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IJOT
Published by Research Parks Publishing
ISSN : 26157071     EISSN : 26158140     DOI : https://doi.org/10.31149/ijot.v4i5
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
International Journal on Orange Technologies (IJOT) is an online international peer-reviewed journal that publishes high-quality original scientific papers, short communications, correspondence, and case studies in areas of research, development, and applications of orange technology and engineering. Review articles of current interest and high standards may be considered. Only those manuscripts are considered for publication, the contents of which have not been published and are not being considered for publication in any other journal. The journal focuses on various learning and investigation areas to reach better excellence in research development as a whole.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 831 Documents
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Influence of the Composition of the Mixture and the Type of Processed Fibers on the Quality Indicators of Fabrics Patxullayev S.; Mengnarov Sh.S.; Ismoilov D.A.
International Journal on Orange Technologies Vol. 6 No. 1 (2024): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v6i1.5279

Abstract

This article presents the results of studies to determine the influence of the type of fibers and recycled fibrous waste on the quality indicators of fabric. For this purpose, in production conditions, a sliver with a linear density of 5000 tex was obtained on a JFA-226 carding machine, and in the laboratory of the Department of Spinning Technology, slivers were also obtained in three versions on an HSR-1000 brand draw machine. To obtain twill weave fabric on a Picanol loom, warp threads were mixed with yarn consisting of 100% cotton, and weft thread was mixed with yarn consisting of recycled fibers and the quality parameters of the fabric were examined.
News-Buffet: A Global News Aggregator for Real-Time, Location-Based Updates Rajest, S. Suman; Regin, R.
International Journal on Orange Technologies Vol. 6 No. 2 (2024): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v6i2.5306

Abstract

Mobile devices have become indispensable instruments for staying current, thanks to the revolutionary change brought about by the rapid rise of technology. With an emphasis on giving users real-time access to worldwide news in an engaging and aesthetically pleasing format, this Android news app is meant to bring the latest news from more than 120 newspapers across 50+ countries. This app fills a need in the media application industry by providing quick access to news stories, which is becoming increasingly important as mobile internet usage continues to rise. One of the app's strongest points is how well it compiles and displays news stories from around the world. To keep the platform current and relevant, it has an admin interface for managing news that writers or admins can use to add, edit, or remove content. Also, users can get news stories that are particular to their area thanks to a module that uses their current location. This function, together with the app's built-in ad choices, shows how the app may be a great tool for brand marketing by letting companies advertise their wares within the news stories themselves. In order to guarantee the system's ongoing growth and relevance, this research application system conducts literature studies, market research, and comparative analysis to examine future development trends and strategies for media apps.
Big Data Enables E-Government to Implement Sustainable Development Al Qudah, Mohammad Ali; Muradkhanli, Leyla; Weshah, Hadeel Abdullah; Hamdan, Hala; Abuhashish, Mutaz Mohammed
International Journal on Orange Technologies Vol. 6 No. 3 (2024): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v6i3.5323

Abstract

This study explores the theoretical foundations of artificial intelligence (AI) and big data, focusing on their role in the Fourth Industrial Revolution and sustainable development. Despite growing recognition of big data’s transformative potential, there is limited understanding of its specific impact on decision-making and societal transformation towards achieving sustainable development goals (SDGs). The research aims to fill this gap by analyzing how big data can support e-government initiatives and development objectives. Using a descriptive and analytical methodology, including a case study approach, the study examines the primary techniques and projects that facilitate large-scale data analysis in digital transformation. Results reveal that big data plays a critical role in monitoring progress, informing decisions, and driving social change aligned with SDGs. These findings contribute to a better understanding of big data’s value in modern governance and sustainable development efforts.
Sentiment-Enhanced Stock Price Prediction Using LSTM and Machine Learning Techniques S. Saranya; Anjugam Subramani; C. Elayaraja; M. Pandi Maharajan
International Journal on Orange Technologies Vol. 7 No. 1 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i1.5408

Abstract

The stock market is highly complex and volatile, influenced by both positive and negative sentiments shaped by media releases. Accurate stock price analysis depends on the ability to recognize stock movements and identify underlying trends. Stock price prediction has long been an active area of research, but achieving ideal precision remains a challenging task. This paper proposes a combined approach that leverages efficient machine learning techniques alongside deep learning, specifically Long Short-Term Memory (LSTM) networks, to predict stock prices with greater accuracy. Sentiments derived from news headlines significantly impact traders' buying and selling decisions, as they tend to be influenced by the media. By integrating sentiment analysis with traditional technical analysis, we aim to enhance prediction accuracy. LSTM networks are particularly effective for learning and predicting temporal data with long-term dependencies. In our approach, the LSTM model utilizes historical stock data in conjunction with sentiment data from news items to build a more robust predictive model. This fusion of sentiment and technical analysis can improve the model's ability to predict stock price movements, offering a more comprehensive and accurate prediction mechanism for stock market behavior.
Detection of DDoS Attacks in Software-Defined Networks Using Random Forest Classifier M. Gandhi; J. Jayaprakash; P. Mahendran; K. Lachimipriya
International Journal on Orange Technologies Vol. 7 No. 1 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i1.5409

Abstract

Distributed Denial of Service (DDoS) attacks are a major concern in today's linked world because they can compromise the availability and security of networks. We offer a new method for detecting DDoS attacks in real-time by utilising machine learning, more especially the Random Forest algorithm, to counter this threat. Our solution is designed to be easily integrated into web settings using the widely used Streamlit framework. It offers users a user-friendly and interactive platform to keep an eye out for and deal with any risks. Our first step is to compile a large dataset that includes characteristics of network traffic that have been retrieved from both legitimate and malicious sources. The data is prepared for training and evaluation through feature engineering and careful preparation. We build a prediction model that can distinguish between typical traffic patterns and abnormal ones that indicate DDoS attacks using the Random Forest algorithm, which is known for being robust and scalable. To prove its effectiveness in identifying and categorising DDoS attacks with little false positives, the created model is subjected to thorough testing using well-established performance measures. In addition, we improve the model's accessibility and usability by integrating it easily into a web application that is built on Streamlit. With the model displaying great accuracy and efficiency in real-time circumstances, our testing results demonstrate promising detecting capabilities. In ever-changing web environments, our solution helps to strengthen network resilience and protects against disruptive cyber threats by giving stakeholders proactive DDoS mitigation capabilities.
Study of Augmented Reality Based Applications in Education Pal Yadav, Amar; Singh, Sachin; Chaudhary, Manish
International Journal on Orange Technologies Vol. 7 No. 2 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i2.4214

Abstract

A technology known as augmented reality mixes and communicates with both virtual and actual situations. Applications for augmented reality are being used in many industries, but education is the most significant. We can combine actual and virtual information, augmented reality (AR) technology helps kids study while strengthening their connection to their physical surroundings. Virtual reality technology, which is still in development, enables students to learn challenging subjects in a pleasant and simple method. Students can learn more about the objects by interacting with them in virtual environments. We can organise virtual excursions to museums and zoos in a completely different nation and work with teacher as if they were physically present. The use of augmented reality technology in various facets of education was demonstrated in this context. According to the recommendations offered at the end of the research, educators should carefully investigate prepared portions and practise them in their classes.
Soaring Fuel Prices: Sentiments of Filipinos on Excise Tax Caballo, John Harry; G. Baradillo, PhD, Danilo
International Journal on Orange Technologies Vol. 7 No. 2 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i2.4931

Abstract

This study analyzed the sentiments of 100 Facebook comments on excise tax using Orange Software. Using the word cloud feature, the top 10 are chosen from the list of frequently used words with at least fifteen instances in the hundred Facebook comments. In the sentiment analysis, the Facebook comments were analyzed as positive, negative, or neutral. Based on the results, 52% of the comments showed positive sentiment, 41% displayed negative sentiment, and 7% expressed neutrality on the issue. In the qualitative analysis of the sentiments, two positive sentiments were extracted, which are: excise tax aids the operations of the government and excise tax subsidizes the transport and business sector. For the negative sentiments, three themes were extracted: excise tax suspension addresses inflation, the government has no concern for its citizens, and leaders are ineffective and corrupt. Positive sentiments demonstrate public support for the excise tax. It is considered essential for government revenues, and suspending it could have significant economic consequences. However, negative sentiments stem from concerns about inflation, distrust in leadership, and perceptions of corruption within the government.
Error Correction Strategies and Writing Competency of Senior High School Students Navarro, Ana Louella; Caballo, John Harry; Ngo, Cristy Grace
International Journal on Orange Technologies Vol. 7 No. 2 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i2.4947

Abstract

This study aimed to unravel the relationship between error correction strategies and writing competency of students. There were 120 Humanities and Social Sciences senior high school students from three different schools in Davao City who were chosen as respondents using a purposive sampling technique. The students were asked to write a 10-sentence essay, 60 of which were corrected using Selective Direct Feedback and the other half with Selective Indirect Feedback. The researcher sought help from interraters who used a 5-point rubric in checking three areas of grammar: subject-verb agreement, tenses, and connectives. Three statistical tools were used: Mean Scores, T-test for dependent samples, and T-test for independent samples. Results revealed that before the use of the two strategies in the first set of output there were several errors in the written outputs, In the second set, after the use of the Selective Direct Feedback and Selective Indirect Feedback, there were fewer errors found in the essay. However, the reductions in errors were not significantly different between the two feedback methods.
Analysis of The Stochastic Model of Epidemic Malaria Transmission With Discrete Time Markov Chain in Gedebgie, Ethiopia Belay, Zemenu; Wassie, Aman
International Journal on Orange Technologies Vol. 7 No. 1 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i1.5109

Abstract

Malaria is an infectious disease caused by the Plasmodium parasite and transmitted between humans through bites of female Anopheles mosquitoes. This thesis modifies the SIR model to predict the spread of malaria in Gedebgie using the data from Gedebgie health station. A stochastic model describes the dynamics of malaria and human population compartments in terms of stochastic and deterministic equations and these equations represent the relations between relevant properties of the compartments. The aim of the study is to understand the important parameters in the transmission and spread of epidemic malaria disease. Our results show that the reproduction number R0, is less than 1, so that the disease dies out and the probability of an outbreak is zero. Numerical simulations have been carried out applying the numerical software Matlab and python. These simulations show the behavior of the infected population in time. From the analysis and discussions of the model, SIR model is a good model to study the spread of malaria in Gedebgie.
Use of Carbon Nano Particles in Concrete Kumar, Mr. Sameer; Kumar, Dr. Ajay
International Journal on Orange Technologies Vol. 7 No. 1 (2025): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v7i1.5275

Abstract

Over the past 100 years, RCC has been used in construction projects. RCC has been used most extensively in India for the past 50–60 years. We have built a great deal of infrastructure over this time, including buildings, bridges, sports stadiums, and other structures that are essential to a civilized society. These were created with massive resource speculation. Not even the notion of developing such resources from our meager national resources can occur to us. Therefore, keeping them in operational condition is crucial. This study investigated how to improve the mechanical properties of Portland cement concrete as a building material by utilizing nanotechnology-based nano-elements, such as carbon nanotubes (CNTs) & nanofibers (CNFs), as reinforcement or filler. CNTs and CNFs have been used as excellent R/Fs in enhancing the mechanical and physical properties of polymer, metallic, and ceramic composites because of their extremely high aspect ratios and ultra-high strength. The application of nano-elements in the building sector has received very little research attention. Consequently, the goal of this thesis was to close the knowledge gap between nanomaterials and building supplies. This was accomplished by utilizing cutting-edge methods to test the incorporation of CNTs and CNFs in regular Portland cement paste. Various mixes with varied concentrations of CNTs or CNFs were prepared in fixed proportions (e.g., water-to-cement ratio, air content, admixtures). Various methods that are frequently employed in current research to assess the CNTs' strength CNT strengths are ascertained by running the cube analysis test, entering the results into the Etabs Model, and comparing the results to find the difference. After Test & Evaluation on CNTs cube test results with adding of 0.2wt.% by weight of cement, create a computer-based software model & compare normal strength as well as Strength with carbon nanotubes (CNTs) & nanofibers (CNFs). Also, all possible compare taken care like base share match, R/F consumption, cost analysis, etc.

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