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JOIN (Jurnal Online Informatika)
Published by Universitas Islam Negeri Sunan Gunung Djati Bandung
ISSN : 25281682     EISSN : 25279165     DOI : 10.15575/join
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : -
Articles 490 Documents
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Prototype Program Hand Gesture Recognize Using the Convex Hull Method and Convexity Defect on Android Anshary, Muhammad Adi Khairul; Hidayat, Eka Wahyu; Amalia, Tiara
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.594

Abstract

One of the research topics of Human-Computer Interaction is the development of input devices and how users interact with computers. So far, the application of hand gestures is more often applied to desktop computers. Meanwhile, current technological developments have given rise to various forms of computers, one of which is a computer in the form of a smartphone whose users are increasing every year. Therefore, hand gestures need to be applied to smartphones to facilitate interaction between the user and the device. This study implements hand gestures on smartphones using the Android operating system. The algorithm used is convex hull and convexity defect for recognition of the network on the hand which is used as system input. Meanwhile, to ensure this technology runs well, testing was carried out with 3 scenarios involving variable lighting, background color, and indoor or outdoor conditions. The results of this study indicate that Hand gesture recognition using convex hull and convexity defect algorithms has been successfully implemented on smartphones with the Android operating system. Indoor or outdoor testing environment greatly affects the accuracy of hand gesture recognition. For outdoor use, a green background color with a light intensity of 1725 lux produces 76.7% accuracy, while for indoors, a red background color with a light intensity of 300 lux provides the greatest accuracy of 83.3%.
Geographic Information Systems for Crime Prone Areas Clustering Mulyani, Heti; Nurjaman, Jajang; Nugraha, Muhammad
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.599

Abstract

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.
Decision Support System for Employee Recruitment Using El Chinix Traduisant La Realite (Electre) And Weighted Product (WP) Irfan, Mohamad; Syaripudin, Undang; Alam, Cecep Nurul; Hamdani, Muhammad
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.606

Abstract

Management of human resources (HR) is important to achieve company goals. One of the activities in HR management is recruitment, selection, and training. Recruitment and selection are usually done not using a system so that the calculations are still done manually. But by processing data using the system can produce a decision in recommending prospective employees that can have a positive impact on the company. The company selection process is carried out through two stages: administrative selection and final selection in the form of psychological test assessment, interviews, ability tests and communication. The use of the Elimination Et Choix Traduisant La Realite (ELECTRE) method in the administrative selection stage and the Weighted Product (WP) method in the final selection stage is a new discovery made to get the best decision in accordance with the required criteria. By using this method the final results will be obtained namely the recommendation of several prospective employees who are fit to work in the company. The performance results of this system reach one hundred percent, the data from the system is in accordance with the expected calculation.
Comparison of C4.5 Algorithm and Support Vector Machine in Predicting the Student Graduation Timeliness Mailana, Agus; Putra, Andi Agung; Hidayat, Sarifudlin; Wibowo, Arief
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.608

Abstract

In higher educational institutions, graduation rates are one of the many aspects to assess the quality of the learning process. Al-Hidayah Islamic University in Bogor is one of the established private Islamic universities to create skilled human resources with moral values required by many companies nowadays. Having another institution in Bogor as a competitor with the same direction and objective is a challenge for Al-Hidayah Islamic University. Thus a solution is required to face the competition. One solution is to predict the student graduation timeliness of the students using data mining method with classification function. The implemented methodology in the data mining is Discovery Knowledge of Database (KDD), starting from selecting, preprocessing, transformation, data mining, and evaluation/ interpretation. There were two Algorithm models used in this paper, namely C4.5 and Support Vector Machine (SVM). The classification procedure consists of predictor variables and one of the target variables. Predictor variables are gender, Grade Point Average, marital status, and job status. Rapid Miner software was used to process the data. The final results of both Algorithms show an 81% precision rate and 80% accuracy level for the C4.5 Algorithm, while SVM has an 88% precision rate and 85% accuracy level.
Product Review Ranking in e-Commerce using Urgency Level Classification Approach Zuhri, Hamdi Ahmad; Maulidevi, Nur Ulfa
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.612

Abstract

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.
FoFA: Diet Information for Children with Autism with Semantic Technology in Android Based Application Febrianto, Lutfi Aristian; Wardani, Dewi Wisnu; Wijayanto, Ardhi
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.615

Abstract

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.
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 Sulaiman, Maulana Muhamad; Andrianto, Romi; Yulianto, Muhamad Arief
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.630

Abstract

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.
Sentiment Analysis on Social Distancing and Physical Distancing on Twitter Social Media using Recurrent Neural Network (RNN) Algorithm Nugraha, Fikri Aldi; Harani, Nisa Hanum; Habibi, Roni; Fatonah, Rd. Nuraini Siti
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.632

Abstract

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%.
Implementation of the Simple Multi Attribute Rating Technique Method (SMART) in Determining Toddler Growth Wahana, Agung; Alam, Cecep Nurul; Rohmah, Siti Nur
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.634

Abstract

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.
Discovering Computer Science Research Topic Trends using Latent Dirichlet Allocation Nastiti, Kartika Rizqi; Hidayatullah, Ahmad Fathan; Pratama, Ahmad Rafie
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.636

Abstract

Before conducting a research project, researchers must find the trends and state of the art in their research field. However, that is not necessarily an easy job for researchers, partly due to the lack of specific tools to filter the required information by time range. This study aims to provide a solution to that problem by performing a topic modeling approach to the scraped data from Google Scholar between 2010 and 2019. We utilized Latent Dirichlet Allocation (LDA) combined with Term Frequency-Indexed Document Frequency (TF-IDF) to build topic models and employed the coherence score method to determine how many different topics there are for each year’s data. We also provided a visualization of the topic interpretation and word distribution for each topic as well as its relevance using word cloud and PyLDAvis. In the future, we expect to add more features to show the relevance and interconnections between each topic to make it even easier for researchers to use this tool in their research projects.

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