelatin Using Deep Learning-Based E-Nose to Support Halal Authentication Mahmudah, Kunti R.; Biddinika, Muhammad K.; Hakika, Dhias C.; Tresna, Wildan P.; Sugiarto, Iyon T.; Syafarina, Inna
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.654

Abstract

Authenticating gelatin sources is essential for consumers, particularly those with dietary restrictions or religious concerns regarding pork-derived ingredients. Porcine gelatin, widely used in food and pharmaceutical products, poses considerable challenges for authentication due to its prevalence and the difficulty of detecting it, especially in processed products. In this study, we developed and evaluated an integrated electronic nose (e-nose) system with a Recurrent Neural Network (RNN) to detect and classify gelatin type based on their sources. The e-nose system utilized an array of gas sensors to capture the unique volatile organic compounds (VOCs) associated with each gelatin type, which was subsequently classified by the RNN. The classification performance of the integrated 7-module e-nose system showed promising results based on time points after sample preparation, with accuracy, sensitivity, and AUC of 96.3%, 96.6%, and 98.2% at the 0-hour point, respectively, rising to 99.1% for all three metrics at 2-hour point. The sensitivity of the system also showed an increase over time for single gelatin samples, from 100%, 97.8%, and 91.9% to 98.6%, 99.3%, and 99.3% for pig-derived, cow-derived, and fish gelatin, respectively. For mixed gelatin samples, the system maintained high accuracy, sensitivity, and AUC at 98.2%, 97.9%, and 98.1%, respectively. In conclusion, the integrated e-nose system demonstrates the potential for robust performance in gelatin authentication, paving the way for more efficient and reliable methods of halal food authentication.
Prevalence of Hypertension in Indonesia: 2018 Basic Health Research Ikhlasia, Nafasha Fairly; Syafarina, Inna; Latifah, Arnida L
Jurnal Kesehatan Masyarakat Vol. 20 No. 3 (2025)
Publisher : Universitas Negeri Semarang in collaboration with Ikatan Ahli Kesehatan Masyarakat Indonesia (IAKMI Tingkat Pusat) and Jejaring Nasional Pendidikan Kesehatan (JNPK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/kemas.v20i3.21685

Abstract

Hypertension is one of the main factors contributing to premature death. The nationwide prevalence rate of hypertension in Indonesia is relatively high. Understanding the factors contributing to hypertension is essential to reduce the prevalence of hypertension. This paper investigates the risk factors associated with hypertension based on the survey data of Riskesdas 2018. The risk factors related to behaviors or lifestyle include smoking every day, being less active, eating fatty or salty foods once a day, drinking caffeine once a day, and overweight status. Using multiple linear regression, this study finds that being overweight with a body mass index in range 25-27 and having a daily coffee intake habit of one cup are the most significant risk factors to the prevalence of hypertension. These findings should be used as a reference for preventative and promotional actions to reduce the prevalence of hypertension in Indonesia.
Co-Authors Biddinika, Muhammad K. Hakika, Dhias C. Ikhlasia, Nafasha Fairly Iyon T. Sugiarto, Iyon T. Latifah, Arnida L Mahmudah, Kunti R. Tresna, Wildan P.