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Nyoman Gunantara
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Program Studi Teknik Elektro Fakultas Teknik - Universitas Udayana d/a. Kampus Bukit Jimbaran Bali - 80364 Phone/ Fax: +62 361 703315
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Jurnal SPEKTRUM
Published by Universitas Udayana
ISSN : 23023163     EISSN : 26849186     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering
Jurnal SPEKTRUM is peer review journal, published four times a year by the Department of Electrical Engineering, Faculty of Engineering, Universitas Udayana. This journal discusses the scientific works containing results of research in the field of electrical, include: power systems, telecommunications, computers, informatics, controls, and electronics. Authors are expected to include original scientific papers in accordance with the scope of the discussion of this journal including all aspects of the theory and practice are used.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 582 Documents
 55   56   57   58   59 
PERBANDINGAN METODE KLASIFIKASI SUPPORT VECTOR MACHINE DAN NAÏVE BAYES PADA ANALISIS SENTIMEN KENDARAAN LISTRIK Ni Wayan Ernawati; I Nyoman Satya Kumara; Widyadi Setiawan
Jurnal SPEKTRUM Vol 10 No 3 (2023): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2023.v10.i03.p12

Abstract

Electric vehicles are one of the solutions that can be used to deal with the problem of greenhouse gas emissions. Switching to electric vehicles can be an effective solution because electric vehicles have many advantages. However, the acceptance of electric vehicles in Indonesia depends on the opinions or sentiments given by the community. Sentiment analysis can provide a specific picture of how the sentiment or opinion given by the Indonesian people towards electric vehicles. The sentiment analysis process is carried out using the Python programming language. This research compares SVM and Naïve Bayes methods in sentiment analysis in terms of accuracy and time efficiency. A total of 717 data were used as test data and SVM correctly classified 150 negative data, 152 neutral data, and 277 positive data. Meanwhile, Naïve Bayes correctly classified 166 negative data, 143 neutral data, and 282 positive data. training time required for the SVM method is 37.42 seconds while Naïve Bayes is 0.10 seconds. Naïve Bayes is the best method in this study because of its high accuracy and fast training time.
RANCANG BANGUN PERANGKAT KERAS SISTEM SMART LAMPU PENERANGAN JALAN UMUM BERBASIS INTERNET OF THINGS GUNA MENDUKUNG IMPLEMENTASI SMART CITY Dharma Dutaluhur Artha Lesmana; I Made Arsa Suyadnya; I Wayan Shandyasa
Jurnal SPEKTRUM Vol 10 No 3 (2023): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2023.v10.i03.p3

Abstract

Public Street Lighting (PJU) is a lighting system designed to provide street lighting at night with the aim of increasing comfort for pedestrians and motorists passing through. However, the obstacles faced regarding PJU lights at this time are that when carrying out monitoring and control officers are still checking and visiting the location of every whereabouts of PJU lights. So that to make it easier for officers to manage PJU lights in this study, they will conduct discussions related to the design and development of hardware that is applied to PJU lights. The methods used in the development of this system are design, development, and testing. To build hardware using components such as ESP32 as a microcontroller, PZEM004Tv30 sensor, DHT22 sensor, IC RTC DS3231, Relay 30 A, IC LM2596 5V, IC AMS1117 3.3V, GSM SIM808 Module and LDR sensor, while for implementing the protocol using the MQTT protocol and Antares as the MQTT platform. The results of tests carried out on each circuit block in hardware such as the DHT22 sensor have an accuracy range of ~0.1 – 0.2, the PZEM004Tv30 sensor has an accuracy range of ~0.3 – 0.5, Regulator IC LM2596 5V and AMS1117 3.3V each has an appropriate output voltage of ~5V and ~3.3V, and the CH340C IC Driver IC can work and read properly.

Page 59 of 59 | Total Record : 582

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