Article Per Year (5 Year)
p-Index From 2021 - 2026
3.619
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Economic, Bussines and Accounting (COSTING) Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) MOVE: Journal of Community Service and Engagement Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Community Service (IJCS) Bulletin of Social Informatics Theory and Application IIJSE International Transactions on Artificial Intelligence (ITALIC) Jurnal Teknologi dan Bisnis Cerdas
Dhimas Tribuana
Universitas Handayani Makassar
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 28 Documents
Search

 1   2   3 
PENERAPAN TEKNOLOGI WEB DALAM SISTEM PEMESANAN MAKANAN (FOOD ORDER SYSTEM) SISTEMATIC LITERATUR REVIEW Abel, Abel; Ahkas, Andi Suciana; Aziza, Nur; Wulan Dari, Rika; Mutmainnah, Mutmainnah; Tribuana, Dhimas
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.19

Abstract

The implementation of web technologies in food ordering systems has experienced rapid growth in recent years, driven by post-pandemic digital transformation, increasing internet usage, and the adoption of mobile devices. This study aims to conduct a Systematic Literature Review (SLR) to identify technological trends, innovations, and implementation challenges of web-based food ordering systems during the 2020–2025 period. Referring to the PRISMA 2020 guidelines, 20 scientific articles were selected from an initial set of 100 articles sourced from Scopus and Google Scholar. The findings reveal five main points: (1) digitalization of ordering systems can increase operational efficiency by up to 45%; (2) QR Code integration supports accessibility without requiring application installation; (3) the use of RESTful API architecture enables real-time connectivity between customer, kitchen, and cashier modules; (4) the adoption of payment gateways such as QRIS, Midtrans, and Xendit enhances transaction security; and (5) the utilization of artificial intelligence (AI) supports personalized menus and automated recommendations. Additionally, the study highlights several critical success factors, including data security through SSL/TLS encryption, cloud-based scalability, responsive interfaces using modern frameworks, and appropriate selection of development methodologies. Future research is recommended to explore digital inclusion, the social impacts on labor, and implementation strategies for MSMEs with limited technological and financial resources.
SISTEM BERBASIS WEB, MANAJEMEN TRANSPORTASI, DIGITALISASI, TINJAUAN LITERATUR SISTEMATIS Ramadhana, Sahru; Damayanti, Sisil; Berlian, Andi Fajar; Yunansi Bonsa, Putri; Masdar, Imelda; Tribuana, Dhimas
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.21

Abstract

The transportation industry is undergoing a major transformation with the development of digital technology. Challenges such as complex fleet management, dynamic routes, high operational costs, and customer demand for fast service have driven the emergence of Web-Based Transportation Management Systems (WBTMS). This study conducted a Systematic Literature Review (SLR) to analyze various studies discussing the implementation of WBTMS in the transportation sector. The SLR process was conducted following the PRISMA guidelines, which include the stages of identification, screening, feasibility assessment, and final selection of studies. Literature was collected through several major databases such as Scopus, IEEE Xplore, ScienceDirect, and Google Scholar, with publications reviewed from 2020 to 2025. The purpose of this study was to identify trends, benefits, challenges, and existing research gaps. The review results indicate that WBTMS can improve operational efficiency, transparency, and customer service quality. However, major challenges remain in the aspects of IT infrastructure, integration with legacy systems, and human resource readiness. This study provides recommendations for the transportation industry and academia to strengthen strategies for adopting web-based systems in the future.
IMPLEMENTASI WEB-BASED TRANSPORTATION MANAGEMENT SYSTEM DI INDUSTRI TRANSPORTASI : SYSTEMATIC LITERATURE REVIEW Nur Alifah, Alyah; Elsa, Elsa; Ahmadi, Muh. Taufiq; Rivaldi, Riksal; Tribuana, Dhimas
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.26

Abstract

This systematic literature review examines 20 publications from 2020 to 2025 addressing the implementation of web-based Transportation Management Systems (TMS) across various transport sectors. Our analysis identifies three major clusters: first, enhanced operational visibility and fleet tracking via web/cloud solutions; second, process optimization through system integration, automation, and log-based analytics; third, significant implementation challenges stemming from organizational readiness, legacy system integration, and web security concerns. The three clusters interact with each other, so the success of web-based TMS depends not only on technology, but also on human involvement, processes, and infrastructure. From a theoretical perspective, our findings suggest extending technology adoption frameworks (e.g., TOE) to include variables such as data interoperability, digital readiness, and data governance. In practical terms, companies should conduct a comprehensive data readiness assessment, plan system integration (such as API or ERP), manage organizational change, and implement robust web security before launching a web-based transportation management system (TMS). Additionally, implementing real-time analytics and process mining on TMS logs is essential for continuous improvement. This review is limited by the heterogeneity of publication types (academic journals, industry reports, implementation projects), the lack of long-term quantitative performance data, and the absence of cross-country comparative studies. Future research should pursue multi-industry longitudinal studies, systematically evaluate web-based TMS performance metrics, and investigate security and interoperability issues as core components of the modern digital transportation ecosystem.
OPTIMALISASI E-COMMERCE MELALUI TEKNOLOGI WEB MODERN Ramadhani, Asnia; Melni, Melni; Sahra, Nurkhafitri; Nabila, Alya; Tribuana, Dhimas
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.27

Abstract

This research aims to identify adoption trends, key benefits, and challenges in e-commerce optimization using modern web technologies such as Next.js, Laravel, Headless/Decoupled architecture, and Progressive Web Applications (PWA). The method used is a Systematic Literature Review (SLR) of academic publications from 2020 to 2025, with a comprehensive search across various scientific databases. The main results show a significant shift towards Headless/Decoupled Commerce, where Next.js is the dominant frontend framework and Laravel is the preferred backend. The implementation of these technologies consistently improves Core Web Vitals scores, data delivery efficiency, and SEO indexing, as well as increasing user engagement and retention on mobile through PWAs. Nevertheless, the challenges faced include initial development complexity, third-party integration, and a steep learning curve. In conclusion, the adoption of Headless Commerce with Next.js and PWA is an essential strategy to achieve competitive advantage in e-commerce business metrics.
PENGGUNAAN TEKNOLOGI WEB UNTUK SISTEM E-LEARNING ADAPTIF DI PENDIDIKAN: SYSTEMATIC LITERATURE REVIEW 2020–2025 Nurwafia, Andi; Sugiarti, Iin; Rahmadani, Nia; Rejeki, Sri; Tribuana, Dhimas
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.29

Abstract

This study aims to synthesize recent findings on the use of web technologies in adaptive e-learning systems in education and to identify the main research themes, benefits, and implementation challenges. The development of web technology has significantly influenced the evolution of e-learning systems, particularly in creating adaptive learning environments that cater to individual student needs. This study employs a Systematic Literature Review (SLR) guided by the PRISMA 2020 framework to analyze 40 relevant articles published between 2020 and 2025 The review identifies key themes, including web-based architectures, adaptive algorithms and personalization, learning analytics, user experience, and implementation and adoption challenges. The findings highlight that adaptive e-learning systems The findings indicate that adaptive e-learning systems can increase course completion and engagement by up to 40% and reduce learning time by around 30% while improving knowledge retention. However, challenges related to data privacy, infrastructure limitations, interoperability, and limited teacher training, as well as concerns about algorithmic transparency and ethics, remain significant barriers to widespread adoption. This study proposes a five-layer conceptual model that integrates technology infrastructure, data and intelligence components, pedagogical design, and user-centric interfaces to guide the development of effective adaptive e-learning systems.
IPFS Based Secure and Decentralized Web Architecture A Systematic Review Dhimas Tribuana; Apriani Sijabat; Titih Nursugiharti; Wijaya, Rizky Charles
APTISI Transactions on Management (ATM) Vol 10 No 1 (2026): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/4z339025

Abstract

The rapid development of digital technology has driven a transition from Web 2.0 to Web 3.0, where decentralization, user autonomy, and data security have become fundamental priorities. This transition introduces critical challenges in distributed systems, peer-to-peer networking, and security engineering, particularly concerning fault tolerance, data integrity, and resilience against centralized failures. Traditional centralized web architectures often suffer from single points of failure, making them vulnerable to cyberattacks and censorship. This study investigates the InterPlanetary File System (IPFS) as a content-addressed, peer-to-peer distributed storage architecture that enhances decentralized web infrastructures by enabling immutable data validation, node redundancy, and improved resistance to system-level attacks. This study adopts a Systematic Literature Review (SLR) approach to examine the application of IPFS in developing secure and decentralized websites within the Web 3.0 ecosystem. Following PRISMA-guided procedures, recent peer-reviewed studies are systematically analyzed to identify architectural patterns, security mechanisms, and system-level challenges associated with decentralized web hosting. The findings are synthesized to assess the implications of IPFS for data integrity, system resilience, and fault tolerance in distributed environments. These results lead to the conclusion that integrating IPFS into website development represents a strategic step toward creating a more transparent, resilient, and decentralized web ecosystem aligned with the core principles of Web 3.0.
AIoT Driven Smart Solar System for Real Time Predictive Sustainable Energy Management Indrawan, Rizki; Very, Eka Dawn; Tribuana, Dhimas; Nabila, Efa Ayu
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.968

Abstract

The rapid expansion of solar photovoltaic (PV) technologies has increased the demand for intelligent, adaptive, and data-driven energy management systems. However, conventional and IoT only solar infrastructures still face limitations, including inefficient energy distribution, delayed fault detection, and an inability to respond dynamically to fluctuating environmental conditions. This study proposes an AIoT-based Smart Solar System that integrates IoT-enabled sensing modules with artificial intelligence for real-time monitoring, predictive analytics, and autonomous control. The system employs a distributed architecture consisting of edge devices, cloud analytics, and machine learning models particularly Long Short-Term Memory (LSTM) networks and regression-based predictors to enhance forecasting accuracy and operational responsiveness. The objective of this research is to improve power utilization, predictive reliability, and maintenance efficiency within solar energy systems. Experimental results demonstrate a 22.8% increase in power utilization, a 17% reduction in maintenance downtime, and a forecasting accuracy of 95.2% (R2 = 0.952). These findings indicate that AIoT integration significantly enhances energy intelligence, system reliability, and sustainability. Overall, the proposed architecture establishes a scalable foundation for next generation renewable energy systems capable of self learning, adaptive optimization, and real-time decision making.
Explainable rice yield from Sentinel-1 and Sentinel-2 satellite data for food security Tribuana, Dhimas; Sattar, Usman; Mide, Baharuddin; Dayanti, Dayanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp615-627

Abstract

Reliable, explainable crop-yield estimates are essential for food-security planning in data-sparse regions. We present a transparent pipeline for district-level (regency) rice yield prediction in Indonesia that fuses Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 normalized difference vegetation index (NDVI), and weather/reanalysis features. The system standardizes inputs per province, fixes a 16-day temporal key, and uses a small, auditable ensemble of tree models (gradient boosting+light gradient-boosting machine (LightGBM)). Trained on ≤2023 data and evaluated on a 2024 temporal hold-out, a joint West Java ∪ South Sulawesi model achieves root mean square error (RMSE)≈0.80 t/ha, mean absolute error (MAE)≈0.48 t/ha, and R-squared (R²)≈0.33 at regency scale. Feature importances and Shapley additive explanations (SHAP) confirm that phenology (NDVI peak, integral, green-up/senescence), SAR backscatter (vertical transmit-vertical receive/vertical transmit-horizontal receive (VV/VH)), and wind/pressure are consistent drivers under monsoon conditions. The workflow supports routine, one-click provincial updates and produces parity maps and error bars for actionable diagnostics. These results demonstrate that combining Sentinel-1, Sentinel-2, and basic meteorology delivers accurate, interpretable, and operational yield signals suited to Indonesia’s food security needs, while providing a clear recipe for scaling to additional provinces.
Co-Authors Abdul Latief Arda Abel, Abel Ahkas, Andi Suciana Ahmad Dani Ahmad, Andani Ahmadi, Muh. Taufiq Andani Achmad Apriani Sijabat Asmarani, Adelia Awalya, Nurul Aziza, Nur Baharuddin Baharuddin Berlian, Andi Fajar Damayanti, Sisil Dayanti Dayanti, Dayanti Dedi Triyanto Dewi Haryanti Agustan , Andi Dewi Haryanti Agustan, Andi Dewi, Kharisma Dianah, Koas Diath Yogmar, Amsar elsa, elsa Eman Suherman Fakbua, Nidanuch Febriansyah, Angky Fibrilya Herman, Radika Firdania, Andi Fitri, Anisa Halimah, Endang Hazriani Hazriani, Hazriani Hidayat Isiswanty Jusnidar, Jusnidar Khomsiah, Kharismatul Konate, Siaka Masdar, Imelda Melni, Melni Mide, Baharuddin Muhammad Resky, Andi Muhammad Rusli Musfida, Firdha Mutmainnah Mutmainnah Nabila, Alya Nabila, Efa Ayu Nur Alifah, Alyah Nurfadilla, Nurfadilla Nurhinaya, Nurhinaya Nurwafia, Andi Pratama, Denis Puri Swastika Gusti Krisna Dewi Puspita Ayu, Novalinda Rael Astillero, Marlon Rahma Wahdiniwaty Rahmadani, Nia Ramadhana, Sahru Ramadhani, Asnia Ramdan Satra Revalina, Revalina Riskayanti, Riskayanti riswanto riswanto Rivaldi, Riksal Rizki Indrawan Sahra, Nurkhafitri Said Uddin, Abu Sattar, Usman Setiawan, Yudhika Sri Rejeki Sugiarti, Iin Supriadi Supriadi Syafei, M. Yani Syafei, M. Yani Syafei Titih Nursugiharti Ulfani, Tri Umi Kalsum, Andi Umi Narimawati Umiyati, Hesti Usman Usman Very, Eka Dawn Whardani, Kristina Whardani Wijaya, Rizky Charles Wulan Dari, Rika Yunansi Bonsa, Putri Yusni Yusni Yuyun, Yuyun