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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

Imperceptible Image Watermarking based on Chinese Remainder Theorem over the Edges Prajanto Wahyu Adi; Yani Parti Astuti; Egia Rosi Subhiyakto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This paper introduced a watermarking method using the CRT and Canny Algorithm that able to improve the imperceptibility of watermarked image and preserving the robustness of watermark image as well. The classical CRT algorithm is spread the watermark bits evenly on the image area. It causes significant degradation when the embedding location lies on the least significant region or in the homogeny area. Otherwise, the proposed method embeds the watermark on the edges of the image which have significant difference value to maintain the imperceptibility. The Canny algorithm is used to indexing the embedding location based on the filtering output of host image. The watermark is then embedded into the host image using pair-wise coprime integers of 6 and 11 within the CRT modulo. The results show that the proposed method has significant improvement in the quality of watermarked image with the average value of 0.9995 compared to the CRT method which results in value of 0.9985. In compression and additive noise attacks the CRT has average values of 0.6618 and 0.9750, while the proposed method results in similar values of 0.6616 and 0.9752 respectively. These prove that the proposed method is able to preserve the robustness while improving the imperceptibility.

Wood Texture Detection with Conjugate Gradient Neural Network Algorithm Setyawan Widyarto; I Nyoman Suryasa; Otto Fajarianto; Mohd Shafry Mohd Rahim; Khairul Annuar bin Abdullah; Gigih Priyandoko; Gilang Anggit Budaya
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This project explored fundamental methods to find the factors that can be used in classifying and detecting the type of wood. Whereas, the literatures have been reviewed to determine the algorithms developed. Some experiments have been conducted to analyze the model and system. The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient method of training function in the process of identification. The experiments carried out to be more accurate than the ANN system, the result is about 96% accuracy. It is expected the method can be used and applied for the detection of the type and classification of wood in the industrial sector, especially agriculture

Spoken Word Recognition Using MFCC and Learning Vector Quantization Esmeralda C. Djamal; Neneng Nurhamidah; Ridwan Ilyas
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Identification of spoken word(s) can be used to control external device. This research was result word identification in speech using Mel-Frequency Cepstrum Coefficients (MFCC) and Learning Vector Quantization (LVQ). The output of system operated the computer in certain genre song appropriate with the identified word. Identification was divided into three classes contain words such as "Klasik", "Dangdut" and "Pop", which are used to playing three types of accordingly songs. The voice signal is extracted by using MFCC and then identified using LVQ. The training and test set were obtained from six subjects and 10 times trial of the words "Klasik", "Dangdut" and "Pop" separately. Then the recorded sound signal is pre-processed using Histogram Equalization, DC Removal and Pre-emphasize to reduce noise from the sound signal, and then extracted using MFCC. The frequency spectrum generated from MFCC was identified using LVQ after passing through the training process first. Accuracy of the testing results is 92% for identification of training sets while testing new data recorded using different SNR obtained an accuracy of 46%. However, the test results of new data recorded using the same SNR with training data has an accuracy of 75.5%.

A Hierarchical Description-based Video Monitoring System for Elderly Mochamad Irwan Nari; Agung Wahyu Setiawan; Widyawardana Adiprawita
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

The increase in the number of elderly motivates academic researchers to develop technologies that can ensure self- sufficiency in their lives. In this research, prototype of an inexpensive video monitoring system for the elderly using a single RGB camera proposed. In the process is divided into two, namely vision and event recognition module. For event recognition, we use a hierarchical description-based approach with three attributes, namely posture (e.g., stand, sit and lie), location (e.g., walking zone, relaxing zone and toilet zone) and duration (e.g., short and long). Output this system is description activity recognized in the text. The experiment result shows our system can provide the effectiveness of the context description.

Performance Measurement Based on Coloured Petri Net Simulation of Scalable Business Processes Abd. Charis Fauzan; Riyanarto Sarno; Muhammad Ainul Yaqin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Business process is also a complex area which receives much attention in recent years especially in increasing productivity and saving cost. Meanwhile, situation at the company allows existing business processes to be enlarged. This paper proposed the performance measurement based on coloured petri net simulation of scalable business processes, which has purpose to compare the performance of scalable business processes. For experiments, this paper uses real-world business processes. Then compare it to some business processes that have been enlarged. The result shows that scalable business processes influence the performance of business process. This paper provides feedback to business process developers for determine appropriate business processes based on the performance through coloured petri net simulation.

Implementation of Decision Expert (DEX) in The “SALADGARDEN” Application Anita Hidayati; Fityan Aula Juyuspan; Cindy Novianty; Muhammad Bima D S
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

In the field of agriculture, it is necessary to make right decisions for determining various things. Among others is in determination of plants to be planted with several criteria such as knowledge, budget, land area, human resources, and investment value possessed. Therefore, decision support systems constitute appropriate method to facilitate farmers or non- farmers to make decisions. The expert system will be developed is desktop-based and uses Decision Expert (DEX) method to generate recommendations for most appropriate decision selection therefore it can be reference for all users. This study will define criteria on value set of Salad Garden application in the DEX evaluation model. To be prepared for all possible combinations of input and output criteria values. Rules specified by decision maker with aggregation function declared point-by- point for all possible combinations of attribute values. From test results based on DEX method calculation, decision for plant species to be planted through determination of each criterion and rule.

Optimizing Effort and Time Parameters of COCOMO II Estimation using Fuzzy Multi-objective PSO Kholed Langsari; Riyanarto Sarno
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

The estimation of software effort is an essential and crucial activity for the software development life cycle. Software effort estimation is a challenge that often appears on the project of making a software. A poor estimate will produce result in a worse project management. Various software cost estimation model has been introduced to resolve this problem. Constructive Cost Model II (COCOMO II Model) create large extent most considerable and broadly used as model for cost estimation. To estimate the effort and the development time of a software project, COCOMO II model uses cost drivers, scale factors and line of code. However, the model is still lacking in terms of accuracy both in effort and development time estimation. In this study, we do investigate the influence of components and attributes to achieve new better accuracy improvement on COCOMO II model. And we introduced the use of Gaussian Membership Function (GMF) Fuzzy Logic and Multi-Objective Particle Swarm Optimization method (MOPSO) algorithms in calibrating and optimizing the COCOMO II model parameters. The proposed method is applied on Nasa93 dataset. The experiment result of proposed method able to reduce error down to 11.891% and 8.082% from the perspective of COCOMO II model. The method has achieved better results than those of previous researches and deals proficient with inexplicit data input and further improve reliability of the estimation method.

Evaluation of Knowledge Management System Using Technology Acceptance Model Jarot S. Suroso; Astari Retnowardhani
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This study was motivated to assess the Knowledge Management System (KMS) using Technology Acceptance Model (TAM). TAM is the best concept to be taken as model on explaining user attitude of new technology. TAM model used in the study because it has been widely adopted among IT researchers and appears to be growing rapidly, has the reliability and construct validity were established, and realized that the model has not been applied to the acceptance KMS. The data population in this study is the employees in PT. XYZ who have work-related to development and maintenance process. The data analysis was done using Partial Least Squares (PLS). The analysis was proof to be statistically significant: a) perceived ease of use and perceived usefulness, b) perceived ease of use and attitude, c) perceived usefulness and attitude, d) perceived usefulness and behavioral intention to use, e) behavioral intention to use and actual use.

Analysis of Statement Branch and Loop Coverage in Software Testing with Genetic Algorithm Rizal Broer Bahaweres; Khoirunnisya Zawawi; Dewi Khairani; Nashrul Hakiem
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Software testing is one important aspect of the software development process. About 50% of the time and cost in the software development process used for software testing process. There are two methods of software testing, black-box testing and white-box testing. This research using white-box testing. Software testing can be done manually or automatically. Based on research conducted, genetic algorithm has been widely implemented in software testing, such as test data generator. The purpose of this study is to apply a genetic algorithm in software testing and comparing the results with manual testing, automated, and automated with genetic algorithm. The test parameters are coverage measurements (statement, branch and loop coverage) and the time of testing. The conclusion of this study is automated testing with genetic algorithm requires fewer time and test cases to achieve coverage of 100%

Deep Learning on Curriculum Study Pattern by Selective Cross Join in Advising Students’ Study Path Tekad Matulatan; Muhammad Resha
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Advising engineering students in their study path need to understand the curriculum structure, student capabilities and challenge that commonly appear in courses. This paper offered the simple method to help student advisor in analyzing student performance in their study path based on academic progress record of the student it-self and pattern that been built from other students that have taken the courses. Using selective cross join for each possible permutation of pair courses with respect to courses’ grade to create knowledge base. This knowledge base will be used to construct complex tree of any possible study path that might be taken by student to reach the end of study including course that must be retaken. Finding the best suggestion for study path using Monte Carlo tree search style

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