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 The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
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<![CDATA[Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation ]]>
<![CDATA[Victor Paskalathis]]>;
<![CDATA[Azhari SN]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.16631
<![CDATA[Common practice in crowdsourced delivery services is through direct delivery. That is by dispatching direct trip to a driver nearby the origin location. The total distance can be reduced through multiple pickup and delivery by increasing the number of requests in a trip.The research implements exact algorithm to solve the consolidation problem with up to 3 requests in a trip. Greedy heuristic is performed to construct initial route based on highest savings. The result is then optimized using Ant Colony Optimization (ACO). Four scenarios are compared. A direct delivery scenarios and three multiple pickup and delivery scenarios. These include 2-consolidated delivery, 3-consolidated delivery, and 3-consolidated delivery optimized with ACO. Four parameters are used to evaluate using Analytical Hierarchical Process (AHP). These include the number of trips, total distance, total duration, and security concerns.The case study is based on Yogyakarta area for a whole day. The final route optimized with ACO shows 178 requests can be completed in 94 trips. Compared to direct delivery, consolidation can provides savings up to 20% in distance and 14% in duration. The evaluation result using AHP shows that ACO scenario is the best scenario. ]]>
<![CDATA[Prediksi Kerawanan Wilayah Terhadap Tindak Pencurian Sepeda Motor Menggunakan Metode (S)ARIMA Dan CART ]]>
<![CDATA[Pradita Eko Prasetyo Utomo]]>;
<![CDATA[Azhari SN]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.16643
<![CDATA[Motor vehicle theft is a crime that is most common in Indonesia. Growth of vehicle motorcycle significant in each year accompanied by the increasing theft of motorcycles in each year, we need a system that is able to forecast the development and the theft of the motorcycle.This research proposes the development of forecasting models vulnerability criminal offense of theft of motorcycles with ARIMA forecasting method. This method not only forecast from variable of theft but also residents, vehicles and unemployment. The study also determined the classification level of vulnerability to the crime of theft of a motorcycle using a method based on the Decision Tree CART ARIMA forecasting method.Forecasting time series data with ARIMA method performed by each of the variables to produce the best ARIMA forecasting model which varies based on the data pattern of each of those variables. The results of classification by CART method to get the value of accuracy of 92% for the city of Yogyakarta and 85% for DIY. Based on the above, the results of ARIMA forecasting and classification CART can be used in determining the level of vulnerability to the crime of theft of motorcycles.]]>
<![CDATA[Platform Gamifikasi untuk Perkuliahan ]]>
<![CDATA[David Kristiadi]]>;
<![CDATA[Khabib Mustofa]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.17053
<![CDATA[Gamification in lecturing has a lot of variety designs. A flexible platform is needed for that matter. This research aims to develop a gamification platform for lecturing that flexible, has a good performance and acceptable by users.Generic Gamification Platform (GGP) concept is used to develop platform. GGP is a kind of gamification solution that applies service oriented architecture Architecture (SOA) principles and puts gamification components (data, logic and rewards) and Information System (IS) separately. The platform has some capabilities such as able to manage game mechanics, actions, tasks and rules. The other platform capabilities are able to auto generate rules and to be integrated to IS.The results of tests show that a gamification platform for lecturing can be developed. The platform has a good level of flexibility, has a good performance, and acceptable by users (5 lecturers and 2 non-lecturers but well knowing on lecturing activities). Its flexibility level is 85%. Its average of response time on event execution is lower than 336ms. Its System Usability Scale (SUS) average score is 60 and its acceptability range in low marginal.]]>
<![CDATA[Penentuan Kematangan Buah Salak Pondoh Di Pohon Berbasis Pengolahan Citra Digital ]]>
<![CDATA[Pawit Rianto]]>;
<![CDATA[Agus Harjoko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.17416
<![CDATA[Because there is no a system based on Digital Image Processing to determine the degree of ripeness of Salak Pondoh (Salacca zalacca Gaertner Voss.) on tree, then this study has attempted to implement such a system. System was built with consists of several sub-processes. First, the segmentation process, the system will perform a search of pixels alleged pixels salak pondoh, by utilizing the features of color components r, g, b, and gray of each pixel salak pondoh then calculated large the dissimilarity ( Euclidean Distance ) against values of data features , , , and comparison. If the value of dissimilarity less than the threshold value and is also supported by the neighboring pixels from different directions has a value of dissimilarity is less than a threshold value, the pixel is set as an object pixel, for the other condition set as background pixels. For the next, improvements through an elimination noise stage and filling in the pixels to get a perfect binary image segmentation. Second, classification, by knowning the mean value of R and V of the entire pixel object, then the level of ripeness salak pondoh can be determined by using the method of classification backpropagation or k -Nearest Neighbor. From the test results indicate that the success of the system by 92% when using a backpropagatioan classification algorithm and 93% with k-Nearest Neighbor algorithm.]]>
<![CDATA[Rancang Bangun Plugin Protégé Menggunakan Ekspresi SPARQL-DL Dengan Masukan Bahasa Alami ]]>
<![CDATA[Muhammad Fahrurrozi]]>;
<![CDATA[Azhari SN]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.18360
<![CDATA[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.]]>
<![CDATA[Group Decision Support System Determination Of Best Employee Using Topsis And Borda ]]>
<![CDATA[Made Arya Budhi]]>;
<![CDATA[Retantyo Wardoyo]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.22773
<![CDATA[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. ]]>
<![CDATA[Sistem Penjadwalan Pertandingan Pencak Silat Berbasis Algoritma Genetika ]]>
<![CDATA[Ari Kusuma Wardana]]>;
<![CDATA[Sri Hartati]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.24214
<![CDATA[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.]]>
<![CDATA[Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network ]]>
<![CDATA[Ira zulfa]]>;
<![CDATA[Edi Winarko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.24716
<![CDATA[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%.]]>
<![CDATA[Deteksi Kualitas Telur Menggunakan Analisis Tekstur ]]>
<![CDATA[Enny Itje Sela]]>;
<![CDATA[M Ihsan]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.24756
<![CDATA[Currently to find out the quality of eggs was conducted on visual observation directly on the egg, both the outside of the egg in the form of eggshell conditions or the inside of the egg by watching out using sunlight or a flashlight. This method requires good accuracy, so in the process it can affect results that are not always accurate. This is due to the physical limitations of each individual is different. This study examines the utilization of digital image processing for the detection of egg quality using eggshell image.The feature extraction method performed a texture feature based on the histogram that is the average intensity, standard deviation, skewness, energy, entropy, and smoothness properties. The detection method for training and testing is K-Means Clustering algorithm. The results of this application are able to help the user to determine the quality of good chicken eggs and good quality chicken eggs, with accurate introduction of good quality eggs by 90% and poor quality eggs by 80%.]]>
<![CDATA[Deteksi Dini Retinopati Diabetik dengan Pengolahan Citra Berbasis Morfologi Matematika ]]>
<![CDATA[Lukman Heryawan]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 11, No 2 (2017): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.24761
<![CDATA[Diabetic retinopathy is a complication caused by diabetes mellitus. Diabetic retinopathy, if not handled properly can lead to blindness. A necessary step to prevent blindness is early detection. Early detection can be done by finding the initial symptoms that microaneurysm. In this research, a system made to detect diabetic retinopathy using algorithms detection microaneurysm with mathematical morphology. The algorithm is divided into three stages of preprocessing, detecting candidate microaneurysm and postprocessing. In this research, the system will be made by using a raspberry pi as the media. To see how well the system detects diabetic retinopathy, the test will be done. in the tests performed, system obtained an accuracy of 90%, sensitivity 90, and specificity of 55% using data diaretdb1. While testing using data from e-ophtha obtained results with an accuracy of 70.5%, a sensitivity of 80% and a specificity of 60%.]]>
