CHANGE OF MAXIMUM RAIN PATTERN BASED ON RAINFALL DATA OF BANJARBARU CLIMATOLOGY STATION CAUSED BY CLIMATE CHANGE

According to the World Meteorological Organization that 2014 was the hottest year in which the hot weather alternated with high rainfall and floods which destroyed the people's economy. Banjarbaru, as one of the central cities of the government of South Kalimantan Province, has a topographic condition that is at an altitude of 0-500 m above sea level, causing rainfall, which is enough frequent. Banjarbaru itself is one of the cities affected by climate change in 2014. Disasters that occurred in the form of flooding at several points of residents and also crippled traffic at that time. Thus, it is important to know the pattern of maximum rainfall changes that occur. By knowing the pattern of maximum rainfall changes, the impact of the high rainfall that can occur will be minimized and can even be anticipated as early as possible. Data processing is performed with maximum daily rainfall data of 30 years and divided into a database before and after climate change that is 25 years old data and 5 years of new data. Each database calculates the planned rainfall for the return period of 2-1000 years with the distribution obtained from the analyzed database. Next, analyze the deviation of the two data. The purpose of analyzing the deviation of old data and new data is to determine changes in the planned rainfall from both data. Deviation analysis uses the Peak-Weight Root Mean Square Error function. The conclusion of the analysis is that based on the Statistical Parameters test, the Chi-Square test, and the Smirnov-Kolmogorov test on the old database using the Gumbel distribution and the new data using the Pearson Log Type III distribution for the calculation of the planned rain. Based on the analysis of the rain plan to get new data 5 years has the results of the rain plan is greater than the old data of 25 years and the analysis of the deviation to get the results of the new data 5 years has a greater value of deviation each time when revisiting the old data of 25 years. So it can be suggested that rainfall data with the same characteristics, can use 5 years of new data for the analysis of water building planning.


I. INTRODUCTION
Indonesia is a country that has a tropical climate, where the most influential climate parameter is rainfall. The rainy season that occurs will vary by region, depending on the altitude, climate, and other factors. Rainfall patterns in Indonesia are generally dominated by monsoons, which are characterized by a significant difference between the rainy season and the dry season. Climate elements such as rainfall become a natural resource that is needed by living things. But rainfall can also be a disaster when climate change occurs. The disaster occurred when the transformation of rainfall into floods, landslides, and others.
According to the World Meteorological Organization (2014), 2014 was the hottest year in which the hot weather alternated with high rainfall and floods, which destroyed the people's economy. Banjarbaru, as one of the central cities of the government of South Kalimantan Province, has a topographic condition that is at an altitude of 0-500 m above sea level, causing rainfall, which is enough frequent. Banjarbaru itself is one of the cities affected by climate change in 2014. The disaster occurred in the form of flooding at several points of residents and also crippled the traffic at that time.
Then, it is important to know the pattern of maximum rainfall changes that occur. By knowing the pattern of maximum rainfall changes, the impact of the high rainfall that can occur will be minimized and can even be anticipated as early as possible. So there needs to be an analysis of the pattern of maximum rainfall change from old data on new data that begins with climate change that has already occurred. Where this analysis is intended to determine the magnitude of changes that occur from old data to the present, the results of this analysis can be used for planning for further prevention efforts when the rain repeats or even exceeds so that no disasters occur again.

Research Objective
The objectives of the research discussed are as follows: 1. It is knowing the changes in the maximum rainfall pattern from old data to new data after the occurrence of climate change in 2014 based on rainfall data from the Banjarbaru Climatology Station.
2. It is knowing the magnitude of changes in the maximum rainfall pattern from old data to new data after the occurrence of climate change in 2014 based on rainfall data from the Banjarbaru Climatology Station.
3. Knowing the rainfall data that can be used for the analysis of Banjarbaru water area planning.

Research Location
Banjarbaru Climatology Station is located in the city of Banjarbaru, which is one of the cities in the province of South Kalimantan, Indonesia. The

Deviation Analysis
This analysis uses the Peak-Weighted Root Mean Square Error function. This function is used to test data reliability by using the mean square error function. The formula for testing data reliability is as follows. The data used in this study is the maximum rainfall data from the Banjarbaru Climatology Station. The data is 30 years old, from 1989 to 2018, divided into two databases that will be analyzed, namely the 25-year old database and the 5-year new data. The following rainfall data used are presented in Table 3.  Table 4.
The results of the statistical parameter analysis are summarized in Table 4 : Cs 0 distribution of the rainfall data. The following results for the Chi-Square and Smirnov-Kolmogorov tests are presented in Table 5 and Table 6.

d. Calculation Of Rain Plan
The planned rainfall results from the distribution obtained for the old database, and new data are summarized in Table 7   From the calculation of the rainfall plan for the 25-year old database and the new 5-year data as in Table 7 above. Then it can be seen for a comparison of the two data in Figure 2 below.

e. Deviation Analysis
The results of the deviation analysis from 25 years old data and 5 years new data using the Peak-weighted root mean square error formula are summarized in Table  8 below:

Discussion
Based on the results of the analysis that has been done, the following discussion is obtained:

Suggestion
a. Based on the characteristics of rainfall (statistical parameters) that are different for each region in Indonesia, it is likely to produce a different analysis as well. For this reason, further research is needed on rainfall data with other regional characteristics.
b. The results of the analysis of changes in the pattern of maximum rainfall data at the Banjarbaru Climatology Station are expected to be able to be used to analyze rainfall data in the South Kalimantan region.