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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
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Articles 67 Documents
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Search results for , issue "Vol 22, No 2: May 2021" : 67 Documents clear
Android-based capacitor discharging calculator application Wisnu Kartika; Erika Loniza; Meilia Safitri
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp760-764

Abstract

Nowadays, many people using smartphone to connet to her colleague. The electronic device using capacitor and transistor. The electronic device’s size recently become smaller. The capacitor can be used to the most important function that is used to store the energy and on the DC system is used to decrease the ripple from AC source. This research purpose build an apps which can calculate the charge remaining inside the capacitor. The method is using RC time constant. This research work well and can work functionally. 
A comparative analysis on traditional wired datasets and the need for wireless datasets for IoT wireless intrusion detection Teh Boon Seong; Vasaki Ponnusamy; Noor Zaman Jhanjhi; Robithoh Annur; M N Talib
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp1165-1176

Abstract

IoT networks mostly rely on wireless mediums for communication, and due to that, they are very susceptible to intrusions. And due to the tiny nature, processing complexity, and limited storage capacities, IoT networks require very reliable intrusion detection systems (IDS). Although there are many IDS types of research available in the literature, most of these systems are suitable for wired network environments, and the benchmark datasets used for these research works are mostly relying on wired datasets such as KDD Cup’99 and NSL-KDD. IoT and wireless networks are distinct in nature as wireless networks give more emphasis on the data link layer and physical layer. These concerns are not given much attention in traditional wired datasets in the body of knowledge. Therefore, in this research, an IDS system is developed using a newly available IoT wireless dataset (NaBIoT) in the literature with the datasets focusing much on the common IoT related attacks, and related layers are taken into consideration. The IDS system developed is evaluated by comparing with various machine learning algorithms in terms of evaluation metrics such as accuracy, F1 score, false positive, and false negative. Moreover, the IoT wireless dataset is compared against the traditional NSL-KDD datasets to evaluate the need for IoT wireless datasets. The NaBIoT datasets show its effectiveness in detecting wireless intrusions. Besides that, the simulation is performed with different combinations of features to conclude that certain features are primary in detecting attacks, and IDS does not require all the features to perform detection. This can reduce the detection time mainly for machine learning and creating the models. This research results have proposed some of the critically important features to be used and eliminating not such important features.   
Development of an IoT-based water and power monitoring system for residential building Leah Santos; John Carlo Bautista; Matt William Estanque; Christian John Paloa; Ana Beatrice Villaran
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp744-751

Abstract

This study provides information between tenants and landlords on the use of the Internet of Things for power and water monitoring systems. It is one way to make reading meters and water meters easier to access using the available internet connection. The developed application using the android studio software is installed on a smartphone/tablet and verified to fully working on android versions from 4.1 (jellybean) to android 9.0 (pie). Tests were carried out in a household where the prototype was installed in a residential apartment. The data collected was monitored in the application and viewed by tenants and landlords. The results from the mean comparison of the power and volume readings measured by the wattmeter and water meter claim that the readings from the conventional meters and designed prototype have no significant difference using the Mann-Whitney U test. Evaluations were conducted showing that the device and the developed application using IoT is reliable, accurate, functional and user-friendly to use by tenants and landlords.
A survey of distance learning in Morocco during COVID19 Sara Ouahabi; Kamal El Guemmat; Mohamed Azouazi; Sanaa El Filali
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp1087-1095

Abstract

The face-to-face mode is always considered as the normal mode of teaching, and distance education is often understood as a remedy for the lack of material and human resources necessary to conduct training; but to prevent the spread of the coronavirus (COVID19), the distance course system has been launched in different countries to ensure continuity of teaching during the period when courses are stopped. In order to shed light on the role of distance learning during the spread of the coronavirus and its effectiveness in successfully continuing the learning process, an investigation was carried out in the Moroccan context. This survey was launched as a questionnaire with 565 participants; they are students and teachers from primary, secondary, university and professional training. The objective is to answer several research questions concerning the current use of distance education during the COVID19 pandemic. The results of this survey are presented in this article as well as their analysis showing that solutions and alternatives must be adopted in order to improve the teaching and learning process in the event of a situation like COVID19.
Exploiting non-orthogonal multiple access in device-to-device communication Sang Hoon Lee; Soo Young Shin
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp919-926

Abstract

This paper proposes an uplink non-orthogonal multiple access (NOMA) system with device-to-device (D2D) communication, enabling NOMA users to communicate with other users/devices using D2D communication to improve the system capacity. In the NOMA-D2D system, two cellular users communicated with the BS using uplink NOMA, and two cellular users simultaneously communicated with the D2D users using downlink NOMA. Closed-form solutions for the ergodic sum capacity of the proposed system are derived analytically. The analytical results are validated via simulations and they are compared with the results obtained from conventional schemes. The comparison shows that, in scenarios where efficient interference cancellation can be achieved, the proposed NOMA system with the D2D model can achieve higher capacity gains than conventional benchmark schemes. When  dB, NOMA-D2D achieves capacity gains of 192.2% and 157.5% over the conventional OMA and the time-sharing-based NOMA, respectively.
Design of gas concentration measurement and monitoring system for biogas power plant Iswanto Iswanto; Alfian Ma’arif; Bilah Kebenaran; Prisma Megantoro
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp726-732

Abstract

Biogas is a gas obtained from the breakdown of organic matter (such as animal waste, human waste, and plants) by methanogenic bacteria in an oxygen-free (anaerobic) state. The biogas produced mainly consists of 50-70% methane, 30-40% carbon dioxide, and other gases in small amounts. The gas produced has a different composition depending on the type of animal that produces it. It is challenging to obtain biogas concentration data because the monitoring equipment is currently minimal. Therefore, this research discusses how to make a monitoring system for biogas reactors. Sensors are installed in the digester tank and storage tank. The installed sensors are the MQ-4 sensor to detect methane gas (CH4), MG-811 sensor to detect carbon dioxide (CO2) gas, MQ-136 sensor to detect sulfide acid gas (H2S), and Thermocouple Type-K to detect temperature. The sensor will send a signal to the control unit in Arduino Mega 2560, then processed and displayed on the liquid crystal display (LCD). The sensor calculation results' accuracy is not much different from the reference based on the sensor readings. The sensor deviation standard is below 5.0, indicating that the sensor is in precision. The sensor's linearity of MQ-4 is 0.7%, the MG-811 is 0.17%, the MQ-136 is 0.29%, and the Type-K Thermocouple is 1.19%. The installed sensor can be used to monitor gas concentration and temperature in a biogas reactor.
A multi-criteria assessment of decision support systems in educational environments Amjad Alowaigl; Khalil H. A. Al-Shqeerat; Mohammed Hadwan
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp985-996

Abstract

Decision support systems (DSS) are useful business intelligence (BI) tools as they help managers in large organizations make the best out of many decisions. Decisions are based on various types of raw data, models, documents, knowledge, and past experiences. This paper examines numerous criteria of decision support systems in the educational environment. Two effective methods were discovered and applied in this research, the analytic hierarchy process (AHP) and simple multi-attribute rating technique (SMART). These methods were selected due to their abilities to deal with complex decisional environments in general and widely used in practice for the educational environment in specific. The performance of methods is compared using two datasets called xApi-Education and IPEDS datasets. The obtained results based on the measurement of space complexity showed the level of convergence and similarity between these two methods. However, the experiments show that the Simple Multi-Attribute Rating Technique outperformed the analytic hierarchy process in terms of accuracy, deviation, and time complexity measurement.
Predicting temperature of Erbil City applying deep learning and neural network Sardar M. R. K. Al- Jumur; Shahab Wahhab Kareem; Raghad Z. Yousif
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp944-952

Abstract

One of the most significant and daunting activities in today's world is temperature prediction. The meteorologists traditionally predict temperature via some statistical models aimed to forecast the fluctuations that might have happened to atmospheric parameters such as temperature, humidity, etc. The main objective of this paper is to build an intelligent temperature prediction model of Erbil city in KRG/ Iraq based on a historical dataset from 1992 to 2016 in each year there are twelve months’ average temperature readings from (January to December). Hence to resolve this prediction problem an up-to-date deep learning neural network has been used, the network model is based on long short-term memory (LSTM) as an artificial recurrent neural network (RNN) architecture which employed to estimate the future average temperature. The implementing model uses the dataset from real-time 30 weather stations deployed in the area of the city. The prediction performance of the proposed recurrent neural network model has been compared with some state of art algorithms like Adeline neural network, Autoregressive neural network (NAR), and  generalized regression neural network (GRNN). The results show that the proposed model based on deep learning gives minimum prediction error.
The trends of supervisory control and data acquisition security challenges in heterogeneous networks M. Agus Syamsul Arifin; Susanto Susanto; Deris Stiawan; Mohd Yazid Idris; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp874-883

Abstract

Supervisory control and data acquisition (SCADA) has an important role in communication between devices in strategic industries such as power plant grid/network. Besides, the SCADA system is now open to any external heterogeneous networks to facilitate monitoring of industrial equipment, but this causes a new vulnerability in the SCADA network system. Any disruption on the SCADA system will give rise to a dangerous impact on industrial devices. Therefore, deep research and development of reliable intrusion detection system (IDS) for SCADA system/network is required. Via a thorough literature review, this paper firstly discusses current security issues of SCADA system and look closely benchmark dataset and SCADA security holes, followed by SCADA traffic anomaly recognition using artificial intelligence techniques and visual traffic monitoring system. Then, touches on the encryption technique suitable for the SCADA network. In the end, this paper gives the trend of SCADA IDS in the future and provides a proposed model to generate a reliable IDS, this model is proposed based on the investigation of previous researches. This paper focuses on SCADA systems that use IEC 60870-5-104 (IEC 104) protocol and distributed network protocol version 3 (DNP3) protocol as many SCADA systems use these two protocols.
K-means method for clustering learning classes A. D. Indriyanti; D. R. Prehanto; T. Z. Vitadiar
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp835-841

Abstract

Learning class is a collection of several students in an educational institution. Every beginning of the school year the educational institution conducts a grouping class test. However, sometimes class grouping is not in accordance with the ability of students. For this reason, a system is needed to be able to see the ability of students according to the desired parameters. Determination of the weight of test scores is done using the K-Means method as a grouping method. Iteration or repetition process in the K-Means method is very important because the weight value is still very possible to change. Therefore, the repetition process is carried out to produce a value that does not change and is used to determine the ability level of students. The results of the class grouping test scores affect the ability of students. Application of K-Means method is used in building an information system grouping student admissions in an educational institution. Acceptance of students will be grouped into 3 groups of learning classes. The results of testing the system that applies K-Means method and based on data on the admission of prospective students from educational institutions have very high accuracy with an error rate of 0.074. 

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