The histogram in the image appears to represent monthly rainfall data ("Curah Hujan Bulanan") in millimeters. Based on its shape, we can attempt to determine the distribution it resembles:

1. Right Skewness: The histogram has a longer tail to the right, suggesting it may be skewed right. This is typical of rainfall data, which often follows a positively skewed distribution.

2. Possible Distribution:

   • Exponential Distribution: This is possible for rainfall, where many months have low rainfall and fewer months have extreme rainfall.
   • Gamma Distribution: Often used for rainfall, as it can model skewed data with a non-negative range.
   • Log-Normal Distribution: If the log-transformed data produces a symmetric distribution, it may follow a log-normal distribution.
   • Normal Distribution: While it is somewhat symmetric in the middle range, the skewness makes it unlikely to follow a true normal distribution.

To confirm the exact distribution, statistical fitting or goodness-of-fit tests (e.g., Kolmogorov-Smirnov test) would need to be performed.

Would you like me to:

1. Fit the data to a specific distribution?
2. Explain any of these distributions in more detail?
3. Guide you on how to calculate goodness-of-fit tests?
4. Provide Python code for further analysis?
5. Explore how to transform the data for symmetry (e.g., log transformation)?

Tip: Always visually inspect the histogram and combine it with statistical tests to confirm the distribution type