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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 7 Documents
 1 
Search results for , issue "Vol. 5 No. 2 (2024): June 2024" : 7 Documents clear
A Decision Support System is Developed to Determine the Optimal Criteria for Selecting Exceptional Lecturers Based on Their Lecturer Performance Index Nurhindarto, Aris; Sari, Wellia Shinta; Hendriyanto , Novi; Sulistyono, MY Teguh
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.1783

Abstract

Decision Support Systems (DSS) are computer systems that analyze data and convert it into actionable information for decision-making. The prior application mainly emphasized design analysis in web development, neglecting the use of decision-making knowledge as a responsibility within the Tri Dharma of Higher Education.  Analyzing data to transform it into information is a complex task involving decision-making. The process of decision-making has a significant impact on the information generated for recommendation purposes.   Suggestions in a decision-making process only sometimes serve as a standard for leaders to implement immediately. However, it is essential to acknowledge that multiple suggestions are required to make a final decision since they provide a basis for comparison with earlier recommendations.  The Decision Support System (DSS) utilized in this research focuses on selecting the optimal criteria from several criteria. The research employed the Analytical Hierarchy Process (AHP) technique, which consists of six stages : Criteria Alternative Determination, Pairwise Matrix Comparison, Criteria And Making Matrix, Square of Pairwise Matrix, Normalisation, and Alternative Ranking.   All six steps must be sequentially executed without skipping any stage, ensuring each stage complements the others and generates accountable information.   The research concludes by proposing a Decision Support System for Determining the Best Criteria for Lecturer Selection. This system utilizes the Lecturer Performance Index to provide recommendations to parties seeking information on selecting criteria for assessing lecturer performance. The system aims to enhance accountability in the performance of the Tri Dharma of Higher Education.
Water Level Monitoring for Flood Early Mitigation Based on Internet of Things (IoT) Syamsi, Nur; Ulfah, Maria; Lesmideyarti, Dwi
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2504

Abstract

Flooding is a disaster that often threatens communities, especially in high-risk areas. It is not surprising that this disaster causes many losses to the community morally and materially. This is because the area is on the riverbank and is the lowest point. The purpose of this final project is to design a flood early warning system as a water level monitoring to minimize the losses caused by floods with a water level monitoring tool to provide early warning to the community in the event of a flood. This water level monitoring tool utilizes solar panels as an energy source, where this tool uses ultrasonic sensors as water level detection and rain sensors as rainfall detection. This tool requires 28.6 Watts of power to power the system and the accuracy of the ultrasonic sensor is 99.94% with an average ultrasonic sensor error of 0.05%. This water level monitoring tool will help improve the flood early warning system, thus enabling the community to take appropriate mitigation steps before floods reach dangerous levels. Thus, losses due to flooding can be reduced, and assets can be restored, communities can be better protected from the threat of flooding.
Cloud Storage for Object Detection using ESP32-CAM Imron, Imron; Satria, Bagus; Karim, Syafei; Ramadhani, Fajar
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2994

Abstract

Cloud storage services can create an object storage bucket to store our pictures, among them the Cloud Storage FUSE, Scaleway, S3 bucket, Firebase,  etc. intelligent IoT systems generate vast amounts of multi-source industrial data, which necessitate a large amount of storage and processing power to enable real-time data processing and analysis. Cloud computing can be intricately linked into intelligent IIoT systems due to its strong computational and storage capabilities. Cloud Storage for Object Detection using ESP32-CAM. Create a workable solution that supports distributed storage bucket and implement it in a real-world setting. Implement the entire system as an addition to the well-known IoT cloud storage and run multiple experiments to evaluate its functionality in scenarios with varying setups and system. The target objects that are used as data sets are the ESP8266, Wemos D1, and Arduino Uno. Figuring out the ideal parameters for training the FOMO (First Object, More Object) model and then putting it into practice. It was necessary to find a balance between learning rate and accuracy, on the other hand, to maintain the highest possible accuracy in the identification of the microcontroller object to minimise the number of false positive reports. Find the value learning rate effective to this object is 0.01 with F1 score 98.7% and accuracy score 89.58%.
Decision Support System for Wedding Package Using Multi-Objective Optimization of Ratio Analysis Method Astuti, Indah Fitri; Kridalaksana, Awang Harsa; Alex, Rasni; Fitri, Dewi; Cahyadi, Dedy; Khoirunnita, Aulia
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2995

Abstract

Some   of the problems in preparing a wedding day are determining the venue, event concept, concept and others are very time-consuming. Wedding organizers are an option to overcome these problems; one of the wedding organizers in Samarinda is Galeri Shella, which has various wedding packages with facilities and prices, making it difficult for brides-to-be. To make it easier to make the right wedding package decision, a decision support system is made. The decision aims to provide wedding package recommendations with criteria that can be chosen by the bride and groom and their budget. The method used in this system is Multi-Objective Optimization of Ratio Analysis (MOORA) using six criteria catering, venue, decoration, documentation, makeup and price, as a reference calculation that can produce the best wedding package recommendations according to the wishes of the bride and groom. The research results show that the system functions well, is easy to use, and makes it easier for brides to choose wedding packages. From the results of accuracy testing, it is known that the results of manual calculations and the system make no difference, and this study obtained an accuracy value of 100%.
Medicinal Plants Recommendation System using ROC and MOORA Widians, Joan Angelina; Tejawati, Andi; Yuniarti, Wenty Dwi
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.3019

Abstract

Kalimantan has extraordinary biodiversity, including medicinal plants. Medicinal plants are a type of plant that certain parts, such as roots, leaves, bark, stems, and the results of their excretions. However, people sometimes need help choosing plants that suit their needs because of the many types of medicinal plants and the need for knowledge regarding their use. Decision support systems (DSS) combine computer capabilities with data processing or manipulation that utilizes unstructured models or solution rules. Furthermore, the method of documenting knowledge of traditional medicine is through the media of information systems. This system helps select medicinal plants according to user needs. This research developed a DSS using Rank Order Centroid (ROC) and Multi-Objective Optimization by Ratio Analysis (MOORA) methods to select medicinal plants for fungal and skin infections, including Furuncles, Tinea corporis, Tinea versicolor, and Acne. ROC method for determining criteria weight values. This research has four criteria: plant part, processing method, use method, and habitus. Determining recommendations for alternative ranking results using the MOORA method. This study aims to help the public get recommendations for medicinal plants in human skin disease treatment. This study aims to increase the preservation of biodiversity, particularly sustainable medicinal plants in the tropical rainforest of East Kalimantan.
Application of Bubble Sort Optimization in New Student Admission Selection Using Brute Force Algorithm Arbansyah, Arbansyah; Ilham, Muhammad Fauzan Nur; Suryawan, Sayekti Harits; Wirayuda, Pandu
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.3055

Abstract

This study investigates the application of a Brute Force algorithm optimized with Bubble Sort for new student admission selection. The Brute Force algorithm, while guaranteeing accurate results, suffers from exponential time complexity with increasing data size, posing a challenge for large applicant pools. To address this limitation, this research integrates Bubble Sort optimization to reduce the execution time complexity of the Brute Force algorithm. This study goes beyond solving the student admission selection problem; it explores optimizing the Brute Force algorithm by leveraging the simplicity and efficiency of Bubble Sort. This approach aims to determine the extent to which the Brute Force algorithm can be optimized for student selection, particularly regarding execution time complexity. The integration of Bubble Sort is hypothesized to significantly improve the performance of the Brute Force algorithm by reordering data before processing, thereby minimizing unnecessary comparisons. This paper presents a comparative analysis of execution times between the traditional Brute Force approach and the optimized version. Preliminary results indicate a substantial improvement in efficiency, suggesting that this hybrid approach could be a valuable solution for similar combinatorial problems with time complexity constraints. Further research could explore the applicability of this optimized algorithm in other domains where time complexity is a critical factor.
Development of the “Digihet” Multimedia Education Program to Improve Health Quality in the Setara Community Group Nurhasanah, Nurhasanah; Andrea, Reza; Ardan, M
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.3058

Abstract

The digital divide and low health quality are challenges faced by the Setara South Sempaja community group. The impact of flooding is a health problem frequently experienced by this community group. The Technology and Health Education Program (Digihet) is designed to address this issue by providing education on the use of digital technology and clean and healthy living patterns to vulnerable groups affected by health problems. This study aims to develop and evaluate the effectiveness of the Digihet program in improving digital literacy, specifically in clean and healthy living patterns, and the quality of life of the community. The Digihet program is developed using multimedia development techniques, starting from the concept design stage to distribution. The Digihet program teaches about 10 clean and healthy living skills for households, including childbirth assisted by healthcare professionals, exclusive breastfeeding for babies, weighing babies and toddlers, using clean water, washing hands with clean water and soap, using healthy latrines, eradicating mosquito larvae at home, eating fruits and vegetables every day, engaging in physical activity every day, and not smoking indoors. Data were collected through beta testing, and the research results showed that the Digihet program is effective in increasing digital literacy in forming clean and healthy living patterns. The results of this study are expected to serve as a basis for developing multimedia health education programs and contribute to enhancing the understanding of the relationship between digital literacy, public health, and information technology in the context of household health quality.

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