SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst
<p>To publish research articles and academic articles (Review articles, Technical article, Special Articles) in science and technology. SAU JOURNAL OF SCIENCE & TECHNOLOGY is published two issues annually. The first volume is published between January and June and the second is published July and December in each year.</p>en-USsaujournalst@sau.ac.th (Weerapun Duangthongsuk)saujournalst@sau.ac.th (ชุมภูนุช แย้มรู้การ)Fri, 27 Jun 2025 00:00:00 +0700OJS 3.3.0.8http://blogs.law.harvard.edu/tech/rss60Applying Data Mining Techniques to Develop a Model for Predicting Suitable Academic Fields for University Applicants at Kamphaeng Phet Rajabhat University
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260261
<p>This research aimed to develop predictive models for determining the suitability of academic programs for undergraduate students by applying five data mining techniques: Decision Tree (DT), Naive Bayes, Support Vector Machine (SVM), Random Forest, and AdaBoost. The study utilized a dataset of 1,392 students across 10 academic programs at Kamphaeng Phet Rajabhat University. Students’ academic performance was grouped into four levels include Excellent (A), Good (B), Fair (C), and Low (E). The experimental results indicated that Naive Bayes achieved the highest average F1-Score in 6 out of 10 programs, particularly in programs with simple data structures and clearly separable classes. In contrast, SVM performed well in programs with complex or overlapping data structures, while Random Forest demonstrated outstanding performance in handling high-variance data, especially in the General Management program, where it achieved the highest F1-Score of 0.75. The findings suggest that selecting an appropriate model should consider the underlying structure of the dataset in each specific context. Although Naive Bayes yielded the best overall results, data overlapping between classes in several programs remained a limiting factor, resulting in moderate classification accuracy. Future research should consider incorporating behavioral, interest-based, or skill-related features to enhance prediction accuracy and support educational guidance systems that better align with each student’s potential.</p>Kanokwan Khiewwan, Narut Butploy, Jindaporn Ongate, Khumphicha Tantisantisom, Phrommate Veeraphan, Komkrit Klin-art
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260261Fri, 27 Jun 2025 00:00:00 +0700Localization error reduction for an electric aircraft tractor prototype using Kalman filter
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260177
<p>Operating an autonomous vehicle in an airport requires high localization precision to safely navigate the airside and avoid collisions with aircraft, buildings, and personnel. This paper presents an accuracy analysis of the localization system for a small electric aircraft tractor prototype. The system utilizes a Global Navigation Satellite System (GNSS) for positioning and enhances accuracy through data fusion with a wheel odometer using a Kalman Filter. A pilot system was installed on the autonomous small electric aircraft tractor prototype to evaluate performance. Experimental results indicate that the data fusion-based approach reduced GNSS positioning errors by 32.35% in the worst case and up to 56.47% in the best case while also increasing satellite data availability through computational estimation with an Inertial Measurement Unit (IMU). Additionally, the IMU reduces signal error data in certain areas and reduces covariance noise, resulting in more accurate and efficient movement of the electric aircraft tractor.</p>Thitiyos Prakaitham, Chawalit Panya-isara, Soontorn Odngam, Chayut Sumpavakup
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260177Fri, 27 Jun 2025 00:00:00 +0700The Internet of Battle Things (IoBT) – Perception and Adoption of Special Operation Agents : Case Study of Counter Terrorist Operations Center
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260475
<p>The objectives of this study were to 1) Examine the factors influencing the perception of Internet of Battle Things (IoBT) technology among special operation agents of the Counter Terrorist Operations Center (CTOC). 2) Examine the factors influencing the adoption of IoBT technology among special operation agents of the CTOC. This research employed both quantitative and qualitative methods. For the quantitative part, a questionnaire was used to collect data from all 104 special operation agents of CTOC. For the qualitative part, in-depth interviews were conducted with 5 commanders. The data were analyzed using descriptive statistics, including percentage, arithmetic mean, and standard deviation. Hypothesis testing was conducted through mean comparison using the Independent Samples T-Test and One-Way Analysis of Variance (ANOVA). The findings revealed that personal factors had no statistically significant effect on either the perception or adoption of IoBT technology among special operation agents at the 0.05 significance level. Furthermore, <br />the commanders proposed guidelines for the development of personnel in the area of information technology, as well as recommendations for the safe and effective use of IoBT technology. These insights can serve as valuable input for the future development of personnel, equipment, and organizational capabilities.</p>Jirawat Noonlaong, Chutima Pisarn
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260475Fri, 27 Jun 2025 00:00:00 +0700Module Integrated Flyback DC-DC Converter using Partial Power Processing Technique for Photovoltaic System
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/261693
<p>This research proposes the design of a flyback DC-DC converter circuit intended for integration with photovoltaic (PV) modules. The module-level power conversion provides an effective solution to mitigate power losses resulting from mismatch conditions among photovoltaic (PV) modules in conventional string configurations. The proposed circuit employs the Partial Power Processing (PPP) technique to reduce the power transfer through the power stage, thereby improving overall system efficiency. Additionally, the compact circuit design allows for easy integration with individual PV modules. A prototype of the proposed system was developed and tested with PV modules exhibiting a wide range of maximum output power from 30 W to 250 W. The experimental results demonstrate that the proposed partial power processing converter can accurately track the maximum power point of PV modules under various operating conditions. The converter processes only 20–30% of the total power through the flyback converter, while achieving an overall system efficiency ranging from 95% to 97%.</p>Chokchai Chuenwattanapraniti, Montana Rungsiyopas
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/261693Fri, 27 Jun 2025 00:00:00 +0700Utilizing Software for Model Development and Cost Estimation in Highway Engineering
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260890
<p>This research aims to study and utilize software for the design and cost estimation of roadworks by using Blender for 3D modeling and Road Price for cost estimation. A case study was conducted on a road improvement project from the Yala Provincial Office of Public Works and Town & Country Planning. The findings revealed that the percentage difference between the construction cost estimated using the software and the conventional calculation method was 1.36%. This indicates that the software provides cost estimates that closely align with the actual construction costs. Moreover, revisions can be made and recalculated more conveniently and quickly, reducing the working time by 69.57%. The development of integrated design and cost estimation software minimizes errors and enables users to select or change materials in cases where project costs exceed the set budget. It also enhances the effectiveness of data presentation. The satisfaction level of practitioners increased from an average score of 3.04 (moderate level) to 4.16 (high level), an increase of 1.12 points or 36.84%.</p>Suwimol Jairtalawanich; Thamma Jairtalawanich, Sirichai Pethrung
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/260890Fri, 27 Jun 2025 00:00:00 +0700A Study of the Learning Achievement results of Active Learning on Mobile Application in Mathematics Subject: Case Study of MTTS Math Application of Military Technical Training
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/261100
<p>This research aimed 1) to develop active learning media on Mobile applications for math subjects of the Military Technical Training students called the MTTS math application. 2) to compare the academic achievement in math subjects of the Military Technical Training students between learning in the classroom and the MTTS math application, and 3) to evaluate the efficiency of the MTTS math application. The research design was quantitative research. The sample consisted of 30 Military Technical Training students studying math subjects, which were divided into 2 groups: A group studied in the classroom (15 students), and a group studied actively on Mobile Applications (15 students). The research instrument used for data collection was the Mobile Application. Academic achievement was compared between the groups and the questionnaire was collected from math teachers to ask about their satisfaction with using mobile applications. It was found that the academic achievement in mathematics of the first-year military vocational students who learned actively on the Mobile Application had a higher average score than learning in the classroom. The <em>t</em><em>-test</em> value was found to be greater than 1.76, which is statistically significant at the 0.05 level, indicating that active learning on the MTTS math application) has different achievements from learning mathematics in the classroom. The overall satisfaction with the application's use was found to be \bar{x} = 4.52 S.D. = 0.69, with the satisfaction evaluation results having the highest average value.</p>Thitiya Kanbuakaew; Chutima Pisarn
Copyright (c) 2025 SAU JOURNAL OF SCIENCE & TECHNOLOGY
https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/261100Fri, 27 Jun 2025 00:00:00 +0700