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JOIN (Jurnal Online Informatika)
ISSN : 25281682     EISSN : 25279165     DOI : 10.15575/join
Core Subject : Science,
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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Articles 8 Documents
Search results for , issue "Vol 5, No 1 (2020)" : 8 Documents clear
Rupiah Exchange Prediction of US Dollar Using Linear, Polynomial, and Radial Basis Function Kernel in Support Vector Regression Alida, Mufni; Mustikasari, Metty
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.v5i1.537

Abstract

As a developing country, Indonesia is affected by fluctuations in foreign exchange rates, especially the US Dollar. Determination of foreign exchange rates must be profitable so a country can run its economy well. The prediction of the exchange rate is done to find out the large exchange rates that occur in the future and the government can take the right policy. Prediction is done by one of the Machine Learning methods, namely the Support Vector Regression (SVR) algorithm. The prediction model is made using three kernels in SVR. Each kernel has the best model and, the accuracy and error values are compared. The Linear Kernel has C = 7, max_iter = 100. The Polynomial Kernel has gamma = 1, degree = 1, max_iter = 4000 and C = 700. The RBF kernel has gamma = 0.03, epsilon = 0.007, max_iter = 2000 and C = 100. Linear kernels have advantages in terms of processing time compared to Polynomial and Radial Basis Function (RBF) kernels with an average processing time of 0.18 seconds. Besides that, in terms of accuracy and error, the RBF kernel has advantages over the Linear and Polynomial kernels with the value R2 = 95.94% and RMSE = 1.25%.
Virtual Reality Headset Implementation on Parsec Cloud Gaming Platform Rahadiansyah, Muhammad Fadhil; Muldina, Ridha; Sussi, Sussi
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.v5i1.578

Abstract

Virtual reality (VR) based games are a type of game that provides immersive gaming experience, allowing players to dive into the virtual world of the game being played. VR-based games require a high minimum computer specification, so thin clients cannot play VR-based games properly. This research aims to see how to enable thin computers to play VR-based games by utilizing cloud gaming technology. Using a high specification computer as a server, an android device as a VR headset, this Final Project implements a VR headset device so that it can be used in conjunction with cloud gaming services to be able to play VR-based games on thin computers and see how well the implementation by seeing the result from computer resources used and the Quality of Services. With Parsec cloud gaming services, the application carried out in this Final Project can run well on computers with low specifications. CPU usage on the client computer when the service is running is high at 91% usage, with 2818 MB RAM usage. Quality of Service is obtained when setting the highest quality preset, with a throughput of 16MB with a delay of about 2 ms. VR games that are played can run well with a minimum bandwidth of 15 Mbps selected from the Frame per Second (FPS) results obtained to reach 56 FPS with medium quality settings.
Exploiting Web Scraping for Education News Analysis Using Depth-First Search Algorithm Arumi, Endah Ratna; Sukmasetya, Pristi
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.v5i1.548

Abstract

Online news is one source of data that is always up to date and provides information or factual data. The search engine is one of the features for users to be able to enter keywords based on the expected category quickly. The development of education in Indonesia makes it essential to discuss, in this study using unstructured data in online news with the keyword Education included as a parameter, and adding search methods in the field of Artificial Intelligence so that the data becomes more accurate. Data that used here was from online news, namely CNN Indonesia, Detikcom, and Liputan6. Using Python Programming with depth-first search method (DFS), when compared with the results data for relevant news. Web erosion using DFS will be very helpful in searching because this method can check the date data was sent and then track the destination URL. Of the three online media sites, Detikcom produces the highest monthly data yielding an average of 885 news about education. At the same time, Liputan6 has the least amount of data on average, 28 news per month, but the data obtained are very relevant compared to Detikcom and CNN Indonesia.
Analysis and Implementation Machine Learning for YouTube Data Classification by Comparing the Performance of Classification Algorithms Amanda, Riyan; Negara, Edi Surya
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.v5i1.505

Abstract

Every day, people around the world upload 1.2 million videos to YouTube or more than 100 hours per minute, and this number is increasing. The condition of this continuous data will be useless if not utilized again. To dig up information on large-scale data, a technique called data mining can be a solution. One of the techniques in data mining is classification. For most YouTube users, when searching for video titles do not match the desired video category. Therefore, this research was conducted to classify YouTube data based on its search text. This article focuses on comparing three algorithms for the classification of YouTube data into the Kesenian and Sains category. Data collection in this study uses scraping techniques taken from the YouTube website in the form of links, titles, descriptions, and searches. The method used in this research is an experimental method by conducting data collection, data processing, proposed models, testing, and evaluating models. The models applied are Random Forest, SVM, Naive Bayes. The results showed that the accuracy rate of the random forest model was better by 0.004%, with the label encoder not being applied to the target class, and the label encoder had no effect on the accuracy of the classification models. The most appropriate model for YouTube data classification from data taken in this study is Naïve Bayes, with an accuracy rate of 88% and an average precision of 90%.
Website Based Greenhouse Microclimate Control Automation System Design Hafiz, Muhammad; Ardiansah, Irfan; Bafdal, Nurpilihan
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.v5i1.575

Abstract

Microclimate control is very important for plants cultivation in a greenhouse, two of microclimate variables are temperature and humidity, this variable can be controlled using several methods, one option is to use the misting cooling system, but this process is still done manually. This study aims to create a greenhouse microclimate control system that can be automatically displayed and controlled via a website. This research uses engineering design methods. The results show that the system can automatically turn on the misting cooling system when temperatures are above 30 ℃ and RH below 80%. Greenhouse microclimate data can be displayed and controlled via a website. The UV index greatly influences the performance of the misting cooling system on temperature and RH conditions in the greenhouse, while the UV index rises to 12 the temperature cannot be lowered and RH cannot be increased, but when the UV index falls from 12 the temperature can be reduced by ± 3 ℃ and RH can be increased by ± 12%.
Modelling the Measurement of Engagement Index of the Regional Governments' Social Media in Indonesia Abdillah, Rosyid; Rakhmawati, Nur Aini
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.v5i1.577

Abstract

Several types of engagement index and its variables can predict the engagement index of social media. However, no research has yet to use Structural Equation Modelling to model the engagement index of the variables from the prior researchers. This study was conducted to test the metrics of social media including like, comment, share and reply towards the online engagement variables that are measured by its affective engagement, cognitive engagement and behavioural engagement. The results indicate that the reply from the admin variable is the most significant factor in creating engagement on the social media of the Local Governments in Indonesia. This will then be used to increase the engagement index of the local governments in Indonesia.
Comparison of Template Matching Algorithm and Feature Extraction Algorithm in Sundanese Script Transliteration Application using Optical Character Recognition Gerhana, Yana Aditia; Atmadja, Aldy Rialdy; Padilah, Muhamad Farid
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.v5i1.580

Abstract

The phenomenon that occurs in the area of West Java Province is that the people do not preserve their culture, especially regional literature, namely Sundanese script, in this digital era there is research on Sundanese script combined with applications using Feature Extraction algorithm, but there is no comparison with other algorithms and cannot recognize Sundanese numbers. Therefore, to develop the research a Sundanese script application was made with the implementation of OCR (Optical Character Recognition) using the Template Matching algorithm and the Feature Extraction algorithm that was modified with the pre-processing stages including using luminosity and thresholding algorithms, from the two algorithms compared to the accuracy and time values the process of recognizing digital writing and handwriting, the results of testing digital writing algorithm Matching algorithm has a value of 87% word recognition accuracy with 236 ms processing time and 97.6% character recognition accuracy with 227 ms processing time, Feature Extraction has 98% word recognition accuracy with 73.6 ms processing time and 100% character recognition accuracy with 66 ms processing time, for handwriting recognition in feature extraction character recognition has 83% accuracy and 75% word recognition , while template matching in character recognition has an accuracy of 70% and word recognition has an accuracy of 66%.
Reactive Forwarding and Proactive Forwarding Performance Comparison on SDN-Based Network Suranegara, Galura Muhammad; Ichsan, Ichwan Nul; Setyowati, Endah
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.v5i1.382

Abstract

Software-defined networking (SDN) technology is one key technology in telecommunications networks that are currently widely studied. In SDN-based networks, the controller holds the key to the reliability of a network because all control functions are held by the controller as one of the open-source controllers, the Open Network Operating System (ONOS) has two forwarding mechanisms, namely reactive forwarding, and proactive forwarding. This study compares performance between reactive forwarding and proactive forwarding on ONOS with VM migration as traffic. The parameter measured is the total migration time using simple network topology. From the test results, the proactive forwarding scenario can optimize the fastest potential of the topology tested by using the path that has the largest bandwidth available on the network topology. In comparison, reactive forwarding can only pass through the smallest hops of the tested topology. From the measurement results, the average migration time performance using a proactive forwarding scenario is 36.16% faster than the reactive forwarding scenario.

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