Dry and Rainy season prediction can be used to determine the right time to start planting agriculture commodities and maximize its output.Īlso, this information can help the government to prepare any policy as a prevention method against a flood that occurred due to heavy rain on the rainy season or against drought on dry season. It can be a beneficial insight for the country which relies on agriculture commodity like Indonesia. With this, we can assign Dry Season on April-September period and Rainy Season on October-March. Rainfall will begin to climb again after September and reach its peak in January. The horizontal lines indicate rainfall value means grouped by month, with using this information we’ve got the insight that Rainfall will start to decrease from April and reach its lowest point in August and September. Using seasonal boxplot and sub-series plot, we can more clearly see the data pattern. In this article, we will try to do Rainfall forecasting in Banten Province located in Indonesia (One of the tropical country which relies on their agriculture commodity), we have 2006–2018 historical rainfall data¹ and will try to forecast using “R” Language.Ī simple workflow will be used during this process: Another example is forecast can be used for a company to predict raw material prices movements and arrange the best strategy to maximize profit from it. As an example, in the tropics region which several countries only had two seasons in a year (dry season and rainy season), many countries especially country which relies so much on agricultural commodities will need to forecast rainfall in term to decide the best time to start planting their products and maximizing their harvest. Until this year, forecasting was very helpful as a foundation to create any action or policy before facing any events. Banten, Indonesia 2019–2020 Rainfall forecasting using “R” LanguageĪ forecast is calculation or estimation of future events, especially for financial trends or coming weather.
0 kommentar(er)
