PARAMETERS ESTIMATION OF THE DYNAMIC SYSTEM MODEL FOR UNEMPLOYMENT MODEL IN EAST JAVA PROVINCE
MELKI IMAMASTRI PULING TANG, S. Si., M. Mat
Unemployment in an area becomes more serious if there is relatively slow employment growth and a rapid increase in the growth rate of the workforce Unemployment is a very complex problem because it affects and is influenced by many interacting factors, following a pattern that is not always easy to understood. The magnitude of the unemployment rate can be said to be very important in measuring the success of economic development in a region. This research leads to parameter estimation of the unemployment model.Estimated parameters include the rate of unemployment increase,the rate of change in the number of unemployed employed, the rate of people hired resigning or being laid off from their jobs, unemployment mortality rate, labor migration rate, the rate of reduction in job vacancies available due to lack of government funding, the level of infrastructure,and small and medium enterprises.These parameters can affect the unemployment rate , the employment rate, and job vacancies . To overcome the unemployment rate for employment (job vacancies), one of the efforts made by the government is to increase investment, especially in the infrastructure sector, revitalizing supporting facilities for the agricultural sector, and clearing new land and small and medium enterprises. The purpose of this study is to construct a model of a system of nonlinear ordinary differential equations on unemployment and determine the estimation results. parameters on the unemployment model. Research Methods through Literature Studies and Mathematical Model Stages (mathematical models, namely recognizing and naming independent and dependent variables and making assumptions as necessary to simplify phenomena so that they can be traced mathematically, apply known mathematical theories to mathematical models that have been formulated to get mathematical conclusions, draw mathematical conclusions and interpret them as information related to the modeled problem by providing explanations or making estimates, and testing estimates against real data. If the estimates made are not proportional to reality, then the model obtained needs to be refined or formulate new model and start recycling (or by correcting the given assumptions).Numerical simulation on parameter estimation using matlab states that the curve that approximates the rate of increase in the number of unemployed (A) is the parameter estimate curve A_1 (linear parameter estimate); The curve that approximates the data on the rate of change in the number of unemployed employed (k) is the result of the estimated value of the k_2 parameter (quadratic parameter estimate); The curve that approximates the data on the rate of people being employed resigning, or being laid off from their job / poverty rate (β)) is the estimate curve β_3(estimated cubic parameter); The curve approximating the parameter estimation data for the unemployment rate(μ) is μ_2 (quadratic estimation parameter); The curve that approximates the data parameter estimation of the rate of migration, retirement or worker mortality (α) is α_3 (cubic estimation parameter). The curve that approximates the parameter estimate of the rate of reduction in job vacancies available due to lack of government funding (δ) is δ_3 (estimated cubic parameter); The curve that approximates the parameter estimation data for the level of investment in infrastructure, revitalization of supporting facilities for the agricultural sector, and new land clearing (I_1)) is adalah 〖(I_1)〗_3 (estimation parameter cubic); and the curve that approximates the parameter estimate data (I_2) is (I_2 )_3 (cubic parameter estimate)