JOIN (Jurnal Online Informatika)
JOIN (Jurnal Online Informatika) is a scientific journal published by the Department of Informatics UIN Sunan Gunung Djati Bandung. This journal contains scientific papers from Academics, Researchers, and Practitioners about research on informatics. JOIN (Jurnal Online Informatika) is published twice a year in June and December. The paper is an original script and has a research base on Informatics.
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<![CDATA[Geographic Information Systems for Crime Prone Areas Clustering ]]>
<![CDATA[Mulyani, Heti]]>;
<![CDATA[Nurjaman, Jajang]]>;
<![CDATA[Nugraha, Muhammad]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.599
<![CDATA[Crime is one of the problems that is quite complicated and very disturbing to the community. Crimes can occur at different times and places, making it difficult to track which areas are prone to such actions. K-means algorithm is used to cluster prone areas and Geographic Information System is used to map crime-prone areas. Web-based application is developed with the PHP programming language. The data used is quantitative data in the form of the number of crimes committed and the coordinates of the cases. The attributes of the crime used consist of five parameters: theft, mistreatment, rape, women and child protection cases and fraud. The results of this study are clustering areas into 3 cluster and mapping prone areas that is safe area, safe enough area and prone area. From the overall crime data for 2019 in Purwakarta district, it was found that 68.75% was safe, 18.75% was quite safe and 12.5% was prone area.]]>
<![CDATA[Product Review Ranking in e-Commerce using Urgency Level Classification Approach ]]>
<![CDATA[Zuhri, Hamdi Ahmad]]>;
<![CDATA[Maulidevi, Nur Ulfa]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.612
<![CDATA[Review ranking is useful to give users a better experience. Review ranking studies commonly use upvote value, which does not represent urgency, and it causes problems in prediction. In contrast, manual labeling as wide as the upvote value range provides a high bias and inconsistency. The proposed solution is to use a classification approach to rank the review where the labels are ordinal urgency class. The experiment involved shallow learning models (Logistic Regression, Naïve Bayesian, Support Vector Machine, and Random Forest), and deep learning models (LSTM and CNN). In constructing a classification model, the problem is broken down into several binary classifications that predict tendencies of urgency depending on the separation of classes. The result shows that deep learning models outperform other models in classification dan ranking evaluation. In addition, the review data used tend to contain vocabulary of certain product domains, so further research is needed on data with more diverse vocabulary.]]>
<![CDATA[FoFA: Diet Information for Children with Autism with Semantic Technology in Android Based Application ]]>
<![CDATA[Febrianto, Lutfi Aristian]]>;
<![CDATA[Wardani, Dewi Wisnu]]>;
<![CDATA[Wijayanto, Ardhi]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.615
<![CDATA[The number of people with autism in Indonesia increases by 0.15% or 6,900 children per year. One of the actions that can be done to overcome developmental disorders of children with autism is to do Feingold and Failsafe Diet, Specific Carbohydrate Diet (SCD diet), and Casein-Free Gluten Free diet (CFGF diet) on foodstuffs given to children with autism. There is a need for socialization and presentation of information regarding the regulation of food items given to children with autism. Currently, there is no presentation of information in the form of mobile-based applications as a forum for parents to exchange information, especially those that utilize semantic technology. By utilizing semantic technology, the Food For Autism (FoFA) application was created to share knowledge for users related to food and beverage diet menus for children with autism. The test results show that the application of FoFA can apply semantic technology related to diet and food diets for children with autism.]]>
<![CDATA[The Development Of Learning Media For Mobile Learning Application The Language And Automata Theory On Finite State Automata (FSA) And Deterministic Finite Automata (DFA) Material Use Adobe Air for Android ]]>
<![CDATA[Sulaiman, Maulana Muhamad]]>;
<![CDATA[Andrianto, Romi]]>;
<![CDATA[Yulianto, Muhamad Arief]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.630
<![CDATA[The language and automata theory are which required course must implemented by college student in informatic engineering study program. In this course, there are finite state automata (FSA) and deterministic finite automata (DFA) which are important materials in language and automata theory. This material requires more understanding of mathematical logic from students to determine an input which can be accepted or rejected in an abstract machine system. The assist students to understand the material, it is need to develop the learning media for mobile learning applications for language and automata theory on finite state automata (FSA) and deterministic finite automata (DFA) based on android as an evaluation of learning media for students. And the development of this learning media use the ADDIE development model (analysis, design, development, implementation, evaluation) to design language and automata theory applications learning so can be support the learning process for students and then assist lecturer to explain the material more dynamic and applicative.]]>
<![CDATA[Sentiment Analysis on Social Distancing and Physical Distancing on Twitter Social Media using Recurrent Neural Network (RNN) Algorithm ]]>
<![CDATA[Nugraha, Fikri Aldi]]>;
<![CDATA[Harani, Nisa Hanum]]>;
<![CDATA[Habibi, Roni]]>;
<![CDATA[Fatonah, Rd. Nuraini Siti]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.632
<![CDATA[The government is seeking preventive steps to reduce the risk of the spread of Covid-19, one of which is social restrictions that have become popular with social distancing and physical distancing. One way to assess whether the steps taken by the government regarding social and physical distancing are accepted or not by the community is by conducting sentiment analysis. The process of sentiment analysis is carried out using a variant of the Recurrent Neural Network (RNN), namely Long Short-Term Memory (LSTM). In this study, the results obtained from the sentiment analysis, where the public response to social distancing and physical distancing has more positive sentiments than negative sentiments. To measure the accuracy level of sentiment analysis using the Recurrent Neural Network (RNN) algorithm and evaluation of the modeling is done using confusion matrix where the results obtained for the training dataset are 89% accuracy, 89% recall, 89% precision, and 89% F1 Score. Meanwhile, for the test dataset, an accuracy of 80% was obtained, a recall of 79%, a precision of 81%, and an F1 score of 80%.]]>
<![CDATA[Implementation of the Simple Multi Attribute Rating Technique Method (SMART) in Determining Toddler Growth ]]>
<![CDATA[Wahana, Agung]]>;
<![CDATA[Alam, Cecep Nurul]]>;
<![CDATA[Rohmah, Siti Nur]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.634
<![CDATA[Toddler nutritional status is an important factor in efforts to reduce child mortality. The development of community nutrition can be monitored through the results of recording and reporting of community nutrition improvement programs reflected in the results of weighing infants and toddlers every month at the Pos Pelayanan Terpadu (Posyandu/ Integrated Service Post) , where these efforts aim to maintain and improve health and prevent and cope with the emergence of public health problems, especially aimed at toddlers. However, in carrying out the health service activities of Medical Officers, faced with an important problem that is still difficult in providing information related to the results of monitoring the growth and development of infants, because information on growth and development of infants owned is obtained from the data collection done manually such as; make records and calculations to find out the condition of a toddler declared good, less, or bad. Implementation of the SMART method in Toddler's growth and development, this method can be used based on the weights and criteria that have been determined. The criteria used are based on the Anthropometric index assessment criteria. The results of the analysis are the results of ranking the greatest value to be used as the material in the decision-making process.]]>
<![CDATA[Detection of Fraudulent Financial Statement based on Ratio Analysis in Indonesia Banking using Support Vector Machine ]]>
<![CDATA[Sibaroni, Yuliant]]>;
<![CDATA[Ekaputra, Muhammad Novario]]>;
<![CDATA[Prasetiyowati, Sri Suryani]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.646
<![CDATA[This study proposes the use of ratio analysis-based features combined with the SVM classifier to identify fraudulent financial statements. The detection method used in this study applies a data mining classification approach. This method is expected to replace the expert in forensic accounting in identifying fraudulent financial statements that are usually done manually. The experimental results show that the proposed classifier model and ratio analysis-based features provide more than 90% accuracy results where the optimal number of features based on ratio analysis is 5 features, namely Capital Adequacy Ratio (CAR), (ANPB) to total earning assets and non-earning assets (ANP), Impairment provision on earning assets (CKPN) to earning assets, Return on Asset (ROA), and Return on Equity (ROE). The contribution of the study is to complement the research of fraudulent financial statements detection where the classifier method used here is different compare to other research. The selection of banking cases in Indonesia is also unique in this research which distinguishes it from other research because the financial reporting standards in each country can be different. ]]>
<![CDATA[Genetic Algorithm to Optimize k-Nearest Neighbor Parameter for Benchmarked Medical Datasets Classification ]]>
<![CDATA[Prasetio, Rizki Tri]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.656
<![CDATA[Computer assisted medical diagnosis is a major machine learning problem being researched recently. General classifiers learn from the data itself through training process, due to the inexperience of an expert in determining parameters. This research proposes a methodology based on machine learning paradigm. Integrates the search heuristic that is inspired by natural evolution called genetic algorithm with the simplest and the most used learning algorithm, k-nearest Neighbor. The genetic algorithm were used for feature selection and parameter optimization while k-nearest Neighbor were used as a classifier. The proposed method is experimented on five benchmarked medical datasets from University California Irvine Machine Learning Repository and compared with original k-NN and other feature selection algorithm i.e., forward selection, backward elimination and greedy feature selection. Experiment results show that the proposed method is able to achieve good performance with significant improvement with p value of t-Test is 0.0011.]]>
<![CDATA[Multiscale Retinex Application to Analyze Face Recognition ]]>
<![CDATA[Supriyanto, Supriyanto]]>;
<![CDATA[Harika, Maisevli]]>;
<![CDATA[Ramadiani, Maya Sri]]>;
<![CDATA[Ramdania, Diena Rauda]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.668
<![CDATA[The main challenge that facial recognition introduces is the difficulty of uneven lighting or dark tendencies. The image is poorly lit, which makes it difficult for the system to perform facial recognition. This study aims to normalize the lighting in the image using the Multiscale Retinex method. This method is applied to a face recognition system based on Principal Component Analysis to determine whether this method effectively improves images with uneven lighting. The results showed that the Multiscale Retinex approach to face recognition's correctness was better, from 40% to 76%. Multiscale Retinex has the advantage of dark facial image types because it produces a brighter image output.]]>
<![CDATA[Knowledge Management System for Railway Supply Chain Perspective ]]>
<![CDATA[Jayakrishnan, Mailasan]]>;
<![CDATA[Mohamad, Abdul Karim]]>;
<![CDATA[Yusof, Mokhtar Mohd]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
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DOI: 10.15575/join.v5i2.675
<![CDATA[Knowledge Management System (KMS) is a monitoring system that emphasizes the desired and actual performance of an industry. Aligning KMS to viably execute the Railway Industry methodology and supply chain operations utilizing legitimate knowledge management capabilities. Yet KMS controls the planning and priorities through action controls that emphasize on operational control level, result controls toward the strategic planning level, personnel controls on retaining the right operation with the right skills, and transaction control on the accurate and complete legal transactions for ensuring strategic management. Therefore, we have come up with a dynamic KMS for the Railway Supply Chain context that focuses on operational, tactical, and strategic perspectives on the information sources, value, analytics, and requirement for current and future drivers of an industry perspective. Moreover, this KMS aims to redesign the Information System by promoting a reductionist approach to problem-solving and best decision-making practices within an industry context.]]>
