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Analysis of Rainfall Data Compatibility from 1991 to 2020 with the Balinese Sasih Calendar in Bali Province

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This study aims to analyze the alignment between the traditional Balinese Sasih calendar system and observed rainfall data from BMKG across the Province of Bali for the period 1991–2020. Sasih, a form of local wisdom, has long been used by Balinese farmers as a guide for determining planting times. In this study, the Gregorian calendar was converted into the Sasih system to synchronize rainfall and rainy days data based on Sasih periods. Rainfall data were categorized according to BMKG classification standards for both monthly rainfall totals and the number of rainy days per month. A contingency table method was used to calculate the accuracy between Sasih-based predictions and observed BMKG data. The results show that the accuracy of Sasih in predicting the number of rainy days was higher (average 62%) than its accuracy in predicting total monthly rainfall (average 37%). This indicates that the Sasih calendar is more relevant in representing rainfall frequency rather than rainfall intensity. The spatial distribution of accuracy shows that highland regions such as Jembrana and Tabanan demonstrated better agreement compared to the southern coastal and central lowland areas. Although the overall accuracy is not optimal, these findings highlight the importance of integrating local knowledge systems like Sasih with modern climate data to support sustainable agricultural planning in Bali.
Title: Analysis of Rainfall Data Compatibility from 1991 to 2020 with the Balinese Sasih Calendar in Bali Province
Description:
This study aims to analyze the alignment between the traditional Balinese Sasih calendar system and observed rainfall data from BMKG across the Province of Bali for the period 1991–2020.
Sasih, a form of local wisdom, has long been used by Balinese farmers as a guide for determining planting times.
In this study, the Gregorian calendar was converted into the Sasih system to synchronize rainfall and rainy days data based on Sasih periods.
Rainfall data were categorized according to BMKG classification standards for both monthly rainfall totals and the number of rainy days per month.
A contingency table method was used to calculate the accuracy between Sasih-based predictions and observed BMKG data.
The results show that the accuracy of Sasih in predicting the number of rainy days was higher (average 62%) than its accuracy in predicting total monthly rainfall (average 37%).
This indicates that the Sasih calendar is more relevant in representing rainfall frequency rather than rainfall intensity.
The spatial distribution of accuracy shows that highland regions such as Jembrana and Tabanan demonstrated better agreement compared to the southern coastal and central lowland areas.
Although the overall accuracy is not optimal, these findings highlight the importance of integrating local knowledge systems like Sasih with modern climate data to support sustainable agricultural planning in Bali.

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