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Journal of Advances in Information Systems and Technology
Published by Universitas Negeri Semarang
ISSN : -     EISSN : 2715999X     DOI : https://doi.org/10.15294/jaist
Core Subject : Science,
Computer Science & IT
Journal of advances in Information Systems and Technology (JAIST) seeks to promote high quality research that is of interest to the international community.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 10 Documents
 1 
Search results for , issue "Vol 5 No 1 (2023): April" : 10 Documents clear
Factors Influencing Community Behavior towards SIKER: An Extension of the TAM model
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.64274

Abstract

Sistem Kerja (SIKER) is a system that allows the public to make yellow cards/AK1, join job training, look for job vacancies and invite for interviews. In its application, not many public of Semarang city have adopted SIKER even though the city of Semarang is ranked 2nd in the excellent category in Central Java province in the e-government rankings. This study will observe the effect of perceived usefulness, perceived ease of use, facilitating conditions, and social influence on the behavioral intention of the public of Semarang city in utilizing SIKER, and the variables age and perceived trust will be used as intervening variables. This study uses a quantitative descriptive method with a data analysis approach using Partial Least Square Structural Equation Modeling (PLS-SEM) by utilizing SmartPLS version 3.2.9 tools. A number of 330 valid respondents participated in this current study. The results of this study show that the factors that influence the behavioral intention of the public of Semarang are perceived trust, perceived usefulness, facilitating conditions, and age with a negative direction. Perceived trust is proven to be the biggest factor influencing the behavioral intention to use SIKER services. Whereas the intervening effect of perceived trust is proven to intervene with perceived ease of use and perceived usefulness towards behavioral intention with the intervening effects of full mediation and partial mediation. However, for age, it is proven not to intervene with no intervening effect and unmediated effect.
Sentiment Analysis of student on Online Lectured During Covid-19 Pandemic Using K-Means and Naïve Bayes Classifier
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.64903

Abstract

The Covid-19 pandemic that occurred at the end of 2019 caused life changes, one of which was the learning process in universities. in accordance with the instructions issued by the Minister of Education as an effort to prevent the spread of Covid-19 by conducting online learning. Learning that is carried out online with a long period of time there are many obstacles such as networks and learning processes that are not optimal. Thus, students have mixed opinions on online lectures. Twiter is one of the social media used by students in expressing opinions on online lectures. The sentiment that users write on Twitter has not been determined in a more positive or negative direction. Sentiment analysis is needed to determine the tendency of student opinions towards online lectures. In this study, a sentiment analysis of online lectures was carried out using the K-Means and Naïve Bayes Classifier methods. The K-Means method is used to perform labeling or clustering and the Naïve Bayes Classifier is used as the classification. Based on research conducted with testing the Naïve Bayes Classifier model with a 70% division of training data and 30% test data using matrix confussion resulted in an accuracy of 95.67%.
The Influence of Recommendation System Quality on E-commerce Customer Loyalty with Cognition Affective Behavior Theory
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.65910

Abstract

The high number of internet users and the growth of e-commerce make it important for companies or businesses that provide e-commerce services to know the quality of their services to increase customer trust and loyalty. In addition, with the proliferation of e-commerce, there is more information related to available products, sometimes it also causes problems that users feel confused and frustrated to sort out information and make purchase decisions. In some e-commerce, there is already a recommendation system that makes it easier for users to make their choice. This study aims to find out what factors affect customer loyalty to Shopee e-commerce as well as test how much influence the quality of Shopee's e-commerce recommendation system have on customer loyalty with user trust as mediation variables. This research uses a quantitative approach using cognition affective behavior theory. Data collection in this study was carried out by distributing questionnaires through Google forms with purposive sampling techniques. A total of 356 respondents have participated in the study. The obtained data were analyzed with partial least squares – structural equation model (PLS-SEM). From the results of the analysis, seven hypotheses exist. All independent variables affect dependent variables. It was found that recommendation quality (RQ) can affect directly on the LO or indirectly through the trust mediation variable (TR).
Heart Disease Diagnosis Using Tsukamoto Fuzzy Method
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.67565

Abstract

As one of the leading causes of death in the world, heart disease needs special attention. Heart disease often causes sudden death because the signs of a heart attack are not easy to detect. However, early detection efforts can still be pursued and continue to be carried out, especially using information technology. This study aims to diagnose the risk level of heart disease using Tsukamoto method and involving 11 input variables such as cholesterol, blood pressure, ECG, and others. At the same time, the output variables include healthy, small, medium, large, and very large. The stages of the method consist of four main processes, namely literature review, fuzzy inference system design, applying of Tsukamoto fuzzy, and evaluation. The research concluded that the fuzzy logic of the Tsukamoto method can be used to diagnose the risk level of heart disease, although the model performance is still limited to an accuracy value of 58%.
A Analysis of Information System Audit Using Control Objectives for Information and Related Technology 5 Framework on Permata Hebat Application
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.64187

Abstract

Permata Hebat application is an application created as a service to develop micro businesses among housewifes in Semarang City. However, to fulfill this expectation, of course, the application needs good IT management or governance, so that the application can be optimally utilized by its users. However, since its operation on March 23, 2021, it is not yet known how the quality or level of management capability or IT governance services run by the organization. Information system audit itself is an activity to evaluate and ensure that the system has met the standards. Meanwhile, one of the frameworks that can be used to conduct an audit is COBIT 5. COBIT 5 is a good practice whose processes have been adapted to current standards. As for the process control used is the Deliver, Services, and Support (DSS) domain. The results of the calculation show that for domains DSS01, DSS03, and DSS06 each received a maturity level value of 0.60, 0.52, and 0.61 or at level 1 performed. Meanwhile, domains DSS02, DSS04, and DSS05 each received maturity level values of 0.45, 0.35, and 0.42 or are still at level 0 incomplete. Therefore, there is still a need for a lot of improvement or improvement in each process. The goal is that the system can run in accordance with organizational expectations.
Digital Transformation Analysis in the Manufacturing Module in Aluminium Companies using the TAM Method
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.66567

Abstract

This research was conducted to identify the factors affecting the success of digital transformation through the use of the manufacturing module in aluminum companies. The Technology Acceptance Model (TAM) method was used to measure technology acceptance through the use of the manufacturing module with variables of perceived usefulness (PU), perceived ease of use (PEOU), and perceived risk (PR) that affect the behavioral intention of use (BIU) at PT. Allure Allumunio and the success of digital transformation were measured through descriptive analysis. The sample was taken using the entire population with a total of 50 manufacturing module users. The collected data was analyzed using Partial Least Square – Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0.8 software. A total of 48 respondents with valid data were obtained and validity and reliability tests were performed, resulting in valid and reliable instruments. The R-square, Q-square, and t-test were used to analyze the proposed hypothesis. The results showed that three hypotheses were accepted: PU > BIU, PEOU > BIU, and PEOU > PU, and one hypothesis was rejected: PR > BIU because risk did not have a significant impact on the behavior intention of technology acceptance. Additionally, the analysis of digital transformation success was conducted with results showing an increase in company productivity and a decrease in risk, marked by an increase in units received on time after digital transformation and a 78% level of adaptation satisfaction. The conclusion is that technology acceptance was achieved through perceived usefulness and perceived ease of use, as well as increased productivity, level of adaptation satisfaction, and decreased risk, which are factors contributing to the success of the digital transformation.
Analysis of Public Opinion on the Impact of the Implementation of Community Activity Restrictions (PPKM) During the Covid-19 Pandemic Using Long Short Term Memory and Latent Dirichlet Allocation Gebyar Bintang Taufikurohman; Alamsyah Alamsyah
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.64964

Abstract

Technology social is the fastest and most up-to-date source of information. A model that can provide mapping will help in sorting out information more precisely and quickly. Public opinion in the mass media always develops quickly to talk about an issue in just a few days or even hours, so we do not know what the opinions of the people in the mass media are on the issue. In this study, the author applied topic modeling to the results of sentiment analysis on PPKM. The source of data in this study was obtained from twitter using SNScrape. The collected data was analyzed sentiment using the Long Short-term Memory (LSTM) method, so that public opinion was obtained with positive, negative, and neutral sentiments. The classification obtained from the results of the sentiment analysis process is continued with the topic modeling process using the Latent Dirichlet Allocation (LDA) method and visualized in the form of a wordcloud to find out the relationship between one topic and another. The sentiment analysis process produces a model with an accuracy rate of 90.8% and the topic modeling process successfully presents topics that are easy to interpret so that conclusions can be known about an issue.
Application of Anisotropic Diffusion Filters and Convolutional Neural Network with Mobilenet Framework On X-Ray Image to Detect Pneumonia Zhazkeiya Sheelfa Irawaty; Zaenal Abidin
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

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

Abstract

Pneumonia is the largest infectious disease that occurs in children worldwide. WHO reported that pneumonia killed 808,694 children under five years in 2017; 15% of children under five years died. Pneumonia is the largest infectious disease that can occur in children worldwide. These cases are most common in South Asia and Africa. All the experts suggest that it an easy to diagnose by using x-rays. The x-ray results from the lungs of patients with pneumonia can give an idea of ​​how the pneumonia virus causes the infection in the lungs of patients. This study aimed to determine how the convolutional neural network method works with the framework MobileNet and anisotropic diffusion filters to detect pneumonia and determine the level of accuracy produced by the convolutional neural network method with the MobileNet framework and anisotropic diffusion filters in detecting pneumonia. In this study, the Chest X-ray Images (Pneumonia) dataset from Kaggle was used as an object to be classified using Anisotropic Diffusion Filters and Convolutional Neural Networks to determine the presence of pneumonia based on x-ray images. Classification is carried out on the Chest X-ray Images (Pneumonia) dataset for two weeks from August 14, 2021 to August 28, 2021 which will go through a classification process on x-ray images using the Convolutional Neural Network algorithm and Anisotropic Diffusion Filters. The results of testing with this method have increased compared to previous studies, with an accuracy of 96.67%.
Supply Chain Performance Analysis of Plant Seedling Distribution System Using Supply Chain Operations Reference Method Efrilianda, Devi Ajeng; Adhirajasa, Danendra Yassar
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.65630

Abstract

In the industrial world, distribution activities are one of the important things in the flow of a business process. The role of advances in information technology also has a considerable good impact on the process of exchanging information in business processes. The XYZ agency is responsible for organizing the distribution of plant seeds to all communities and farmer groups as an effort to improve the economy in the agro-industrial sector. However, there are obstacles in the distribution process activities carried out by the XYZ agency such as the lack of harmonization of information exchange with regional posts. This causes the distribution process to be hampered and also not even distributed. Therefore, it is necessary to describe the process flow using the Supply Chain Management (SCM) method to manage seeds distribution management appropriately. SCM elaborates each supply chain process in detail by categorizing each process with the attributes of plan, source, make, deliver, and return. In addition, performance measurement using the Supply Chain Operations Reference (SCOR) model is carried out to determine and provide recommendations for improvements needed for each related performance metric. There are 31 Key Performance Indicators (KPI) that are in accordance with the distribution process and validated in XYZ agency. The result of performance measurement based on the Key Performance Indicator reached 83.12, which indicated the performance monitoring of the actual seeds distribution process by XYZ agency at the Good level.
Analysis of Application Success in XYZ Agency as an Online Learning Media Using the Delone and Mclean Models Erika Noor Dianti; Endang Sugiharti
Journal of Advances in Information Systems and Technology Vol 5 No 1 (2023): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i1.65794

Abstract

Internet users in Indonesia have shown a rapid increase. This indicates that the development of information and communication technology is growing, bringing many life changes, thus demanding the education industry to strive to improve the quality of education continuously. However, at the beginning of 2019, COVID-19 pandemic emerged, which required that all students not be allowed to do face-to-face learning. Because of this problem, companies are starting to create online learning technologies that have a positive impact. In 2022, XYZ application is a learning application ranked 9th among the most popular applications. Nevertheless, in its use, there are still obstacles. Based on this description, this study will analyze application's success using Delone and Mclean models to determine whether application has been considered successful. The research data was obtained by distributing questionnaires online with a total of 240 respondents who were users who had used e-learning in XYZ agency with an age range of 15 to 45 years. This study used quantitative methods and data processing using Smart PLS version 4 software to test inner and outer models. The results showed that success rate of e-learning in XYZ agency was very high, and out of twelve hypotheses, eight were accepted, and four were rejected. The factors that support success of e-learning in XYZ agency are seen from accepted hypotheses. At the same time, factors that hinder application's success are information quality, system quality, service quality, instructor quality, and user satisfaction. From these inhibiting factors, appropriate recommendations are then given. The results of this research are expected to be considered by e-learning in XYZ agency developers and providers

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