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All Journal Telaah Journal of Electronics, Electromedical Engineering, and Medical Informatics
Iyon T. Sugiarto, Iyon T.
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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PERANCANGAN ALAT UKUR PEMILIH JANGKAUAN UNTUK MENGUKUR DAYA OPTIK Hanto, Dwi; Setiono, Andi; Sugiarto, Iyon T.; Waluyo, Thomas B.; Widiyatmoko, Bambang
Telaah Vol 32, No 2 (2014)
Publisher : Research Center for Physics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/tel.32.2.183

Abstract

Tulisan ini menjelaskan tentang pembuatan rangkaian pemilih jangkauan pada perancangan alat ukur daya optik atau powermeter optik. Penelitian yang dilakukan adalah membuat rangkaian pengkondisi sinyal. Rangkaian ini dibuat berdasarkan penguat transimpedansi dengan 6 buah pilihan resistansi umpan balik, yaitu 1 kΩ, 10 kΩ, 100 kΩ, 510 kΩ, 1 MΩ, dan 2 MΩ. Pengukuran dilakukan dengan menggunakan sumber cahaya berupa laser dengan panjang gelombang 1310 nm. Untuk variasi nilai, daya optik dari laser diatenuasikan dengan menggunakan atenuator optik sampai dengan 60 dB. Keluaran dari rangkaian ini berupa tegangan listrik yang diukur dengan menggunakan voltmeter. Dari hasil pengukuran kami menemukan bahwa setiap nilai resistansi memiliki jangkauan yang berbeda. Nilai daya optik pada masing-masing pemilihan resistansi adalah seperti berikut: -15 dBm s.d. -4.96 dBm pada resistansi 1 kW, -20 dBm s.d. -8 dBm pada resistansi 10 kΩ, -32 dBm s.d -18 dBm pada resistansi 100 kΩ, -40 dBm s.d. -28 dBm pada 510 kΩ, -45 dBm s.d. -28 dBm pada resistansi 1MΩ, dan -50 dBm s.d. -40 dBm pada resistansi 2 MΩ. Penelitian ini dapat dikembangkan untuk membuat alat ukur daya optik multijangkauan dengan ketelitian yang baik dengan mengganti beberapa nilai resistansi sesuai dengan jangkauan yang diinginkan.
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.
Co-Authors Andi Setiono Bambang Widiyatmoko Biddinika, Muhammad K. Dwi Hanto Hakika, Dhias C. Mahmudah, Kunti R. Syafarina, Inna Thomas B. Waluyo, Thomas B. Tresna, Wildan P.