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All Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Industrial Research Workshop and National Seminar
Aldi Lugina
Politeknik Negeri Bandung
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Sistem Pengenalan Penggunaan Masker dan Pemantauan Suhu Penumpang Pesawat Menggunakan Sensor Fusion Feni Isdaryani; Noor Cholis Basjaruddin; Aldi Lugina
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 2: Mei 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1503.82 KB) | DOI: 10.22146/jnteti.v11i2.3835

Abstract

Transportation is currently an unavoidable necessity. However, the COVID-19 pandemic has impacted all lines of industry, including the Indonesian aviation transportation industry. Technology is one of the solutions to deal with these problems. The monitoring system of masked face recognition and body temperature detection for the check-in process of passengers at the airport is aimed to be developed in this research. The contribution of this research is that the system can distinguish the type of face mask used. Therefore, this monitoring system classified only medical masks and N95/KN95 respirator masks as ‘Good Masked’. IP camera and thermal camera are used to identify a masked face and body temperature, respectively. The sensor fusion method was used for decision-making on passengers whether they can be departed or not. The decision was taken based on the measured body temperature, the use of standardized face masks, and the face recognition of the airport passengers. Convolutional neural network (CNN) method was used for face and face mask recognition. The CNN model training was conducted four times according to the four proposed scenarios. The CNN model that has been trained can distinguish a masked face and a face without a mask. The best results were obtained in the fourth scenario with the comparison of the training dataset to the testing dataset was 9:1 and the epoch was 500 times. The basic deep learning model used for face detection was the single shot multibox detector (SSD) using the ResNet-10 architecture. Meanwhile, the CNN method with the MobileNetV2 architecture was used to detect the use of masks. The accuracy of the CNN model for face recognition and mask recognition was 100%. All check-in monitoring and verification process data were displayed on the web application which was built on the localhost.
Purwarupa Pembersih Kandang Ayam Otomatis Berbasis Mikrokontroler Ricky Evan Anugrah Firdaus; Aldi Lugina; Gandhi Surya Permana; Noor Cholis Basjarudin; Edi Rakhman
Prosiding Industrial Research Workshop and National Seminar Vol 11 No 1 (2020): Prosiding 11th Industrial Research Workshop and National Seminar (IRWNS)
Publisher : Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (603.334 KB) | DOI: 10.35313/irwns.v11i1.1991

Abstract

Kandang merupakan salah satu bagian dari manajemen ternak unggas yang sangat penting untuk diperhatikan. Fungsi utama dari kandang adalah memberikan kenyamanan dan melindungi ternak dari panasnya sinar matahari, hujan, angin, udara dingin dan untuk mencegah gangguan seperti predator. Untuk meningkatkan kualitas ayam dan meminimalisir gangguan kesehatan pada ayam, maka pembuatan kandang ayam juga perlu memperhatikan kebersihan dan sirkulasi udara. Dalam mengatasi hal tersebut maka diperlukan sebuah alat yang dapat membantu peternak supaya kandang tetap dalam kedaan bersih dan nyaman bagi ayam. Alat ini berupa motor stepper dan kipas yang dikendalikan oleh mikrokontroler yang akan mendeteksi gas amonia oleh sensor MQ-135 yang kemudian diproses oleh mikrokontroler. Alat akan membersihkan udara dan kotoran pada kandang ayam sehingga kebersihan kandang ayam tetap terjaga. Alat akan mendeteksi kadar ammonia dalam kandang Ketika kadar ammonia >10 ppm (Part Per Million) fan akan bekerja dan juga setiap pukul 7 pagi konveyor akan menyala untuk melakukan pembersihan kotoran ayam. Pengujian komponen seperti RTC (Real Time Clock), driver motor, motor stepper, fan,dan LCD (Liquid Crystal Display) dilakukan agar didapat keberhasilan alat 100%.
Co-Authors Edi Rakhman FENI ISDARYANI Gandhi Surya Permana Noor Cholis Basjaruddin Noor Cholis Basjarudin Ricky Evan Anugrah Firdaus