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 The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.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[HOG Feature Extraction and KNN Classification for Detecting Vehicle in The Highway ]]>
<![CDATA[Firnanda Al Islama Achyunda Putra]]>;
<![CDATA[Fitri Utaminingrum]]>;
<![CDATA[Wayan Firdaus Mahmudy]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.54050
<![CDATA[Autonomous car is a vehicle that can guide itself without human intervention. Various types of rudderless vehicles are being developed. Future systems where computers take over the art of driving. The problem is prior to being attention in an autonomous car for obtaining the high safety. Autonomous car need early warning system to avoid accidents in front of the car, especially the system can be used in the Highway location. In this paper, we propose a vision-based vehicle detection system for Autonomous car. Our detection algorithm consists of three main components: HOG feature extraction, KNN classifier, and vehicle detection. Feature extraction has been used to recognize an object such as cars. In this case, we use HOG feature extraction to detect as a car or non-car. We use the KNN algorithm to classify. KNN Classification in previous studies had quite good results. Car detected by matching about trining data with testing data. Trining data created by extract HOG feature from image 304 x 240 pixels. The system will produce a classification between car or non-car.]]>
<![CDATA[Development of Android Based Hajj and Umrah Pilgrims Monitoring Application In Dago Wisata International ]]>
<![CDATA[Muhammad Ilham Budiawan]]>;
<![CDATA[Irawan Afrianto]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.55199
<![CDATA[ Hajj and Umrah are worship activities carried out by Muslims around the world. The problem that often occurs during the implementation of the Hajj and Umrah is that pilgrims are often lost and separated from the group. Pilgrims also find it difficult to look for prayers because they are still using guidebooks, they have to look for prayers one by one in the feeling of a busy and hot holy land. The case study was carried out at Dago Wisata Internasional. The solution used is utilizing geofencing technology and Firebase Cloud Messaging that allows the process of monitoring pilgrims to be carried out easily and the pilgrims can get prayer notifications in accordance with the location of pilgrims. Research supporting data obtained from interviews with employees of Dago Wisata Internasional and literature studies. Based on testing on the application that has been built, the following results are obtained 93.33% supervisor states that this application simplifies the process of monitoring pilgrims, 84% worshipers claim to be able to ask for help easily from the supervisor using this application, and 86% worshipers claim this application makes it easy for pilgrims in looking for the practice deeds.]]>
<![CDATA[An Expert System of Chicken Disease Diagnosis by Using Dempster Shafer Method ]]>
<![CDATA[Yaqutina Marjani Santosa]]>;
<![CDATA[Suprapto Suprapto]]>;
<![CDATA[Wahyono Wahyono]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.55632
<![CDATA[ Chicken is an animal that can provide many benefits for human life, meat and eggs can be used as food to fulfill the needs of human food, the excrement can be made fertilizer, and frequently its be used as a farm animal. Although it can provide many benefits, but for chicken farmers, the maintenance of chicken meet some obstacles that must be faced such as disease, poor environmental sanitation, and the production of eggs are declining. From some of the obstacles that have been mentioned, the most frequently encountered are animals infected with the disease. Based on the results of interviews that have been done to some chicken farmers, it can be said that the knowledge of chicken farmers against chicken disease and its handling is still very lacking. But the number of experts who understand and know about the type of chicken disease and the way of handling is limited, then it takes an expert system that can simulate knowledge and understanding of experts to overcome the problem. Based on the study of the libraries, the method suitable for use in the expert system is the Dempster shafer method by processing the value of belief in a disease. Dempster shafer method is a method used to calculate uncertainty due to the addition or reduction of new facts that will change the existing rules. Based on tests in 40 cases using an expert system applying the Dempster Shafer method, obtained the percentage of diagnostic compatibility result given by experts and system is 95%.]]>
<![CDATA[A HYBRID Approach for Determine the Location of Stand Establishment at Batik Hatta Semarang ]]>
<![CDATA[Saifur Rohman Cholil]]>;
<![CDATA[Leatitia Daphne Adhisti Putri Pertiwi]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.56206
<![CDATA[Semarang has various types of business. One of them is Batik Hatta Boutique, a small and medium business under the guidance of the Bank of Central Java that deals specifically in the world of batik art. This business develops and maintains its existence by participating in various exhibitions in several shopping centers as a media product promotion. To minimize losses, it needs accurate calculation in making decision of determining the location of establishment. It is reviewed by rental cost, location, layout, profit, and security. However, that calculation is still manual so it is inefficient and susceptible to error. Therefore, Decision Support System (DSS) is made to help in getting recommended location of best establishment at the Butik Batik Hatta. The method used in this research is the HYBRID MCDM AHP-TOPSIS Method. Validation process of this research has been done by using comparison of actual data and its result is 0.90 in the Sparman Correlation Coefficient. The conclusion is that the AHP-TOPSIS HYBRID MCDM method can be used in determining the location of establishment stand at the Batik Hatta Boutique.]]>
<![CDATA[Curriculum 4.0: Adoption of Industry Era 4.0 as Assessment of Higher Education Quality ]]>
<![CDATA[Chandra Lukita]]>;
<![CDATA[Suwandi Suwandi]]>;
<![CDATA[Eka Purnama Harahap]]>;
<![CDATA[Untung Rahardja]]>;
<![CDATA[Chairun Nas]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.57321
<![CDATA[Indonesia is the 4th largest country in Southeast Asia with a population of 262 million which needs to be considered the success rate of its human resources, because of a strong country that has a strong foundation, one example is the intelligence of human resources. Global competition proves that HR requires strong competence in all fields, generally in the field of technology. However, the lack of equitable education, as well as the conventional education system, makes the country of Indonesia far behind compared to other neighboring countries. The challenge of this 4.0 era is an opportunity to bring up the development of a combination of Industry 4.0 and the education curriculum in Indonesia. There are four issues why the Indonesian education system and curriculum needs to be reviewed. Where there is a literature study and SWOT analysis method used as a reference in solving problems and there is a significant scope. In this paper, competencies are needed to enable success between the integration of education management and the industrial era 4.0 which will be discussed and analyzed based on the facts and reality of the education system in Indonesia which can then be presented in a comprehensive curriculum.]]>
<![CDATA[Securing Web-Based E-Voting System Using Captcha and SQL Injection Filter ]]>
<![CDATA[Amiruddin Amiruddin]]>;
<![CDATA[Apriza Noer Ramadhan]]>;
<![CDATA[David Herdianto]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.57416
<![CDATA[ The electoral system is very necessary in the democratic life of students, especially to elect a senate chairman in a higher education environment. The use of conventional electoral system is slow, inefficient, and insecure compared to that of electronic-based because it requires a long time for the registration to implementation and counting of votes; use a lot of papers; and it raises the potential for manipulation of ballot papers. In this research, we developed a student electoral system that is safe from non-human participants and electronic-based called e-voting. The system was built with a web platform using PHP and MySQL programming applications. The system development method follows the System Life Cycle (SLC) which consists of the stages of planning, analysis, design, implementation, and testing of the system. This system implements a security mechanism in the form of verification using captcha and SQL injection filter and is implemented in the activities of Komisi Pemilihan Umum Mahasiswa (KPUM). System testing to measure the suitability of implementation with the needs was done using a blackbox method. The result of this research is an e-voting system that satisfies the prevention test of SQL injection and non-human participants attacks]]>
<![CDATA[Optimizing Virtual Resources Management Using Docker on Cloud Applications ]]>
<![CDATA[Rendra Felani]]>;
<![CDATA[Moh Noor Al Azam]]>;
<![CDATA[Derry Pramono Adi]]>;
<![CDATA[Agung Widodo]]>;
<![CDATA[Agustinus Bimo Gumelar]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.57565
<![CDATA[This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.]]>
<![CDATA[Multithreading Application for Counting Vehicle by Using Background Subtraction Method ]]>
<![CDATA[Yohanssen Pratama]]>;
<![CDATA[Puspoko Ponco Ratno]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.57594
<![CDATA[Image and video processing has become important part in intelligent transportation system (ITS) application, especially for collecting road traffic data. Pictures that already collected by a charged coupled device (CCD) camera usually being processed by several image processing algorithms and the application’s code will be executed in a large number of iteration because many algorithms are getting involved in processing the frame which captured by the camera. Typical application will process the first frame until finish and then continue to the next frame, so the application must wait until the first frame being processed. If the algorithms that executed quite complex and have a significant running time there will be a dropped frame and the time difference between data acquisition and real time video is divided by large margin. We proposed an implementation of multithreading to boost the application performance so the data can be acquire in real time and every new frame could be processed in short time. The application performance before and after using a multithreading is known by comparing the data acquisition time that stored in the database. The application effectiveness could define by running a multiple video streaming in same resolution.]]>
<![CDATA[Determining Community Structure and Modularity in Social Network using Genetic Algorithm ]]>
<![CDATA[Taufan Bagus Dwi Putra Aditama]]>;
<![CDATA[Azhari SN]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.57834
<![CDATA[ Research on determining community structure in complex networks has attracted a lot of attention in various applications, such as email networks and social networks. The popularity determines the structure of a community because it can analyze the structure.Meanwhile, to determine the structure of the community by maximizing the value of modularity is difficult. Therefore, a lot of research introduces new algorithms to solve problems in determining community structure and maximizing the value of modularity. Genetic Algorithm can provide effective solutions by combining exploration and exploitation.This study focuses on the Genetic Algorithm which added a cleanup feature in the process. The final results of this study are the results of a comparison of modularity values based on the determination of the community structure of the Genetic Algorithm, Girvan and Newman Algorithm, and the Louvain Algorithm. The best modularity values were obtained using the Genetic Algorithm which obtained 0.6833 results for Zachary's karate club dataset, 0.7446 for the Bottlenose dolphins dataset, 0.7242 for the American college football dataset, and 0.5892 for the Books about US politics dataset.]]>
<![CDATA[Segmentation-Based Sequential Rules For Product Promotion Recommendations As Sales Strategy (Case Study: Dayra Store) ]]>
<![CDATA[Dayan Ramly Ramadhan]]>;
<![CDATA[Nur Rokhman]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.58107
<![CDATA[One of the problems in the promotion is the high cost. Identifying the customer segments that have made transactions, sellers can promote better products to potential consumers. The segmentation of potential consumers can be integrated with the products that consumers tend to buy. The relationship can be found using pattern analysis using the Association Rule Mining (ARM) method. ARM will generate rule patterns from the old transaction data, and the rules can be used for recommendations. This study uses a segmented-based sequential rule method that generates sequential rules from each customer segment to become product promotion for potential consumers. The method was tested by comparing product promotions based on rules and product promotions without based on rules. Based on the test results, the average percentage of transaction from product promotion based on rules is 2,622%, higher than the promotion with the latest products with an average rate of transactions only 0,315%. The hypothesis in each segment obtained from the sample can support the statement that product promotion in all segments based on rules can be more effective in increasing sales compared to promotions that use the latest products without using rules recommendations.]]>
