Prediction of Poor Inhabitant Number Using Least Square and Moving Average Method

Abstract

Poor population in South Kalimantan recently shows a decreased number for the last three years, compared to few previous years. The number of poor population differs from time to time. This dynamical scaled number has actually been a problem for South Kalimantan local government to take proper policies to solve this matter.  It will then be necessary to predict potential number of poor population in the next year as the basis of subsequent policy making. This research will apply both Least Square and Moving Average methods as measurement to count prediction values. From the result, we can say that prediction analysis using those two methods is valid for predicting acquired number of potential people population based on its previous data due to its closest result to the actual condition. Reviewing the test result of last three years, the applied least square method shows validity of 92, 8%. Meanwhile, the applied moving average method shows validity of 98,8% both are considered valid.