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  Subjects -> ELECTRONICS (Total: 207 journals)
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Jurnal Teknik Elektro
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  This is an Open Access Journal Open Access journal
ISSN (Print) 1411-0059 - ISSN (Online) 2549-1571
Published by Universitas Negeri Semarang Homepage  [79 journals]
  • Pengkondisi Sinyal RTD Presisi pada Terowongan Angin Indonesian Low-Speed
           Tunnel

    • Authors: Muhamad Muflih, Munawar Agus Riyadi, Ivranza Zuhdi Pane, Franky Surya Parulian
      Pages: 44 - 51
      Abstract: The temperature of the Indonesian Low-Speed Tunnel (ILST) wind tunnel test section was measured using a Pt100-type Resistance Temperature Detector (RTD) sensor. With the upgrade of the Indonesian Low-Speed Tunnel - Data Acquisition and Reduction System (ILST-DARS) using Ethernet communication, an integrated RTD linearization circuit was designed with the Conditioning Unit (CU) Mk3 to replace the Newport 267B 16-bit parallel and DAS-Hub as the current RTD interface. In this research, the design of the signal conditioner uses the RTD_Linearization_v7.xls program from Texas Instruments, the LTspice simulator software, and the AMP01E precision instrumentation amplifier. Based on the calibration results in the range of 20 – 50 0C, this signal conditioner has an average deviation value of 0.38 0C (1.31%). In the wind tunnel speed variation testing with a range of 30 – 65 m/s, the RTD signal conditioner had an average deviation of 0.41 K (0.14%). The Repeatability Test procedure was carried out at a wind speed of 65 m/s with an angle of attack for the test model from -90 to 200 and data were collected 10 times at each angle. The average deviation of temperature against variations in the angle of attack of the test model in this procedure is 0.25 K (0.08%) and the average deviation of wind speed against variations in the angle of attack of the test model is 0.03 m/s (0.04%).
      PubDate: 2023-01-27
      DOI: 10.15294/jte.v14i2.39415
      Issue No: Vol. 14, No. 2 (2023)
       
  • Classroom Occupancy Monitoring System using IoT Device and the k-Nearest
           Neighbors Algorithm

    • Authors: Yarnish Dwi Sagita Fidarliyan, Agung Budi Prasetijo, Dania Eridani
      Pages: 36 - 43
      Abstract: The occupancy monitoring system is one of the substantial aspects of building management. Through monitoring the occupancy in the area in a building, the obtained information can be used for building management purposes such as controlling indoor area air quality and improving building security. Some technologies such as video surveillance cameras, Radio Frequency Identification (RFID), and motion sensors have been used in the occupancy monitoring system. However, those technologies pose several disadvantages including privacy concerns and limited information generated. A classroom occupancy monitoring system using an Internet of Things (IoT) device and the k-Nearest Neighbors (k-NN) algorithm was built to monitor classroom occupancy by classifying the number of occupants based on classroom environmental data into occupancy levels by using the k-NN classifier model. By utilizing IoT devices, CO2, temperature, and humidity data in a naturally ventilated classroom were recorded using the MQ-135 and BME280 sensors, as well as WiFi-based NodeMCU, was used to distribute data to the cloud. The collected data were trained and tested by the k-NN algorithm to produce a k-NN classifier model. From the tests conducted, the performance of the k-NN classifier model in classifying the number of occupants into occupancy levels resulted in an accuracy of 88%. In addition, the proposed system also produces a web-based classroom occupancy monitoring application that has been integrated with the k-NN classifier model so the classification can be done for real-time data and monitored directly.
      PubDate: 2022-12-30
      DOI: 10.15294/jte.v14i2.37141
      Issue No: Vol. 14, No. 2 (2022)
       
 
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