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[Embedding a Blockchain Technology Pattern Into the QR Code for an Authentication Certificate ]]>
<![CDATA[Qurotul Aini]]>;
<![CDATA[Untung Rahardja]]>;
<![CDATA[Melani Rapina Tangkaw]]>;
<![CDATA[Nuke Puji Lestari Santoso]]>;
<![CDATA[Alfiah Khoirunisa]]>
<![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.v5i2.583
<![CDATA[In the disruptive 4.0 era that emphasizes technological sophistication, blockchain is present as a technology that increasingly influences human life, helping humans in all aspects, including education. The role of blockchain technology in the world of education is to test the validity of diplomas, the increasing number of fake diplomas for an interest, both for work and continuing education to a higher level. The purpose of this research with the implementation of blockchain is expected to make it easier for users to verify the authenticity of a diploma. This study uses the SWOT analysis method to identify all possibilities that exist in blockchain technology. The final result of this research, the system will print a physical certificate in the form of paper in general, then the certificate will be printed a QR code. To verify numeric code on QR Code via scanning on smartphone or QR Reader. It is hoped that the blockchain technology applied to digital assets can reduce cases of forgery of diplomas and other important documents.]]>
<![CDATA[Genetic Algorithm to Optimize k-Nearest Neighbor Parameter for Benchmarked Medical Datasets Classification ]]>
<![CDATA[Rizki Tri Prasetio]]>
<![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[Sentiment Analysis on Social Distancing and Physical Distancing on Twitter Social Media using Recurrent Neural Network (RNN) Algorithm ]]>
<![CDATA[Fikri Aldi Nugraha]]>;
<![CDATA[Nisa Hanum Harani]]>;
<![CDATA[Roni Habibi]]>;
<![CDATA[Rd. Nuraini Siti Fatonah]]>
<![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[Prototype Program Hand Gesture Recognize Using the Convex Hull Method and Convexity Defect on Android ]]>
<![CDATA[Muhammad Adi Khairul Anshary]]>;
<![CDATA[Eka Wahyu Hidayat]]>;
<![CDATA[Tiara Amalia]]>
<![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.v5i2.594
<![CDATA[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%.]]>
<![CDATA[Long Short-Term Memory Approach for Predicting Air Temperature In Indonesia ]]>
<![CDATA[Putu Harry Gunawan]]>;
<![CDATA[Devi Munandar]]>;
<![CDATA[Anis Zainia Farabiba]]>
<![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.v5i2.551
<![CDATA[Air temperature is one of the main factors for describing the weather behaviour in the earth. Since Indonesia is located on and near equator, then monitoring the air temperature is needed to determine either global climate change occurs or not. Climate change can have an impact on biological growth in various fields. For instance, climate change can affect the quality of production and growth of animal and plants. Therefore, air temperature prediction is important to meteorologists and Indonesian government to provide information in many sectors. Various prediction algorithms have been used to predict temperature and produce different accuracy. In this study, the deep learning method with Long Short-Term Memory (LSTM) model is used to predict air temperature. Here, the results show that LSTM model with one layer and Adaptive Moment Estimation (ADAM) optimizer produce accuracy which is 32% of , 0.068 of MAE and 0.99 of RMSE. Moreover, here, ADAM optimizer is found better than Stochastic Gradient Descent (SGD) optimizer.]]>
<![CDATA[Customer Loyality Segmentation on Point of Sale System Using Recency-Frequency-Monetary (RFM) and K-Means ]]>
<![CDATA[Rizki, Bayu]]>;
<![CDATA[Ginasta, Nava Gia]]>;
<![CDATA[Tamrin, Muh Akbar]]>;
<![CDATA[Rahman, Ali]]>
<![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.v5i2.511
<![CDATA[It is no doubt that the development of the business world has been progressive. Point of sale is one of the many system used as a means of payment in various existing businesses, especially in heterogeneous markets. The activity of transactions between Point of Sale Systems and Customers occur in the business world. Keep in mind also that one of the main factors of business success, is from customers. There is the need of an attractive strategy and certainly it will be to increase the income and assets of a business. To know that, this research will explore the behavior of customer which is based marketing, through RFM Method (Recency, Frequency and Monetary). The case of this study is in Goldfinger Store. It will do segmentation and also use data mining technique to do clustering by using K-Means with result of loyal and potential customer. The results of segmentation using RFM (Recency, Frequency, Monetary) and K-Means methods have produced multiple clusters by dividing them into groups.]]>
<![CDATA[Long Short-Term Memory Approach for Predicting Air Temperature In Indonesia ]]>
<![CDATA[Gunawan, Putu Harry]]>;
<![CDATA[Munandar, Devi]]>;
<![CDATA[Farabiba, Anis Zainia]]>
<![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.v5i2.551
<![CDATA[Air temperature is one of the main factors for describing the weather behaviour in the earth. Since Indonesia is located on and near equator, then monitoring the air temperature is needed to determine either global climate change occurs or not. Climate change can have an impact on biological growth in various fields. For instance, climate change can affect the quality of production and growth of animal and plants. Therefore, air temperature prediction is important to meteorologists and Indonesian government to provide information in many sectors. Various prediction algorithms have been used to predict temperature and produce different accuracy. In this study, the deep learning method with Long Short-Term Memory (LSTM) model is used to predict air temperature. Here, the results show that LSTM model with one layer and Adaptive Moment Estimation (ADAM) optimizer produce accuracy which is 32% of , 0.068 of MAE and 0.99 of RMSE. Moreover, here, ADAM optimizer is found better than Stochastic Gradient Descent (SGD) optimizer.]]>
<![CDATA[Feasibility Testing of a Household Industry Food Production Certificate Using an Expert System with Forward Chaining Method ]]>
<![CDATA[Ardiansah, Irfan]]>;
<![CDATA[Efatmi, Fajri]]>;
<![CDATA[Mardawati, Efri]]>;
<![CDATA[Putri, Selly Harnesa]]>
<![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.v5i2.579
<![CDATA[Quality and safe food products are the basic right of every consumer, including food products produced by small and medium industries. Good food production is an important factor in meeting quality standards or food safety licensing requirements. In setting standards, the government also plays an important role in providing direction and assistance to small and medium industries on achieving the specified quality standards. During this time the process is still carried out in a conventional manner directly to the industry. This conventional process is still considered ineffective by seeing the low level of business actors’ knowledge of the standards for Good Food Production Practice (GFPP). So, with this lack of knowledge, business actors’ interest in making food licensing is low. This study designed the application of an expert system that stimulates and provides an illustration for a standards assessment of Good Food Production methods. This research was conducted using Object Oriented Programming (OOP) engineering method for program development and using forward chaining for reasoning methods. This research proved that the application of an expert system for licensing due diligence can function in accordance with standards set by the government.]]>
<![CDATA[Embedding a Blockchain Technology Pattern Into the QR Code for an Authentication Certificate ]]>
<![CDATA[Aini, Qurotul]]>;
<![CDATA[Rahardja, Untung]]>;
<![CDATA[Tangkaw, Melani Rapina]]>;
<![CDATA[Santoso, Nuke Puji Lestari]]>;
<![CDATA[Khoirunisa, Alfiah]]>
<![CDATA[ JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020) ]]>
Publisher : <![CDATA[Department of Informatics, UIN Sunan Gunung Djati Bandung ]]>
Show Abstract
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DOI: 10.15575/join.v5i2.583
<![CDATA[In the disruptive 4.0 era that emphasizes technological sophistication, blockchain is present as a technology that increasingly influences human life, helping humans in all aspects, including education. The role of blockchain technology in the world of education is to test the validity of diplomas, the increasing number of fake diplomas for an interest, both for work and continuing education to a higher level. The purpose of this research with the implementation of blockchain is expected to make it easier for users to verify the authenticity of a diploma. This study uses the SWOT analysis method to identify all possibilities that exist in blockchain technology. The final result of this research, the system will print a physical certificate in the form of paper in general, then the certificate will be printed a QR code. To verify numeric code on QR Code via scanning on smartphone or QR Reader. It is hoped that the blockchain technology applied to digital assets can reduce cases of forgery of diplomas and other important documents.]]>
<![CDATA[Prototype Program Hand Gesture Recognize Using the Convex Hull Method and Convexity Defect on Android ]]>
<![CDATA[Anshary, Muhammad Adi Khairul]]>;
<![CDATA[Hidayat, Eka Wahyu]]>;
<![CDATA[Amalia, Tiara]]>
<![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.v5i2.594
<![CDATA[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%.]]>
