ANALYSIS OF THE IMPACT OF CLIMATE VARIABLES ON BANJARBARU CITY RAINFALL

Changes in weather and climate have a negative impact on agricultural production, fisheries, and development in Banjarbaru City. An important indicator of weather and climate is rain. Using multiple regression analysis modeling, the goal of this study was to determine the magnitude of climate influences (air pressure, air temperature, air humidity, and wind speed) on rainfall, as well as the relationship between free variables and bound variables. A regression and significance analysis was performed using the SPSS program, with data on daily climate variables averaging 5 years. Multiple linear regression equation modeling was obtained after analysis: = 5063,775 - 5,235X1 + 0,633X2 + 2,930X3 – 0,328X4. And for significance analysis, partial test results were obtained where the significance values of air pressure and air humidity were respectively 0,041 and 0, 038 less than the values = 5%, meaning that they significantly affect the high and low rainfall, and from the simultaneous test results, all variables simultaneously affect the rainfall because the significance value is 0,017 less than the value = 0,05. Keywords: Climate Influences, Rainfall, Regression, Significance, Banjarbaru

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Publication Details

Journal
CERUCUK
Published
2024-09-05
DOI
https://doi.org/10.20527/crc.v8i1.13374
Primary Topic
Water and Land Management
Type
article
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article

ANALYSIS OF THE IMPACT OF CLIMATE VARIABLES ON BANJARBARU CITY RAINFALL

Amin Dawamudin
CERUCUK
Water and Land Management
article

ANALYSIS OF THE IMPACT OF CLIMATE VARIABLES ON BANJARBARU CITY RAINFALL

Amin Dawamudin
article en

Abstract

Changes in weather and climate have a negative impact on agricultural production, fisheries, and development in Banjarbaru City. An important indicator of weather and climate is rain. Using multiple regression analysis modeling, the goal of this study was to determine the magnitude of climate influences (air pressure, air temperature, air humidity, and wind speed) on rainfall, as well as the relationship between free variables and bound variables. A regression and significance analysis was performed using the SPSS program, with data on daily climate variables averaging 5 years. Multiple linear regression equation modeling was obtained after analysis: = 5063,775 - 5,235X1 + 0,633X2 + 2,930X3 – 0,328X4. And for significance analysis, partial test results were obtained where the significance values of air pressure and air humidity were respectively 0,041 and 0, 038 less than the values = 5%, meaning that they significantly affect the high and low rainfall, and from the simultaneous test results, all variables simultaneously affect the rainfall because the significance value is 0,017 less than the value = 0,05. Keywords: Climate Influences, Rainfall, Regression, Significance, Banjarbaru

CERUCUKVol. 8(1)
Climate action
Openalex Percentile: Top 63%
Water and Land Management
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