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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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E-Commerce For Village Information System Using Agile Methodology Fitriani, Leni; Hakim, Prayoga; Al Haq, R. Mujahid
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.v7i1.825

Abstract

With the entry into the era of Industrial Revolution 4.0, the development of digitization of various aspects at the village level began. The level of use of mobile devices in the commercial transactions of society is now a massive number of users. It happens not only in large transactions but also in small transactions. With the community's high interest in the use of smartphone devices, this is a different opportunity to explore the potential of each village by helping the community, tiny and medium enterprises in conducting transactions, sales, and marketing online through the village government website. The village information system itself requires an e-commerce feature on its page to help small and medium enterprises in the area to sell products online through a simple page display. This research aims to design and develop new features of the village system that plays a role in the field of e-commerce with the Direct Message transaction method. The system development methodology used is Agile with Scrum as a framework. The Agile Model is a short-term development model that requires rapid adaptation and development to changes in any form. This e-commerce feature is for local communities, especially Micro, Small, and Medium Enterprises, so their products' marketing reach is even more outstanding while being recorded in the village system.
Chatbot for Signaling Quranic Verses Science Using Support Vector Machine Algorithm Syaripudin, Undang; Suparman, Deden; Gerhana, Yana Aditia; Rahayu, Ayu Puji; Mintarsih, Mimin; Alawiyah, Rizka
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.v6i2.827

Abstract

The many verses in the Qur'an encourage finding the right way how to understand it thematically. The purpose of the research is to develop a chatbot application that can be used to explore and elaborate the content of verses in the Qur’an that hint at science. The support vector machine (SVM) algorithm classifies question and answers datasets in chatbot applications. The number of data sets used is 76, with test data as much as 10%. The test results show that the SVM algorithm is quite good in classifying, with an accuracy value of 87.5%. While the user test results obtained an average MOS of 8.4, which means the chatbot application developed is very effective in understanding the Qur'an, which implies science. This research is expected to provide an overview of the explanation of the Qur'an about science and technology.
Determinant Factors in the Implementation of Information Technology Strategic Management to Academicians' Performance in Higher Education Institution Slamet, Cepy; Rahman, Aedah binti Abdul; Ramdhani, Muhammad Ali
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.v6i2.829

Abstract

This study aimed to understand the determinant factors of information technology (IT) strategic management to individual (lecturer) performance using data samples from selected higher education institutions in Indonesia. Since the use of IT innovation in (HEI) is often considered a lens representing the strength of strategy, competitiveness, and quality within a corporate view, it is vague on its impact on individual performance. The investigation included data collection based on an online survey conducted on 325 respondents to investigate the relationship between strategic factors, elaborated into several relevant criteria. The results of statistical data processing showed that of all the strategic factors involved, the business model and strategic alignment categorized in high determinations in influencing academicians' performance at HEI.
Development of a Digital Platform Prototype, to Facilitate Inclusive Learning for Children with Special Needs Andrian, Rian Andrian; Yasin, Aldi; Hanan, Muhammad Raihan Ijlal; Ramadhan, Muhamad Irwan; Ridwan, Taufik; Hikmawan, Rizki
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.v7i2.835

Abstract

Persons with disabilities have the same rights and responsibilities as citizens. Based on the 1945 Constitution Republic of Indonesia, article 31 paragraph 1 and Law Number 20 of 2003 concerning the National Education System, it can be concluded that the state provides full guarantees for Children with Special Needs to obtain quality education services. Many of the problems of inclusive learning that occurred during the Covid-19 pandemic, ranging from the unpreparedness of the school to various problems with environmental factors so that innovation was needed to overcome these problems. In this article, the author develops a prototype of a digital-based learning platform as a solution to facilitate inclusive learning for children with special needs.
Analysis of the Combination of Naïve Bayes and MHR (Mean of Horner’s Rule) for Classification of Keystroke Dynamic Authentication Sari, Zamah; Chandranegara, Didih Rizki; Khasanah, Rahayu Nurul; Wibowo, Hardianto; Suharso, Wildan
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.v7i1.839

Abstract

Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a nonattacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.
Anti-Corruption Disclosure Prediction Using Deep Learning Utomo, Victor Gayuh; Kumkamdhani, Tirta Yurista; Setiarso, Galih
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.
Pattern Analysis of Drug Procurement System With FP-Growth Algorithm Zulham, Zulham; Putri, Ega Evinda; Hasugian, Buyung Solihin
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.v7i1.841

Abstract

The Medan Marelan Health Center is one of the health centers in the city of Medan. The supply of medicines is considered necessary so that these medicines can still be available at any time with various types and functions. In order not to experience difficulties in distributing medicines and anticipating the supply of medicines in the Puskesmas, research was carried out using the Data Mining method. In this study, a test will be carried out on the Association Rule which is used as a solution to problems with the pattern of the drug procurement system, and will display information about the value of support and confidence from each Data Mining process. Tests in this study using Weka Software to determine the procurement of drugs that are often needed. Information obtained from the stages of the FP-Growth Algorithm is to produce patterns in the procurement of medicines, and an itemset combination pattern has been formed using the FP-Growth Algorithm method so that the results of this study can be used in drug supply effectively and efficiently.
Random Forest Method Approach to Customer Classification Based on Non-Performing Loan in Micro Business Muhajir, Muhammad; Widiastuti, Julia
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.v7i2.842

Abstract

This study aims to classify potential customers’ characteristics based on non- performing loans through the random forest method. This research uses data obtained from Syariah Mandiri Bank branch in Jambi, which includes data on micro-financing customers in years 2016–2020. The random forest method is used for analysis. The novelty of this work is that, unlike existing researches that used other soft-computing methods, we employ Random Forest method, specifically using an imbalanced class sampling technique. The obtained results show that credit risk can be estimated by taking into account factors such as age, monthly installments, margin, price of insurance, loan principal, occupation, and long installments. The research results indicate that the sensitivity, precision, and G-mean value increase compared to using the original data. Random forest with oversampling technique has the high Area Under the ROC Curve score that is equal to 66.69%.
Multi Rule-based and Corpus-based for Sundanese Stemmer Sutedi, Ade; Nasrulloh, Muhammad Rikza; Elsen, Rickard
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.v7i2.846

Abstract

The purpose of this study is to develop a stemming method by involved several methods including morphological (with affix and pro-lexeme removal), syllable (canonical) pattern, and corpus data as a comparison of the final results of stemming. The algorithm checks a number of the string first and removes affixes, then check the syllable pattern according to the stripping result, then compares to the corpus data which determines the final stemming process. In this study, the corpus data was taken from Sundanese dictionary consists of a single word used for the root word and the extracted dataset from the online Sundanese magazine. The results showed that the stripping of affix and pro-lexeme can remove the corresponding affixes and pro-lexeme then compares words that have a syllable pattern then executes the basic words quickly and the use of corpus can improve accuracy and reduce the over-stemming problems that occur in the stemming process.
Technology Acceptance Model in Government Context: A Systematic Review on the Implementation of IT Governance in a Government Institution Amali, Lanto Ningrayati; Katili, Muhammad Rifai; Suhada, Sitti; Hadjaratie, Lillyan; Mardlatillah, Hanifah
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.

Page 38 of 49 | Total Record : 490

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