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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Sindhuja Manickavasagam
Rajalakshmi Engineering College
Computer Science & IT Engineering

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A comprehensive analysis of consumer decisions on Twitter dataset using machine learning algorithms Vigneshwaran Pandi; Prasath Nithiyanandam; Sindhuja Manickavasagam; Islabudeen Mohamed Meerasha; Ragaventhiran Jaganathan; Muthu Kumar Balasubramanian
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1085-1093

Abstract

An exponential growth posting on the web about the product reviews on social media, there has been a great deal of examination being done on sorting out the purchasing behaviors of the client. This paper depends on utilizing twitter for sentiment analysis to comprehend the customer purchasing behavior. There has been a significant increase in e-commerce, particularly in persons purchasing products on the internet. As a result, it becomes a fertile hotspot for opinion analysis and belief mining. In this investigation, we look at the problem of recognizing and anticipating a client's purchase goal for an item. The sentiment analysis helps to arrive at a more indisputable outcome. In this study, the support vector machine, naive Bayes, and logistic regression methods are investigated for understanding the customer's sentiment or opinion on a specific product. These strategies have been demonstrated to be genuinely for making predictions using the analysis models which examine the client's conclusion/sentiment the most precisely. The exactness for each machine learning algorithm will be analyzed and the calculation which is the most precise would be viewed as ideal.
A comparative and comprehensive study of prediction of Parkinson’s disease N. Prasath; Vigneshwaran Pandi; Sindhuja Manickavasagam; Prabu Ramadoss
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1748-1760

Abstract

Objectives: Parkinson's Disease (PD) is a form of neurodegenerative disease that is caused the progressive weakening of dopaminergic nerve cells that affects a large number of people around the world.  The event of recent treatment methods principally depends upon the experimental data resulting from assessment balances and patients’ journals that take varied boundaries with reference to legitimacy, inter-rater inconsistency, and incessant monitoring. Methods: Nowadays various techniques and algorithms are utilized in predicting the accuracy in PD. A range of those techniques, including SVM, Artificial Neural Network, Naive Bayes, Kernel based extreme learning through subtractive clustering landscapes, Random Forest, The Multi-Layer Perceptron with Back-Propagation Learning Algorithm are widely applied to form the acceptable decision accurately. During this work, and in-depth review was administered on various techniques proposed by numerous researchers. a replacement system must be proposed which uses DL techniques and considers other attributes of paralysis agitans which can improve the prediction and be an advancement within the medical field. Result: It has been observed that many researches have been done in identifying the PD yet there is a need of suitable method or algorithm to improve the prediction of PD which will help in the clinical management. Conclusion and Future work: Most of the methods have used speech as a major attribute for their research and have produced substantial accuracy. In order to increase the precision approaches involving movements, facial expression and other attributes also be considered for evaluation
Co-Authors Islabudeen Mohamed Meerasha Muthu Kumar Balasubramanian N. Prasath Prabu Ramadoss Prasath Nithiyanandam Ragaventhiran Jaganathan Vigneshwaran Pandi Vigneshwaran Pandi