Time Series Analysis

Time series analysis time series is a series of data that is sequentially collected or arranged sequentially in equal time increments (Lazim M.A, 2011). Time series are also described as a series of data over a certain time interval of year, month, day, or time. Why are you interested in time series analysis? Time series analysis is a quantitative or statistical method used to predict specific datasets over time and apply specific metrics to assess accuracy.

Prediction / time series analysis: Time series data is data collected at even intervals. Time series analysis searches this data and extracts meaningful statistical data or data characteristics. It is used when you want to evaluate changes over time based on past changes and predict future events. Data mining: This can be used to find data, typically a large business related data set (also called "big data"), to find business-related insights, patterns, or relationships between variables that can improve performance It is an analysis process to investigate. Therefore it is very useful if you have a large data set that needs to draw insight.

Time series analysis time series is a series of data that is sequentially collected or arranged sequentially in equal time increments (Lazim M.A, 2011). Time series are also described as a series of data over a certain time interval of year, month, day, or time. Why are you interested in time series analysis? - As a parameter of temperature, temperature plays an important role in supplying energy to plants during plant growth. Soil surface temperature affects phytochemical reactions. This is an important factor in nutrient absorption. So the soil surface temperature is an important parameter for the quality and quantity of agricultural products.