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Gedung Fakultas Sains dan Teknologi Lt. 4 Jurusan Teknik Informatika Jl. A.H. Nasution No. 105 Cibiru Bandung 40614 Telp. (022) 7800525 / Fax (022) 7803936 Email : jurnal@if.uinsgd.ac.id
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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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Performance Analysis of ACO and FA Algorithms on Parameter Variation Scenarios in Determining Alternative Routes for Cars as a Solution to Traffic Jams Yuliant Sibaroni; Sri Suryani Prasetiyowati; Mitha Putrianty Fairuz; Muhammad Damar; Rafika Salis
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.797

Abstract

This study proposes several alternative optimal routes on traffic-prone routes using Ant Colony Optimization (ACO) and Firefly Algorithm (FA). Two methods are classified as the metaheuristic method, which means that they can solve problems with complex optimization and will get the solution with the best results. Comparison of alternative routes generated by the two algorithms is measured based on several parameters, namely alpha and beta in determination of the best alternative route. The results obtained are that the alternative route produced by FA is superior to ACO, with an accuracy of 88%. This is also supported by the performance of the FA algorithm which is generally superior, where the resulting alternative route is shorter in distance, time, running time and  there is no influence on the alpha parameter value. But in each iteration, the number of alternative routes generated is less. The contribution of this research is to provide information about the best algorithm between ACO and FA in providing the most optimal alternative route based on the fastest travel time. The recommended alternative path is a path that is sufficient for cars to pass, because the selection takes into account the size of the road capacity.
A Tourism Introduction Application Using Augmented Reality Leni Fitriani; Dini Destiani; Hasbi Muhtadillah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.817

Abstract

Tourism is a journey from one place to another. Whether it is an individual, a group, or a company, participants on this trip are interested in mental balance, such as reducing stress, entertaining themselves, and refreshing. A tourist attraction is one of the products or advantages of an area, where the region can create income and attract tourists to their tourist destinations. One way to promote tourism more attractively is with augmented reality media. This tourism introduction application using Augmented reality technology aims to make it easier for tourists to get to know tourism with interactive media. This tourism introduction application is needed for promotional media, including video playback features of Augmented reality technology and information about tourism. Augmented Reality is a real object in an area map that will become a marker object by detailing the tourist plan. A scan can be carried out to display 2D images, text, audio, and video with the android platform so that it can make it easier for users to use it. This research aims to design and build a tourism introduction application with the Application of Augmented Reality Technology. This research uses the Multimedia Development Life cycle method, with six stages: concept, design, material collecting, assembly, testing, and distribution, with the testing method using alpha and beta tests. The results of this research are in the form of an Android-based tourism introduction augmented reality application. This application can give contributions to assist tourists in finding information about tourism in an area and help the Department of Tourism and Culture promote tourism in the region more attractively.
Automatic Plant Watering System for Local Red Onion Palu using Arduino Iman Setiawan; Junaidi Junaidi; Fadjryani Fadjryani; Fika Reski Amaliah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.813

Abstract

Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.
Technology Acceptance Model in Government Context: A Systematic Review on the Implementation of IT Governance in a Government Institution Lanto Ningrayati Amali; Muhammad Rifai Katili; Sitti Suhada; Lillyan Hadjaratie; Hanifah Mardlatillah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.853

Abstract

Recent trends of studies on technology acceptance in local government had recently been popular; the studies focused on identifying the predictors of human behavior in potential acceptance or rejection of technology. This study investigated the use of information technology/information system (henceforth, IT/IS) acceptance in government as a means to improve the quality of public service and strive for transparent governance. A mixed-methods (quantitative and qualitative) study was conducted, and data were collected through questionnaires involving 125 respondents, interviews, and observations. Technology Acceptance Model (TAM) is used as a theoretical framework for behavioral information systems and Smart Partial least square (Smart PLS) analysis was employed in elaborating the complex correlation between the determinants. The result showed that the perceived ease-of-use (PEOU) contributed positively to the perceived usefulness (PU) and attitude towards using technology (ATUT). Moreover, the ATUT significantly contributed to Behavioral Intention of Use (BITU); further, the BITU also contributed to actual technology use (ATU). The PU, however, possessed a negative impact on the ATUT. These results further the information regarding the quality and performance of IT/IS services that can be used as a basis for higher-level decision-making.
Classification of the Fluency Multipurpose of Bank Mandiri Credit Payments Based on Debtor Preferences Using Naive Bayes and Neural Network Method Putri Armilia Prayesy; Edi Surya Negara
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

One that has an important role in generating bank profits is providing credit to customers, but credit also carries a very high risk. For this reason, in providing credit to debtors, of course the bank will utilize the personal data of prospective debtors in detail to avoid the risk of problems that will arise in the future. One of the appropriate risks for banks in providing credit is the behavior of customers who do not pay installments at the time which causes bad loans. To overcome and overcome the many bad events, there is an algorithmic calculation method with an intelligent computing system that helps banks in selecting prospective debtors who will be given credit. There are many algorithmic methods that can be used in this kind of research. This study analyzes the classification of staffing credit based on the criteria that become the Bank's standard.The data used by the author in this study uses existing debtor credit data from 2017 to 2020, the modeling process is carried out using split validation with the Naive Bayes algorithm and Neural Network, with this algorithm the 1,314 datasets is divided into 2 parts, namely 80% used as training data and 20% used as testing data. The results showed that the Neural Network algorithm has better results with a correct value of 84.13%, while the Naive Bayes algorithm only produces a value of 72.62%
Data Analysis of Social Media’s Impact on COVID19 Pandemic Users’ Mental Health Deshinta Arrova Dewi
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.912

Abstract

Social media has a significant impact on people's daily lives and spread widely. Unrestrained usage of social media could have worsening consequences on mental health. The majority of COVID-19 users who were exposed to social media learned about numerous facts, which made their anxiety and depression-related mental health disorders worse. This study aims to determine how social media usage affects users' mental health during the COVID19 pandemic. Through surveys and expert interviews, this study collects both quantitative and qualitative data. Total number of respondent involved was 106 with average age group of 18-41 year old. Using reliability testing (Cronbach alpha test) and inferential statistic (Pearson Correlation and Chi Square), results show that during the COVID-19 pandemic, there is a significant link between social media use and mental health. Anxiety and depression brought on by social media are common among young adults, predominantly female, between the ages of 18 and 24, than in men. Additionally, correlation plot analysis with variety of queries reveal the mental health issues and activities on social media.
Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods Jelita Asian; Moneyta Dholah Rosita; Teddy Mantoro
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.900

Abstract

Sexual harassment is defined as giving sexual attention both verbally, either in speech or writing, and physically to victims who are predominantly women, On July 13, 2022, there was a tweet featuring a video of sexual harassment that made it trend in various countries. The video irritated Twitter users and made various comments resulting in various sentiments that can be analyzed using sentiment analysis. The purpose of this study is to see what the public thinks about the sexual harassment case of Brazilian anesthesiologist. Besides the sentiment analysis, another aim of this study is to see how objective are those sentiments based on their polarity. This study uses a comparison of two methods in sentiment analysis, namely Multi-Layer Perceptron Classifier and Random Forest, and labeling automatically using TextBlob.  This results in 94.44% accuracy, 94.44% precision, 92% recall and 93% f1_score. For MLP Classifier and accuracy 96.42%, precision 94.44%, recall 96.66% and f1_score 95.56% for Random Forest. Sentiment polarity score from the TextBlob is -0.5 and subjectivity is 0.4 which indicates that most statements are negative and subjective score is 0.4, which means those sentiments are subjective in nature.
AR Make-up Filter for Social Media using the HSV Color Extraction Maisevli Harika; Setiadi Rachmat; Nurul Dewi Aulia; Zulfa Audina Dwi; Vandha Pradwiyasma Widartha
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.994

Abstract

Choosing the appropriate cosmetics is an arduous task. Because cosmetics are tested directly on the skin to ensure each person’s preferences are met. The consumer repeatedly tries a sample and then discards it until he discovers one that meets his tastes. The cosmetics business and consumers are affected by this move. Companies can utilize Augmented Reality (AR) technology as an alternative to mass-producing cosmetic samples. The difficulty of deploying augmented reality is the difficulty of putting cosmetics into camera video streams. Each individual bears the burden of skin color and its effect on light. HSV Color Extraction was the method employed for this study. The application of augmented reality intends to enable consumers to test cosmetics with their chosen color and assist businesses in competing in the industry by promoting items and engaging customers. This work makes it easier to choose cosmetics using augmented reality and social media. AR simulates the usage of the desired color cosmetics, whereas social media allows users to obtain feedback on their color preferences. The outcomes of this study indicate that augmented reality (AR) apps can display filters in bright, dim, and even wholly dark lighting conditions. This research contributes originality that cosmetic firms can utilize to market their products on social media.
Anti-Corruption Disclosure Prediction Using Deep Learning Victor Gayuh Utomo; Tirta Yurista Kumkamdhani; Galih Setiarso
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.840

Abstract

Corruption gives major problem to many countries. It gives negative impact to a nation economy. People also realized that corruption comes from two sides, demand from the authority and supply from corporate. On that regard, corporates may have their part in fight against corruption in the form of anti- corruption disclosure (ACD). This study proposes new method of ACD prediction in corporate using deep learning. The data in this study are taken from every companies listed in Indonesia Stock Exchange (IDX) from the year 2017 to 2019. The companies can be categorized in 9 categories and the data set has 8 features. The overall data has 1826 items in which 1032 items are ACD and the other 794 items are non-ACD. In this study, the deep neural network or deep learning is composed from input layer, output layer and 3 hidden layers. The deep neural network uses Adam optimizer with learning rate 0.0010, batch size 16 and epochs 500. The drop out is set to 0.05. The accuracy result from deep learning in predicting ACD is considered good with the average training accuracy is 74.76% and average testing accuracy is 76.37%. However, the loss result isn’t good with average training loss and testing loss are respectively 51.76% and 50.96%. Since the aim of the study to find the possibility of deep learning as alternative of logistic regression in ACD prediction, accuracy comparison from deep learning and logistic regression is held. Deep learning has average prediction accuracy of 76.37% is better than logistic regression with average accuracy of 67.15%. Deep learning also has higher minimum accuracy and maximum accuracy compared to logistic regression. This study concludes that deep learning may give alternatives in ACD prediction compared the more common method of logistic regression.
The Measurement and Evaluation of Information System Success Based on Organizational Hierarchical Culture Reni Haerani; Titik Khawa Abdul Rahman; Lia Kamelia
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this study, the adoption of the Delone & McLean information system success model and its adaptation using the organizational hierarchy culture theory is used to explore the state of information system success and examine the factors that suggest success. This research was conducted at universities in Banten Province, which currently rely on information systems in many ways, especially those related to university management. By measuring the evaluation of the success of information systems and the hierarchical culture in organizations using a model that the researcher built according to the integration of 2 models. The results the measurement of the success of information systems were obtained from distributing questionnaires, there were still 85 (63%) respondents, and 84 (61.3%) were satisfied with the performance of the information system success model. The least squares structural equation modeling analysis (PLS-SEM) was then applied due to the sample size. The previous stage consisted of evaluating the reflective measurement model in evaluating the reliability of internal consistency using Composite Reliability, Reliability indicators, Convergent Validity and Discriminant Validity, finally it was concluded that the success of information system by hierarchical culture integration model in the organization on could be passed on the more complex research terms, especially using samples, and different questionnaires.

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