cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Reza Andrea
Contact Email
reza.andrea@gmail.com
Phone
+6285388729017
Journal Mail Official
admin.tepian@politanisamarinda.ac.id
Editorial Address
Kampus Sei Keledang Jl. Samratulangi, Samarinda Kode Pos 75131
Location
Kota samarinda,
Kalimantan timur
INDONESIA
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 282 Documents
 22   23   24   25   26 
Multi-stream Revenue Model for AI-based Fintech Lending using Enterprise Architecture Framework Edwin Wiyanto Saputra; Richardus Eko Indrajit; Januponsa Dio Firizqi
TEPIAN Vol. 7 No. 2 (2026): June 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i2.3657

Abstract

The contemporary Peer-to-Peer (P2P) lending industry is currently facing existential sustainability challenges, primarily driven by intense market saturation and the escalating risk of Non-Performing Loans (NPL). Conventional business models, which rely heavily on interest-based income, are proving increasingly fragile in this volatile financial landscape. Addressing these critical vulnerabilities, this study proposes a comprehensive Enterprise Architecture (EA) framework to transform Fintech platforms from traditional loan intermediaries into intelligent, data-driven financial orchestrators effectively integrated within a Smart Urban Ecosystem. Methodologically, the research adopts a systematic qualitative Design Science Research (DSR) approach, synthesizing the Business Model Canvas for strategic alignment and ArchiMate 3.1 standards for technical structural modeling. The study critiques the limitations of existing monolithic systems and introduces a novel multi-stream revenue model designed to diversify income sources. This model comprises three core pillars: AI-based Credit Scoring as a Service (CSaaS) to foster cross-platform interoperability and trust, Credit Behavior Analytics, which monetizes previously underutilized "dark data" for deeper risk insights, and Embedded Credit Scoring tailored for real-time, high-frequency transactional environments. Technically, the proposed architecture strategically decouples high-load AI computation from low-latency decisioning processes using a microservices approach, thereby resolving scalability bottlenecks often found in legacy systems. The findings demonstrate that transitioning to this modular "Fintech-as-a-Service" paradigm significantly mitigates financial risk by shifting reliance from uncertain loan interest to stable, fee-based revenue streams. This research provides a strategic blueprint for Fintech stakeholders, offering a pathway to long-term viability and competitive advantage in the emerging data-driven digital economy.
Artificial Intelligence-Based Driver Behavior Scoring for Improving Safety and Delivery Efficiency in Logistics Operations Ibnu Hamdani; Teddy Mantoro; Januponsa Dio Firizqi
TEPIAN Vol. 7 No. 2 (2026): June 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i2.3667

Abstract

The logistics sector faces increasing challenges related to road safety and operational efficiency due to unsafe driving behavior, high accident rates, and inconsistent delivery performance. Traditional monitoring approaches are often reactive and limited in their ability to capture complex driving patterns in real time. This study proposes an artificial intelligence–based driver behavior scoring framework that integrates in-vehicle telematics, GPS route data, and in-cab monitoring to improve safety performance and delivery efficiency in logistics operations. The research utilizes historical and real-time vehicle data collected from onboard diagnostic systems, including speed, acceleration, braking patterns, and driving duration. Three artificial intelligence models Random Forest, Long Short-Term Memory (LSTM), and a hybrid CNN–LSTM were developed and evaluated to classify risky driving behavior and predict safety-critical events. Experimental results indicate that the hybrid CNN–LSTM achieved the best performance, reaching an accuracy of 96.1% and a mean absolute error of 0.054. A three-month pilot deployment in a logistics fleet environment further demonstrated practical benefits, with average driver safety scores improving from 78.4 to 89.7 and on-time delivery rates increasing from 91.2% to 96.5%. These findings highlight the effectiveness of multimodal driver behavior analytics in simultaneously enhancing road safety and logistics performance. The proposed framework provides actionable decision-support insights for fleet managers and contributes to the advancement of AI-enabled intelligent transportation and logistics systems.
Analysis of Customer Perception on Google Maps Reviews of Klinik Kopi Samarinda Using Extreme Gradient Boosting (Xgboost) M.Ariya Parengrengi; Heny Pratiwi; Muhammad Fahmi
TEPIAN Vol. 7 No. 2 (2026): June 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i2.3682

Abstract

This study aims to analyze customer perceptions based on Google Maps reviews of Klinik Kopi Samarinda using the Extreme Gradient Boosting (XGBoost) method. Online customer reviews have become an important source of information for evaluating service quality and customer satisfaction in the food and beverage industry. The data used in this study were collected from Google Maps reviews, consisting of customer comments and ratings. Text preprocessing was conducted through case folding, tokenization, stopword removal, and stemming to prepare the data for analysis. Sentiment labels were classified into positive, negative, and neutral categories. The XGBoost algorithm was applied to perform sentiment classification due to its high performance in handling structured and unstructured data. The results show that the XGBoost model achieved high accuracy in classifying customer sentiment, indicating that most customers have positive perceptions of Klinik Kopi Samarinda. This study demonstrates that machine learning-based sentiment analysis can provide valuable insights for business owners in understanding customer feedback and improving service quality.
IoT-Based K-Nearest Neighbor Classification of Beverage Sugar Levels for Early Diabetes Prevention Nurul Safira; Rizka Azizah; Sri Hayyu Fajhalika; Achmad Ridwan
TEPIAN Vol. 7 No. 2 (2026): June 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i2.3729

Abstract

This study is motivated by the increasing consumption of sugar-sweetened beverages, which significantly contributes to the risk of diabetes mellitus. Therefore, a practical, accurate, and efficient system is required to detect sugar levels in beverages. This study aims to design and implement an Internet of Things (IoT)-based system for classifying sugar levels using the K-Nearest Neighbor (KNN) algorithm. The system is developed using an ESP32 microcontroller integrated with an ultrasonic sensor, a photodiode, and an infrared light source to capture the physical and optical characteristics of liquids. The research focuses on several commonly consumed beverages, namely sweet tea, coffee, milk, syrup, and lemon water, with varying sugar levels ranging from 10 to 60 grams. The collected data are processed through normalization using the StandardScaler method and classified based on Euclidean distance with a k value of 5. The classification results are grouped into three categories: low, medium, and high sugar levels. Experimental results show that the system achieves an accuracy of 85% under testing conditions. These results indicate that the proposed system can perform reliable classification in practical scenarios. In addition, the system provides a low-cost and real-time solution, making it suitable for practical applications in monitoring daily sugar intake and supporting the early prevention of diabetes mellitus.
IoT-Based Smart Temple Prototype for Remote Lamp and Loudspeaker Control at Pengulon Traditional Village Temple Kadek Reda Setiawan Suda; Sri Muntiah Andriami; Muhammad Khalil; Kurnia Dwi Artika; Sukma Firdaus; Muhammad Rezki Fitri Putra
TEPIAN Vol. 7 No. 2 (2026): June 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i2.3754

Abstract

Daily temple operations in Balinese Hindu temples often require caretakers to manually activate and deactivate lamps and loudspeakers, especially for routine prayer activities such as Tri Sandya at 06:00, 12:00, and 18:00. This manual process can be inefficient when operators are unavailable and may cause unnecessary electricity consumption when devices remain active longer than needed. This study develops an Internet of Things (IoT)-based Smart Temple prototype for remote lamp and loudspeaker control at Pengulon Traditional Village Temple. The system was designed using an ESP32 microcontroller, a four-channel relay module, and a web-based interface that enables users to control temple devices through an internet connection. The research applied a prototype development model consisting of communication, quick planning, quick design modelling, prototype construction, deployment, and feedback. Functional testing showed that all connected devices could be activated and deactivated successfully through the web interface. The speaker was activated in 1.51 seconds and deactivated in 2.10 seconds, while the three lamp channels showed activation times between 3.61 and 4.40 seconds and deactivation times between 1.30 and 2.50 seconds. These results indicate that the proposed prototype can support more practical, flexible, and efficient temple device management. The contribution of this study lies in adapting low-cost IoT-based relay control to the operational context of a traditional worship facility, where remote accessibility, ritual scheduling needs, and energy-use efficiency are important practical considerations.
Android Educational Game: Introduction to Basic Logic for Children Nurul Ria Irawan; Nisa Rizqiya Fadhliana; Wahyuni Eka Sari
TEPIAN Vol. 1 No. 1 (2020): March 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i1.46

Abstract

Introduction to Basic Logic aims to develop children's thinking abilities about numbers and quantities to teach activities that are in accordance with the development of their thinking power. Learning in children requires an educational media game facility, one of which is the Educational Game. This educational type game aims to provoke children's interest in learning the subject matter while playing the game. Mobile games can be an alternative in children's learning. Basically children prefer to play rather than learn. This is natural, because child psychology is playing. Based on these problems an educational game application is made for the introduction of basic logic in Android-based children, so that it can produce alternative learning for children. This educational game is intended for children aged 6-7 years because children aged 6-7 years have begun to understand the concept of numbers and develop sensitivity in solving a problem. And trials are carried out using a questionnaire
Application of Digital Image Segmentation of Plantation Fruit Classification in Samarinda Agricultural Polytechnic Ella Pajriyani; Eny Maria; Rusmini Rusmini
TEPIAN Vol. 1 No. 1 (2020): March 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i1.47

Abstract

Applications of Digital Image Segmentation of Plantation Fruit Classification in Samarinda State Agricultural Polytechnic Based on Form The development of computer technology at this time has brought significant progress in various aspects of human life. Such development is supported by the availability of increasingly high hardware and software, one of the technologies experiencing rapid development is image processing. Image processing is a system where the process is carried out by entering an image and the result is also an image. Currently the use of digital images is widely used in various fields one of which is in the plantation sector. Therefore, the purpose of this study is to create a digital image segmentation application for the classification of plantation fruit based on shape. The method used for image segmentation is the Thresholding method, while the image classification uses the Artificial Neural Network (ANN) method. The accuracy generated by the system both in the training process and testing shows that the method used can classify fruit images well
Development of Inventory Management Application Points Of Sale Using Laravel Hanafi Kambivi; Eko Junirianto; Nisa Rizqiyah Fadhliyah
TEPIAN Vol. 1 No. 1 (2020): March 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i1.48

Abstract

development of the business world encourages companies to always try to improve the quality of products and services to consumers. The implementation of these business solutions is a commitment in increasing the competitive advantage of corporate customers in terms of efficiency, effectiveness, performance, and business development. The purpose of this research is to conduct an analysis and design of a point of sale (POS) management application to support the purchasing service system and stock of goods that can help small and medium entrepreneurs in data management. The making of this POS application starts from collecting all the data needed using observation and interview methods, designing an application model with an object-based diagram approach with application design tools in the form of flowchart and Unified Modeling Language (UML) until the implementation of this POS application. With the application of the point of sales (POS) application can help the tasks of related parties or all stakeholders directly related to the POS application.
Expert System for Diagnosing Cocoa Diseases Using the Dempster Shafer Method Annafi Franz; Nurlaila Nurlaila; Putri Yus Andayani
TEPIAN Vol. 1 No. 1 (2020): March 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i1.49

Abstract

Indonesia occupies the third position of the largest cocoa producing country in the world, but the challenge faced is that the disease that attacks the cocoa plant causes only 60% of the cocoa production is export-worthy. The Dempster Shafer method can be used to diagnose types of diseases in cocoa plants. The system can be used by cocoa farmers in Indonesia to minimize the attack of cocoa plant diseases, so that yields can be abundant. This research was conducted at P4S Karya insani, Linking. As a research location for 6 months, from September 2018 to March 2019, it includes taking data, analysis, develop the applications, implementation, and testing. Expert system diagnosis of cocoa plant diseases using the dempster shafer method makes it easy for users to know the symptoms and diseases of the cocoa plant so that it can be used in diagnosing cocoa plant diseases.
Geographical Information System Mapping the Billboards In Samarinda Lidiya Suryaningsih; Wahyuni Eka Sari; Dawamul Arifin
TEPIAN Vol. 1 No. 1 (2020): March 2020
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v1i1.50

Abstract

Advances in information technology on geography are increasingly needed by many people, for example information on distances between regions, locations, facilities and many other information. The information is needed by users for various purposes such as research, development, regional design and natural resource management. Because of this geographical presence can help the presentation of a more interactive information, where users can access complete geographical information using only a computer, web-browser and internet network. So to get that information all in need of a Geographical Information System (GIS). The purpose of this research is to create a web that contains information on the location of billboards in the city of Samarinda. While this research is expected to make it easier for users to obtain information on the location of billboards in Samarinda.

Page 24 of 29 | Total Record : 282

 22   23   24   25   26 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 7 No. 2 (2026): June 2026 Vol. 7 No. 1 (2026): March 2026 Vol. 6 No. 4 (2025): December 2025 Vol. 6 No. 3 (2025): September 2025 Vol. 6 No. 2 (2025): June 2025 Vol. 6 No. 1 (2025): March 2025 Vol. 5 No. 4 (2024): December 2024 Vol. 5 No. 3 (2024): September 2024 Vol. 5 No. 2 (2024): June 2024 Vol. 5 No. 1 (2024): March 2024 Vol. 4 No. 4 (2023): December 2023 Vol. 4 No. 3 (2023): September 2023 Vol. 4 No. 2 (2023): June 2023 Vol 4 No 2 (2023): June 2023 Vol 4 No 1 (2023): March 2023 Vol. 4 No. 1 (2023): March 2023 Vol 3 No 4 (2022): December 2022 Vol. 3 No. 4 (2022): December 2022 Vol. 3 No. 3 (2022): September 2022 Vol 3 No 3 (2022): September 2022 Vol 3 No 2 (2022): June 2022 Vol. 3 No. 2 (2022): June 2022 Vol. 3 No. 1 (2022): March 2022 Vol 3 No 1 (2022): March 2022 Vol 2 No 4 (2021): December 2021 Vol. 2 No. 4 (2021): December 2021 Vol 2 No 3 (2021): September 2021 Vol. 2 No. 3 (2021): September 2021 Vol. 2 No. 2 (2021): June 2021 Vol 2 No 2 (2021): June 2021 Vol 2 No 1 (2021): March 2021 Vol. 2 No. 1 (2021): March 2021 Vol. 1 No. 4 (2020): December 2020 Vol 1 No 4 (2020): December 2020 Vol. 1 No. 3 (2020): September 2020 Vol 1 No 3 (2020): September 2020 Vol 1 No 2 (2020): June 2020 Vol. 1 No. 2 (2020): June 2020 Vol. 1 No. 1 (2020): March 2020 Vol 1 No 1 (2020): March 2020 More Issue