IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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 The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Articles
476 Documents
<![CDATA[Genetic Algorithm for lecturing schedule optimization ]]>
<![CDATA[David Kristiadi]]>;
<![CDATA[Rudy Hartanto]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 1 (2019): January ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.43038
<![CDATA[Scheduling is a classic problem in lecturing. Rooms, lecturers, times and scheduling constraints must be managed well to get an optimal schedule. University of Boyolali (UBY) also encounter the same scheduling problems. The problem was tried to be solved by building a library based on Genetic Algorithm (GA). GA is a computation method which inspired by natural selection. The computation consists of some operators i.e. Tournament Selection, Uniform Crossover, Weak Parent Replacement and two mutation operators (Interchanging Mutation and Violated Directed Mutation (VDM)). The two mutation method are compared to find which better mutation operator. The library was planned to have a capability to define custom constraints (scheduling requirements that were not accommodated by the library) without core program modifications. The test results show that VDM is more promising for optimal solutions than Interchanging Mutation. In UBY cases, optimal solution (fitness value=1) is reached in 12 minutes 41 second with adding 6 new room and inactivated 2 constraint i.e. lecturing begins at 14.00 except for 3rd semester of science law study program with morning class and lecturing participants must not over classroom capacity.]]>
<![CDATA[Apps-based Machine Translation on Smart Media Devices - A Review ]]>
<![CDATA[Hary Gunarto]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 1 (2019): January ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.43066
<![CDATA[Machine Translation Systems are part of Natural Language Processing (NLP) that makes communication possible among people using their own native language through computer and smart media devices. This paper describes recent progress in language dictionaries and machine translation commonly used for communications and social interaction among people or Internet users worldwide who speak different languages. Problems of accuracy and quality related to computer translation systems encountered in web & Apps-based translation are described and discussed. Possible programming solutions to the problems are also put forward to create software tools that are able to analyze and synthesize language intelligently based on semantic representation of sentences and phrases. Challenges and problems on Apps-based machine translation on smart devices towards AI, NLP, smart learning and understanding still remain until now, and need to be addressed and solved through collaboration between computational linguists and computer scientists.]]>
<![CDATA[Comparison of Motion History Image and Approximated Ellipse Method in Human Fall Detection System ]]>
<![CDATA[Mohammad Brado Frasetyo]]>;
<![CDATA[Elvira Sukma Wahyuni]]>;
<![CDATA[Hendra Setiawan]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 2 (2019): April ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.43632
<![CDATA[This paper compares two different method in human fall detection system namely motion history image and approximated ellipse. Research has been done in small studio with 4 CCTV camera as video data recorder, whereas video data are processed using MATLAB software. The experiment was carried out using three object’s fall direction and two type of falling movement. The fall direction is consist of front, side, and back fall. Whereas the falling movement is consist of direct and indirect fall movement. Meanwhile, the object’s initial position is standing and size of captured object is constant. The result is motion history image has accuracy 74.26% for direct falling movement, and 75.69% for indirect falling movement. Whereas approximated ellipse has accuracy 56.85% for direct falling movement, and 61.81% for indirect falling movement. Therefore, motion history image is better than approximated ellipse in human fall detection system.]]>
<![CDATA[System Security Awareness Planning Model Using The Octave Method Approach ]]>
<![CDATA[Zaied Saad Shouran]]>;
<![CDATA[Nur Rokhman]]>;
<![CDATA[Tri Kuntoro Priyambodo]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 3 (2019): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.43922
<![CDATA[Awareness of the security of information systems is an important thing to note. In this study, we will discuss planning models of awareness about information system security using Octave models or methods. The analytical method used is qualitative descriptive analysis. The results of the study show that the Octave model can increase awareness about the importance of security in an information system and companies that implement it will be able to improve their performance in the future.]]>
<![CDATA[The K-Means Clustering Algorithm With Semantic Similarity To Estimate The Cost of Hospitalization ]]>
<![CDATA[Ida Bagus Gede Sarasvananda]]>;
<![CDATA[Retantyo Wardoyo]]>;
<![CDATA[Anny Kartika Sari]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 4 (2019): October ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.45093
<![CDATA[ The cost of hospitalization from a patient can be estimated by performing a cluster of patient. One of the algorithms that is widely used for clustering is K-means. K-means algorithm, based on distance still has weaknesses in terms of measuring the proximity of meaning or semantics between data. To overcome this problem, semantic similarity can be used to measure the similarity between objects in clustering, so that, semantic proximity can be calculated. This study aims to conduct clustering of patient data by paying attention to the similarity of the patient’s disease. ICD code is used as a guide in determining a patient’s disease. The K-means method is combined with semantic similarity to measure the proximity of the patient’s ICD code. The method used to measure the semantic similarity between data, in this study, is the semantic similarity of Girardi, Leacock & Chodorow, Rada, and Jaccard Similarity. Cluster quality measurement uses the silhouette coefficient method. Based on the experimental results, the method of measuring semantic similarity data is capable to produce better quality clustering results than without semantic similarity. The best accuracy is 91.78% for the three semantic similarity methods, whereas without semantic similarity the best accuracy is 84.93%.]]>
<![CDATA[Application of Text Message Held in Image Using Combination of Least Significant Bit Method and One Time Pad ]]>
<![CDATA[Eferoni Ndruru]]>;
<![CDATA[Taronisokhi Zebua]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 4 (2019): October ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.46401
<![CDATA[Stenography and security are one of the techniques to develop art in securing data. Stenography has the most important aspect is the level of security in data hiding, which makes the third party unable to detect some information that has been secured. Usually used to hide textinformationThe (LSB) algorithm is one of the basic algorithms proposed by Arawak and Giant in 1994 to determine the frequent item set for Boolean association rules. A priory algorithm includes the type of association rules in data mining. The rule that states associations between attributes are often called affinity analysis or market basket analysis. OTP can be widely used in business. With the knowledge of text message, concealment techniques will make it easier for companies to know the number of frequencies of sales data, making it easier for companies to take an appropriate transaction action. The results of this study, hide the text message on the image (image) by using a combination of LSB and Otp methods.]]>
<![CDATA[DSS for Selection of Coffee Plants against a Land Using ANP and Modification Of Profile Matching ]]>
<![CDATA[Indra Pratistha]]>;
<![CDATA[Retantyo Wardoyo]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 3 (2019): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.46490
<![CDATA[Based on BPS data, the growth of plantation crop production in NTB Province in 2011 to 2016 was recorded to have decreased by an average of 3.3 thousand tons annually. Coffee plants in particular are 0.1 thousand tons on average, the lack of public interest in planting coffee properly on land owned so that it impacts on land use that is not in accordance with its potential which will result in decreased productivity and erosion of land quality [1]. The first study of land suitability analysis for coffee plantations used a matching method in robusta coffee with a matching method producing a class (S1) of 0,46% [2] the second using a matching method on robusta coffee producing a class (S1) of 0,015% [3] These results indicate the ability of each land is different so that the results of the analysis vary. This study applies the ANP method and modified matching profile where the level of recommendations of coffee plants on the ability of land in East Lombok Regency through validation based on coffee production data from the East Lombok District Agricultural Service produces a match in rank 1 of 87,5% and 75% with non-modified profile matching.]]>
<![CDATA[Outlier Detection Credit Card Transactions Using Local Outlier Factor Algorithm (LOF) ]]>
<![CDATA[Silvano Sugidamayatno]]>;
<![CDATA[Danang Lelono]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 4 (2019): October ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.46561
<![CDATA[Threats or fraud for credit card owners and banks as service providers have been harmed by the actions of perpetrators of credit card thieves. All transaction data are stored in the bank's database, but are limited in information and cannot be used as a knowledge. Knowledge built with credit card transaction data can be used as an early warning by the bank. The outlier analysis method is used to build the knowledge with a local outlier factor algorithm that has high accuracy, recall, and precision results and can be used in multivariate data. Testing uses a matrix sample and confusion method with attributes date, categories, numbers, and countries. The test results using 1803 transaction data from five customers, indicating that the average value accuracy of LOF algorithms (96%), higher than the average accuracy values of the INFLO and AFV algorithms (84% and 77%).]]>
<![CDATA[DSS for "E-Private" Using a Combination of AHP and SAW Methods ]]>
<![CDATA[Ni Komang Yanti Suartini]]>;
<![CDATA[I Made Agus Wirawan]]>;
<![CDATA[Dewa Gede Hendra Divayana]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 3 (2019): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.46625
<![CDATA[Private tutoring was non-formal education and it was needed to help student in learning.There were already tutoring system developed where the selection of private tutors was done by filtering peocess. However, filtering process was not suitable with needs and desires of students.Besides the filtering process, to support the solution in making decisions on the selection of private tutors on the E-Privat system it also used the Decision Suport System (DSS) concept, namely a combination of AHP and SAW methods. AHP method was used to find the weights in each criterion, and the ranking calculation with the SAW method.E-Privat aimed to help parents / students in choosing private tutors that suit the needs and desires of students by involving multi-criteria and various alternative. This system was also developed to help private tutors to get the opportunity to fill out private lessons. The testing process results showed that the system had been successful and suitable for used. There were 5 testing processes : (1)black box testing, (2)white box testing, (3)accuracy test which showed a percentage of 87%, and (4)user's response test whichused the SUS method showed a percentage 92.08% with best imaginable category.]]>
<![CDATA[Detection Of Spam Comments On Instagram Using Complementary Naïve Bayes ]]>
<![CDATA[Nur Azizul Haqimi]]>;
<![CDATA[Nur Rokhman]]>;
<![CDATA[Sigit Priyanta]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 3 (2019): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/ijccs.47046
<![CDATA[Instagram (IG) is a web-based and mobile social media application where users can share photos or videos with available features. Upload photos or videos with captions that contain an explanation of the photo or video that can reap spam comments. Comments on spam containing comments that are not relevant to the caption and photos. The problem that arises when identifying spam is non-spam comments are more dominant than spam comments so that it leads to the problem of the imbalanced dataset. A balanced dataset can influence the performance of a classification method. This is the focus of research related to the implementation of the CNB method in dealing with imbalance datasets for the detection of Instagram spam comments. The study used TF-IDF weighting with Support Vector Machine (SVM) as a comparison classification. Based on the test results with 2500 training data and 100 test data on the imbalanced dataset (25% spam and 75% non-spam), the CNB accuracy was 92%, precision 86% and f-measure 93%. Whereas SVM produces 87% accuracy, 79% precision, 88% f-measure. In conclusion, the CNB method is more suitable for detecting spam comments in cases of imbalanced datasets.]]>
