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Journal : Journal of Electrical Technology UMY

Voice Recognition Security Reliability Analysis Using Deep Learning Convolutional Neural Network Algorithm Wahyu Ibrahim; Henry Candra; Haris Isyanto
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14281

Abstract

This study discusses the reliability analysis of voice recognition security using the deep learning convolutional neural network (CNN) algorithm. The CNN algorithm has learning advantages in that it is safer, faster, and more accurate. CNN also can solve user identification problems in large amounts of data. The measured voice input is ten types of user's voice with the number of iterations of 6000, 12000, and 15000 sound files. Furthermore, voice extraction features are performed to recognize conversations and retain information that is very much needed. After that, the voice file iteration data is trained to register the user's voice so that a trained model is obtained. These results measure performance (confusion matrix) to analyze the actual value compared to the predicted value in the CNN algorithm. The results obtained are that the best accuracy is obtained at 15000 sound file iterations, 96.87%, 12000 sound file iterations get 96.30%, and 6000 sound file iterations get 95.77%. CNN's performance data shows that 15000 iterations of voice files produce high accuracy. Voice recognition security helps provide high security and maintain the privacy of one's identity.
Design of Monitoring Device for the Process of Organic Waste Decomposition into Compost Fertilizer and Plant Growth through Smartphones based on Internet of Things Smart Farming Haris Isyanto; Jumail Jumail; Rahayu Rahayu; Nofian Firmansyah
Journal of Electrical Technology UMY Vol 5, No 2 (2021): December
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v5i2.12815

Abstract

Based on data published by the Ministry of Living Environment and Forestry in 2020, Indonesia produces at least 93,200 tons of waste per day in various types of composition or around 34 million tons of waste per year. From the collection of waste, it could be used as compost fertilizer which is taken from leaf waste. From these problems, a device was designed that could monitor the decomposition process of organic waste into compost fertilizer. This device is equipped with a temperature sensor, humidity sensor, sensor of soil pH, soil moisture sensor, and color sensor to monitor the composting fertilizer process. The device could also detect plant growth as an indication that the compost fertilizer made is in good condition. Our device was used on the Internet of Things (IoT) and the blynk application as a monitoring application. From the test results, the temperature sensor's accuracy is 98.2%, the humidity sensor is 96.1%, the soil pH sensor is 95.26%, the soil moisture sensor is 98.55%, and the color sensor successfully detects the results of plant growth well. The design of this device is expected to invite the public to be wiser in sorting waste and using it for the surrounding environment.
Design of Security System Device for Motorized Vehicles through the Telegram Messenger Application and Updating GPS Locations on Smartphones in Real Time with IoT-based Smart Vehicles Haris Isyanto; Husnibes Muchtar; Rasma Rasma; Adam Rasyid Dinata
Journal of Electrical Technology UMY Vol 6, No 2 (2022): December
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i2.16182

Abstract

Currently, the number of cases of motorized vehicle theft is increasing. Lack of double security, when left by the owner, is one of the factors that cause vehicles to be easily stolen. Based on these problems, we designed a motorized vehicle security system device that can monitor the condition and update the vehicle location with a smartphone through Global Positioning System (GPS). Furthermore, it can send an active alarm in the form of a buzzer alarm when there is an indication of the danger of vehicle theft. Furthermore, send notifications to the user so that the user immediately locks the vehicle by controlling it remotely in real-time through the Internet of Things (IoT)-based Smart Vehicle Security System using the Telegram Messenger Application and Google Maps (GMaps). The results of testing the response time show that the best performance is very responsive at 2.776 seconds in monitoring and controlling the vehicle. Moreover, the results of testing the vehicle distance position with GMaps and GPS obtained the best performance with a success rate percentage of 97.35% and an error rate percentage of 2.65%. It aims to make vehicle owners feel safe and comfortable and prevent motorized vehicle theft.