Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Contemporary accession for GST using K-means algorithm and data mining
PaperId: :  9487
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 5 Issue 1 2019
DUI:    16.0415/IJARIIE-9487
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Dnyanesh JindamMarathwada Mitra Mandal's Institute of Technology
Akshay GaikwadMarathwada Mitra Mandal's Institute of Technology
Aishvarya PatilMarathwada Mitra Mandal's Institute of Technology
Namrata MasihMarathwada Mitra Mandal's Institute of Technology
Swapnil ChaudhariMarathwada Mitra Mandal's Institute of Technology

Abstract

Computer Engineering
GST (Goods and service tax), K-Means clustering
GST application is an electronic application which is utilized to make mindfulness in the general public about the GST standards and the different taxes which have been actualized in each product. Goods and services tax which is typically called as GST is a taxing system executed by the present government with the goal of diminishing the tax complexity in the system. The goods and service tax is aimed at making a single unified marketplace that is intended to make a valuable situation for both the corporate and public sector. The tax replaced existing multiple cascading taxes levied by the central and state governments. Goods and services are partitioned into five expense sections for collection of tax - 0%, 5%, 12%, 18% and 28%. However, Petroleum products, alcoholic drinks, electricity, are not taxed under GST and rather are taxed independently by the individual state governments, according to the past expense routine. There is an uncommon rate of 0.25% on rough precious and semi-precious stones and 3% on gold. In addition a cess of 22% or other rates on top of 28% GST applies on couple of things like aerated drinks, luxury cars and tobacco products. Pre-GST, the statutory assessment rate for most merchandise was about 26.5%, Post-GST, most merchandise are relied upon to be in the 18% tax range.The tax rates, rules and regulations are governed by the GST Council which consists of the finance ministers of centre and all the states. The system uses K Means Clustering method which is a type of data analysis technique. Cluster an analysis does the task of grouping a set of the element in a way that similar types of elements are placed in clusters. The algorithm works sequentially to assign data point to one of the K groups.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. "Contemporary accession for GST using K-means algorithm and data mining" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 1 2019 Page 537-541
MLA Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. "Contemporary accession for GST using K-means algorithm and data mining." International Journal Of Advance Research And Innovative Ideas In Education 5.1(2019) : 537-541.
APA Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, & Swapnil Chaudhari. (2019). Contemporary accession for GST using K-means algorithm and data mining. International Journal Of Advance Research And Innovative Ideas In Education, 5(1), 537-541.
Chicago Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. "Contemporary accession for GST using K-means algorithm and data mining." International Journal Of Advance Research And Innovative Ideas In Education 5, no. 1 (2019) : 537-541.
Oxford Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. 'Contemporary accession for GST using K-means algorithm and data mining', International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 1, 2019, p. 537-541. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Contemporary_accession_for_GST_using_K_means_algorithm_and_data_mining_ijariie9487.pdf (Accessed : 22 May 2020).
Harvard Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. (2019) 'Contemporary accession for GST using K-means algorithm and data mining', International Journal Of Advance Research And Innovative Ideas In Education, 5(1), pp. 537-541IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Contemporary_accession_for_GST_using_K_means_algorithm_and_data_mining_ijariie9487.pdf (Accessed : 22 May 2020)
IEEE Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari, "Contemporary accession for GST using K-means algorithm and data mining," International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 1, pp. 537-541, Jan-Feb 2019. [Online]. Available: https://ijariie.com/AdminUploadPdf/Contemporary_accession_for_GST_using_K_means_algorithm_and_data_mining_ijariie9487.pdf [Accessed : 22 May 2020].
Turabian Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. "Contemporary accession for GST using K-means algorithm and data mining." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 5 number 1 (22 May 2020).
Vancouver Dnyanesh Jindam, Akshay Gaikwad, Aishvarya Patil, Namrata Masih, and Swapnil Chaudhari. Contemporary accession for GST using K-means algorithm and data mining. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2019 [Cited : 22 May 2020]; 5(1) : 537-541. Available from: https://ijariie.com/AdminUploadPdf/Contemporary_accession_for_GST_using_K_means_algorithm_and_data_mining_ijariie9487.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 5/22/2020 3:56:47 AM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Autoimmune Disease Detection in women Using Machine Learning Approachcomputer science EngineeringJ. L. V. S. Download
Medicine Overdose Detection System Using Machine LearningComputer Science EngineeringDr.Somashekhar B M Download
Home Price Prediction Using Machine LearningComputer Science & Engineering G Tushar Download
Heat diseases prediction using machine learningComputer EngineeringProf. Meghashree M B Download
GRIDSHIELD AIComputer EngineeringDr. Archana B Download
Diabetic Retinopathy Detection with AI InsightsComputer EngineeringJay Mahesh Gurav Download
Personalized Fitness Segmentation with Actionable InsightsMachine LearningAnju Tiwari Download
Sentiment-Based Machine Learning Approach for Mapping Citizen ProblemsComputer science and EngineeringDr. Madhu B K Download
Deligro: A Dual-Purpose Web Platform for Food Ordering and Leftover Food Donation ManagementComputer Science EngineeringRakesh Reddy K Download
AI-RATIONMITRA: SMART PUBLIC DISTRIBUTION THROUGH AI AND IOTComputer Science and EngineeringDr. Madhu B K Download
Driver Drowsiness Detection System Using OpenCV And IOTComputer Science And EngineeringAkshay Amrutkar Download
Stock Sense: Deep Learning based stock-market prediction toolComputer Science and Engineering (Data Science)Meet Manoj Agarwal Download
Glaucoma prediction using machine learningComputer Science Engineering Prof. Vinutha N Download
AN AI POWERED MENTAL HEATH AND WELLNESS COMPAIONComputer Science EngineeringDr . Archana B Download
PREDICTING GENETIC VARIANTS PATHOGENECITYComputer EngineeringSyed Arbeena Kausar Download
12