Prediction of financial distress: Analyzing the industry performance in stock exchange market using data mining

Clicks: 182
ID: 69849
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Star

Ranked #2 of 2 articles by views in 2019 16th international conference on service systems and service management, icsssm 2019

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract is not available for this article.
Login to Search Abstract
Reference Key
putri2019prediction2019 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Putri, H.
Journal 2019 16th international conference on service systems and service management, icsssm 2019
Year 2019
DOI
10.1109/ICSSSM.2019.8887824
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.