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Proceeding of the Electrical Engineering Computer Science and Informatics
Published by Institute of Advanced Engineering and Science
ISSN : 2407439X     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, students, engineers and practitioners together to participate and present their latest research finding, developments and applications related to the various aspects of electrical, electronics, power electronics, instrumentation, control, computer & telecommunication engineering, signal processing, soft computing, computer science and informatics.
Arjuna Subject : -
Articles 85 Documents
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Search results for , issue "Vol 6: EECSI 2019" : 85 Documents clear
Performance Evaluation of Superstate HMM with Median Filter For Appliance Energy Disaggregation Erwin Nashrullah; Abdul Halim
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1945

Abstract

Information on electricity consumption is one of the essential elements in terms of regulating the distribution of electricity in smart micro grid. Besides, information on electricity consumption can help consumers carry out an evaluation process to reduce electricity bill costs, which indirectly affect overall energy efficiency. One method in the process of monitoring electricity consumption is Non-Intrusive Load Monitoring (NILM). The main problem in NILM is to determine the energy disaggregation consumed by several equipment by merely performing the retrieval of data from only one measuring point. We used the Superstate Hidden Markov Model as the tool for modelling and analysis. A median data filter to the input data is applied to improve the performance of the disaggregation process. Based on the results of tests conducted using the REDD, the lowest accuracy was 96.69% for all tests performed.
Modified Backward Chaining Android Application to Diagnose Psychoneurosis and Psychosomatic Disorder Wibby Aldryani Astuti Praditasari; Eva Novianti; Ikhwannul Kholis; Rian Andriyusadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1946

Abstract

Stress, depression, mental illness are serious problems but the most often overlooked problems. Ironically, the number of mental problems is greater than health services. The purpose of this study is to develop a system consisting of Admin Webpage and Android Application which analyze mental illness with artificial intelligence that can diagnose and carry out therapy for people with mental disorders which has the types of psychoneurosis and psychosomatic disorders. This research used the methodology of Modified Backward Chaining which works backward towards the initial condition of the patient. Moreover, the system used the Expert System as reference data from the expert, in this case, psychologist. Results could be diagnosed via smartphone by a doctor or expert so they could provide faster and easier treatment in accordance with the application of this Psychological PPD (Psychoneurosis and Psychosomatic Disorders). Finally, the application was successfully implemented to give diagnoses and treatments. The system's ability to deal with mental illness was carried out at Raden Mataher General Hospital, Jambi, Indonesia. This study consisted of 21 respondents consisting of 13 men and 8 women. The result showed that the application was tested Usability Testing which had score 4.22 of 5.
DNSBL for Internet Content Filtering Utilizing pfSense as The Next Generation of Opensource Firewall Alby A Mugni; Muhammad Herdiansah; Muhammad Andhika; Muhammad Ridwan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1947

Abstract

The internet at this time has become an important part of everyday life. From an early age, children already introduced to a digital environment and used to use internet connected devices for various activities such as learning, entertainment, have a chat with family and friends. Apart from convenience and benefits, the Internet also poses a threat to children and adolescents, from inappropriate content such as pornography, violence, narcotics culture, exposure to online pedophiles or dangerous behavior that can make children unsafe. The role of parents in monitoring the online activities of children and adolescents becomes very important. The market offers a variety of control systems for parents who can block or filter content, manage usage, monitor activities, set boundary lines, and quota. This research was conducted to collect basic information about several sites that are often accessed by children with the aim of implementing an internet content screening program utilizing DNSBL and pfSense to increase parental awareness of various technologies that can be used to protect children from the dangers of cyberspace, providing various information for parents of tools that can protect children, and as a form of socialization about the importance of children internet usage monitoring by parents. The study was conducted in the city of Sukabumi by using 30 respondents who were parents of children aged 3-11 years. The most accessible site for children in the city of Sukabumi is Youtube. Therefore, preventive measures are needed to reduce the negative impact caused by filtering content.
Design-of-Experiment Based Systematic Tuning of Square Open Loop Resonator Teguh Prakoso; Imam Santoso; Munawar Riyadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1948

Abstract

Stub-loaded, square open loop resonator (SOLR) is a type of bandpass filter with dual-band response. It is believed that its center frequency values are determined by entire length of open loop resonator’s and open stub's lengths, the bandwidth values are determined by coupling between two resonators. However, design of experiments (DOE) method applied in this paper shows that the center frequency values are also affected by interaction between resonator length, stub length, and distance between the two resonators in pair. The DOE also shows that bandwidth values, both upper and lower bands, are not only affected by the distance between resonators but also by the resonator’s and stub’s lengths. Utilizing slope values of the significant factors, systematic tuning to SOLR can be done. With few steps, small error on frequency responses can be obtained.
Interference Management in Heterogeneous Network With Particle Swarm Optimization Rummi Sirait; Nifty Fath
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1949

Abstract

In heterogeneous network, femtocell is deployedinside macrocell coverage. Femtocell and macrocell use thesame  frequency as the resource. Thus, if the resources are notproperly allocated, the interference will arise. The higher levelof interference results in decreasing signal quality. Therefore,interference management is needed to increase networkcapacity and system performance. This research implementsparticle swarm optimization (PSO) algorithm to minimizeinterference on the heterogeneous network. Based on thesimulation results, it is shown that PSO algorithm worksefficiently to increase the throughput value of femto userequipment (femto UE) up to 62,2 Mbps by minimizing theinterference.
Intelligent System for Recommending Study Level in English Language Course using CBR Method Mirza Sutrisno; Utomo Budiyanto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1950

Abstract

In the admission process, an English Course uses a level placement test. The implementation of the test encountered some problems such as slow determination of student learning levels based on the results of paper based test that are still conventional. The purpose of this research provides the recommendations for an intelligent knowledgebased system in recommending student learning levels using the Case-Based Reasoning (CBR) method. CBR is one of the method that uses the Artificial Intelligence approach and focuses on solving problems based on knowledge from the previous cases, by calculating numerical local similarity and global similarity using the nearest neighbor algorithm as the basic for the technical development of this intelligent system. The result of the study was tested for the data accuracy with the confusion matrix method by the result 100% for the accuracy. For evaluating the system systematically was using the User Acceptance Test (UAT) method with the results of the evaluation is 88% of the system meets user needs and expectations
Low-Power And High Performance Of An Optimized FinFET Based 8T SRAM Cell Design Nurul Ezaila Alias; Afiq Hamzah; Michael Loong Peng Tan; Usman Ullah Sheikh; Munawar A. Riyadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1951

Abstract

The development of the nanotechnology leadsto the shrinking of the size of the transistors to nanometerregion. However, there are a lot of challenges due to sizescaling of the transistors such as short channel effects (SCEs)and threshold voltage roll-off issues. Fin-Type Field EffectTransistor (FinFET) is another alternative technology tosolve the issues of the conventional MOSFET and increasethe performance of the Static Random Access Memory(SRAM) circuit design. FinFET based SRAMs are faster andmore reliable which are often used as memory cache for highspeed operation. However, 6T SRAM cell suffers from accesstransistor sizing conflict resulting in a trade-off between readand write stability. This paper presents an investigation ofthe stability performance in retention, read and write modeof 22nm FinFET based 8T SRAM cell. The performancecomparison of 22nm FinFET based 6T and 8T SRAMs weremade. The simulation of the SRAM model are carried out inGTS Framework TCAD tool based on 22nm technology. In8T SRAM cell, two n-FinFETs are added to the conventional6T SRAM cell which will be controlled by the Read WordLine (RWL) to isolate the read and write operation path forbetter read stability. FinFET based 8T SRAM cell givesbetter performance in Static Noise Margin (SNM) and powerconsumption than 6T SRAM cells. The simulation resultsaffirms the proposed FinFET based 8T SRAM improvedread static noise margin by 166.67% and power consumptionby 76.13% as compared to the FinFET based 6T SRAM.
Testing Big Data Applications Narinder Punn; Sonali Agarwal; Muhammad Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1952

Abstract

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications.
Object Distance Measurement System Using Monocular Camera on Vehicle Fussy Mentari Dirgantara; Arief Syaichu-Rohman; Lenni Yulianti
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1953

Abstract

To support autonomous vehicles that are currently often studied by various parties, the authors propose to make a system of predicting the distance of objects using monocular cameras on vehicles. Distance prediction uses four methods and the input parameter was obtained from images processed with MobileNets SSD. Calculations using linear regression are the simplest calculations among the four methods but have an error of 1% with a standard deviation of 1.65 meters. While using the first method, the average error value is 9% with a standard deviation of 0.43 meters. By using the second calculation, the average error resulted in 6% with a standard deviation of 0.35 meters. The experimental method had an average error of 1% with a standard deviation of 0.26 meters, so the experimental method was used.
Technologies, methods, and approaches on detection system of plant pests and diseases Devie Rosa Anamisa; Muhammad Yusuf; Wahyudi Agustiono; Mohammad Syarief
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1954

Abstract

This research aims to identify the technology, methods, approaches applied in developing plant pest and disease detection systems. For this purpose, it mainly reviews systematically related research on identification, monitoring, detection, and control techniques of plant pests and diseases using a computer or mobile technology. Evidence from the literature shows previous both academia and practitioners have used various technologies, methods and approaches for developing detection system of plant pests and diseases. Some technologies have been applied for the detection system, such as web-based, mobile-based, and internet of things (IoT). Furthermore, the dominant approaches are expert system and deep learning. While backward chaining, forward chaining, fuzzy model, genetic algorithm (GA), K-means clustering, Bayesian networks and incremental learning, Naïve Bayes and Certainty Factors, Convolutional Neural Network, and Decision Tree are the most frequently methods applied in the previous researches. The review also indicated that no single technology or technique is best for developing accurate pest/disease detection system. Instead, the combination of technologies, methods, and approaches resulted in different performance and accuracies. A possible explanation for this is because the systems are used for detecting, controlling and monitoring various plants, such as corn, onion, wheat, rice, mango, flower, and others that are different. This research contributes by providing a reference for technologies, methods, and approaches to the detection system for plant pests and diseases. Also, it adds a way of literature review. This research has implications for researchers as a reference for researching in the computer system, especially for the detection of plant pest and disease research. Hence, this research also extends the body of knowledge of the intelligence system, deep learning, and computer science. For practice, the method references can be used for developing technology for detecting plant pest and disease.

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