Journal of Information Systems and Informatics (Journal-ISI)
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Supplier Evaluation at Small-Medium Enterprise Using Simple Additive Weighting
Get PDFThis study focuses on the importance of information systems in today's intensely competitive business landscape. Companies of all sizes rely on information systems to stay afloat, streamline operations, and make informed decisions based on accurate data. To remain competitive, a medium-sized company specializing in vending motorcycle accessories and spare parts faced various challenges, including determining the best supplier for each item. To address this issue, a decision support system was developed using the Simple Additive Weighting technique. This method calculates the weighted sum of performance evaluations for each option based on all qualities. The system underwent user acceptance testing and achieved a flawless success rate of 100%. Overall, this study highlights the crucial role of decision support systems in enabling businesses to make strategic decisions based on accurate and reliable data
Sentiment Analysis of Raja Ampat Tourism Destination Using CRISP-DM: SVM, NBC, DT, and k-NN Algorithm
Get PDFThis study presents a sentiment analysis of tourists' opinions on Raja Ampat Tourism Destination using data mining techniques. The study collected data from Tripadvisor and processed it through sentiment classification. The algorithms used in the analysis were Support Vector Machine, Naive Bayes Classifier, Decision Tree, and k-Nearest Neighbor. The study followed the Cross-Industry Standard for Data Mining methodology and went through several stages such as business and data comprehension, data preparation and cleaning, feature selection, modeling, model evaluation, result presentation, deployment, and maintenance. The study's findings revealed that visitors generally had positive opinions about Raja Ampat's tourism attractions, particularly cultural diversity, and undersea beauty. The Decision Tree algorithm showed the highest accuracy value of 99.12%, precision of 98.96%, recall of 99.34%, AUC of 0.991, and f-measure of 99.13%. SVM also had excellent performance with an accuracy value of 100%, precision of 100%, recall of 100%, AUC of 1.000, and f-measure of 100%. The study concludes that Decision Tree and SVM, with the assistance of SMOTE operators, are the best algorithms for sentiment analysis in this context
Leveraging COBIT 2019 Framework to Implement IT Governance in Business Process Outsourcing Company
Get PDFThe company specializes in delivering information and technology services to businesses operating in the same industry. Recognizing the pivotal role of information technology in achieving its vision, mission, and goals, the company emphasizes the proper implementation of IT governance to drive overall company success. To evaluate the management of IT resources, the study employs the COBIT-2019 framework for measurement. The data collection approach encompasses interviews, questionnaires, observation, and document analysis. The findings indicate that most IT governance processes currently operate at level 2 capability. However, the company aspires to reach level 3 for these processes. Consequently, recommendations are proposed to enhance these processes based on the best practices outlined in COBIT-2019. Key suggestions include implementing performance measurements and facilitating access to knowledge repositories to foster skill and competency development
GoPrintBot: An Interactive E-Commerce for Online Printing Services
Get PDFGoPrintBot is an innovative endeavor focused on creating an interactive e-commerce chatbot tailored specifically for online printing services. The primary objective is to enhance the customer experience by offering a seamless and efficient ordering process, eliminating the need for customers to navigate complex websites or wait for customer service representatives. This study addresses common issues encountered in traditional e-commerce platforms, including unintuitive navigation, ineffective search and filter systems, and slow response times for customer inquiries. The proposed solution involves developing a chatbot system that will revolutionize the online printing industry, significantly improving the customer experience and operational efficiency. The methodology employed encompasses comprehensive requirements gathering, followed by the design and development of the chatbot system using established System Development Life Cycle (SDLC) methodologies. GoPrintBot serves as a prototype, showcasing the potential of chatbots to streamline the online printing process and provide personalized and efficient services. The findings of this study have significant implications for businesses that prioritize customer satisfaction and aim to optimize their online printing services
Point of Sales (POS) System Design using Design Thinking Framework for Motorcycle Workshop
Get PDFThe challenge of MSME business is the change of transaction systems from conventional to digital processes to minimize human error. This research offers an idea to identify problems, classify digital innovation ideas, analyze needs, and design management information systems Point of Sales (POS) modules in CV. Renaldi Motor. The method used in designing the management information system of the POS module of the OmO Jaya Workshop application is design thinking. The stages in this research consist of empathizing, defining, ideating, prototyping, and testing. The results of this study show that the problem faced by Micro, Small, and Medium Enterprises (MSMEs) workshop businesses is the process of recording transactions that still use conventional methods. Through the digital innovation of the POS module management information system in the form of the OmO Jaya workshop application. Through the application, a CV. Renaldi Motor is expected to optimize the digital transaction recording system and improve business performance. Thus, the risk of business losses due to human error can be minimized. In addition, the Blackbox test results show that the test results in each process have been successful and as expected. This study concluded that the Point of Sales (POS) System can improve CV. Renaldi Motor's business performance through digitizing the sales transaction recording process
Development of Logistics Driver Tenko System (ORIENT) Application Using Scrum Framework
Get PDFOccupational safety and health hold significant importance for both agencies and individuals alike. A crucial aspect of assessing driver readiness involves examining their physical well-being. Truck drivers who possess unhealthy physical conditions face a four-fold higher risk of work accidents compared to those with sound physical health. PT. Toyota Motor Manufacturing Indonesia (TMMIN), being a manufacturing company, must prioritize occupational safety and health, particularly within the logistics domain. Presently, some logistics partners collaborating with TMMIN adhere to their own standards when conducting checks, relying on paper records for documenting the results. Unfortunately, this approach hinders proper archiving of inspection records and fails to establish a direct link with logistics partner customers in cases involving drivers with health issues. Hence, PT. Toyota Motor Manufacturing Indonesia is dedicated to enhancing the quality of driver health checks through logistics partners by implementing an integrated recording system called the Logistics Driver Tenko System Application (ORIENT). The development of ORIENT is based on the Scrum framework. This research aims to offer insights into the direct implementation of the Scrum method in project development
Comparison of Naïve Bayes and Logistic Regression in Sentiment Analysis on Marketplace Reviews Using Rating-Based Labeling
Get PDFThis research focuses on sentiment analysis in the marketplace reviews in Google Play Store, a platform for downloading Android applications and providing reviews. Sentiment analysis is essential for understanding user responses to applications, particularly in the app marketplace. In this study, two machine learning algorithms, Naïve Bayes and Logistic Regression, are employed to classify user reviews. The application rating is used as a reference to determine the sentiment of each comment. The dataset is divided into two conditions: using 2 labels (positive & negative) and 3 labels (positive, neutral, & negative). The test results indicate that the highest performance is achieved by classifying with Logistic Regression on the Shopee dataset with 2 labels. The accuracy reaches 84.58%, precision reaches 84.66%, and recall reaches 84.63%. Additionally, the fastest processing time occurs when testing the Lazada 2-label dataset with Naïve Bayes, taking only 0.038 seconds. Overall, the research suggests that datasets with 2 labels tend to yield higher accuracy compared to datasets with 3 labels
Black Box Testing of Futsal Field Rental Information Systems Using Automated Testing Method
Get PDFA pivotal aspect of software development is testing, which serves as the final phase preceding the release of a software or information system. The realm of software testing encompasses a diverse array of methods, and within the scope of this investigation, the focus is on black box testing. In pursuit of this objective, the study leverages the capabilities of the Katalon Studio for Automated Testing. Its application is directed towards evaluating the functionality of an information system dedicated to the rental of futsal fields in the city of Singkawang. The essence of this examination lies in affirming the integrity of each feature and menu that constitutes the futsal field rental information system. This validation process is integral to ensuring that the system aligns seamlessly with the requisites of its users. The culmination of these testing endeavors culminates in the confirmation that the information system harmoniously resonates with user expectations. Consequently, it stands primed for implementation and subsequent release, signifying the attainment of a pivotal milestone in its development journey
Empowering Pregnancy Risk Assessment: A Web-Based Classification Framework with K-Means Clustering Enhanced Models
Get PDFThis study aims to determine whether there is an increase in accuracy results for predicting pregnancy risk with a classification algorithm that goes through and without going through the clustering stage. After that, compare which classification algorithm gets the best improvement. This study uses the K-Means clustering approach, as well as the SVM, Naive Bayes, and K-Nearest Neighbor (KNN) classification algorithms. The pregnancy risk dataset used comes from the UCI Machine Learning Repository. Evaluation metrics used include accuracy, precision, recall, and F1-score. The results of the study revealed that the K-Means model with KNN provided the highest performance compared to the other two, with an accuracy of 79.53% and an average F1-score of 0.8. The implementation of K-Means resulted in an increase in accuracy of 0.4%, 1.57%, and 2.76% on KNN, SVM, and Naive Bayes respectively, which confirms the impact of clustering in improving classification performance. The resulting model can be used in real-time via a website built using the Flask API, and offers tools that can help health practitioners to plan treatments effectively and minimize the risk of pregnancy
Assessment of Village Readiness for Electronic Citizen Complaint Services (e-AduMas) Using COBIT 4.1
Get PDFThe objective of this study is to investigate the implementation of the electronic community complaint service, known as e-AduMas, in villages utilizing SMS Gateway and GSM network technologies. The research aims to evaluate both the technological readiness of village offices using COBIT 4.1 and the community's acceptance of the e-AduMas system. The study employs a comprehensive research methodology that includes the analysis of community needs, the design of the e-AduMas system, the development of an integrated SMS Gateway application with the village government platform, and field testing involving active participation from the village community. Data will be collected through surveys, interviews, and observations to assess the level of implementation success, user response, and technical feasibility. The anticipated outcomes of this research include practical guidance for other villages looking to construct similar systems to enhance citizen participation in local governance. This study is poised to make a significant contribution to the application of technology in village governance, specifically in the development and utilization of the e-AduMas service. The findings of this research are expected to provide valuable insights for strengthening citizen engagement in local governance through innovative technological solutions