Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve their knowledge in those particular areas and intended to spread the knowledge as the result of studies.
KINETIK journal is a scientific research journal for Informatics and Electrical Engineering. It is open for anyone who desire to develop knowledge based on qualified research in any field. Submitted papers are evaluated by anonymous referees by double-blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully within 4 - 8 weeks. The research article submitted to this online journal will be peer-reviewed at least 2 (two) reviewers. The accepted research articles will be available online following the journal peer-reviewing process.
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<![CDATA[Geographic Information System for a Community-Based Water Quality Mapping of Rivers in Indonesia ]]>
<![CDATA[‘Uyun, Shofwatul]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1042
<![CDATA[River Water with good quality status is the primary needs for the Indonesian people who live along the river. Indonesia has more or less 303 rivers with varied status of water quality. On the other side, the government is obliged to conduct the current situation mapping and to spread the status of river water quality to the surrounding society. It is certainly not an easy job considering the amount and width of the monitoring area. Therefore, this research has proposed a new concept to map the status of river water quality using the STORET method by involving the active participation of the local river community. The locations of research are: Kambaniru river, Brantas river, dan Gajah Wong river. There are seven parameters used to determine the status of river water quality those are: temperature, EC/DHL, TDS, PH, DO, BOD and Caliform. The river community can report the data of analysis result into a system in accordance with the sampling location by enclosing the spatial data. The system will present the status of water quality starting from each point of location to the status of water quality of certain river. The testing result functionally indicates that the system is able to give perfect accuration value. While from its usability, the respondents’ responses are as follows: very agree 60.40%, agree 37.95%, and disagree 1.65%.]]>
<![CDATA[The Comparison of Imbalanced Data Handling Method in Software Defect Prediction ]]>
<![CDATA[Khadijah, Khadijah]]>;
<![CDATA[Sasongko, Priyo Sidik]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1049
<![CDATA[Software testing is a crucial process in software development life cycle which will affect the software quality. However, testing is a tedious task and resource consuming. Software testing can be conducted more efficiently by focusing this activitiy to software modules which is prone to defect. Therefore, an automated software defect prediction is needed. This research implemented Extreme Learning Machine (ELM) as classification algorithm because of its simplicity in training process and good generalization performance. Aside classification algorithm, the most important problem need to be addressed is imbalanced data between samples of positive class (prone to defect) and negative class. Such imbalance problem could bias the performance of classifier. Therefore, this research compared some approaches to handle imbalance problem between SMOTE (resampling method) and weighted-ELM (algorithm-level method).The results of experiment using 10-fold cross validation on NASA MDP dataset show that including imbalance problem handling in building software defect prediction model is able to increase the specificity and g-mean of model. When the value of imbalance ratio is not very small, the SMOTE is better than weighted-ELM. Otherwise, weighted-ELM is better than SMOTE in term of sensitivity and g-mean, but worse in term of specificity and accuracy.Software testing is a crucial process in software development life cycle which will affect the software quality. However, testing is a tedious task and resource consuming. Software testing can be conducted more efficiently by focusing this activitiy to software modules which is prone to defect. Therefore, an automated software defect prediction is needed. This research implemented Extreme Learning Machine (ELM) as classification algorithm because of its simplicity in training process and good generalization performance. Aside classification algorithm, the most important problem need to be addressed is imbalanced data between samples of positive class (prone to defect) and negative class. Such imbalance problem could bias the performance of classifier. Therefore, this research compared some approaches to handle imbalance problem between SMOTE (resampling method) and weighted-ELM (algorithm-level method).The results of experiment using 10-fold cross validation on NASA MDP dataset show that including imbalance problem handling in building software defect prediction model is able to increase the specificity and g-mean of model. When the value of imbalance ratio is not very small, the SMOTE is better than weighted-ELM. Otherwise, weighted-ELM is better than SMOTE in term of sensitivity and g-mean, but worse in term of specificity and accuracy.]]>
<![CDATA[SDN-Honeypot Integration for DDoS Detection Scheme Using Entropy ]]>
<![CDATA[Irmawati Feren Kilwalaga]]>;
<![CDATA[Fauzi Dwi Setiawan Sumadi]]>;
<![CDATA[Syaifuddin Syaifuddin]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1058
<![CDATA[Limitations on traditional networks contributed to the development of a new paradigm called Software Defined Network (SDN). The separation of control and data plane provides an advantage as well as a security gap on the SDN network because all controls are centralized on the controller so when the compilation of attacks are directed the controller, the controller will be overburdened and eventually dropped. One of the attacks that can be used is the DDoS attack - ICMP Flood. ICMP Flood is an attack intended to overwhelm the target with a large number of ICMP requests. To overcome this problem, this paper proposes detection and mitigation using the Modern Honey Network (MHN) integration in SDN and then makes reactive applications outside the controller using the entropy method. Entropy is a statistical method used to calculate the randomness level of an incoming packet and use header information as a reference for its calculation. In this study, the variables used are the source of IP, the destination of IP and protocol. The results show that detection and mitigation were successfully carried out with an average value of entropy around 10.830. Moreover, CPU usage either in normal packet delivery or attacks showed insignificant impact from the use of entropy. In addition, it can be concluded that the best data collected in 30 seconds in term of the promptness of mitigation flow installation.]]>
<![CDATA[Reduced Overshoot of The Electroforming Jewellery Process Using PID ]]>
<![CDATA[Utomo, Arie Cahyo]]>;
<![CDATA[Siwindarto, Ponco]]>;
<![CDATA[Setyawati, Onny]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1059
<![CDATA[The electroforming jewellery is the electrodeposition process of coating metal on an insulator object to make a jewellery product. The problems are burnt and uneven results in their products, it happened because electrical currents while the process increased. So, too many metal particles attached to object. The problems of electroforming process can fix with a control system, where controller must makes constant electrical currents while the process. In this paper, the problems was changed to the equation by the polynomial regression method as a plant. Secondly the characteristic of current sensor was found by the linier regression method as a feedback system. The system used buck converter as the actuator, where it was written to the equation by the state space method. The controller was chosen by comparison 4 types controller, they are a conventional controller, proportional controller, proportional – integral (PI) controller, and proportional – integral – derivative (PID) controller. Xcos Scilab used to simulated the system and got the system with a proportional – integral – derivative controller is the best controller. The system with a proportional – integral – derivative controller have a Rise time 1.3687 Seconds and Overshoot 2.5420%. The result of research will be base to makes hardware system where it will help the advancement of the creative economy industry in Malang City.]]>
<![CDATA[Various Implementation of Collaborative Filtering-Based Approach on Recommendation Systems using Similarity ]]>
<![CDATA[Romadhon, Zainur]]>;
<![CDATA[Sediyono, Eko]]>;
<![CDATA[Widodo, Catur Edi]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1062
<![CDATA[The Recommendation System plays an increasingly important role in our daily lives. With the increasing amount of information on the internet, the recommendation system can also solve problems caused by increasing information quickly. Collaborative filtering is one method in the recommendation system that makes recommendations by analyzing correlations between users. Collaborative filtering accumulates customer item ratings, identifies customers with common ratings, and offers recommendations based on inter-customer comparisons. This study aims to build a system that can provide recommendations to users who want to order or choose fast food menus. This recommendation system provides recommendations based on item data calculations with customer review data using a collaborative filtering approach. The results of applying cosine similarity calculation to determine fast food menu recommendations obtained for the item-based recommendation is Pizza Frankfurter BBQ Large with a value of 1.0, item-based with genre recommendation is Calblend Float with value 1.0 and user-based recommendation is Pizza Black Pepper Beef / Chicken Large with mean score 2.5.]]>
<![CDATA[Document Preprocessing with TF-IDF to Improve the Polarity Classification Performance of Unstructured Sentiment Analysis ]]>
<![CDATA[Alzami, Farrikh]]>;
<![CDATA[Udayanti, Erika Devi]]>;
<![CDATA[Prabowo, Dwi Puji]]>;
<![CDATA[Megantara, Rama Aria]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1066
<![CDATA[Sentiment analysis in terms of polarity classification is very important in everyday life, with the existence of polarity, many people can find out whether the respected document has positive or negative sentiment so that it can help in choosing and making decisions. Sentiment analysis usually done manually. Therefore, an automatic sentiment analysis classification process is needed. However, it is rare to find studies that discuss extraction features and which learning models are suitable for unstructured sentiment analysis types with the Amazon food review case. This research explores some extraction features such as Word Bags, TF-IDF, Word2Vector, as well as a combination of TF-IDF and Word2Vector with several machine learning models such as Random Forest, SVM, KNN and Naïve Bayes to find out a combination of feature extraction and learning models that can help add variety to the analysis of polarity sentiments. By assisting with document preparation such as html tags and punctuation and special characters, using snowball stemming, TF-IDF results obtained with SVM are suitable for obtaining a polarity classification in unstructured sentiment analysis for the case of Amazon food review with a performance result of 87,3 percent.]]>
<![CDATA[Implementation of K-Means Clustering and Weighted Products in Determining Crime-Prone Locations ]]>
<![CDATA[Rahmatika, Yuni]]>;
<![CDATA[Sediyono, Eko]]>;
<![CDATA[Widodo, Catur Edi]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1067
<![CDATA[Clustering algorithms can be used to build geographic mapping systems to determine crime-prone locations. This study aims to establish a geographical mapping system to determine crime-prone locations that can help police control certain locations that often occur crime and provide information to people in crime-prone locations. Criminal groups are calculated based on crime data from November 2018 to October 2019 which occurred in 9 districts in Kudus Regency. The crime grouping process uses the k-means method used to classify based on regional vulnerability and uses a weighted product method that functions as a vulnerability ranking that is vulnerable to crime selection. The grouping results obtained from this study are that there are 1 very vulnerable area, 5 areas in the vulnerable category, and 3 safe areas. While the weighted product method produces Melatilor area as a vulnerable area to be defeated by a score of 0.182093. This research provides benefits for the public to see crime-prone areas so that they can be more vigilant, while for the police to analyze crime so as to speed up the process of resolving crime and increase and improve crime prevention measures.]]>
<![CDATA[Visualization of Granblue Fantasy Game Traffic Pattern Using Deep Packet Inspection Method ]]>
<![CDATA[Stiawan, Deris]]>;
<![CDATA[Prabowo, Christian]]>;
<![CDATA[Heryanto, Ahmad]]>;
<![CDATA[Afifah, Nurul]]>;
<![CDATA[Minarno, Agus Eko]]>;
<![CDATA[Budiarto, Rahmat]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1073
<![CDATA[Granblue Fantasy is one of Role Playing Games (RPG). It’s a video role-playing game developed by Cygames. This research to observes the Granblue Fantasy Game. The purpose is to analyze the traffic data of the Granblue Fantasy to find the pattern using Deep Packet Inspection (DPI), Capturing the Data Traffic, Feature Extraction Process and Visualize the Pattern. The Pattern are Gacha, Solo Raid, Casino and Multiraid. This research demonstrate that Multiraid battle has more data than other pattern with TTL 237.]]>
<![CDATA[Game Development of “Kwace Adat Bali” for The Socialization of Balinese Traditional Dress-Up Ethics ]]>
<![CDATA[Cahya Dewi, Dewa Ayu Indah]]>;
<![CDATA[Murpratiwi, Santi Ika]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1081
<![CDATA[Many young people have begun to violate the ethics of Balinese traditional dress up by using strict lacy blouse (kebaya), high split sarong (kamen), men sarong (kamen) that not taper on the tip and excessive accessories. Game of “Kwace Adat Bali” is expected as a means of socialization in Balinese traditional dress-up ethics appropriately. In this game, the Balinese traditional dress-up style is classified into three types, namely light traditional clothing (payas alit), middle traditional clothing (payas madya), and great traditional clothing (payas agung). The proposed method is Design Game Based-Learning Instructional Design (DGBL-ID) which is combined with a shuffle random algorithm to shuffle game items. The Game of “Kwace Adat Bali” has tested using alpha testing, beta testing, t-test, and game engagement questionnaire (GEQ). The alpha testing result was 100% game functionality has run suitable for the design. Beta testing shows that overall this game got a value of 77% from 65 respondents. There was a significant difference between user knowledge before and after playing the game of “Kwace Adat Bali” as indicated by t table value of 1.997, t value of 6.5, and the critical value of α = 0.05. The proposed method had an engagement rate of 8.7% higher than just using the DGBL-ID method in developing the game. Therefore, it can be concluded that the game feasible is considered as a new means of socialization in Balinese traditional dress up ethics for the younger generation.]]>
<![CDATA[Leave Management Information System using InsideDPS Software for the Efficiency of Human Resources Management ]]>
<![CDATA[Sentot Imam Wahjono]]>;
<![CDATA[Anna Marina]]>;
<![CDATA[Ismail Rasulong]]>;
<![CDATA[Fam Soo Fen]]>
<![CDATA[ Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Malang ]]>
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DOI: 10.22219/kinetik.v5i3.1087
<![CDATA[The purpose of this research is to study the management information system and the benefits of InsideDPS software. The study was designed with an embeded mixed method, namely quantitative-qualitative-quantitative. The questionnaire as a quantitative tool was built based on previous research (MSQ), distributed to 250 employees and 198 sets of analyzed multiple linear regression. The questionnaire was distributed 2 times, before and after qualitative research. Interviews, observation and document collection were held with informants for HR managers, IT managers, and selected employees. This study found evidence that MIS InsideDPS software can support HRD performance improvement which is also supported by increased employee satisfaction. The technical implication of the findings of this study is the need for a wider web-based MIS application in the company]]>
