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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 : -
Core Subject :
Arjuna Subject : -
Articles 63 Documents
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Search results for , issue "Vol 12, No 3: December 2018" : 63 Documents clear
Performance of Bidirectional Converter Based On Grid Application D. Vidhyalakshmi; K. Balaji
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1203-1210

Abstract

A transformer less bidirectional inverter fed grid-connected system has implemented and function as both forward and reverse power flow by battery and photovoltaic system. In dc distributed system has utilized the renewable energy such as PV, wind, battery and fuel system. In conventional method the dc bus regulation by using the one line cycle regulation method and one-sixth line cycle regulation. In proposed method utilize both converter and inverter operates bidirectional direction and utilize both solar and PV source. The solar energy had less cost, pollution less energy generation and fed into the bidirectional converter. The PI-based control method is used to operate both forward and reverse direction. The model predictive control method is used in the bidirectional inverter for control the current and voltage of the grid-connected system. The power flow control in the distribution system by the constant power loads such as dc/dc converter because conduct the negative dynamic impedance. The three-phase bidirectional inverter is designed and implemented in MATLAB/Simulink environment.
Eigenvalue of Analytic Hierarchy Process as The Determinant for Class Target on Classification Algorithm Mustakim Mustakim; Novia Kumala Sari; Jasril Jasril; Ismu Kusumanto; Nurul Gayatri Indah Reza
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1257-1264

Abstract

Data mining has two main concepts of data distribution, namely supervised learning and unsupervised learning. The most easily recognizable concepts from data distribution is related to the dataset, with and without target class. Analytic Hierarchy Process (AHP) technique that carries the concept of pairwise comparison able to answer the problem related to the dataset, which is to change unsupervised to be supervised by determining eigenvalue value of each attribute and sub attribute in AHP method. The case study conducted in this issue is related to determining the target classes used to predict the success of a student learning in UIN Suska Riau. The three main attributes are Procrastination, Total Credits (SKS) and Number of Repeated Courses, each having eigenvalues of 0.319; 0.189 and 0.171 which become the feedback in the determination of the Target Timely Graduation (TG) or Possibility of Timely Graduation (PTG). The biggest consistency ratio generated in the AHP case is 9.4% in the GPA attribute. This research recommends that further research should use datasets that have been arranged based on experimental combinations of the three main attributes above, then applied to the classification or prediction algorithm. So that it would obtain a decision of accuracy from data used against the real result on the field.
A Study of Meat Freshness Detection using Embedded-based pH Sensor Rajina R. Mohamed; Razali Yaacob; Mohamad A. Mohamed; Arniyati Ahmad; Munir Tajuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1386-1393

Abstract

For the past few years, food safety incidents often occur as a result of food poisoning from various food sources such as in schools, hospitals, night markets, street stalls and the like. When the quality of food is reduced due to the low level of freshness, cleanliness factor, safety and nutrition, it can contribute to health risks. According to World Health Organization, food poisoning ailment is a global problem and almost 1 in 10 people fall ill every year from eating degraded food and 420 000 die as a result. Factors such as cost savings, low awareness on food freshness and busy routine lifestyle aggravate the food poisoning problem. Hence it is important to at least maintain the freshness of the food mainly at the prominent area such as school and hospital. There are many methods used to test the freshness food, such as visual appearance, and also classical olfaction including normal olfactory and Scentometer, which requires trained panels to taste or smell the food samples to ensure the quality or strength of the odor. However, this method is rather subjective, because the human sense of smell and taste is different and may be influenced by the weather and experience. Conventional pH and litmus paper also are the alternatives, however the material itself is easily damaged and not suitable for the color blind person. In this paper, we presented raw meat examination using pH sensor based on food acidity. Examination of food freshness level is much easier using pH sensor since it is more practical to be used by consumers at home since it can be mobile, long lived, and accurate embedded-based application. Some testing has been conducted on sensor capability reacting with several buffer solutions on meat samples left at room temperature at various periods of time. Generally, the embedded pH sensor developed has successfully tested raw meat freshness level based on acidity level of meat.

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