Identify Company Insolvency Using Multiple Linear Regression Algorithms

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Authors

    Deny Haryadi( 1 ) Arif Rahman Hakim( 2 ) Dewi Marini Umi Atmaja( 3 ) Amat Basri( 4 ) Risma Adisty Nilasari( 5 )

    (1) Universitas Telkom | Indonesia
    (2) Universitas Medika Suherman | Indonesia
    (3) Universitas Medika Suherman | Indonesia
    (4) Universitas Buddhi Dharma | Indonesia
    (5) Universitas Duta Bangsa Surakarta | Indonesia

Abstract

Corporate bankruptcy can hurt the company and affect the state of the economy. Therefore, many interested parties want to know the business situation related to the company. These parties include creditors, auditors, shareholders, and management itself who have an interest in knowing the state of the company in the context of bankruptcy. The past financial statements of a company can be used to predict future financial conditions using report analysis techniques. In the risk assessment process, expert knowledge is still seen as an important task, because expert predictions are subjective. This study aims to predict the bankruptcy of the company using influencing factors such as the level of research and development costs, the growth rate of total assets, and the current asset turnover rate. The method used in this research is the prediction method using the Linear Regression Algorithm. Based on the test results show that the variables or attributes used in this study have a significant effect, as evidenced by using a linear regression algorithm to be able to produce a Root Mean Squared Error value: 0.162 +/- 0.000.

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