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Proceeding of the Electrical Engineering Computer Science and Informatics

EECSI
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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.

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Articles 140 Documents

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Search results for , issue "Vol 4: EECSI 2017" : 140 Documents clear

A Combination of the Evolutionary Tree Miner and Simulated Annealing Afina Lina Nurlaili; Riyanarto Sarno
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

In recent years, process mining is important to discover process model from event logs; however the existing methods have not achieved good in overall fitness. In this context, this paper proposes a combination of the Evolutionary Tree Miner (ETM) and Simulated Annealing (SA). The ETM aims to reduce randomness of population so that it can improved the quality of individuals. SA aims to increase overall fitness in the population. The results of the proposed method which was compared to other approaches show that the proposes method had better in overall fitness and better quality of individuals.

Target Tracking in Mobile Robot under Uncertain Environment using Fuzzy Logic Controller Ade Silvia Handayani; Tresna Dewi; Nyayu Latifah Husni; Siti Nurmaini; Irsyadi Yani
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper discusses a design of fuzzy logic algorithm in a robot. This algorithm is useful for the robot in seeking and reaching the target. The robot is also accomplished with an ability to avoid obstacles. Although the fuzzy rule that is embedded to the robot is very simple, it gives a good result in target seeking and obstacles avoiding task. The originality of this research is an approach to the rules that can simplify the task by creating faster track for the robot in uncertain environment.

Determining The Nutrition of Patient Based on Food Packaging Product Using Fuzzy C Means Algorithm Sri Winiarti; Sri Kusumadewi; Izzati Muhimmah; Herman Yuliansyah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

The main idea in this research is the utilization of Fuzzy C Means (FCM) method as the determination of patient's nutritional status, which is implemented, in mobile application. Parameters used to cluster nutritional status are height, weight and age. The result of the decision will give 3 clusters on nutritional status is good nutrition, malnutrition and better nutrition. Mobile apps are used as a reminder of the nutritional value or ingredients contained in the packaging of food products while consuming food. The result of system testing for application of FCM algorithm in this mobile application obtained validation of 80%.

Empirical Investigation on Factors Related to Individual of Impact Performance Information System Tri Lathif Mardi Suryanto; Djoko Budiyanto Setyohadi; Nur Cahyo Wibowo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Today, many Information System Success studies are performed however only a few studies which focused on the impact of a personal user to succeed of applying IS. The aim of this study is to investigate and to measure the effect of End User Computing Satisfaction into Individual of Impact Performance, with regard the successful implementation of Information system at higher education. Random sampling technique is conducted offline on 100 IS college users and Structural Equation Model technique is used to analyze survey data based on Information System Success model. Our result show that IOIP is influenced by EUCS.

Renewable Energy Inclusion on Economic Power Optimization using Thunderstorm Algorithm A.N. Afandi; Goro Fujita; Yunis Sulistyorini; Nedim Tutkun
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper presents an economic operation considered renewable energy which is optimized using thunderstorm algorithm. The problem is constrained by an emission standard and various technical limits implemented on the 62-bus system model. Simulations showed that the renewable energy inclusion penetrates to the unit commitment of generating units with strongly approach for the computational solution. This inclusion also affects to the individual power production in accordance to the fuel cost and pollutant discharge.

Nitrogen (N) Fertilizer Measuring Instrument On Maize-Based Plant Microcontroller Hendra Yufit Riskiawan; Taufiq Rizaldi; Dwi Putro S. Setyohadi; Tri Leksono
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

One of the growth factors of corn plant is fertilizer according to nitrogen fertilizer requirement. The identification of nitrogen fertilizer requirement in corn plant can be done by measuring the green leaf level using Color Leaf Manual, using TCS3200 color sensor combined with Arduino Uno Board microcontroller, and information. In this study a tool was created that could automatically measure the amount of fertilizer needed for corn per hectare. The results of the measurements displayed on the LCD 2x16 bits Micro made a measurement of fertilizer based on leaf color for corn plants. By taking the RGB value from the leaf that comes through the color sensor and then compared with the RGB value in the leaf color chart that has been saved in microcontroller will get the information of the fertilizer dosage needed. The level of truth of the measuring instrument of fertilizer can be categorized good enough with the level of accuracy reached 82%.

Feature Extraction and Classification of Thorax X-Ray Image in the Assessment of Osteoporosis Riandini Riandini; Mera Kartika Delimayanti
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Previous studies showed that it was possible to have a prediction or an early detection of osteoporosis by measuring the thickness of the cortex of the clavicle of thorax x-ray image. The drawback of this system was that it was still dependent on the operator of subjective vision applications in the measurement. In addition, the accuracy of the system very much relied on the x-ray image quality. Therefore, it is in urgent need of another system which can automatically classify x-ray image and another method of image processing to identify and acknowledge a certain texture of the based image using a set of classes or texture classification given. In this paper, calculation and analysis of a series of image processing algorithms to perform x-ray image classification are done using the K-Nearest Neighbor (KNN) and feature extraction techniques Gray Level Co-occurrence Matrix (GLCM) on small sample size data of 46. Thorax x-ray images of 44 females and 2 males with the average age of 63 years old. T-score of these images had been measured using DEXA scan before as a justification. The proposed method shows that the clavicle cortex thickness measurement using GLCM and KNN method as feature extraction and image classification has its sensitivity of 100% and specificity of 90%. Furthermore, the accuracy which is obtained from the entire implementation capability in correctly assessing osteoporosis is 97.83%. Thus, it is evident that it is significantly correlated with predetermined T-score of DEXA in the assessment of osteoporosis.

Scalable Attack Analysis of Business Process based on Decision Mining Classification Dewi Rahmawati; Riyanarto Sarno
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Banking crime is one of the widespread phenomena in 2016 are closely associated with the used of computer-based technology and internet networks that constantly evolving. One of them is the burglary of customer accounts through the internet banking facility. To overcome this, we need a method of how to detect a conspiracy of bank burglary case of customer accounts. The way to scalable is by get a mining decision to get a decision tree and from the decision tree to get a decision attribute value to determine the level of anomalies. Then of all the attributes decision point is calculated rate of fraud. The rate of fraud is classified through level of security of attack by the attacker then entropy gain is used to calculate the relative effort between the level of attacks in the decision tree. The results show that the method could classify three levels of attacks and the corresponding entropy gains. The paper uses decision trees algorithm, alpha++ and dotted chart analysis to analyze an attack that can be scalable. The results of the analysis show that the accuracy achieved by 0.87%.

Incremental High Throughput Network Traffic Classifier H.R. Loo; Alireza Monemi; Trias Andromeda; M. N. Marsono
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Today’s network traffic are dynamic and fast. Con-ventional network traffic classification based on flow feature and data mining are not able to process traffic efficiently. Hardware based network traffic classifier is needed to be adaptable to dynamic network state and to provide accurate and updated classification at high speed. In this paper, a hardware architecture of online incremental semi-supervised algorithm is proposed. The hardware architecture is designed such that it is suitable to be incorporated in NetFPGA reference switch design. The experimental results on real datasets show that with only 10% of labeled data, the proposed architecture can perform online classification of network traffic at 1Gbps bitrate with 91% average accuracy without loosing any flows.

Optimum Phase Number for Multiphase PWM Inverters Anwar Muqorobin; Pekik Argo Dahono; Agus Purwadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper investigates the optimum phase number for multiphase PWM inverters. The input current ripple is used as a performance indicator. Analysis results show that phase number more than nine cannot provide significant input current ripple reduction. Experimental results are included in this paper to show the validity of the proposed analysis method.

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