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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Setrum IJITEE (International Journal of Information Technology and Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Rian Fahrizal
Universitas Sultan Ageng Tirtayasa
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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Designing a Smart Mirror as a Laboratory Information Media Using Raspberry Pi Denny Hardiyanto; Galang Wicaksono; Anggoro S Pramudyo; Rian Fahrizal; Romi Wiryadinata
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1379.643 KB) | DOI: 10.22146/ijitee.48436

Abstract

Development of microprocessor technology provides new ideas for creating smart devices, one of which is in the field of smart home. Smart home is a concept of a home integrated with a smart system and supported by technology that enables all work to be more effective and efficient. Mirror is a household device that is beneficial to humans. In this paper, a research on smart mirrors is explained. A smart mirror is a mirror integrated with an intelligent system so that it can display multimedia data originating from the internet using Raspberry as a computing tool, PIR sensor as a tool to control monitors, and DC fans as a tool to control temperature system. In this paper, the mirror was able to display information about time, weather, academic calendar, lab work schedules, prayer schedules, and academic news. A PIR sensor has a good accuracy when the device is placed at 180 cm above the ground and the distance between mirror and humans when mirroring is 70 cm. A DC fan was utilized to stabilize the system temperature in a range of 40 to 50 oC.
Rancang Bangun Deteksi Masker Sebagai Akses Pintu Masuk Untuk Pencegahan Covid-19 Dengan Notifikasi Telegram Fadil Muhammad; Nugroho Anis Rahmanto; Rian Fahrizal
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 11, No 2 (2022): Edisi Desember 2022
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36055/setrum.v11i2.17854

Abstract

Penelitian ini merancang sebuah sistem akses pintu masuk berbasis deteksi masker dengan memanfaatkan aplikasi Telegram sebagai penerima notifikasi. Melalui deteksi masker yang telah dirancang tersebut, mendapatkan akurasi pada kondisi memakai masker sebesar 92,693%, pada kondisi tidak memakai masker sebesar 92,411%, dan pada kondisi pemakaian masker salah sebesar 91,521% dengan waktu proses sampai notifikasi Telegram muncul rata-rata sebesar 8,81 detik. Kecepatan mendeteksi menghasilkan rata-rata waktu selama 0,23 detik. Mendapat hasil kinerja dari Jetson Nano dengan menghasilkan FPS sebesar 5,8 FPS, penggunaan CPU mencapai 19,6% dan memori yang terpakai sebesar 1,55 GB dari 3,86 GB.
Electrical Tomography Sensor Modelling for Detection of Fuel Proportion in Vessel Rian Fahrizal; Jaga Sobar Julianto; Alief Maulana; Rocky Alfanz; Ceri Ahendyarti; Rohmadi Rohmadi; Imamul Muttakin
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26304

Abstract

Electrical capacitance volume tomography (ECVT) is a method for determining the volumetric distribution of dielectric permittivity using the capacitance measurement principle. The determination of volumetric distribution of dielectric permittivity is important to regulate a process in which quantity of materials is a decisive parameter such as in industrial setting or vehicle sub-system. ECVT is a relatively fast and non-radiating method to observe spatio-temporal phenomena inside a process, making it a valuable technique. Sensor modelling and image reconstruction study are essentials in designing a suitable imaging system based on measurements from plurality of electrodes providing higher degree of information being observed. This research conducts sensor modelling with varying fuel objects in the interior of a cylindrical vessel. The capacitance value was simulated between a combination of eight electrodes mounted encapsulating the tube. Each measured electrode was given an excitation voltage as a source of an electrostatic field, which interacts with the object’s presence. The objects in this study are benzene, kerosene, and diesel fuel, along with reference dielectric values of water and air. Image reconstruction used the linear back projection (LBP) method. Matrix operations between sensor’s pre-defined sensitivity and capacitance values produce data that can be plotted into an image estimating the true distribution of objects. Capacitance values from modelling are proportional to the actual object’s permittivity. The reconstruction provides qualitative information on the proportion of fuel in the vessel based on the capacitance value. Images have distinct values according to the presence of different objects under investigation. The research contribution is a proof of concept in using capacitance tomography to detect different fuels inside an enclosed tank at modelling stage. In addition, this study serves as a guideline for implementing a non-invasive and non-intrusive system for determining proportions of materials of interests inside a certain setup.
Sistem Presensi Menggunakan Algoritme Eigenface dengan Deteksi Aksesoris dan Ekspresi Wajah Romi Wiryadinata; Umi Istiyah; Rian Fahrizal; Priswanto; Siswo Wardoyo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 2: Mei 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1514.2 KB)

Abstract

Attendance is the documentation of presence and activity in institution. A software has been made to monitor the attendance using face recognition. The software uses camera to capture the image and works on any background color. The aim of this paper is to calculate its performance with sensitivity, specificity, and accuracy using Eigenface Algorithm and Principal Component Analysis (PCA) method. Face recognition in this paper is based on Eigenface algorithm, using pixel information from images captured by webcam. The image is represented using PCA method. The software is tested using different expressions and accessories in object’s face. The performance of the software indicates 73.33%sensitivity, 52.17% specificity, and 86.67% accuracy. The successful rate in identifying the face for distance testing is 70%, while successful rate of 85% is achieved for object wearing eyeglasses and veil (jilbab). Furthermore, the successful rate for various expression is 85.33%.
Co-Authors Alief Maulana Anggoro S Pramudyo Ceri Ahendyarti Denny Hardiyanto Fadil Muhammad Galang Wicaksono Imamul Muttakin Jaga Sobar Julianto Nugroho Anis Rahmanto Priswanto Rocky Alfanz Rohmadi Rohmadi romi wiryadinata Siswo Wardoyo Umi Istiyah