International Journal of Information Technology, Research and Applications最新文献

Smart Agriculture: A Comprehensive Survey on IoT-Enabled Plant Disease Detection and Agricultural Automation 智能农业：物联网植物病害检测与农业自动化综合调查

International Journal of Information Technology, Research and Applications Pub Date : 2024-06-15 DOI: 10.59461/ijitra.v3i2.107

T. Thilagavathi, L. Arockiam, I. Priya Stella Mary

{"title":"Smart Agriculture: A Comprehensive Survey on IoT-Enabled Plant Disease Detection and Agricultural Automation","authors":"T. Thilagavathi, L. Arockiam, I. Priya Stella Mary","doi":"10.59461/ijitra.v3i2.107","DOIUrl":"https://doi.org/10.59461/ijitra.v3i2.107","url":null,"abstract":"This research paper is dedicated to the comprehensive review and discussion of diverse techniques employed in plant disease detection within the realm of agriculture. Emphasizing notable contributions and showcasing innovative methodologies, the research work takes a critical turn to address the myriad issues and challenges intricately woven into the integration of IoT data analytics in agriculture. The paper meticulously unravels the complexities associated with plant disease detection in the era dominated by IoT and data analytics. Serving as more than just a repository of current methodologies and technologies, this work actively illuminates the challenges that await further exploration. The insights derived from this exploration will provide a substantial foundation for emerging researchers. By shedding light on the evolving landscape of plant disease detection and the nuances of IoT integration in agriculture, this paper empowers researchers to actively contribute to the resilience and sustainability of agricultural practices in the face of ongoing challenges.","PeriodicalId":503010,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"8 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141337748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ensemble Approach for Predicting The Price of Residential Property 预测住宅物业价格的集合方法

International Journal of Information Technology, Research and Applications Pub Date : 2024-06-15 DOI: 10.59461/ijitra.v3i2.99

Renju K, Freni S

引用次数: 0

Integrating Technical Indicators and Ensemble Learning for Predicting the Opening Stock Price 整合技术指标和集合学习预测开盘股价

International Journal of Information Technology, Research and Applications Pub Date : 2024-06-10 DOI: 10.59461/ijitra.v3i2.96

Jency Jose, Varshini P

{"title":"Integrating Technical Indicators and Ensemble Learning for Predicting the Opening Stock Price","authors":"Jency Jose, Varshini P","doi":"10.59461/ijitra.v3i2.96","DOIUrl":"https://doi.org/10.59461/ijitra.v3i2.96","url":null,"abstract":"Accurately predicting stock prices poses a significant challenge due to the dynamic and complex nature of financial markets. This paper introduces a novel method that combines technical indicators with ensemble learning techniques to effectively forecast opening stock prices. Technical indicators offer valuable insights into market trends and patterns, while ensemble learning methods merge multiple models to enhance predictive precision. The study utilizes various technical indicators such as moving averages, Relative Strength Index (RSI), and Bollinger Bands to capture diverse aspects of market behaviour. Ensemble learning techniques like Random Forest, Gradient Boosting, Support Vector Regressor, and ARIMA model are then employed to consolidate the forecasts from these indicators. The proposed framework is assessed using historical stock market data, and extensive experiments showcase its superior performance compared to individual indicators and traditional forecasting approaches. The findings reveal that integrating technical indicators with ensemble learning leads to a significant improvement in accuracy, with a success rate of 91.45% in predicting opening stock prices, thus providing valuable insights for investors and financial analysts.","PeriodicalId":503010,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":" 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141364712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Unveiling the Best-fit Model: A Comparative Analysis of Classification Methods in Predicting Student Success 揭开最合适模型的面纱：预测学生成功的分类方法比较分析

International Journal of Information Technology, Research and Applications Pub Date : 2024-03-07 DOI: 10.59461/ijitra.v3i1.84

A. G. Daligcon, Jemima Priyadarshini, Lilibeth Rivera Decena

引用次数: 0

Analysis Of Inhibiting Factors Implementation Of Electronic Medical Records In East Pamulang Community Health Center 东帕穆兰社区卫生中心实施电子病历的阻碍因素分析

International Journal of Information Technology, Research and Applications Pub Date : 2024-03-05 DOI: 10.59461/ijitra.v3i1.85

Gama Bagus Kuntoadi1, Rita Dwi Pratiwi, Hasan Sadikin, Iah Bilqiz Khairul Barriyah, Brojo Kishore Mishra

{"title":"Analysis Of Inhibiting Factors Implementation Of Electronic Medical Records In East Pamulang Community Health Center","authors":"Gama Bagus Kuntoadi1, Rita Dwi Pratiwi, Hasan Sadikin, Iah Bilqiz Khairul Barriyah, Brojo Kishore Mishra","doi":"10.59461/ijitra.v3i1.85","DOIUrl":"https://doi.org/10.59461/ijitra.v3i1.85","url":null,"abstract":"Patient medical records in Indonesia are starting to transform into electronic-based medical records. Electronic Medical Records (EMR) are medical records created using an electronic system. It is an electronic repository of information about a patient's health status and health services throughout patient life. The impact if health services have not implemented EMR is that it could hamper patient health services. This research aims to identify factors inhibiting the implementation of EMR at the East Pamulang Community Health Center (Puskesmas). The research method used is descriptive with a qualitative approach. The research subject population was medical records officer and chief administrative officer, while the object population was the medical records, registration, clinics, laboratory, and pharmacy room. The results of the research identified several factors inhibiting the implementation of EMR, such as inadequate infrastructure, no officers with a background in medical records, and still using paper-based manual medical records. The conclusion of this research is the discovery of several factors inhibiting the implementation of EMR, human resource factors where it doesn’t yet have an officer with an educational background in medical records, the number of computers is still limited which supporting EMR in each service unit, and the electronic-based medical record applications are still not used comprehensively in the service units of the Puskesmas. Suggestions from the results of this research are that Puskesmas immediately recruits officers who have an educational background in Medical Records, increases the number of computer devices that support the implementation of EMR, and immediately implements electronic-based medical records.","PeriodicalId":503010,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"352 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140397730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of Mathematical Models in IT System Design and Optimization 数学模型对 IT 系统设计和优化的影响

International Journal of Information Technology, Research and Applications Pub Date : 2024-02-02 DOI: 10.59461/ijitra.v3i1.83

Krishnaveni Veeranan, Vaidhyanathan Pandian, Thamaraiselvi, Antonyraj Martin

引用次数: 0