Journal of Ubiquitous Computing and Communication Technologies
IRO Journals
Volume 6 — Issue 1 — March 2024

AI-Driven Exploration and Prediction of Company Registration Trends with Registrar of Companies (RoC)

https://doi.org/10.36548/jucct.2024.1.006
Ramya Venkatakrishnan
Department of Computer Science and Engineering, University College of Engineering, Villupuram, TamilNadu, India-605103
Mohanavarshini Sivagurunathan
Department of Computer Science and Engineering, University College of Engineering, Villupuram, TamilNadu, India-605103
Lalitha Siva
Department of Computer Science and Engineering, University College of Engineering, Villupuram, TamilNadu, India-605103
Subiksha Subramani
Department of Computer Science and Engineering, University College of Engineering, Villupuram, TamilNadu, India-605103
Arjun Paramarthalingam
Department of Computer Science and Engineering, University College of Engineering, Villupuram, TamilNadu, India-605103
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How to Cite

Venkatakrishnan, Ramya, Mohanavarshini Sivagurunathan, Lalitha Siva, Subiksha Subramani, and Arjun Paramarthalingam. 2024. “AI-Driven Exploration and Prediction of Company Registration Trends With Registrar of Companies (RoC)”. Journal of Ubiquitous Computing and Communication Technologies 6 (1): 64-75. https://doi.org/10.36548/jucct.2024.1.006.
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Keywords

— Company Registration Trends
— Registrar of Companies (Roc)
— Exploratory Data Analysis
— Predictive Analytics
— Machine Learning Algorithms
— Weka
— Tableau Visualization
Published: 02-05-2024

Abstract

This study presents a comprehensive analysis of company registration trends in India, focusing on data sourced from the Registrar of Companies (RoC). The study investigates the temporal patterns of company registrations, emphasizing principal business activities and classifications into public and private sectors. Leveraging advanced data pre-processing techniques, The Study explores the spatial and temporal dynamics of company registrations. Furthermore, a suite of machine learning algorithms, including Linear regression, Decision tree, Random Forest, GBM, SVM, KNN, Naive Bayes, and Weka, is employed to predict future registration trends. Visualization of insights is facilitated through the use of Tableau. The findings provide valuable insights for stakeholders in business, policy, and investment sectors, aiding informed decision-making and strategic planning.

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