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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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Comparison of Machine Learning Classification Methods in Hepatitis C Virus Syafa’ah, Lailis; Zulfatman, Zulfatman; Pakaya, Ilham; Lestandy, Merinda
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.v6i1.719

Abstract

The hepatitis C virus (HCV) is considered a problem to the health of societies are the main. There are around 120-130 million or 3% of the world's total population infected with HCV. Without treatment, most major infectious acute evolve into chronic, followed by diseases liver, such as cirrhosis and cancer liver. The data parameters used in this study included albumin (ALB), bilirubin (BIL), choline esterase (CHE), -glutamyl-transferase (GGT), aspartate amino-transferase (AST), alanine amino-transferase (ALT), cholesterol (CHOL), creatinine (CREA), protein (PROT), and Alkaline phosphatase (ALP). This research proposes a methodology based on machine learning classification methods including k-nearest neighbors, naïve Bayes, neural network, and random forest. The aim of this study is to assess and evaluate the level of accuracy using the algorithm classification machine learning to detect the disease HCV. The result show that the accuracy of the method NN has a value of accuracy are high, namely at 95.12% compared to the method KNN, naïve Bayes and RF in a row amounted to 89.43%, 90.24%, and 94.31%.
Design of an Information System for Class Scheduling a Web-Based Lecture Schedule (Case Study: Faculty of Engineering and Science, Ibn Khaldun University) Ginting, Novita BR; Afrianto, Yuggo; suratun, Suratun
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.727

Abstract

During the Covid-19 pandemic, the lecture process was carried out online, so it impacted other academic activities such as the preparation of lecture schedules. The results of observations at the Faculty of Engineering and Science found that the practice of lecture schedules was carried out manually, such as the schedule coordination process was carried out face-to-face between study programs, faculties, and lecturers to overcome conflicts in the use of rooms and teaching time. Changes in the teaching schedule need to be re-checked on the use of the room and the lecturer's teaching time because it has not been documented with the information system. Hence, this study aims to build an information system for preparing lecture schedules using the Greedy Best First Search Method based on the willingness of lecturers to teach. The system was developed using the RAD (Rapid Application Development) and testing using BlackBox testing. The results of this study succeeded in building a lecture scheduling information system that was able to generate lecture schedules automatically and quickly without having to coordinate face-to-face to support online lectures during the Covid-19 pandemic.
Data Visualization of COVID-19 Vaccination Progress and Prediction Using Linear Regression Nuha, Hilal H; Absa, Ahmad Abo
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.v7i1.736

Abstract

This paper provides a data visualization and analysis of the COVID-19 vaccination program. Important information such as which countries have the highest vaccination rates and numbers. In addition to the types of vaccines used and used by countries in the world, an infographic on the geographic distribution of vaccine use is also shown. To model the obtained data, daily vaccination rates were modeled by linear regression in which five sample countries with different vaccination ranges were processed using data science approach, namely, linear regression. The modeling results show a gradient coefficient that represents an increase in vaccine rates. The prediction results showed that the highest rate of increase in daily vaccination was 1,826,126 additional vaccines per day.
Enhancement of White Blood Cells Images using Shock Filtering Equation for Classification Problem Vito, Gregorius; Gunawan, Putu Harry
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.739

Abstract

Medical image processing has developed rapidly in the last decade. The autodetection and classification of white blood cells (WBC) is one of the medical image processing applications. The analysis of WBC images has engaged researchers from medical also technology fields. Since WBC detection plays an essential role in the medical field, this paper presents a system for distinguishing and classifying WBC types: eosinophils, neutrophils, lymphocytes, and monocytes, using K-Nearest Neighbor (K-NN) and Logistic Regression (LR). This study aims to find the best accuracy of pre-processing images using original grayscale, shock filtering, and thresholding grayscale. The highest average accuracy in classifying WBC images in the conducting research is 43.54% using the LR algorithm from 2103 images. It is obtained from the combination of thresholding grayscale image and shock filtering equation to enhance the quality of an image. Overall, using two algorithms, KNN and LR, the classification accuracy can increase up to 12%.
Application of Augmented Reality to Replicate Couples Sit in Wedding Ceremony Rivaldhi, Achmad Ariq; Dijaya, Rohman
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

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

Abstract

In Indonesia, the bride and groom do pre-wedding photos like a tradition before marriage with couple sit in wedding ceremony. The splendor of the wedding ceremony made many vendors interested in running a wedding party business. These vendors provide services and goods related to wedding parties, such as wedding organizers, bridal, party decorations (couples sit in of wedding ceremony), as well as photo and video documentation. To give more virtual wedding nuance experience to customer, augmented reality was applied. This research develop application of augmented applying to replicate couples sit in of wedding ceremony. Augmented reality (AR) technology adopted to promote couples sit in of wedding ceremony. Moreover, combines wedding ceremony nuance and augmented reality make consumers who want to find 3D wedding background desired.
Interactive Digital Catalog for Canopy Workshop Using Augmented Reality Dijaya, Rohman; Wardana, Rizky Bayu; Suprianto, Suprianto
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.761

Abstract

This research study develops a product promotion method for a canopy roofs. The development of this method is to apply a 3-dimensional (3D) catalog using Augmented Reality (AR) technology. By utilizing Augmented Reality technology, sellers do not need to create markets or miniature products that are commonly used to provide examples to consumers to save costs, attract consumer interest, and display objects that appear natural. Based on the tests that have been done, it is concluded that implementing Augmented Reality in the canopy sales promotion media using the Luther development method with the stages of analysis, design, implementation, testing, and maintenance. Implementation of Augmented Reality in canopy sales promotion media uses concept data from the types of canopies included in the Augmented Reality-based application, namely stainless and hollow types made using a 3D blender program. A marker as a sign to bring up 3D objects in the application. Markers are created using Photoshop and entered the database so that they can be stored online. System testing uses the BlackBox testing method where the program's functionality is running as desired.
Classification of the Fluency Multipurpose of Bank Mandiri Credit Payments Based on Debtor Preferences Using Naive Bayes and Neural Network Method Prayesy, Putri Armilia; Negara, Edi Surya
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%
Kansei Engineering in Designing Web-Based e-Commerce UMKM Product Isa, Indra Griha Tofik; Ariyanti, Indri
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.786

Abstract

Human-Computer Interaction (HCI) is a part of the development of a system in addition to the usability factor. Several methods were developed in HCI to produce a User Interface design that persuasively attracts the user’s interest. One of these methods was Kansei Engineering which involved psychological factors and user emotions in the stage. The study focused on developing the e-commerce User Interface for UMKM products which based on how to maximize the service and quality of e-Commerce because so far the development of the web-based UMKM  e-Commerce product user interface has not paid attention to psychological factors. The Research followed Kansei Engineering Type 1 (KEPack) with the stages: (1) Research Initiation, (2) Collecting Kansei Words (KW), (3) Translating KW into SD scale, (4) Collecting Specimens, (5) Classifying Item / Category Specimens, (6) Evaluating Questionnaire Participants’ Data, (7) Multivariate Statistical Analysis, (8) Translating Statistical Data into Design Elements, (9) Creating Guideline Matrix Kansei Engineering. This study involved 40 participants, 20 Kansei Words, and ten specimens of UMKM e-Commerce products. The final result is the Kansei e-Commerce matrix guideline for web-based UMKM products, which had two main concepts, they were complexity consisting of formal, natural and simple emotion factors; and Uniqueness consisting of Comfortable, Soft, and Unique which consists of 8 main parts which divided into 65 design elements. The contribution of this Research in the informatics area is to provide recommendations for the appearance of  web-based UMKM  e-Commerce products based on the psychological factors of the user through the Kansei Engineering Stages.
Implementation of Generative Adversarial Network to Generate Fake Face Image Pardede, Jasman; Setyaningrum, Anisa Putri
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.790

Abstract

In recent years, many crimes use technology to generate someone's face which has a bad effect on that person. Generative adversarial network is a method to generate fake images using discriminators and generators. Conventional GAN involved binary cross entropy loss for discriminator training to classify original image from dataset and fake image that generated from generator. However, use of binary cross entropy loss cannot provided gradient information to generator in creating a good fake image. When generator creates a fake image, discriminator only gives a little feedback (gradient information) to generator update its model. It causes generator take a long time to update the model. To solve this problem, there is an LSGAN that used a loss function (least squared loss). Discriminator can provide astrong gradient signal to generator update the model even though image was far from decision boundary. In making fake images, researchers used Least Squares GAN (LSGAN) with discriminator-1 loss value is 0.0061, discriminator-2 loss value is 0.0036, and generator loss value is 0.575. With the small loss value of the three important components, discriminator accuracy value in terms of classification reaches 95% for original image and 99% for fake image. In classified original image and fake image in this studyusing a supervised contrastive loss classification model with an accuracy value of 99.93%.
A Model-Driven IS 4.0 Development Framework for Railway Supply Chain Jayakrishnan, Mailasan; Mohamad, Abdul Karim; Yusof, Mokhtar Mohd
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.v7i2.794

Abstract

Railway Industry (RI) in Malaysia possess below-average Information System (IS) skills and seldom use the IS for decision making at their operation level while they likewise discover digital transformation adaption is crucial and hence RI in Malaysia are in the slow mass of adapter classification. Perceiving the significant task of IS to RI in the economy, the government is resolved to assist and support the improvement of IS to guarantee their sustainability and competitiveness. IS framework being significant because it set up the computerized industry, lively digital, who can structure with simple to utilize and basic dynamic interaction. The present IS model utilized in Malaysia depends on the knowledge and experience of the specialist like system developers and academicians. The maximum of these IS models to identify the visual view of performance in RI are precise and are not strategized toward railway utilize and do not give prescriptive evaluation. The issue is no transition development and the absence of industry capacity to do the transition phases. This research focuses on the technology parameters influencing the adaption of IS to assist decision-makers, administrative bodies, and IS analysis to approach the advantages of its continued and expected improvement in the RI.

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