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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 83 Documents
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Implementation of Naïve Bayes Method with Certainty Factor for Disease and Pest Diagnosis on Onion Plants
Journal of Advances in Information Systems and Technology Vol 4 No 2 (2022): October
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v4i2.61189

Abstract

Shallots can be regarded as non-substituted, which is a plant that is used as a food seasoning and herbal medicine. Every year, the demand for shallots is increasing. But along with the ever-increasing demand, it is inversely proportional to the lack of availability. The cause of this is the lack of knowledge about shallot cultivation, including pest and disease disturbances. The purpose of this research is to help farmers diagnose early diseases and pests that attack shallot plants. With the presence of these pests and diseases, a system that contains knowledge from an expert is needed to diagnose early symptoms experienced by plants. In this study, the authors created an expert system for the diagnosis of diseases and pests on shallot plants. Researchers used the Naïve Bayes method as a classification method for each selected symptom. Then the Certainty Factor as a method of determining the value of confidence in the diagnosis results in the first method. In this study, it produced an accuracy rate of 97%.
Factor Analysis of Continuance Intention to Use QR Code Mobile Payment Services: An Extended Expectation-Confirmation Model (ECM)
Journal of Advances in Information Systems and Technology Vol 4 No 2 (2022): October
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v4i2.61468

Abstract

QR code mobile payment is a payment method that is quite popular in Indonesia where users only need to open or display a QR code on the m-payment application when making transactions. Users can make payments easily, anywhere and anytime. Apart from the benefits of QR codes on m-payments, there are still obstacles regarding the intention to continue using them. Some users stopped using the QR code service on the m-payment application due to the potential risks involved. The purpose of this study is to find out what factors can affect continued intention to use QR code m-payment. The research model used is the Extended Expectation-Confirmation Model (ECM) by combining ECM and UTAUT and adding trust and perceived risk variables. The number of samples in this study was 313 participants who were users who had used QR code m-payment OVO, GoPay, or ShopeePay with a minimum age of 17 years. The sampling technique used is purposive sampling. This study uses quantitative methods and data analysis with the PLS-SEM approach using SmartPLS version 3. The results of this study are three rejected hypotheses and nine accepted hypotheses. Based on the accepted hypotheses, it shows that social influence, trust, and satisfaction affect continuance intention to use QR code m-payment. Social influence is the biggest factor affecting continuance intention to use QR code m-payment service. These results can be considered for developers and companies such as OVO, GoPay, and ShopeePay.
Electric Vehicle Routing Problem with Fuzzy Time Windows using Genetic Algorithm and Tabu Search
Journal of Advances in Information Systems and Technology Vol 4 No 2 (2022): October
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v4i2.62314

Abstract

The distribution of goods becomes a very calculated thing in the economic aspect, especially in the case of wide and complex distribution. The greater the range of distribution of goods, the more precise, fast, and accurate calculations are needed. Specifically, the calculation of the distribution required starts from mileage, total travel time, customer satisfaction level based on customer time windows, and operational costs. Vehicle Routing Problem (VRP) is a solution to the problem of distributing goods from the depot to its customers. This study aims to determine the optimal route. The methods used for VRP optimization are the Genetic Algorithm (GA) and Tabu Search (TS) methods. Fuzzy logic is used to provide leeway on the limitations of the time windows parameters, thus providing a time tolerance in the event of early arrival of the vehicle or delay in delivery. Data processing using the GA-TS combination was carried out as many as two types of trials, namely trials with the same dataset ten times and trials with various types of datasets ten times. The results of the first trial fitness value on E-VRPFTW average increased by 14.39% compared to the results of the E-VRPTW fitness value that did not use fuzzy. The results of the second trial also experienced an average increase of 8.49% compared to the results of the E-VRPTW fitness value that did not use fuzzy. Therefore, the addition of fuzzy logic has an effect in determining the optimum route of E-VRPTW.
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.

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