Planting time determination for food crops using decision tree

Abstract

Before the world experienced climate change, people can predict rainy and dry seasons easily. It is because the period is fixed throughout the year. The industrial revolution has caused global warming and affect climate change resulting in climate anomalies may decrease or increase in air temperature extreme, rainfall and seasons are shifting from the usual pattern and not erratic as well as rising sea levels and the occurrence of rob in some areas including in Indonesia. As consequence, the planting period is become difficukt to predict. Climatic factors, especially temperature, humidity, and rainfall strongly influences the process of determining the planting period for food crops. The domino effect of this mistake stimulates pest explosions, increased production costs as well the difficulty of providing food in the market. One of the technologies to assist farmers in determining the planting period is based on climate predictions from BMKG and data on food crops from the Dinas Pertanian. The process of extraction of climate data from BMKG can be applied with webservice technology. The process of determining the planting period and selection of the appropriate plant species is the application of data mining using the method of decision tree. The data in the process in this study is weather and harvest data in 2014 to 2016. The results of this study is an application that can facilitate farmers in determining the right planting or type of seeds.