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Digitus : Journal of Computer Science Applications
Published by PT Penerbit Ilmiah Indonesia
ISSN : -     EISSN : 30313244     DOI : https://doi.org/10.61978/digitus
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Digitus : Journal of Computer Science Applications with ISSN Number 3031-3244 (Online) published by Indonesian Scientific Publication, is a leading peer-reviewed open-access journal. Since its establishment, Digitus has been dedicated to publishing high-quality research articles, technical papers, conceptual works, and case studies that undergo a rigorous peer-review process, ensuring the highest standards of academic integrity. Published with a focus on advancing knowledge and innovation in computer science applications, Digitus highlights the practical implementation of computer science theories to solve real-world problems. The journal provides a platform for academics, researchers, practitioners, and technology professionals to share insights, discoveries, and advancements in the field of computer science. With a commitment to fostering interdisciplinary approaches and technology-driven solutions, the journal aligns itself with global challenges and contemporary technological trends.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 2 (2024): April 2024" : 5 Documents clear
Impact Marketing Techniques: Instagram, WhatsApp, and Consumer Predisposition Acquire Prepared Foods Diantoro, Karno; Sinar, Corizon; Rinaldo; Rohman, Abdur
Digitus : Journal of Computer Science Applications Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i2.258

Abstract

With the growth of social media and messaging platforms, businesses are investigating new marketing methods to reach and impact consumer behavior. This study investigates the effect of marketing strategies on Instagram and WhatsApp on consumers' inclination to buy prepared, home-cooked meals. It looks into how companies use these platforms' interactive and visual elements to market their products and influence customer choices. The research examines consumer surveys and marketing initiatives data to identify the primary drivers of engagement and buy intentions. It investigates how direct messaging, targeted advertising, and influencer marketing affect customer attitudes and decision-making. The study also explores the ethical issues of these marketing strategies and how they may affect consumers' privacy and autonomy.  This research intends to increase awareness about responsible practices that respect consumer interests while guiding firms in optimizing their methods by offering insights into the efficacy of social media and messaging app marketing strategies. The results add to the growing conversation about how digital marketing impacts food consumption habits and how consumer-business relationships are changing.
Internet of Things-Based Bus and Student Monitoring System on Free School Transportation Madiun City Rosyadi, Arfian Dwiki; Puspaningrum, Lintang Diah; Hakimi, Musawer
Digitus : Journal of Computer Science Applications Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i2.464

Abstract

Traffic incidents and violations, particularly among students, pose safety concerns for parents and authorities. To address this issue, the Madiun City Government introduced the Free School Transport program through the Madiun City Transportation Office, providing school buses for students in Madiun City. However, despite this initiative, students and parents face challenges tracking bus arrivals due to weather conditions, traffic congestion, and schedule delays. This study proposes developing MASBUS, an Internet of Things (IoT)-based monitoring system for real-time school bus tracking. The system integrates a GPS module for location tracking and an RFID module for student identification. Data is transmitted via NodeMCU ESP8266 to a web server, stored in a MySQL database, and accessed through an Android application. The MASBUS app provides real-time location updates and sends automatic notifications when students board or leave the bus. The implementation of this system enhances student safety, improves transportation efficiency, and enables real-time monitoring for parents and school authorities. MASBUS contributes to a smarter and safer school transportation system by offering a more transparent and reliable tracking solution.
Toward Data-Driven Health Transformation: Accessibility, Interpretability, and Institutional Readiness for AI Soderi, Ahmad
Digitus : Journal of Computer Science Applications Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i2.833

Abstract

Artificial intelligence (AI) and big data analytics are increasingly recognized as vital tools in transforming healthcare delivery, particularly within hospital settings. This narrative review aims to explore the challenges and opportunities associated with the implementation of these technologies in urban healthcare systems. Using literature obtained from Scopus, PubMed, and Google Scholar, the review employs keywords such as "AI in healthcare," "big data analytics," and "predictive analytics in medicine" to synthesize peer-reviewed studies that examine both theoretical and practical dimensions of AI adoption. The analysis reveals that while developed countries are more equipped with infrastructure and training, developing nations often face systemic challenges such as limited funding, inadequate technology, and insufficient regulatory support. Accessibility remains a key concern, with disparities in technological adoption driven by geographic, demographic, and institutional factors. Furthermore, the review identifies gaps in the interpretability and integration of AI tools, especially in infection management and clinical decision-making. The discussion emphasizes the need for adaptive policy interventions, targeted investments in healthcare training, and the development of transparent AI systems. The study also recommends enhancing cross-sector collaboration to build scalable and inclusive health innovations. In conclusion, addressing the structural, ethical, and educational dimensions of AI deployment is essential for realizing its full potential in global healthcare improvement.
Toward Equitable Digital Mental Health: Integrating AI and Telepsychiatry in Global Practice Algristian, Hafid; Sitorus, Anwar T
Digitus : Journal of Computer Science Applications Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i2.834

Abstract

In response to the growing mental health crisis and the expansion of digital healthcare, this narrative review explores the application of telepsychiatry and artificial intelligence (AI) in mental health services. The study aims to synthesize recent developments, challenges, and future directions in digital mental health innovation. A systematic literature search was conducted across PubMed, Scopus, and Web of Science databases, focusing on studies published between 2016 and 2023. Keywords such as "telepsychiatry," "mental health," "artificial intelligence," and "technology adoption" were used to identify relevant empirical and theoretical works. Inclusion criteria emphasized real-world applications and stakeholder perspectives. The results reveal substantial variability in the understanding and implementation of telepsychiatry across different regions and populations. Socioeconomic factors, digital literacy, and cultural perceptions significantly influence the acceptance and success of digital interventions. While AI-driven tools improve diagnostic efficiency and reduce treatment delays, systemic barriers such as regulatory limitations, institutional resistance, and data privacy concerns impede widespread adoption. Comparative analysis highlights a more favorable reception in high-income countries, though underserved populations in both developed and developing nations continue to face accessibility challenges. These findings underscore the urgent need for inclusive policies, capacity-building initiatives, and ethical AI governance frameworks. Addressing these factors can bridge existing gaps and ensure more equitable mental healthcare. The study concludes by emphasizing the importance of sustained interdisciplinary research to refine telepsychiatric models and promote socially responsible technology integration.
Balancing Cadence and Flow: Evaluating Agile Frameworks for Optimal Software Delivery Outcomes Yuni T, Veronika
Digitus : Journal of Computer Science Applications Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i2.950

Abstract

This study compares the impacts of Scrum and Kanban on software quality, team sustainability, and project predictability within Agile project management. As Agile adoption expands across industries, organizations face the challenge of selecting methods that fit their operational needs and team dynamics. By drawing on empirical case studies and literature, this research highlights the practical differences between Scrum’s cadence-based framework and Kanban’s flow-based model. A comparative analysis was conducted using data from major implementations (e.g., Adobe, John Deere, BBC Worldwide), supported by Agile maturity studies and academic evaluations. Metrics examined include defect reduction, cycle time, velocity stability, lead time, and team stress levels. Scrum demonstrated strong outcomes in early-stage quality improvement and structured delivery. Kanban, in contrast, offered stronger long-term flow consistency and fewer customer-reported defects. Furthermore, hybrid approaches such as Scrumban emerged as practical alternatives that balance predictability with adaptability. Results indicate that both frameworks yield significant benefits when implemented with high team autonomy and cultural alignment. While Scrum enhances predictability through time boxed sprints, Kanban facilitates flexibility and continuous delivery. The study highlights the critical role of implementation quality and Agile maturity in determining success. In conclusion, method choice should reflect organizational context, with growing support for hybrid adoption. This research provides actionable insights for Agile teams and decision makers seeking to align methodology with project goals, workforce dynamics, and customer expectations.

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