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JABM JOURNAL of ACCOUNTING - BUSINESS & MANAGEMENT
Published by STIE Malangkucecwara
ISSN : 0216423X     EISSN : 26222167     DOI : -
Core Subject : Economy, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Other
Journal of Accounting, Business and Management (JABM) provides a scientific discourse about accounting, business, and management both practically and conceptually. The published articles at this journal cover various topics from the result of particular conceptual analysis and critical evaluation to empirical research. The journal is also interested in contributions from social, organization, and philosophical aspects of accounting, business and management studies. JABM goal is to advance and promote innovative thinking in accounting, business and management related discipline. The journal spreads recent research works and activities from academician and practitioners so that networks and new links can be established among thinkers as well as creative thinking and application-oriented issues can be enhanced. A copy of JABM style guidelines can be found inside the rear cover of the journal. The Journal of Accounting, Business and Management (JABM) is published twice a year that is in April and October
Arjuna Subject : -
Articles 11 Documents
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Search results for , issue "Vol 30 No 2 (2023): October" : 11 Documents clear
Can the WEKA Data Mining Tool be Used in Developing an Economic Growth Model? Zahid B Zamir
Journal of Accounting, Business and Management (JABM) Vol 30 No 2 (2023): October
Publisher : STIE Malangkucecwara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31966/jabminternational.v30i2.919

Abstract

WEKA is a free and open source software program that is written in JAVA™ language and contains GUI for interacting with data files and produces visual results. Although conventional economic theories assert that inflation and economic growth are negatively related, researchers found throughout the last 5 decades using different models and datasets, in favor and against that conventional beliefs. To help predict the expected economic growth or Inflation using 7 attributes such as: war, totch, pssurp, drelief, inflation, invsh, and growth found in the World Bank dataset (link was provided above), three models/algorithms and 2 testing options were used to find out the best model for decision support. As far as the Correlation Coefficient or measurement of how well the predicted values from a forecast model "fit" with the real-life data is concerned, Linear regression algorithm seems to predict the expected growth much better than other two algorithms in this study namely ZeroR and REPTree using both 10 fold cross validation as well as 75 percentage split test options.

Page 2 of 2 | Total Record : 11

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