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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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Unlocking the Influence of Digital Marketing Strategies on Startup Performance: A Case Study in Bangladesh Kabir, Md. Rishad
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.994

Abstract

This study investigates the impact of different digital marketing tools on the growth and sustainability of startups in Rangpur City, Bangladesh. With the proliferation of digital technology, entrepreneurs in Rangpur are increasingly employing strategies such as social media marketing, search engine optimization (SEO), e-mail marketing, and social networking to augment their exposure and compete in local and global markets. The research aims to analyze different digital marketing methods, and identify challenges that impacts on business performance in Rangpur city. A survey of 132 startup entrepreneurs and business professionals indicates that digital marketing, mainly social media marketing and social networking, substantially impacts business success by explaining 75.3% of the variance in performance outcomes. The findings suggest enterprises with less than 10 years of Operation should emphasize digital marketing specifically social media marketing to leverage the expanding digital trend, particularly in the restaurant, retail, and textile industries. Despite its diminished effectiveness, e-mail marketing continues to be a technique that warrants optimization. The findings offer substantial insights for entrepreneurs, marketers, and policymakers, emphasizing the essential function of digital marketing in facilitating corporate growth and economic development in emerging countries like Bangladesh. This study contributes to the existing literature by highlighting the importance of digital marketing tools for startups in growing regions like Rangpur City. It provides practical recommendations for enhancing digital marketing tactics to promote business success and growth.
Exploring the Impact of IoT and Blockchain on Supply Chain Management in Developing Countries Rafifing, Neo; Mabina, Alton; Rafifing, Leatile W.; Mosinki, Joyce; Mphale, Ofaletse
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.997

Abstract

The rapid development of the Fourth Industrial Revolution is having diverse effects on underdeveloped nations, influencing them in various ways. Developed countries have an advantage over underdeveloped countries since they embraced industrialization earlier, widening the gap between them. This comprehensive survey paper examines the multifaceted landscape of industry 4.0 in supply chain, shedding light on the potential challenges and key value drivers in the context of a developing country. Findings revealed that inadequate digital infrastructure, limited access to electricity, and a shortage of skilled workforce are the primary challenges faced by developing countries in the supply chain domain. The study systematically examines industry 4.0 technologies and indicates a 20-30% improvement in supply chain efficiency through the adoption of key technologies like IoT, AI, and blockchain. The study concludes by offering future research on industry 4.0 in supply chain management. The study results are assumed to offer insightful information to supply chain managers in developing countries, by enabling them with a deeper understanding of the major challenges and key drivers involved in integrating Industry 4.0 in their organizations and network.
Impact Assessment of Digital Learning Tools in South African Higher Education Esan, Dorcas Oladayo; Masombuka, Themba
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.999

Abstract

Technological advancements have significantly reshaped the operational landscape of tertiary institutions, enhancing both student and academic efficiency processes. In South Africa, many students in higher learning institutions scrambled to use technology for teaching and learning due to load shedding, poor internet connectivity, lack of technological skills, lack of technology training by the tertiary institutions, etc. This study employs the UTAUT to understand better how technological innovations impact South African higher institutions. The UTAUT model includes components such as effort expectancy, self-awareness, social influence, facilitating conditions, and voluntary use to fully understand the factors influencing technology development and adoption. Three hundred and ten (N=310) students from underprivileged tertiary institutions in the Eastern Cape participated in this study. The study used a quantitative research methodology based on a 5-point Likert scale to gauge the respondents' intention to use technology for teaching and learning. Regression analysis and NOVA statistical tools were used to analyse the acquired data. The findings revealed that most participating students believe that technological advancements had a positive impact on their ability to teach and learn. The research findings imply that faculty should implement training programs on digital tools, improve IT infrastructure, provision of free internet bundles, and develop policies that support the adoption of e-learning technologies.
The Influence of Presidential Debate Comment Sentiment on YouTube on Candidate Electability: Naïve Bayes and Pearson Analysis Manoppo, Arnoldus Yitzhak Petra; Istiono, Wirawan
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1001

Abstract

Campaigns significantly influence candidate electability. Presidential debates, a key campaign strategy, generate extensive public comments on social media, reflecting voter sentiment. This study employs VADER for automated sentiment labeling and Naïve Bayes for classification, analyzing comments from the KPU and Najwa Shihab YouTube channels. Electability data were sourced from national survey reports for correlation analysis. Pearson correlation results indicate that positive sentiment has a moderate negative correlation with electability, while negative sentiment shows a strong positive correlation. This suggests that negative sentiment in YouTube comments is more indicative of a candidate’s rising electability, whereas positive sentiment does not necessarily translate into increased support. The Naïve Bayes model achieved 65% accuracy, 59% precision, 57% recall, and 57% F1-score when including neutral comments. Excluding neutral comments improved accuracy to 77%, with 68% precision, 68% recall, and 67% F1-score. The dataset comprised 17,872 comments, ensuring a robust sample. Despite these findings, limitations exist, such as potential biases in sentiment classification and representativeness, as social media users may not fully reflect the general voting population. Furthermore, while correlation is established, causality remains uncertain, requiring further research. This study enhances the understanding of social media sentiment in political campaigns and highlights the importance of integrating online sentiment analysis with traditional polling methods for a comprehensive assessment of electability.
Traffic Violation Clustering Using K-Medoids and Word Cloud Visualization S, Muhammad Sabri; Utami, Ema
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1002

Abstract

Traffic is the space for people to move around, including both drivers and pedestrians. According to data from the Central Statistics Agency in 2020, the number of motor vehicles in Makassar City was recorded by type: 248,682 passenger cars, 17,501 buses, 85,968 trucks, and 1,338,306 motorcycles, with a tendency for an increase in the following year. The high number of vehicle users can certainly affect the rising traffic violation rates on the road. This study aims to classify traffic violation types in Makassar City by utilizing the K-Medoids algorithm and to visualize the clustering results using Word Cloud, which is expected to provide information related to patterns of traffic violation clusters. This study uses a case study from the Traffic Police Department of Makassar City in 2021, with a total of 5,893 traffic violation cases. The data used is ticket data consisting of article and vehicle type features. The clustering results show that motorcycles and minibuses are the most frequently involved in traffic violations. Motorcycles (R2) are not only dominated by violations related to the use of standard SNI helmets but also significantly involved in violations related to incomplete requirements and the possession of SIM/STNK (Driver's License/Vehicle Registration) and failing to meet roadworthiness standards such as mirrors, headlights, horns, etc. Passenger vehicles, especially minibuses and cars, also dominate traffic violations. The violations involve not only the use of seat belts for R4 vehicles but also violations such as not having complete STNK, not being able to show SIM, failing to display the Vehicle Registration Mark (TKB), and others. The results of this study demonstrate that the clustering obtained is very strong, as evidenced by the high Silhouette Score of 0.867 at k = 9.
A Model for Digitization Success in Ugandan TVETs: Evaluation Through Structured Walkthroughs and Simulation Muinda, Patrick Emmanuel; Basaza-Ejiri, Annabella Habinka; Maiga, Gilbert; Mayoka, Kituyi
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1004

Abstract

This study proposes an information systems model to enhance the success of digitization projects in Ugandan Technical and Vocational Education and Training (TVET) institutions. The research was based on agency theory, with additional insights drawn from the DeLone and McLean Information Systems Success Model and the Dynamic Capabilities Framework. The model was developed based on key constructs such as Communication, Task Programmability, Goal Conflict, Shirking, and Process Quality. To evaluate its effectiveness, a structured walkthrough was conducted using a prototype simulator (SimPro), where expert evaluators assessed its usability, completeness, and performance. Results indicate that 96% of experts rated the model as highly usable, while 92% agreed that it accurately represents key digitization principles. The model’s usability significantly influenced expert recommendations for adoption (Spearman’s rho = 0.457, p = 0.001). Based on expert feedback, refinements were made to enhance stakeholder engagement, accountability tracking, and task efficiency. These findings suggest that the model has strong potential to improve digitization success rates by enhancing stakeholder engagement, accountability tracking, and task efficiency. Expert evaluators confirmed that these factors are critical to successful digitization in TVETs, indicating that structured implementation of this model could lead to more effective digitization outcomes. However, further empirical validation through real-world implementation is recommended to measure long-term impact.
Exploring the Determinants of Advanced Big Data Analytics Adoption in Zimbabwe’s Telecom Sector: A TOE Framework Analysis Ngwendere, Jethro Simbarashe; Mlitwa, Nhlanhla
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1008

Abstract

The way in which organisations conduct business has been revolutionised by Big Data Analytics (BDA). Several organisations have experienced improved productivity and effectiveness from the insights resulting from BDA which in turn impacts economic development. The adoption and use of BDA in the Zimbabwean telecommunication industry was limited. The aim of the research was to identify the factors limiting the adoption and usage of BDA within the Zimbabwean telecommunications industry. The objective of the research was therefore to pinpoint impediments which would then inform recommendations to improve the adoption and use of BDA in the Zimbabwean telecommunications industry. The study adopted critical realism and the Technology Organisation Environment (TOE) framework to identify the causal forces limiting the adoption and use of BDA. The findings indicate that IT infrastructure, service quality, senior management support, skills and expertise, financing, government policy, and economic conditions are the primary factors affecting BDA adoption.
A Comparative Study of Drug Prediction Models using KNN, SVM, and Random Forest Purba, Susi Eva Maria
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1013

Abstract

Accurate drug classification is essential in medical decision-making to ensure patients receive appropriate prescriptions based on their physiological and biochemical characteristics. This study compares the performance of K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest models in predicting drug prescriptions using patient attributes such as age, sex, blood pressure, cholesterol level, and sodium-to-potassium ratio. The dataset, obtained from Kaggle, was preprocessed and split into training and testing sets to evaluate model performance using accuracy as the primary metric. The results indicate that Random Forest outperformed KNN and SVM, achieving a perfect test accuracy of 100%, demonstrating superior generalization and robustness. SVM also performed well, with a test accuracy of 97.50%, while KNN achieved the lowest accuracy of 70%, indicating its limitations in handling complex feature interactions. These findings highlight the effectiveness of ensemble learning methods in medical classification tasks, suggesting that Random Forest is the most suitable model for drug prediction. Furthermore, the potential applications of these findings in clinical settings could enhance treatment outcomes and patient care. Future research should explore feature engineering techniques, larger datasets, and additional machine learning approaches to enhance predictive accuracy and applicability in real-world healthcare settings.
The Impact of Artificial Intelligence (AI) for Transforming Tourism Marketing on the USA Industry Practices Abid, Raghib; Saha, Palash; Islam, Md. Mominul
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1016

Abstract

This study explores the transformative role of Artificial Intelligence (AI) in tourism marketing, highlighting its ability to enhance personalization, operational efficiency, and consumer engagement. The objective is to bridge the gap between theoretical capabilities and practical applications of AI in the USA tourism marketing. The methodology employs a PRISMA-based approach, focusing on recent studies from 2020 onward to analyze AI’s impact on marketing practices. A thorough examination of 389 publications obtained from databases like Scopus, Google Scholar, and Scimago for detailed qualitative analysis. The key contribution of this paper lies in its structural approach, which discuss the potential of various AI tools such as tailored recommendations and AI chatbots etc., offering fresh insights on their influence on the American Tourism Marketing sector. The report presents a framework for assessing the impact of AI on customer satisfaction and productivity, providing pragmatic solutions for tourism enterprises. In near future AI will develop enhancing human critical thinking and converting human cognition capabilities.
BlueHarvest: Enhancing Indonesian Aquaculture with a Market-Driven UI/UX Design Dermawan, Andi; Aziza, Rifda Faticha Alfa
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1017

Abstract

This research aims to design the user interface (UI) and user experience (UX) of an aquaculture marketplace application to improve the promotion and marketing of Indonesian fishery products through an application called “BlueHarvest”. Using the double diamond method, this research explored the needs of expert and non-expert users in the field of aquaculture to create an attractive and intuitive solution. The research started with surveys and interviews to collect in-depth data visualized in empathy maps and user journeys, which revealed key user-centric features such as a dynamic price dashboard to know real-time market trends, a pond monitoring system to help fishermen and buyers, and offering articles on aquaculture as well as aquaculture product recommendations. Usability testing results showed that the app design was generally easy to understand, although there were some suggestions to improve the icons, layout and search filter features. These findings indicate that the applied design approach successfully built a solid user experience foundation, although further refinements are needed for optimal usability.

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