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Agus Harjoko
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INDONESIA
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Published by Universitas Gadjah Mada
ISSN : 19781520     EISSN : 24607258     DOI : https://doi.org/10.22146/ijccs
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 476 Documents
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Klasifikasi Belimbing Menggunakan Naïve Bayes Berdasarkan Fitur Warna RGB Fuzy Yustika Manik; Kana Saputra Saragih
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 1 (2017): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.17838

Abstract

Post harvest issues on star fruit are produced on a large scale or industry is sorting. Currently, star fruit classified by rind color analysis visually human eye. This method does not effective and inefficient. The research aims to classify the starfruit sweetness level by using image processing techniques. Features extraction used is the value of Red, Green and Blue (RGB) to obtain the characteristics of the color image. Then the feature extraction results used to classify the star fruit with Naïve Bayes method. Starfruit image data used 120 consisting of 90 training data and 30 testing data. The results showed the classification accuracy using RGB feature extraction by 80%. The use of RGB as the color feature extraction can not be used entirely as a feature of the image extraction of star fruit.
Motion Detection and Face Recognition for CCTV Surveillance System Ade Nurhopipah; Agus Harjoko
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 12, No 2 (2018): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.18198

Abstract

Closed Circuit Television (CCTV) is currently used in daily life for a variety purpose. Development of the use of CCTV has transformed from a simple passive surveillance into an integrated intelligent control system. In this research, motion detection and facial recognation in CCTV video is done to be a base for decision making to produce automated, effective and efficient integrated system. This CCTV video processing provides three outputs, a motion detection information, a face detection information and a face identification information. Accumulative Differences Images (ADI) used  for motion detection, and Haar Classifiers Cascade used  for facial segmentation. Feature extraction is done with Speeded-Up Robust Features (SURF) and Principal Component Analysis (PCA). The features was trained by Counter-Propagation Network (CPN). Offline tests performed on 45 CCTV video. The test results obtained a motion detection success rate of 92,655%, a face detection success rate of 76%, and a face detection success rate of 60%. The results concluded that the process of faces identification through CCTV video with natural background have not been able to obtain optimal results. The motion detection process is ideal to be applied to real-time conditions. But in combination with face recognition process, there is a significant delay time.
Rancang Bangun Plugin Protégé Menggunakan Ekspresi SPARQL-DL Dengan Masukan Bahasa Alami Muhammad Fahrurrozi; Azhari SN
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.18360

Abstract

Semantic web is a technology that allows us to build a knowledge base or ontology for the information of the web page can be understood by computers. One software for building ontology-based semantic web is a protégé. Protege allows developers to develop an ontology with an expression of logic description. Protégé provides a plugin such as DL-Query and SPARQL-Query to display information that involve expression of class, property and individual in the ontology. The problem that then arises is DL-plugin Query only able to process the rules that involve expression of class to any object property, despite being equipped with the function of reasoning. while the SPARQL-Query plugin does not have reasoning abilities such as DL-Query plugin although the SPARQL-Query plugin can query memperoses rules involving class, property and individual. This research resulted in a new plugin using SPARQL-DL with input natural language as a protégé not provide a plugin with input natural language to see results from the combined expression-expression contained in the ontology that allows developers to view information ontology language that is easier to understand without having think of SPARQL query structure is complicated.
Sentiment Analysis of Movie Opinion in Twitter Using Dynamic Convolutional Neural Network Algorithm Fajar Ratnawati; Edi Winarko
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 12, No 1 (2018): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.19237

Abstract

Movie has unique characteristics. When someone writes an opinions about a movie, not only the story in the movie itself is written, but also the people involved in the movie are also written. Opinion ordinary movie written in social media primarily  twitter.To get a tendency of opinion on the movie, whether opinion is likely  positive, negative or neutral, it takes a sentiment analysis. This study aims to classify the sentiment is positive, negative and neutral from opinions Indonesian language movie and look for the accuracy, precission, recall and f-meausre of the method used is Dynamic Convolutional Neural Network. The test results on a system that is built to show that Dynamic Convolutional Neural Network algorithm provides accuracy results better than Naive Bayes method, the value of accuracy of 80,99%, the value of precission 81,00%, recall 81,00%, f-measure 79,00%   while the value of the resulting accuracy Naive Bayes amounted to 76,21%, precission 78,00%, recall 76,00%, f-measure 75,00%.
Front Cover IJCCS Vol.10 No.2 cover depan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 10, No 2 (2016): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Group Decision Support System Determination Of Best Employee Using Topsis And Borda Made Arya Budhi; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.22773

Abstract

Determining the best employee at Lombok Garden inteded to stimulate the performance of the hotel employees Lombok Garden. Improved performance of employees it will have a direct effect on the quality of hotel services. Employee performance appraisement are conducted by six assessors, namely the head of each department and consists of several criteria. Assessments will be difficult if done manually considering each appraiser has its own preferences in assessment. To solve that problem, we need a computer system that helps decision-making is a group decision support system (GDSS) determination of the best employees in the hotel Lombok Garden.Group decision support system developed in this study using TOPSIS (Technique For Order Preference By Similiarity To Ideal Solution) and Borda to assist decision-making group. TOPSIS method is used for decision-making in each appraiser, while the Borda method used to combine the results of each assessor's decision so as to obtain the final result of the best employees in Lombok Garden.Based on the final result of the system of determination of the best employees in the form of a ranking of the final value of each employee. The highest value will be used as a recommendation as the best employee at Lombok Garden. 
The Determination of the Action towards the Patient’s Psychological Therapy in the Post-accident Using Case-based Reasoning Sri Mulyana; Ilham Sahputra
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 12, No 1 (2018): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.22886

Abstract

The accident that occurred to somebody will give much suffering; moreover, if the accident gives the serious injury, such as a broken bone which needs to get more seriously treatment. Not only does the patient need the action towards his/her injury, but also he/she needs the psychological therapy in facing the problems happened which is suggested by a psychologist. One of the reasoning method in expert systems is Case-Based Reasoning (CBR). In Case-Based Reasoning, a case-based consists of various cases in conditions or symptoms and solution (the psychological therapy) given. To find out the solution from a new problem given, the system will find any cases in the case-based which have higher the degree of similarity between the cases. This research develops a case-based reasoning system to decide the action of the psychological therapy towards the patients in the post-accident who needs seriously treatment. The psychological therapy involves in giving assistance, consultation, psychiatrist support, and the compound of various actions as well. A case study was conducted from the medical records of psychological treatment at ‘Dr Soeharso’ hospital in Surakarta. Based on the result of the research developed, the action of psychological therapy upon the patient has successfully determined. They have accuracy rates of 60% in the threshold 50% compared to the treatments resulted from the psychologist. The result was found by calculating the degree of similarity between the new issue and all cases existing in the case base.
Hospital Nurse Scheduling Optimization Using Simulated Annealing and Probabilistic Cooling Scheme Ferdi Chahyadi; Azhari SN; Hendra Kurniawan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 12, No 1 (2018): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.23056

Abstract

Nurse’s scheduling in hospitals becomes a complex problem, and it takes time in its making process. There are a lot of limitation and rules that have to be considered in the making process of nurse’s schedule making, so it can fulfill the need of nurse’s preference that can increase the quality of the service. The existence variety of different factors that are causing the nurse scheduling problem is so vast and different in every case. The study is aimed to develop a system used as an equipment to arrange nurse’s schedule. The working schedule obtained will be checked based on the constraints that have been required. Value check of the constraint falsification used Simulated Annealing (SA) combined with cooling method of Probabilistic Cooling Scheme (PCS). Transitional rules used cost matrix that is employed to produce a new and more efficient state. The obtained  results showed that PCS cooling methods combined with the transition rules of the cost matrix generating objective function value of  new solutions better and faster in processing time than the cooling method exponential and logarithmic. Work schedule generated by the application also has a better quality than the schedules created manually by the head of the room.
Sistem Penjadwalan Pertandingan Pencak Silat Berbasis Algoritma Genetika Ari Kusuma Wardana; Sri Hartati
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.24214

Abstract

Genetic Algorithm is one of famous algorithm and often used in many sector. Usually genetic algoritm is used in solution searching about complex problems. Pencak silat macth scheduling is a complex scheduling and needs a lot of time to made it. Objective this research implements a genetic algorithm as an algorithm which can solve the problem of pencak silat  macth scheduling and can satisfy all of hard constraint and minimize soft constraint. In this research genetic algorithm roles as algorithm which solves pencak silat mach scheduling problems in Pimda 02 Tak Suci Bantul. Population which produced by genetic algorithm represents solution alternatives which offered. Best chromosome in a population represents macth scheduling solution. This solution is sequence of match partai based on rules of pencak silat match scheduling. This research produces best fitness value ever in each generation is 1. More and more chromosom number and more and more generation number will make batter solution and batter fitness value. This research is expected helping pencak silat match committes make a pencak silat schedule in pencak silat championship.
Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network Ira zulfa; Edi Winarko
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.24716

Abstract

Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN). Deep Belief Network (DBN), which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with  Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine) method with an accuracy of 92.18%.

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