BibTex Citation Data :
@article{JM859, author = {wahyu wibowo and gangsar kurniawan}, title = {PENGGUNAAN REGRESI LOGISTIK STEPWISE DAN ALGORITMA GENETIKA DALAM PEMILIHAN RASIO KEUANGAN YANG BERPENGARUH TERHADAP RATING ISSUER}, journal = {MATEMATIKA}, volume = {10}, number = {1}, year = {2011}, keywords = {}, abstract = { Obligation is one of the financial instruments that can be traded in stock exchange. To help investors, an obligation has rating that shows its prospect. Obligation rating is influenced by many factors. This research will study the effects of financial ratio to rating. Unfortunately, there are many financial ratios that influence rating, so selection to financial ratio must be done. For this purpose, two methods will be applied, i.e stepwise logistics regression and genetics algorithm-artificial neural network. The result shows, that for stepwise logistic regression correctly gives classification 71%, and genetics algorithm 100% training data. For testing data, both methods give the same result, 62% correctly. Genetics algorithm results selected financial ratio more better than stepwise logistic regression. }, url = {https://ejournal.undip.ac.id/index.php/matematika/article/view/859} }
Refworks Citation Data :
Obligation is one of the financial instruments that can be traded in stock exchange. To help investors, an obligation has rating that shows its prospect. Obligation rating is influenced by many factors. This research will study the effects of financial ratio to rating. Unfortunately, there are many financial ratios that influence rating, so selection to financial ratio must be done. For this purpose, two methods will be applied, i.e stepwise logistics regression and genetics algorithm-artificial neural network. The result shows, that for stepwise logistic regression correctly gives classification 71%, and genetics algorithm 100% training data. For testing data, both methods give the same result, 62% correctly. Genetics algorithm results selected financial ratio more better than stepwise logistic regression.
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