Analysis of Financial Statements using the CAMEL Method to Measure the Health Level of Village Credit Institutions (LPD) at the Pakraman Penasan Village LPD, Banjarangkan District, Klungkung Regency

Pratiwi, Ni Luh Putu Nadya and Sugiarta, I Nyoman and Yintayani, Ni Nyoman (2022) Analysis of Financial Statements using the CAMEL Method to Measure the Health Level of Village Credit Institutions (LPD) at the Pakraman Penasan Village LPD, Banjarangkan District, Klungkung Regency. Repositori Politeknik Negeri Bali.

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Abstract

The Village Credit Institution (LPD) is one of the financial institutions located in Bali. The Covid-19 pandemic caused a decrease in profits in 2020 which caused an increase in the number of loans disbursed and the public experienced difficulties in paying loans. Based on this, the health level of LPD is very important to pay attention to where LPD as an institution that concerns the safety of public funds. The purpose of this study was to determine and analyze the health level of the Village Credit Institution in Pakraman Penasan Village, Banjarangkan District, Klungkung Regency during the 2019-2021 period which was reviewed using the CAMEL (Capital, Assets, Management, Earning, and Liquidity) method. This type of research is qualitative research sourced from primary data and secondary data using interview, observation and documentation techniques. In this study, it used a data validity test using triangulation. The data analysis technique used is the analysis of LPD financial statements using the CAMEL method in accordance with Bali Governor Regulation No. 44 of 2017. The results showed that the Pakraman Penasan Village LPD was in good health in 2019 and 2020 with a combined score of 2019 of 88.32%, in 2020 it was 86.67%. Meanwhile, in 2021, it is in a fairly healthy condition with a combined score of 74.57%. From the results of the study, it can be suggested for the LPD of Pakraman Penasan Village to pay attention to the distribution of loans given, one of which is with the 5C and 3R principles in analyzing customers who will be given credit so that bad loans or non-performing loans can be overcome.

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