The Golden Teak : Science and Technology Journal (GTSJ.)

The Development of Shallot Warehouse Management System Using Optical Character Recognition Technology

2026-06-24T14:36:05+07:00

The research on the development of a shallot warehouse management system using Optical Character Recognition technology. The objectives of the study are to: 1) develop a shallot warehouse management system using OCR technology. 2) evaluate the efficiency of the developed management system. 3) To assess user satisfaction with the shallot warehouse information service website. The system was developed with an automatic receipt data recording system using Tesseract OCR technology, which processes character data from receipt scans. The database management system uses MySQL and PHP programming language, a website was developed to provide services for customers to check information, shallot warehouse details, and process service fee payments. The experimental results revealed that, in the scanning tests, the suitable brightness adjustment range for image scanning was between -20 and +20, yielded an accuracy of 100%. The resolution adjustment experiment demonstrated that employing images at 1200 dpi achieved an accuracy rate of 99.33%. The system was able to recognize tilted characters at any angle with 100% accuracy. Scanning black-and-white receipts also achieved 99.33% accuracy. The processing time and data saving duration measured during the experiment averaged 12 seconds. The system also allows for data verification and correction before saving. The website development results demonstrated the ability to display detailed outputs such as quantity, weight, warehouse rental area, receipts, and performance evaluation results. The website's development effectiveness was rated as very good, with an average uses satisfaction score of 4.53 and a standard deviation of 0.76.

Local Wisdom Model of Traditional Herbal Medicine in TAK Province

2026-06-24T15:11:51+07:00

This qualitative research aimed to: (1) examine the local wisdom of traditional herbal healers in Tak Province; (2) explore the characteristics and processes of traditional herbal healers’ wisdom; and (3) investigate the forms of traditional herbal healers’ wisdom in Tak Province. The participants consisted of nine traditional herbal healers, each representing one district in Tak Province. Data were collected through in-depth interviews. The obtained data from audio recordings, transcription, and photography were categorized according to the research objectives and were verified for completeness and reliability through triangulation. The findings revealed that traditional herbal medicine wisdom in Tak Province was rooted in ancestral inheritance, learning, and accumulated experience. This wisdom was applied to treat symptoms or cure diseases among villagers in the community by utilizing local herbs and spells, depending on the specific expertise of each healer. The characteristics and processes of this wisdom involved inheritance from ancestors and learning from textbooks and experts, with an emphasis on the properties of important local medicinal plants. Treatment processes were simple and uncomplicated, focusing on practical application within the community context. The forms of traditional herbal medicine wisdom included ancestral methods of healing, the use of herbal medicine to treat physical illnesses, and the use of spells to heal the mind. These practices were manifested in various forms, such as herbal remedies, decoctions, pills, and ointments.

Effectiveness of Thai Herbal Poultices on the Knees in Treating Osteoarthritis in the Elderly Patients at Mae Ramat Hospital Tak Province

2026-06-24T15:27:50+07:00

This study aimed to investigate the effectiveness of Thai herbal knee poultice therapy in the treatment of knee osteoarthritis among elderly patients at Mae Ramat Hospital, Tak Province. A quasi-experimental research design with a one-group repeated measures approach was employed. The sample consisted of 20 elderly patients aged 60 years and older diagnosed with knee osteoarthritis, with pain scores ranging from 3 to 6, who received treatment at Mae Ramat Hospital. Pain intensity was assessed using the Visual Analogue Scale (VAS). The participants were treated with a Thai herbal knee poultice formula consisting of nine herbal ingredients, applied once a week for three consecutive weeks, with each session lasting 20 minutes. Data were analyzed using descriptive statistics and repeated measures analysis of variance (ANOVA). The results revealed that the mean knee pain score significantly decreased from 5.05 before treatment to 0.97 after the third treatment session. The findings indicated that the Thai herbal knee poultice therapy significantly reduced the severity of knee pain in elderly patients with knee osteoarthritis at a statistical significance level of p < 0.05.

The Effect of Herbal Poultice on Knee Pain Reduction in Elderly Patients with Osteoarthritis at a Health Promotion Hospital in Tak Province

2026-06-24T15:42:51+07:00

This quasi-experimental research aimed to study the effect of herbal poultices on reducing knee pain in elderly people with osteoarthritis who received services at Ban Nam Chon Health Promoting Hospital. The sample consisted of 40 elderly people who received herbal poultices 3 times. Data were collected using a general information record form, health information, and pain level assessment form. Statistics used for data analysis included frequency, distribution, percentage, mean, standard deviation, and t-test The study results found that after applying herbal poultices to elderly patients with osteoarthritis, the average knee pain score was significantly reduced (p < 0.001). The herbal poultices were able to reduce pain and stiffness of the knee joints during standing and walking, resulting in improved functional ability. The results of this study show that herbal poultices are an effective treatment option.

Comparison of Engineering Properties Between Ancient and Modern Laterite

2026-06-26T13:14:57+07:00

The objective of this research is to compare the engineering properties of ancient laterite (approximately 600–700 years old) from Kamphaeng Phet Historical Park and modern laterite available in the current market. The study aims to establish an engineering database for evaluating structural stability and selecting appropriate replacement materials for historical restoration. The research methodology encompasses physical, chemical, and mechanical property testing based on international standards (BS1881-116 and ASTM C 293), including microstructural analysis using Scanning Electron Microscope (SEM) and elemental analysis via Energy Dispersive X-ray Fluorescence (ED-XRF). The results indicate that modern laterite exhibits superior engineering properties compared to ancient laterite in terms of density and strength. Modern laterite shows an average density of 2,373 kg/m³ and a compressive strength of 24.84 kg/cm², whereas ancient laterite recorded averages of 2,122 kg/m³ and 16.70 kg/cm², respectively. Regarding water absorption, ancient laterite demonstrated a higher rate at 8.41%, compared to 4.73% for modern laterite. Chemical and structural analyses revealed that modern laterite contains a high iron (Fe) content of 68.22% with non-interconnected pores, contributing to its higher strength. Conversely, ancient laterite has higher silicon (Si) content and interconnected porosity. These findings provide essential data for conservation planning and the selection of materials compatible with original structures.

Development of Web Application for Chemical Requisition and Dispensing in the Laboratory via an Online System

2026-06-26T13:59:25+07:00

This study aimed to develop a web application for online chemical requisition in laboratory settings to enhance data management efficiency and reduce operational delays. The system’s scope covered all laboratories within the Department of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University. The development process involved analyzing limitations of the conventional method; building an online requisition application; conducting system testing; evaluating the system through focus group discussed; and assessed user satisfaction via an online questionnaire (Google Forms). Statistics used in data analysis included mean and standard deviation. The level of interpretation of the mean was determined using the range formula. Participants compared the conventional method with the newly developed system. Results indicated that the legacy process was inefficient, characterized by limited data accessibility, slow requisition procedures, and non–real-time inventory levels which hindered management when chemicals approached depletion. The developed solution is a web application created using a participatory research and development (R&D) approach, implemented in PHP with a MySQL database, and designed according to object-oriented principles with UML. Authorized stakeholders can access information via the online platform. System testing and focus group evaluations identified issues that were subsequently resolved to refine the application. The overall user satisfaction score averaged 4.29 (SD = 0.51), indicating a very high level of satisfaction. Moreover, the requisition turnaround time was reduced from 3 days to 1 day (a 66.67% reduction).

Deep Learning-Based Image Analysis for Glaucoma Diagnosis

2026-06-26T14:29:38+07:00

This research aims to develop a Convolutional Neural Network (CNN) model for the automatic classification of glaucoma from retinal fundus images. The dataset consisted of 1,000 eye images, divided into normal and glaucoma groups, collected from online databases and patients at Rajthanee Hospital, Rojana, Phra Nakhon Si Ayutthaya Province.The proposed model is a 5-layer CNN architecture designed to suit color image data. The data preprocessing steps included image resizing, grayscale conversion, and data augmentation to increase the diversity of the training dataset. Model performance was evaluated using 5-fold cross-validation on a training and validation set of 800 images. The results showed that the model achieved an accuracy of 87% during training. When tested with a new dataset of 200 images, the model demonstrated high performance, achieving an accuracy of 94.0%, precision of 93.1%, recall of 95.0%, F1-score of 94.0%, and an AUC of 0.98. These results indicate the model’s strong accuracy and balance in distinguishing between normal and glaucoma images, suggesting that the developed CNN model can be effectively applied in real-world scenarios, particularly in healthcare facilities with limited resources and specialized personnel.

Development of an Information System to Support Research and Innovation Management: A Case Study of the School of Information and Communication Technology University of Phayao

2026-06-26T15:17:16+07:00

This research aims (1) to develop an information system to support research and innovation management in the form of a web application for the School of Information and Communication Technology, University of Phayao, and (2) to create reports to support research and innovation administration in the form of dashboards. The system was developed using PHP programming language and MySQL as a database management system. In addition, Microsoft Power BI was used to generate dashboard reports. The web application is categorized into three user levels based on functionality, the system administrator, executive, and general staff. The research findings indicate that the developed system helps overcome the limitations of the previous system by reducing the time required for information retrieval by 85.71% and report generation by 88.89%, while also minimizing data redundancy, improving work efficiency, and supporting strategic decision-making (S.D. = 0.57, high level). In addition, the system enables real-time data access through the integration of Business Intelligence (Power BI). The user satisfaction evaluation revealed that the system was rated at a high level ( = 4.41, S.D. = 0.57). The research findings indicate that the benefits of this system include increased efficiency in data collection and storage, reduced data redundancy, facilitates efficient and rapid information retrieval, and enhanced potential for future system development aligned with organizational needs.