Sistem Penunjang Keputusan Intelijen Pengendalian Produktivitas Pada Industri Susu
Abstract
The government campaigned “Milk Drink Campaign”, so as to make it succesful, the milk industry must increase their production. But the national milk production fulfiled 25% from the national milk needed so the other 75% is by import. It can happen by inefficiency to use resources that can make minimum production and this reason are decreases productivity. Because of that, the milk industry needs a tool to facilitate to count and control productivity. The objective of this research is to design, expand, and apply intelligent decission support system for controlling the productivity in the milk industry, to integrate genetic algoritms and expert system in this Intelligent Decission Support System for solve the productivity problem, and to the integration approach productivity that are labor, material, energy, machine and other expense productivity in the intelligent decision support system. The name of the intelligent decision support system of controlling productivity in milk industry is IDSS_MP. This model consists of 9 models that are base model of total output, labor productivity, material productivity, energy productivity, machine productivity, of other expense productivity, total productivity, decision quantity from packaging labor, and model of consultation from expert. The verification of this base model used data from January until June 2008. The quantity selling in June 2008 was chilled milk 3.488.669 kg, prepack milk 188.739 pack and cup milk 387.662 cup. The objective from the base model of total output was to know the total income in one month. The result in June 2008 is Rp 12.096.903.190. The objective from the base model of labor productivity was to know the value of labor productivity and this index. The labor in MT KPBS consists of 12 levels and 8 head levels that consist of 3 parts those are candidate labor, contract labor and permanent labor with a different salary. The result of that the value of labor productivity in June 2008 was 175,175 with index 1,062. The objective from the base model of material productivity was to know the value of material productivity and this index. This material used 3 products. In the end of Mei 2008, the price of fuel had been increased so that it could influence the price of material that increased 20%. The result of that the value of material productivity in June 2008 was 1,191 with index 1,077. The objective from the base model of energy productivity was to know the value of energy productivity and this index. This energy was fuel (diesel fuel and diesel industry), electricity and water. In the end of Mei 2008, the price of fuel was increased so that it influenced the price and quantity in use. The result of that the value of energy productivity in June 2008 was 37,052 with index 0,965. The objective from the base model of machine productivity was to know the value of productivity and index productivity of prepack machine and cup machine whether operation machine was good or not. The result of that the value of prepack machine productivity was 0,970 with index 0,997 and the value of cup machine productivity was 0,982 with index 1,000. The objective from the base model of other expense productivity was to know the value of other expense productivity and this index. The other expense consists of distribution fee, tax and purchasing spareparts. The result of that the value of other expense productivity in June 2008 was 29,327 with index 0,467. The objective from the base model of the total productivity was to know the the value of total productivity and this index. The result of that the value of total productivity in June 2008 was 1,001 with index 1,050. The next stage was consultation with expert to solve the productivity problem. The result of that index decreased in June 2008 that were labor, energy, prepack machine and other expense and to get the solution for this including certainty factor from expert. The last base model was base model of decision quantity from packaging labor that objective for to get an ideal composition with recruitment or overtime. The result of that in June 2008, labor in prepack packaging and cup packaging must recruit 1 labor. For all, IDSS_MP explain the productivity in milk industry and solve their productivity problem if it was decreased.