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All Journal JTEV (Jurnal Teknik Elektro dan Vokasional Jurnal Teknik Elektro JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Robotics and Control (JRC) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Andalas Journal of Electrical and Electronic Engineering Technology Jurnal Andalas: Rekayasa dan Penerapan Teknologi SAINSTEK

Zaini, Zaini

Andalas University

Author-ID : 2984611

Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

Published : 29 Documents Claim Missing Document

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Identifikasi Pengenalan Wajah Perokok Menggunakan Metode Principal Component Analysis Romi mulyadi yusni; Zaini
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 5 (2020): Oktober 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Cigarettes are one of the biggest contributors to preventable causes of death in society. Cigarette smoke contains various chemicals that can cause various diseases such as chronic coughs, lung cancer, and other health problems. Cigarette smoke not only harms the health of the smoker itself but also the health of others. Sometimes written warnings about smoking bans are often not followed by active smokers. This study aims to identify smokers 'facial recognition in order to recognize and identify smokers' faces who do not obey the rules by using dimensional reduction techniques oriented to the Principal component Analysis (PCA) method. Principal Component Analysis will later be integrated with the Eigenface and Eucladean analysis algorithms to reduce the image size in obtaining the best value vectors to simplify the face image in the input image space and look for the threshold value which is the threshold that the test data must pass so that it can prove the data value. testing becomes recognizable data through the calculation of the distance for each weight. In this study, there were 8 smoker faces with 5 different facial poses that were tested for 40 face recognition experiments and resulted in 34 correct smoker face recognition and 6 wrong smoker face recognition with an accuracy rate of 92.5% and a long face recognition process time of 80. second. This test has proven that the Eigenface and Euclidean distance in the Principal Component Analysis (PCA) are able to handle and recognize smoker's facial image data well.

Sistem Keamanan Gedung Menggunakan Kinect Xbox 360 Dengan Metode Skeletal Tracking Hamdi Alchudri; Zaini
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The incidence of fire and theft is very threatening and causes disruption to people's lifestyles, both due to natural and human factors resulting in loss of life, damage to the environment, loss of property and property, and psychological impacts. The purpose of this study is to create a building security system using Kinect Xbox 360 which can be used to detect fires and loss of valuable objects. The data transmission method uses the Internet of Things (IoT) and skeletal tracking. Skeletal detection uses Arduino Uno which is connected to a fire sensor and Kinect to detect suspicious movements connected to a PC. Kinect uses biometric authentication to automatically enter user data by recognizing objects and detecting skeletons including height, facial features and shoulder length. The ADC (Analog to Digital Converter) value of the fire sensor reading has a range between 200-300. The fire sensor detects the presence of fire through optical data analysis containing ultraviolet, infrared or visual images of fire. The data generated by Kinect by detecting the recognition of the skeleton of the main point of the human body known as the skeleton, where the reading point is authenticated by Kinect from a range of 1.5-3 meters which is declared the optimal measurement, and if a fire occurs, the pump motor will spray water randomly. to extinguish the fire that is connected to the internet via the wifi module. The data displayed is in the form of a graph on the Thingspeak cloud server service. Notification of fire and theft information using the delivery system from input to database

Co-Authors . Darwison Agung P Iswar Akhyar Akhyar Anggara Nasution Audy Aulia Aulia Chatarina Umbul Wahyuni Dwi Mutiara Harfina Dwi Mutiara Harfina Eko Kurniawanto Putra Eko Kurniawanto Putra Eko Rusdi Era Madona Fadhli Palaha Fardhan Arkan Fitria Rahmadina Hamdi Alchudri Laksono, Heru Dibyo Mayang Safira Melda Latif Muhammad Rizky Muhammad Syaiful Amri bin Suhaimi Mumuh Muharam Mumuh Muharram Nasution, Anggara Novi Novi Novi, Novi Putra, Roni Rahmadi Kurnia Rahmadina, Fitria Riko Nofendra Romi Mulyadi Roni Putra Roza Susanti Rusydi, Muhammad Ilhamdi Syarkawi Syamsuddin Taffany Hudalil Alvy Trisya Septiana Waweru Njeri Wisnu Joko Wulung

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)