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TEPIAN
Published by Politeknik Pertanian Negeri Samarinda
ISSN : 27215350     EISSN : 27215369     DOI : -
Core Subject : Science,
Computer Science & IT
The purpose of TEPIAN is to publish original research studies directly relevant to computer science. TEPIAN encompasses the full spectrum of information technology and computer science, including information system, hardware technology, intelligent system, and multimedia applications. TEPIAN welcomes original papers, reviews and commentaries. Suggestions for special issues covering selected topics may be considered. TEPIAN is devoted to publish manuscripts that advance the knowledge of information technology and communication beyond state-of-the-art. Authors may contact the Editor-in-Chief in advance to inquire about whether their research topic is suitable for consideration by TEPIAN. Through an Open Access publishing model, TEPIAN provides an important forum where computer science researchers in academic, public and private arenas can present the latest results from research on information technology and communication in a broad sense.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 225 Documents
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Internet of Things in Greenhouse Cultivation of Chrysanthemum Flowers in Primadona Tomohon Farmers Group Milytia Christabella Tumengkol; Kofal Hilkiah Lasewa; Jarot S Suroso
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3438

Abstract

The application of the Internet of Things (IoT) in greenhouses provides innovative solutions to enhance the efficiency and quality of chrysanthemum cultivation for the Primadona farmer’s group in Tomohon. The application of the automated system created is a condensation system that activates when the average temperature inside the greenhouse reaches 28 °C during the vegetative phase and 23°C during the generative phase, a drip irrigation system that turns on automatically when the average soil moisture value reaches 50%, as well as UV lights and exhaust fans that operate at night. The application of IoT also enables farmers to monitor and control greenhouse climate conditions in real-time using the Blynk application. The research method employed is experimental, incorporating a literature study to understand the application of IoT in greenhouses for chrysanthemum cultivation, as well as analysis of hardware and software requirements, system design, and system testing for real-world operations. The evaluation of the results provides insights into the effectiveness of IoT implementation in greenhouses for chrysanthemum cultivation, particularly for the Primadona Tomohon farmer group.
Online Shopping Experience in Minimarket and The Impact on Sales Figure Christopher Winson Budiman; Alfa Ryano Yohannis
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3445

Abstract

The rise of digital technology has transformed consumer shopping behavior, with online shopping emerging as a dominant force in retail. This study investigates the online shopping experience in minimarkets, a segment traditionally reliant on in-person transactions and explores its impact on sales figures. As consumer preferences increasingly shift towards convenience and accessibility, minimarkets must adapt to integrate online platforms that cater to these demands. This research employs a mixed-methods approach, combining quantitative analysis of sales data from selected minimarkets with qualitative insights gathered through customer surveys and interviews. Key findings reveal that the online shopping experience significantly influences customer satisfaction and purchasing behavior in minimarkets. Factors such as website usability, product variety, delivery options, and customer service quality are found to be critical determinants of the online shopping experience. Additionally, the study highlights that effective online engagement strategies such as personalized promotions, user-friendly interfaces, and responsive customer support can lead to increased customer loyalty, higher average order values, and improved overall sales performance. The research further demonstrates that the integration of online shopping platforms not only complements traditional brick-and-mortar operations but also attracts new customer segments who prioritize convenience and accessibility. In particular, the ability to shop online allows minimarkets to capitalize on trends such as click-and-collect services and home delivery, which have gained traction during the COVID-19 pandemic and continue to shape consumer expectations. Furthermore, the analysis reveals a direct correlation between enhanced online shopping experiences and improved sales figures, suggesting that minimarkets that invest in their digital presence can achieve significant competitive advantages in a rapidly evolving retail landscape. This paper contributes to the growing body of literature on online retailing by providing empirical evidence on the effectiveness of online shopping experiences in small-format retail environments. It offers actionable insights for minimarket managers and stakeholders looking to optimize their online platforms, enhance customer engagement, and ultimately drive sales growth. The findings emphasize the necessity for minimarkets to embrace digital transformation as an integral component of their business strategy to remain relevant and competitive in today’s consumer-driven market
The Implementation of Cloud Technology for Collaboration and Data Management in Property Developers Maria Veronika; Alfa Ryano Yohannis
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3448

Abstract

This study explores the impact of cloud technology implementation on collaboration, data management, and information security within a property development company. Prior to the implementation, the company faced significant challenges, including fragmented data storage, limited cross-team collaboration, and inadequate data security measures. Through a case study approach, this research analyzes the transition from a fragmented system to a centralized cloud infrastructure. The findings indicate that cloud adoption improved real-time collaboration across dispersed teams, reduced data duplication by 30%, and enhanced data security through role-based access control and encryption. Additionally, the centralized data storage system improved the accuracy of project information and sped up decision-making processes by 25%. The research also highlights how cloud technology helped the company meet compliance standards like ISO 27001 while enhancing operational efficiency. This study contributes valuable insights into how cloud solutions can streamline operations in complex industries like property development, emphasizing the need for continuous adaptation of technological solutions to meet evolving business demands.
Enhancing Business Intelligence with Explainable AI: Evaluating Transparency, Interpretability, and User Trust Aji Jayaloka; Alfa Ryano Yohannis
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3462

Abstract

The integration of Artificial Intelligence (AI) into Business Intelligence (BI) systems has significantly advanced data analysis and decision-making capabilities. However, the inherent "black box" nature of many sophisticated AI models poses considerable challenges to transparency, interpretability, and user trust, hindering their full adoption in critical business contexts. Explainable AI (XAI) emerges as a crucial field to address these challenges by rendering AI decision-making processes understandable and verifiable. This paper investigates the impact of different XAI methodologies on transparency, interpretability, and user trust within BI systems through a mixed-methods study. We specifically evaluate the effectiveness of feature importance techniques (LIME, SHAP) and rule extraction methods (Decision Tree Surrogates) in enhancing user understanding and confidence when interacting with an AI-driven BI prototype focused on customer churn prediction. Our findings reveal that while a baseline black-box model achieved high predictive accuracy, XAI-enhanced scenarios significantly improved user trust and perceived interpretability. Notably, a Decision Tree Surrogate model achieved the best balance between explainability, user trust, and decision accuracy. This research provides empirical insights into tailoring XAI explanations for varying user needs in BI, offering guidelines for integrating XAI to build more ethical, transparent, and trustworthy BI solutions, ultimately fostering greater user acceptance and more informed decision-making.
A Business Architecture Framework for Streamlining Post-Production Workflows in the Film Industry Wilson; Alfa Ryano Yohannis; Erick Dazki
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3483

Abstract

The post-production phase of filmmaking is a complex sequence of activities that directly impacts artistic quality, cost-efficiency, and time-to-market. Despite advancements in editing suites and asset repositories, many studios face fragmented systems, manual bottlenecks, and version-control conflicts. This paper presents a comprehensive Business Architecture framework, modeled using ArchiMate and aligned with the TOGAF Architecture Development Method (ADM), to transform post-production into an integrated, transparent ecosystem. We systematically map the current ("as-is") and envisioned ("to-be") states across business, application, and technology layers to identify critical inefficiencies, such as redundancy in asset handling and gaps in process standardization. Key recommendations, derived directly from this architectural analysis, include deploying a cloud-based Digital Asset Management (DAM) solution, instituting standardized handoff and approval workflows, and embedding granular metadata strategies to enhance searchability. These targeted interventions not only streamline collaboration and minimize manual rework but also accelerate overall delivery timelines. By systematically applying a robust enterprise architecture framework to a creative industry often characterized by ad-hoc solutions, this research provides a practical blueprint for studios to achieve sustained operational excellence and strategic agility.
Implementation Augmented Reality for Campus Building Visualization at Politeknik Pertanian Negeri Samarinda Muh. Unicon Riski Yahrib; Syafei Karim; Bagus Satria; Suci Ramadhani
TEPIAN Vol. 7 No. 1 (2026): March 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i1.3289

Abstract

This study aims to develop and implement a marker-based Augmented Reality (AR) application for visualizing campus buildings at Politeknik Pertanian Negeri Samarinda. The application, built using Unity 3D and Vuforia SDK, enables users to scan physical markers on buildings to display interactive 3D models and access detailed information about each facility. The research follows the Multimedia Development Life Cycle method, encompassing stages of concept, design, material collection, assembly, testing, and distribution. Technical testing evaluated the application’s performance across three Android devices, assessing marker detection range (0.5–3 meters), lighting conditions (optimal at 500–100,000 lux), and functionality (100% success in black-box testing). User Acceptance Testing (UAT) involved 30 respondents (new students) and yielded an average score of 4.245 out of 5, indicating high satisfaction. The results demonstrate that the AR application effectively enhances campus navigation and engagement, with marker-based tracking proving reliable for precise object visualization. This project contributes to the adoption of AR technology in educational institutions for promotional and orientation purposes.
Advertising Business Processes through Data-Driven Enterprise Architecture: A Conceptual Model of PT Akuratman Mario Sutardiman; Richardus Eko Indrajit; Erick Dazki
TEPIAN Vol. 7 No. 1 (2026): March 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i1.3390

Abstract

The advertising industry is undergoing a profound transformation driven by rapid advancements in data analytics, digital infrastructure, and artificial intelligence. Traditional marketing methods, which once relied heavily on intuition and generalized audience segmentation, are now being replaced by hyper-targeted strategies that utilize real-time insights to deliver more effective and measurable outcomes. This paper presents a conceptual study aimed at designing and optimizing business processes within PT Akuratman, a fictional digital advertising agency that adopts a data-driven operational model. Using the ArchiMate enterprise architecture framework, the study structures and analyzes four core revenue streams: Campaign Management Fees, Leads-Based Pricing, Technology Licensing, and Performance-Based Advertising. Each stream is examined through a multi-layered integration of business functions, application systems, and supporting technological infrastructure. The proposed architecture leverages cloud platforms, AI-driven analytics, and scalable data pipelines to support real-time decision-making, campaign personalization, and strategic agility. The model not only enhances operational efficiency but also reinforces client engagement and marketing ROI in a competitive digital environment. Furthermore, it serves as a practical reference for industry practitioners and scholars aiming to align enterprise architecture with emerging technological innovations. The study also suggests potential areas for future research, including adaptive architecture evolution, automation strategies, and regulatory considerations in big data ecosystems.
Behavior-Driven Gamification Framework for Enhancing Health Insurance Engagement Using TOGAF-Based Business Architecture Dyah Ayu Arditya; Richardus Eko Indrajit; Erick Dazki
TEPIAN Vol. 7 No. 1 (2026): March 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i1.3436

Abstract

Health insurance providers face significant challenges in engaging policyholders and encouraging preventive health behaviors. Traditional engagement methods often lead to low participation, reducing the effectiveness of wellness programs and increasing long-term healthcare costs. This paper presents a behavior-driven gamification framework designed to enhance policyholder engagement within the health insurance sector, utilizing a TOGAF-based business architecture approach. By integrating the principles of behavioral science with game mechanics, this model aims to motivate policyholders to actively participate in their health management through personalized, interactive experiences. The application of TOGAF’s Architecture Development Method (ADM) ensures that the gamification framework    is aligned with business objectives, operational processes, and technological infrastructure, providing a sustainable and scalable solution for health insurers. The proposed framework enhances customer engagement, improves health outcomes, and reduces operational costs by incentivizing healthy behaviors, fostering a more proactive and satisfied customer base. This research contributes to the growing field of digital health innovation and offers a strategic roadmap for integrating gamification within health insurance systems.  
Decision Support System for Soil Suitability of Banana Cultivation in Banyuwangi using Decision Tree Algorithm Mohamad Aji Hermansya; Diah Rita Nurholifah; Wahyu Rizqi Amalia; Eka Mistiko Rini; Dianni Yusuf
TEPIAN Vol. 7 No. 1 (2026): March 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i1.3451

Abstract

Banana plants (Musa paradisiaca) are among the leading agricultural commodities in Banyuwangi Regency and have long played an essential role in supporting the local economy. However, in recent years, the productivity of banana plantations has experienced a significant decline. This decrease is closely related to unsuitable soil conditions, including excessive moisture, unstable temperature fluctuations, and extreme soil acidity (pH). Such unfavorable conditions create challenges for farmers, who often find it difficult to evaluate soil characteristics accurately. As a result, cultivation strategies become less effective and crop yields fail to reach their optimal potential. To address this problem, this study developed a web-based Decision Support System (DSS) designed specifically for assessing soil suitability for banana cultivation. The DSS applies the Decision Tree algorithm to classify soil conditions based on three key parameters: moisture, temperature, and pH. The system development process followed the Rapid Application Development (RAD) methodology, which emphasizes iterative prototyping and active participation of farmers, ensuring that the solution is practical and aligned with real-world field needs. Validation of the system was carried out through Black Box Testing and model evaluation, which produced an accuracy rate of 70.9% in classifying soil suitability. The DSS not only passed all functional tests but also generated practical recommendations for soil management strategies aimed at improving crop conditions. Ultimately, this research contributes a reliable, user-friendly, and farmer-oriented tool to support sustainable banana cultivation in Banyuwangi, with the potential to enhance productivity and strengthen decision-making capacity.
Impact of Ease of Use, Usefulness, Attitude, and Trust on AI Adoption Intentions in Higher Education Erwin Margatama; Galih Yudha Saputra; Celine Aloyshima Haris
TEPIAN Vol. 7 No. 1 (2026): March 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3485

Abstract

The integration of Artificial Intelligence (AI) in higher education has attracted increasing attention, particularly in computer education. However, students’ acceptance of AI is influenced by several factors that require further investigation. This study aims to examine the effect of perceived ease of use, perceived usefulness, attitude, and trust on the utilization of AI in learning activities among computer education students. A quantitative approach was employed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with data collected from undergraduate students. The findings reveal that ease of use and usefulness significantly influence students’ attitudes toward AI, while trust plays a crucial role in shaping both attitudes and actual utilization. Furthermore, attitude is confirmed as a mediating variable that strengthens the relationship between ease of use, usefulness, trust, and the adoption of AI tools in learning. These results provide empirical support for the Technology Acceptance Model (TAM) and extend it by incorporating trust as an additional construct, offering new insights into AI adoption in higher education. The study highlights both theoretical contributions and practical implications for educators, particularly in the Indonesian context, to integrate AI effectively into learning environments.

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