Pemilihan Varietas Tebu Sesuai Lahan Menggunakan Metode Fuzzy Inferensi System Mamdani
Daniel Alfa Puryono
No 4bdmf, OSF Preprints from Center for Open Science
In line with the government's program to increase the yield and quality in the field of agriculture one of them is able to self-sufficiency. Thus the increase in agriculture cane ranging from seed selection in accordance with the land until the processing of sugar cane into sugar ready for sale with its main partners sugarcane farmers is a must. Indeed there are many varieties of seed cane but there are also many varieties of sugarcane that do not reach the targets with a maximum sugar production because it does not conform with the land at the time of planting, so that farmers suffered losses as well as sugar mills also can not result in the production of sugar in accordance with the target. Selection of sugarcane varieties in accordance with the conditions of land and soil types is very important to improve farm productivity and farm land. Many ways to define the appropriate criteria to obtain varieties with high yield and with a low tonnage in order to produce more sugar at once can reduce transportation costs and cut transport costs. Because sugarcane varieties largely determines the success of the production of sugar in the plant because basically sugar made in the garden, one way of selecting appropriate seeds whith fuzzy logic. This study aims to determine the varieties of sugar cane in accordance with the land by using a model of Mamdani Fuzzy Inference System or often also known as min-max method. Analysis of the system to get the output is done in several steps, namely the establishment of fuzzy sets, Establishment of rules, rules of composition determination, discernment (defuzzification). While the selection of appropriate varieties of sugar cane land based species and varieties of sugarcane, soil, drainage, climate such as rainfall and temperature, sunlight and air speed. The results of this study shows the results obtained proved to be better and more natural. Researchers made this system is expected to help cane farmers and sugar mills in making more accurate decisions to be in recommendations to farmers and overseers field. Because the report is valid and there is no duplication or manipulation of data.
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