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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 3 Documents
 1 
Search results for , issue "Vol. 9 No. 1 (2023): March" : 3 Documents clear
Comparison of Support Vector Machine (SVM) and Random Forest Algorithm for Detection of Negative Content on Websites Syahputra, Hermawan; Wibowo, Aldiva
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i1.25861

Abstract

The amount of negative content circulating on the internet can damage people's morale so that social conflicts arise in society that threaten national sovereignty. Detecting negative content can help identify and prevent harmful events before they occur. This can lead to a safer and more positive online environment. Comparison of Support Vector Machine (SVM) and Random Forest (RF) Algorithm for Detection of Negative Content on Websites. The research contributions are 1) detect negative content on the internet with random forest and SVM, 2) comparing SVM and RF algorithms for detecting negative content on websites, 3) detection of negative content based on text focusing on the categories of fraud, gambling, pornography and Whitelist. The stages of this research are preparing a text content dataset on a website that has been labeled, preprocessing (duplicated data, text cleansing, case folding, stopward, tokenize, label encoding, data splitting, and determine the TF-IDF), finally performing the classification process with SVM and Random Forest. The dataset used in this study is a structured dataset in the form of text obtained from emails that have been registered on the TrustPositive website as negative content.  Negative content includes fraud, pornography and gambling. The results show the accuracy of the SVM is 97%, Precision 90% and Recall 91%, while for Accuracy in Random Forest is 92%, Precision 71%, and Recall 86%. The value obtained is the result of testing using 526 website URLs. The test results show that the Support Vector Machine is better than the Random Forest in this study.
Implementation Of Fuzzy Logic Control Method On Chilli Cultivation Technology Based Smart Drip Irrigation System Umam, Faikul; Dafid, Ach.; Cahyani, Andharini Dwi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i1.25878

Abstract

Herbal chili plants are very beneficial from a health and economic perspective. In the process of cultivating herbal chili plants, there are still many problems that need to be faced, including unfavorable climatic conditions and less intensive cultivation processes. Based on this description, to overcome these problems, technological innovation is needed that can be implemented directly in the cultivation of herbal chili plants. This situation can be achieved by applying a drip irrigation system. This system makes it possible to control the water supply requirements of chili herbs efficiently. System stability can run optimally when combined with a method that can make a decision quickly. Fuzzy logic is used in research because it is able to provide appropriate decisions on temperature and soil moisture data in chili herbs. This research is expected to overcome the problem of water shortages in barren areas. And increase people's interest in the cultivation of herbal chili plants. This research is also an overview and framework for developing the agricultural sector in Madura in the technology field. The results of this study indicate that technology can be designed and integrated with the fuzzy logic control method, then the results of testing the tool also show a 99,98% success rate. This is shown by the results of testing in the morning, afternoon, and evening. The contribution of this study is the control of temperature and humidity which in other studies only focused on the soil, not on the temperature and humidity of the air around the herbal chili plants with a system that has been controlled using the fuzzy method.
Dynamic Voltage Restorer for Mitigation of Voltage Sags Due to 3 Phase Motor Starts Based on Artificial Neural Networks Sujito, Sujito; Gumilar, Langlang; Ridzki, Imron; Syah, Abdullah Iskandar; Falah, Moh. Zainul
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i1.25897

Abstract

The Direct On-Line (DOL) process of starting a high-power 3-phase induction motor causes voltage sags in the distribution system that is connected to one point of common coupling (PCC). Voltage sag can cause damage and failure of sensitive loads. This article analyzes and proposes a simulation of voltage sag recovery using a Dynamic Voltage Restorer (DVR) based on an Artificial Neural Network (ANN). ANN is used as a detector and regulator of the voltage compensation value. In this study, a 3-phase induction motor will be connected to a sensitive load, and the DVR will be placed in series with a voltage source or PCC with a sensitive load. The simulation test system uses Simulink-Matlab R2016a with different configurations of induction motor parameters. Based on the simulation results show that the parameters of the 3-phase induction motor cause the depth and duration of the voltage sag. DVR with ANN control can detect and compensate for a voltage sag of 0.5 pu so that the voltage will be normal to 1 pu.

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