https://ph01.tci-thaijo.org/index.php/jait <h3>Aim and Scope</h3> <hr /> <p><strong>Journal of Applied Informatics and Technology (JIT) </strong>is a peer-reviewed and open-access journal that aims to publish leading edge researches on any possible topic in informatics, technology, and other related areas, both from theoretical and empirical perspectives. </p> <p> </p> <ul> <li><strong>Journal title: </strong>Journal of Applied Informatics and Technology</li> <li><strong>Journal Abbreviation:</strong> </li> <li><strong>Initial:</strong> JIT</li> <li><strong>Languge:</strong> English (Start 2026)</li> <li><strong>Publication:</strong> 2 issues/year (No. 1: January - June, No. 2: July - December)</li> <li><strong>ISSN </strong>3088-1803 (Online)</li> <li><strong>Digital Object Identifier (DOI): </strong>10.14456</li> <li><strong>Article Processing Charges (APC):</strong> No charge</li> <li><strong>Editor-in-Chief:</strong> <a href="https://www.scopus.com/authid/detail.uri?authorId=16176331500" target="_blank" rel="noopener">Olarik Surinta</a> <strong><a href="https://orcid.org/0000-0002-0644-1435" target="_blank" rel="noopener"><img src="https://orcid.org/sites/default/files/images/orcid_16x16.png" alt="ORCID iD icon" /></a></strong></li> <li><strong>Publisher:</strong> <a href="https://it.msu.ac.th" target="_blank" rel="noopener">Faculty of Informatics, Mahasarakham University</a></li> <li><strong>Citation Analysis:</strong> <a href="https://scholar.google.co.th/citations?user=1aICbY8AAAAJ&amp;hl=en" target="_blank" rel="noopener">Google Scholar</a></li> </ul> <p> </p> <p><strong>Scope of the Research</strong></p> <p>Topics of interest include, but are not limited to, the following:</p> <ul> <li>Information Technology</li> <li>Computer Science</li> <li>Geo-Informatics</li> <li>Information Science and Management</li> <li>Digital Media</li> <li>Communication Arts</li> </ul> <p> </p> <p><strong>Types of Manuscripts</strong></p> <p>The JIT journal welcomes submissions in three academic formats: </p> <ul> <li>Research article</li> <li>Review article</li> <li>Academic article</li> </ul> <p class="NoSpacing"> </p> <h3>Brief Overview of Review Process</h3> <hr /> <p class="NoSpacing">The articles must be original and never be published in any other websites or other journals before. The articles which are considered as “<strong><em>plagiarism</em></strong>” articles are strongly prohibited to be published in the JIT journal. The JIT is dedicated to preventing accusations of dishonest publication-plagiarism, the redundant publication (self-plagiarism), author misrepresentation, and content falsification. The manuscript submitted to JIT should not have a similarity index score of more than 25% and the item in the list should have a similarity index score below or equal to 2% when using plagiarism applications, such as turnitin. The editor will immediately reject any manuscript that fails to meet the requirement of the JIT.</p> <p class="NoSpacing">Authors are required to include their names and affiliations in their manuscripts, whereas reviewers are not visible to authors. All submitted manuscripts are subjected to peer-review by at <strong>least three independent reviewers </strong>and all experts come from various institutions and are not specialists from the same institution as the author. Peer reviews are done by a <strong>double-blind review method</strong> where the identity of the reviewers and the authors are not disclosed to either party.</p> <p class="NoSpacing">The final decision regarding acceptance, revision, or rejection rests with the Editor-in-Chief.</p> <p class="NoSpacing">For more details of the peer review process, please follow this link: <a href="https://ph01.tci-thaijo.org/index.php/jait/review">Peer Review Process</a></p> <p class="NoSpacing"> </p> <h3>Indexed In </h3> <hr /> <ul> <li><a href="https://www.tci-thaijo.org" target="_blank" rel="noopener">TCI</a></li> <li><a href="https://doaj.org/toc/2586-8136?fbclid=IwAR1SyS0iZ8sDwDWjHJCAE0Jfex8CUscQTfFlbnMyMhk1191G8S1mBfNPfjk&amp;source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22terms%22%3A%7B%22index.issn.exact%22%3A%5B%222630-094X%22%2C%222586-8136%22%5D%7D%7D%5D%7D%7D%2C%22size%22%3A100%2C%22sort%22%3A%5B%7B%22created_date%22%3A%7B%22order%22%3A%22desc%22%7D%7D%5D%2C%22_source%22%3A%7B%7D%2C%22track_total_hits%22%3Atrue%7D" target="_blank" rel="noreferrer noopener">DOAJ</a></li> <li><a href="https://app.scilit.net/publications?q=Journal%20of%20Applied%20Informatics%20and%20Technology&amp;sort=relevancy" target="_blank" rel="noreferrer noopener">Scilit</a></li> <li><a href="https://www.base-search.net/Search/Results?type=all&amp;lookfor=Journal+of+Applied+Informatics+and+Technology+&amp;ling=1&amp;oaboost=1&amp;name=&amp;thes=&amp;refid=dcresen&amp;newsearch=1" target="_blank" rel="noreferrer noopener">BASE</a></li> <li><a href="https://essentials.ebsco.com/search/eds/details/%E0%B8%A7%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%B2%E0%B8%A3%E0%B8%A7%E0%B8%B4%E0%B8%97%E0%B8%A2%E0%B8%B2%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%99%E0%B9%80%E0%B8%97%E0%B8%A8%E0%B9%81%E0%B8%A5%E0%B8%B0%E0%B9%80%E0%B8%97%E0%B8%84%E0%B9%82%E0%B8%99%E0%B9%82%E0%B8%A5%E0%B8%A2%E0%B8%B5%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B8%A2%E0%B8%B8%E0%B8%81%E0%B8%95%E0%B9%8C?query=%E0%B8%A7%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%B2%E0%B8%A3%E0%B8%A7%E0%B8%B4%E0%B8%97%E0%B8%A2%E0%B8%B2%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%B2%E0%B8%A3%E0%B8%AA%E0%B8%99%E0%B9%80%E0%B8%97%E0%B8%A8%E0%B9%81%E0%B8%A5%E0%B8%B0%E0%B9%80%E0%B8%97%E0%B8%84%E0%B9%82%E0%B8%99%E0%B9%82%E0%B8%A5%E0%B8%A2%E0%B8%B5%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B8%A2%E0%B8%B8%E0%B8%81%E0%B8%95%E0%B9%8C&amp;requestCount=0&amp;db=edsdoj&amp;an=edsdoj.03273eac81a4dceabe794fa3b8a6546" target="_blank" rel="noreferrer noopener">EBSCO</a></li> <li><a href="https://scholar.google.com/scholar?hl=en&amp;as_sdt=0%2C5&amp;as_vis=1&amp;q=source%3AJournal+source%3Aof+source%3AApplied+source%3AInformatics+source%3Aand+source%3ATechnology&amp;btnG=" target="_blank" rel="noreferrer noopener">google Scholar</a></li> <li><a href="https://www.journaltocs.ac.uk/index.php?action=browse&amp;subAction=pub&amp;publisherID=4985&amp;journalID=43263&amp;pageb=1&amp;userQueryID=&amp;sort=&amp;local_page=1&amp;sorType=&amp;sorCol=1" target="_blank" rel="noopener">Journal TOCs</a></li> </ul> <p> </p> <p><img src="https://ph01.tci-thaijo.org/public/site/images/mrolarik/jit-banner-address.png" alt="" width="100%" /></p> en-US <p>All authors need to complete copyright transfer to Journal of Applied Informatics and Technology prior to publication. For more details click this link: <a href="https://ph01.tci-thaijo.org/index.php/jait/copyrightlicense">https://ph01.tci-thaijo.org/index.php/jait/copyrightlicense</a></p> olarik.s@msu.ac.th (Olarik Surinta) suwicha@it.msu.ac.th (Suwicha Chaimuang) Mon, 23 Jun 2025 00:00:00 +0700 OJS 3.3.0.8 http://blogs.law.harvard.edu/tech/rss 60 https://ph01.tci-thaijo.org/index.php/jait/article/view/263426 <p>The Journal of Applied Informatics and Technology (JIT) has published Volume 7, Number 2 (2025): July-December, comprising a total of 15 research articles—ten in English and five in Thai. Each article has undergone peer review by at least three experts from different institutions. The authors revised their articles based on the reviewers’ comments until they were approved for publication. The editorial team also verified the accuracy of the content, references, and language usage to ensure the highest quality. We sincerely thank all the reviewers for their valuable feedback and thoughtful recommendations.</p> <p> </p> <p>The following articles have been published in Volume 7, Number 2 (2025):</p> <p><strong>1) Warfarin Care: Warfarin Management System for Older Adults<br /></strong>Author: Narit Hnoohom, Konlakorn Wongpatikaseree, Autchariya Poungkaew, Junporn Kongwatcharapong (Hnoohom <em>et al.</em>, 2025)</p> <p><strong>2) Measuring Neck Abnormalities for Preliminary Assessment of Neck Pain Disease using Virtual Reality<br /></strong>Author: Manatsawee Sidajan, Kawintra Sittikraipong, Peerapat Kusumannukul, Sasiwimon Pornwachirawit, Waichaya Suwannakeeree, Sutasinee Jitanan (Sidajan <em>et al.</em>, 2025)</p> <p><strong>3) An In-House Time Tracking Application Development with a Low-To-No-Code Platform<br /></strong>Author: Sorn Tanharaphan, Thanabadee Rodvanich, Yatawee Aupasao, Natsuda Kaothanthong (Tanharaphan <em>et al.</em>, 2025)</p> <p><strong>4) Leveraging PyThaiNLP for Sentiment Analysis of Thai Online Text: A Comparative Study of Logistic Regression and Support Vector Machine<br /></strong>Author: Sunisa Duangtham, Setthaphong Lertritrungrot, Nattavadee Hongboonmee, Wansuree Massagram (Duangtham <em>et al.</em>, 2025)</p> <p><strong>5) The Flood Simulation System as a New Process for Public Participation of Local Administrative Organizations in Tha Wang Pha District, Nan Province<br /></strong>Author: Chamnan Kumsap, Vissanu Mungkung, Lanyanat Patanan, Phimraphas Ngamsantivongsa, Arisara Charoenpanyanet, Phonpat Hemwan (Kumsap<em> et al.</em>, 2025)</p> <p><strong>6) Classification of Guanxi Mandarin Orange Grades using Machine Vision Algorithms<br /></strong>Author: Fulian Huang, Jialin Xie, Shijun Jie, Nattawoot Suwannata (Huang <em>et al.,</em> 2025)</p> <p><strong>7) Development and Cost-Effectiveness Analysis of a Fogging Pump Control System Commercial Prototype for Oyster Mushroom Cultivation based on Open-System Greenhouse<br /></strong>Author: Non Pinngern, Bhannawat Wanganusorn (Pinngern &amp; Wanganusorn, 2025)</p> <p><strong>8) Web Scraping-based System for E-commerce Price Comparison and Similar Product Segmentation<br /></strong>Author: Pongsin Jankaew, Wachirawut Thamviset (Jankaew &amp; Thamviset, 2025)</p> <p><strong> </strong><strong>9) A Comparative Study of Sea Lettuce Cultivation in Seawater and Scientific Saltwater using IoT Technology<br /></strong>Author: Suttipong Klongdee, Sriwaree Sujaritchai, Sommart Promput (Klongdee, Sujaritchai, &amp; Promput, 2025)</p> <p><strong>10) Utilizing Association Rule Mining to Understand Phishing Risk Awareness Levels of Thai University Academic Staff<br /></strong>Author: Pita Jarupunphol, Wipawan Buathong (Jarupunphol &amp; Buathong, 2025)</p> <p><strong>11) Approximate String Matching Algorithm using Single Inverted Lists<br /></strong>Author: Soontaree Thumsuwan, Nuanprang Sangurai, Chouvalit Khancome (Thumsuwan, Sangurai, &amp; Khancome, 2025) </p> <p><strong>12) Pneumonia Detection from Chest X-ray Images using Convolutional Neural Networks and Transfer Learning Techniques<br /></strong>Author: Pongsathorn Chedsom (Chedsom, 2025)</p> <p><strong>13) Feature Selection with Linear Discriminant Analysis to Improve the Performance of Heart Disease Classification<br /></strong>Author: Ratiporn Chanklan, Keerachart Suksut, Kedkarn Podhijittikarn (Chanklan, Suksut &amp; Podhijittikarn, 2025) </p> <p><strong>14) Information System for Wet Garbage Bin Data Management in Local Areas: A Case Study of Langu Subdistrict Administrative Organization, Satun Province<br /></strong>Author: Norathep Sakphet, Chatirot Jitrugtham, Annop Bunjan, Kullaphat Yingdumnoon, Sakan Rodklai, Chanyanuch Pumpuang (Sakphet <em>et al.</em>, 2025)</p> <p><strong>15) Rice Seed Production with Smart Farm<br /></strong>Author: chalawan Wantong, Wanida Sumranram, Utis Tahom, Varit Kitthanarut, Ekkaluk Salukkham (Wantong <em>et al.</em>, 2025)</p> <p> </p> <p>The editorial board of JIT sincerely hopes that the 15 articles published in this issue will benefit researchers and serve as a valuable source of knowledge for the advancement of their work. We believe that the insights and findings presented in this issue will contribute to academic and practical developments in the fields of informatics and technology. We warmly invite scholars, practitioners, and students to explore the articles and apply the knowledge gained to their own research and professional activities.</p> <p> </p> <p>Assoc. Prof. Olarik Surinta, Ph.D.</p> <p>Editor-in-Chief</p> Journal of Applied Informatics and Technology Copyright (c) 2025 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/263426 Thu, 07 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/263427 <p>The Journal of Applied Informatics and Technology (JIT) has published Volume 7, Number 2 (2025): July-December, comprising a total of 15 research articles—ten in English and five in Thai. Each article has undergone peer review by at least three experts from different institutions. The authors revised their articles based on the reviewers’ comments until they were approved for publication. The editorial team also verified the accuracy of the content, references, and language usage to ensure the highest quality. We sincerely thank all the reviewers for their valuable feedback and thoughtful recommendations.</p> <p> </p> <p>The following articles have been published in Volume 7, Number 2 (2025):</p> <p><strong>1) Warfarin Care: Warfarin Management System for Older Adults<br /></strong>Author: Narit Hnoohom, Konlakorn Wongpatikaseree, Autchariya Poungkaew, Junporn Kongwatcharapong (Hnoohom <em>et al.</em>, 2025)</p> <p><strong>2) Measuring Neck Abnormalities for Preliminary Assessment of Neck Pain Disease using Virtual Reality<br /></strong>Author: Manatsawee Sidajan, Kawintra Sittikraipong, Peerapat Kusumannukul, Sasiwimon Pornwachirawit, Waichaya Suwannakeeree, Sutasinee Jitanan (Sidajan <em>et al.</em>, 2025)</p> <p><strong>3) An In-House Time Tracking Application Development with a Low-To-No-Code Platform<br /></strong>Author: Sorn Tanharaphan, Thanabadee Rodvanich, Yatawee Aupasao, Natsuda Kaothanthong (Tanharaphan <em>et al.</em>, 2025)</p> <p><strong>4) Leveraging PyThaiNLP for Sentiment Analysis of Thai Online Text: A Comparative Study of Logistic Regression and Support Vector Machine<br /></strong>Author: Sunisa Duangtham, Setthaphong Lertritrungrot, Nattavadee Hongboonmee, Wansuree Massagram (Duangtham <em>et al.</em>, 2025)</p> <p><strong>5) The Flood Simulation System as a New Process for Public Participation of Local Administrative Organizations in Tha Wang Pha District, Nan Province<br /></strong>Author: Chamnan Kumsap, Vissanu Mungkung, Lanyanat Patanan, Phimraphas Ngamsantivongsa, Arisara Charoenpanyanet, Phonpat Hemwan (Kumsap<em> et al.</em>, 2025)</p> <p><strong>6) Classification of Guanxi Mandarin Orange Grades using Machine Vision Algorithms<br /></strong>Author: Fulian Huang, Jialin Xie, Shijun Jie, Nattawoot Suwannata (Huang <em>et al.,</em> 2025)</p> <p><strong>7) Development and Cost-Effectiveness Analysis of a Fogging Pump Control System Commercial Prototype for Oyster Mushroom Cultivation based on Open-System Greenhouse<br /></strong>Author: Non Pinngern, Bhannawat Wanganusorn (Pinngern &amp; Wanganusorn, 2025)</p> <p><strong>8) Web Scraping-based System for E-commerce Price Comparison and Similar Product Segmentation<br /></strong>Author: Pongsin Jankaew, Wachirawut Thamviset (Jankaew &amp; Thamviset, 2025)</p> <p><strong> </strong><strong>9) A Comparative Study of Sea Lettuce Cultivation in Seawater and Scientific Saltwater using IoT Technology<br /></strong>Author: Suttipong Klongdee, Sriwaree Sujaritchai, Sommart Promput (Klongdee, Sujaritchai, &amp; Promput, 2025)</p> <p><strong>10) Utilizing Association Rule Mining to Understand Phishing Risk Awareness Levels of Thai University Academic Staff<br /></strong>Author: Pita Jarupunphol, Wipawan Buathong (Jarupunphol &amp; Buathong, 2025)</p> <p><strong>11) Approximate String Matching Algorithm using Single Inverted Lists<br /></strong>Author: Soontaree Thumsuwan, Nuanprang Sangurai, Chouvalit Khancome (Thumsuwan, Sangurai, &amp; Khancome, 2025) </p> <p><strong>12) Pneumonia Detection from Chest X-ray Images using Convolutional Neural Networks and Transfer Learning Techniques<br /></strong>Author: Pongsathorn Chedsom (Chedsom, 2025)</p> <p><strong>13) Feature Selection with Linear Discriminant Analysis to Improve the Performance of Heart Disease Classification<br /></strong>Author: Ratiporn Chanklan, Keerachart Suksut, Kedkarn Podhijittikarn (Chanklan, Suksut &amp; Podhijittikarn, 2025) </p> <p><strong>14) Information System for Wet Garbage Bin Data Management in Local Areas: A Case Study of Langu Subdistrict Administrative Organization, Satun Province<br /></strong>Author: Norathep Sakphet, Chatirot Jitrugtham, Annop Bunjan, Kullaphat Yingdumnoon, Sakan Rodklai, Chanyanuch Pumpuang (Sakphet <em>et al.</em>, 2025)</p> <p><strong>15) Rice Seed Production with Smart Farm<br /></strong>Author: chalawan Wantong, Wanida Sumranram, Utis Tahom, Varit Kitthanarut, Ekkaluk Salukkham (Wantong <em>et al.</em>, 2025)</p> <p> </p> <p>The editorial board of JIT sincerely hopes that the 15 articles published in this issue will benefit researchers and serve as a valuable source of knowledge for the advancement of their work. We believe that the insights and findings presented in this issue will contribute to academic and practical developments in the fields of informatics and technology. We warmly invite scholars, practitioners, and students to explore the articles and apply the knowledge gained to their own research and professional activities.</p> <p> </p> <p>Assoc. Prof. Olarik Surinta, Ph.D.</p> <p>Editor-in-Chief</p> Journal of Applied Informatics and Technology Copyright (c) 2025 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/263427 Thu, 07 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255097 <p>Warfarin Care emerges as a transformative solution in digital healthcare for the elderly reliant on warfarin. Addressing specific needs, Warfarin Care serves as a communication and information exchange among medical personnel, elderly patients, and family members or caregivers. With a user-friendly interface, rigorous content evaluation, and a shared database architecture, Warfarin Care endeavors to mitigate medication errors and augment overall treatment outcomes. Through the integration of risk assessment, medication history, and warfarin knowledge, medication reminders, and educational tools, the application fosters a deeper understanding of proper medication behavior. The research is based on the clinical trial, in which 60 cases of elderly patients and family members, 30 elderly patients, and 30 family members or caregivers were selected as the sample receiving treatment in the outpatient department of Sakonnakhon Hospital. The study from the clinical trial revealed that the majority of elderly participants fall within the 60–69 age group, predominantly women and married. The data reveals high satisfaction among both elderly users and caregivers, underscoring Warfarin Care's positive impact on enhancing knowledge, confidence, and support for proper medication adherence with user-friendly communication. Users agreed that the use and suitability of the Warfarin Care application had an average of 4.57 and a S.D. of 0.57 from elderly users and an average of 4.67 and a S.D. of 0.61 from caregivers or family members. The robust data analysis utilizing mean and standard deviation values underscores the application's effectiveness.</p> Narit Hnoohom, Konlakorn Wongpatikaseree, Autchariya Poungkaew, Junporn Kongwatcharapong Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255097 Mon, 23 Jun 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/254868 <p>Neck pain is an increasingly prevalent issue in the general population, leading to a growing incidence of chronic cases and potential future health risks. The economic impact is significant, as individuals with neck pain often cease working due to discomfort. Traditional assessments of treatment effectiveness involve the measurement of neck deformity and movement, typically requiring expensive and limited Cervical Range of Motion (CROM) equipment found primarily in large hospitals. The challenges posed by the COVID-19 outbreak further hinder access to such evaluations. This study proposes the development of a Virtual Reality (VR) application designed to measure neck movement range, enabling users to self-administer assessments under the guidance of the VR application. The VR application development process commences with storyboard creation, all components were designed and creates models object using Blender. The development of VR applications for angle measurement follows the storyboard, was executed using the Unity program. Prioritizing user satisfaction, the application capitalizes on the proven accuracy and reliability of VR devices. Usability experimental focused on user independence, with participants autonomously following instructional videos. Noteworthy user satisfaction, reflected in an average score of 4.36 ± 0.52, underscores the potential of the VR application in addressing neck pain symptoms. The study emphasizes meticulous design considerations, including character and scene elements, aiming to enhance user engagement and immersion in the virtual environment. Users demonstrated focused attention during the measurement process, unaffected by external factors. </p> Manatsawee Sidajan, Kawintra Sittikraipong, Peerapat Kusumannukul, Sasiwimon Pornwachirawit, Waichaya Suwannakeeree, Sutasinee Jitanan Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/254868 Mon, 23 Jun 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/254809 <p>We demonstrate a procedure exhaustively to develop an in-house application without requiring database establishment and technician using a low-to-no-code (LCNC) platform that aligns with the organization’s business case for tracking working time and leave request of employees. We developed the application using Google AppSheet and Google Sheets for data storage. The proposed application has three main functions to accurately collect a daily clock-in, clock-out, retrieve the total number of working hours in the current month, and deal with leave requests that align with the organization’s regulations. Furthermore, there are three functions for an administrative employee manage the staff’s information, generate a monthly work report, and perform leave request approvement. The application has been tested at the Artificial Intelligence Association Thailand (AIAT), where time tracking and leave request were previously managed with paper-based. The usability test shows that the staff takes on average less than 1 minute to perform a daily clock-in and clock-out, less than 2 minutes to complete a leave request as well as cancel the submitted request. The learnability test shows that the users take less than 1 minute to complete the daily working timestamp and send leave requests.</p> Sorn Tanharaphan, Thanabadee Rodvanich, Yatawee Aupasao, Natsuda Kaothanthong Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/254809 Mon, 23 Jun 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/256625 <p>The objective of this study is to compare the performance of sentiment analysis models for Thai online text using the existing PyThaiNLP libraries. For extracting text from online sources to create a dataset, the text was manually categorized into positive, neutral, and negative sentiments. Data preprocessing involved removing punctuation marks, tokenizing, removing non-Thai characters, and Bag of Words creation. The data was then divided into training and testing sets to build models using three algorithms: logistic regression, logistic regression with stochastic gradient descent (SGD), and support vector machine (SVM). Upon comparison, the logistic regression model was found to perform the best – achieving accuracy of 80.73% with a 90:10 train-test split using the newmm word tokenization tool and the augmented dictionary. The accuracy for analyzing positive sentiment was 81.10%, for neutral sentiment, 80.16%, and for negative sentiment, 80.97%.</p> Sunisa Duangtham, Setthaphong Lertritrungrot, Nattavadee Hongboonmee, Wansuree Massagram Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/256625 Mon, 23 Jun 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/254822 <p><span style="font-weight: 400;">This research paper discusses the new process for public participation of 7 local administrative organizations in Tha Wang Pha District, Nan Province in preparedness for flooding situation. Activities for the knowledge and technology transfer of a flood simulation system were conducted and attended by 50 invited representatives, who were presented with 5 questionnaires to test their acquired knowledge and skills. The willingness to apply the knowledge and skills to flood situation preparedness of their workplace or missions was analyzed through sub-questions and illustrated in a series of tables. The results showed that the contents of the knowledge sharing were comprehended between 82-90%. Following the technological workshop, the participants planned to use the knowledge to flood preparedness at 100% with measured skills at 100%. The paper concluded that 100% of the respondents agreed with the use of the flood simulation system in terms of building cooperation upon the knowledge and technology exposure, collaboration with relevant agencies, and support for the implementation of the flood simulation system. The official coordination of agencies and institutes was the key for the successfully organized activities, thus be it the new process for the focus-group public participation of local administrative organizations.</span></p> Chamnan Kumsap, Vissanu Mungkung, Lanyanat Patanan, Phimraphas Ngamsantivongsa, Arisara Charoenpanyanet, Phonpat Hemwan Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/254822 Thu, 03 Jul 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/257877 <p><span style="font-weight: 400;">This article proposes a method for categorizing Mandarin orange grades based on Chinese standards using a computer vision system that integrates both hardware and software components. A mechanical roller-flipping device adjusts the Mandarin orange's position in various orientations. Subsequently, a machine vision system acquires thirty photographs of mandarin orange skin from various viewpoints and employs many processing approaches, such as image acquisition, blob analysis, preprocessing, segmentation, and feature extraction. The process of classifying oranges involves applying techniques such as morphology, median filtering, and the Fourier transform to identify and analyze pixels that represent imperfections on the surface of the orange. Then the faulty pixels are transformed into the diameter and the area of the faults in order to classify them for grading. The experiment demonstrates that the diameter and rectangular regions can be utilized to categorize Mandarin oranges into three grades: Special Grade, Grade 1, and Grade 2. Grade 3 can be determined by measurement of the diameter and calculation of the percentage of the faulty region in the orange peel. The overall recognition accuracy by the system is 87.5%. This experimental method can accurately identify defects in the skin of oranges, reducing labor costs and the error rate of manual identification for enterprises.</span></p> Fulian Huang, Jialin Xie, Shijun Jie, Nattawoot Suwannata Copyright (c) 2025 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/257877 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255212 <p><span style="font-weight: 400;">This study proposes a commercial development model for a fogging pump control system (FPCS) for oyster mushroom cultivation in open-system greenhouses, which are the most common type of greenhouses used for mushroom cultivation in Thailand. A prototype system was developed using a commercially available controller that was modified to make it easier to produce in large quantities. The system was designed with two separate components: The first component controlled the operation of the fog pump by alternating between spraying and pausing to maintain the desired humidity. It also acted as an access point to release a Wi-Fi signal that allowed users to access the system settings via a website. The second component was installed in the mushroom greenhouse and sent weather data from sensors to the first component via Wi-Fi. The whole system does not require internet usage. The prototype system was tested in an oyster mushroom greenhouse for 60 days. The results showed that the system was easy to install and operate in commercial mushroom farms. It was also effective in controlling humidity for oyster mushroom cultivation. An economic analysis of the system showed that it could help farmers to reduce unit costs by up to 72.30%. The system also had a positive net present value (NPV) of +332,600, an internal rate of return (IRR) of 281%, and a payback period of one production cycle (2 months). These results suggest that the proposed FPCS is suitable for commercial production for controlling humidity in oyster mushroom cultivation in open-system greenhouses.</span></p> Non Pinngern, Bhannawat Wanganusorn Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255212 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/254655 <p><span style="font-weight: 400;">With the booming growth of e-commerce, finding the best deals amid a multitude of online shopping websites has become a challenge. Consumers often spend a considerable amount of time manually sifting and comparing data, leading to uncertainty in decision-making. To address this issue, our research proposes a system that utilizes web scraping techniques to identify top deals from multiple e-commerce sites. We have developed Python-based web scraping scripts and incorporated a configuration file for customization, enabling users to extract product data from diverse websites. The system scrapes data and displays result each time the user enters a query, ensuring that the scraped data is up to date. Furthermore, our system enhances the user experience by incorporating product model datasets for product identification, enabling specific searches based on product specifications, and offering recommendations for similar product models. Finally, in cases where products remain unidentified, we introduce a feature for grouping similar products through an agglomerative clustering method. This method utilizes product name and image features extracted by TF-IDF and Convolutional Neural Networks (CNN), allowing for price comparisons among similar products and enhancing the overall shopping experience. Preliminary evaluations show that our system successfully extracts data from target websites with proper customizations. The evaluations of similar product clustering demonstrate that using a combined feature of product names and images significantly improves clustering performance, surpassing the use of product names or images alone, with a 9 percent increase and 18 percent increase, respectively.</span></p> Pongsin Jankaew, Wachirawut Thamviset Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/254655 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/256295 <p><span style="font-weight: 400;">Ulva Rigida, known as sea lettuce, is a variety of marine algae that exhibits a high degree of cultivation feasibility. Sea lettuce offers numerous health benefits and is increasingly being considered as a future food source that could promote commercial cultivation. However, challenges arise in assessing the feasibility of utilizing seawater appropriately, which could be addressed by incorporating the Internet of Things (IoT) into this study. This research aims to investigate and compare the growth of sea lettuce between seawater and scientific saltwater using IoT based on temperature-controlling systems. The IoT-enabled sea lettuce cultivation system can record and display real-time data using Arduino Nano. The results show that the scientific saltwater closely approximates the properties of seawater during the 21-day cultivation period. Sea lettuce cultivated in seawater exhibited greater growth and weight gain compared to cultivation in scientific saltwater. The average weight gain per day was 3.27 grams for seawater cultivation and 2.83 grams for scientific saltwater cultivation, indicating a difference of 0.44 grams. These experimental results demonstrate the feasibility of using scientific saltwater, which exhibits properties resembling seawater. Cultivating with scientific saltwater facilitates ease of cultivation and eliminates the need for coastal locations. Additionally, it has the potential to reduce pollution in marine environments.</span></p> Suttipong Klongdee, Sriwaree Sujaritchai, Sommart Promput Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/256295 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255481 <p><span style="font-weight: 400;">This study explores the phishing risk awareness levels among academic staff at Thai universities, employing association rule mining (ARM) to identify critical factors influencing high and low levels of awareness. Targeting a diverse group of 400 academic staff members, the research utilized a structured questionnaire comprising demographic information, direct and indirect experiences with phishing, and perceptions of phishing. In association rules </span><em><span style="font-weight: 400;">(<img src="https://latex.codecogs.com/svg.image?X\Rightarrow&amp;space;Y" alt="equation" /></span></em><em><span style="font-weight: 400;">)</span></em><span style="font-weight: 400;">, a lift value of 1 indicates independence between </span><em><span style="font-weight: 400;">X</span></em><span style="font-weight: 400;"> and </span><em><span style="font-weight: 400;">Y</span></em><span style="font-weight: 400;">, while values greater than 1 or less than 1 indicate positive or negative correlation, respectively. The findings revealed several critical findings: despite being able to define phishing, many individuals do not perceive it as a significant threat; moderate internet skills are not necessarily indicative of high phishing awareness; and direct experiences with phishing do not always correlate with an increased awareness of its potential impact. These results highlight a disconnect between knowledge and perceived risk and suggest that existing internet skills and experiences are insufficient for cultivating a robust understanding of phishing risks. The study underscores the necessity for targeted educational interventions specifically designed to address the varied needs of university staff, enhancing their ability to recognize and respond to cybersecurity threats effectively. </span></p> Pita Jarupunphol, Wipawan Buathong Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255481 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/254917 <p><span style="font-weight: 400;">Approximate string matching is a fundamental technique in data retrieval that allows for typo errors or misspellings. It is widely applied in databases, search engines, and various applications or online services. To enhance the speed and accuracy of data retrieval, the development of new algorithms remains a significant challenge in computer science research. This paper introduces a novel data structure for approximate search, called the Single Inverted List</span><strong>,</strong><span style="font-weight: 400;"> which supports a configurable level of error tolerance. Based on this structure, a new approximate string matching algorithm is developed. Theoretical analysis shows that the proposed structure can be constructed with time complexity proportional to the length of the pattern string and requires storage space equal to the sum of the pattern length and the number of distinct characters. The proposed algorithm achieves search performance with time complexity proportional to the product of the text length and the pattern length, while also supporting error-tolerant matching. Experimental results demonstrate that the proposed structure consumes the least memory compared to well-known existing algorithms, and the developed algorithm performs approximate searches efficiently, nearly as fast as the fastest existing methods, while maintaining linear-time performance.</span></p> Soontaree Thumsuwan, Nuanprang Sangurai, Chouvalit Khancome Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/254917 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255187 <p><span style="font-weight: 400;">According to data from the Bureau of Epidemiology, between January 1 and October 31, 2023, a total of 239,197 cases of pneumonia or lung inflammation were reported. Over the past five years (2018–2022), the average number of cases was approximately 20,000 per month, with a continuously increasing trend</span><strong>.</strong><span style="font-weight: 400;"> Early detection and treatment of pneumonia can significantly reduce mortality rates. This study proposes a classification model for pneumonia based on chest X-ray images using Convolutional Neural Networks (CNNs), specifically the VGG16 and VGG19 architectures, in conjunction with the transfer learning technique. The Chest X-Ray Images (Pneumonia) dataset, consisting of 5,232 images (4,273 pneumonia cases and 1,583 normal cases), was used. Data augmentation techniques were applied, and the dataset was divided into 70% training, 20% validation, and 10% testing sets. The experiments were divided into two groups: Group 1 employed the VGG16 and VGG19 architectures, while Group 2 utilized these architectures with transfer learning and customized Fully Connected (FC) layers. In Group 1, the VGG16 achieved an accuracy of 95.42% with a loss value of 0.18, while VGG19 achieved an accuracy of 94.89% with a loss of 0.21. In Group 2, the best performance was achieved using the VGG16 architecture with customized fully connected (FC) layers, consisting of nine layers with 2048, 1024, 512, 256, 128, 64, 32, 16, and 8 nodes, respectively. This configuration achieved the highest accuracy of 97.83% and the lowest loss of 0.11. Compared to the VGG16, the model achieved a 2.41% improvement in accuracy and a 0.07 reduction in loss. When compared to the unmodified VGG19, accuracy improved by 2.94% and loss decreased by 0.10.</span></p> Pongsathorn Chedsom Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255187 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/256471 <p><span style="font-weight: 400;">Artificial intelligence (AI) technology has become increasingly popular and is widely applied across various fields. In the medical domain, AI has been employed to support disease diagnosis. Heart disease is a common condition that affects individuals of all genders, ages, and races, and remains a leading cause of mortality worldwide. Currently, the diagnosis of heart disease can be performed using AI by leveraging electrocardiogram (ECG) data in combination with machine learning algorithms. However, in some cases, the number of data features required is excessive, which may reduce model performance. In this research, we propose a feature selection method based on Linear Discriminant Analysis (LDA) to improve the classification accuracy of a heart disease dataset. The proposed method is compared with two other feature selection techniques: correlation-based selection and information gain. We then construct classification models using three algorithms: logistic regression, support vector machines (SVM), and artificial neural networks (ANN). The experimental results show that the proposed technique improves the average classification accuracy from 77.82% to 86.46%, representing an 11.10% increase. The highest classification accuracy of 87.39% is achieved when combining ANN with LDA. The researcher employed this technique to develop a program for assessing the risk of coronary heart disease. The program assists in screening individuals at high risk and provides users with personalized information regarding their likelihood of developing the disease.</span></p> Ratiporn Chanklan, Keerachart Suksut, Kedkarn Podhijittikarn Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/256471 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255384 <p><span style="font-weight: 400;">This research focuses on developing an information system for managing wet garbage bin data in the Langu Subdistrict Administrative Organization, Satun Province. The aim is to resolve disorganized wet garbage bin management and enhance the efficiency of local waste data administration. The research methodology consists of three key phases: analyzing system requirements, developing the system using Flutter Framework technology, and evaluating user satisfaction. Experimental results show that the developed system effectively reduces issues related to wet waste in the area, mitigates environmental impacts, and fosters greater community participation in waste management efforts. Furthermore, integrating the findings with relevant theories and previous studies underscores the critical role of innovation and modern technology in establishing sustainable local waste management solutions.</span></p> Norathep Sakphet, Chatirot Jitrugtham, Annop Bunjan, Kullaphat Yingdumnoon, Sakan Rodklai, Chanyanuch Pumpuang Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255384 Wed, 06 Aug 2025 00:00:00 +0700 https://ph01.tci-thaijo.org/index.php/jait/article/view/255470 <p><span style="font-weight: 400;">The rice production process plays a important role in determining the quality of rice seeds. However, the relatively high cost of certified seeds remains a major constraint for farmers in many areas. Consequently, a group of farmers in Ban Nong Suang formed a cooperative to produce and distribute rice seeds locally. Despite these efforts, challenges continue to exist, , particularly in managing water levels in paddy fields, which directly impact productivity. This study aims to develop a smart farming system for rice seed production by integrating Internet of Things (IoT) technology with Geographic Information Systems (GIS) to enable real-time monitoring, tracking, and control of water levels in rice fields. A mobile application with an integrated online map is used to visualize field data in real time. Farmer satisfaction with the system was assessed using a close-ended questionnaire and a Likert scale, while cost-effectiveness was analyzed by comparing implementation costs against the profits generated from rice production. The results demonstrate that the system efficiently monitors and regulates water levels. Farmers expressed a very high level of satisfaction (mean score of 4.88), particularly in relation to time savings on field management tasks. This improvement enabled farmers to allocate more time to alternative income-generating activities. Regarding cost, the average expense for smart farming equipment was 1,433 baht, with an installation cost of 1,500 baht per rai. Farmers with access to existing infrastructure, such as artesian wells, submersible pumps, and solar panels, were able to recover the investment with a profit of 3,033.33 baht per rai from cultivating just one rai of land. In contrast, farmers with only partial or no infrastructure would require a minimum of 14 rai and 23 rai, respectively, to achieve a break-even point.</span></p> chalawan Wantong, Wanida Sumranram, Utis Tahom, Varit Kitthanarut, Ekkaluk Salukkham Copyright (c) 2024 Journal of Applied Informatics and Technology https://creativecommons.org/licenses/by-nc-nd/4.0 https://ph01.tci-thaijo.org/index.php/jait/article/view/255470 Wed, 06 Aug 2025 00:00:00 +0700