KLASIFIKASI KEMATANGAN BUAH SAWIT DENGAN JARINGAN SYARAF TIRUAN METODE PERCEPTRON

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dc.contributor.authorNingsih, Isma Fitria
dc.contributor.supervisorSalambue, Roni
dc.date.accessioned2021-08-31T04:12:32Z
dc.date.available2021-08-31T04:12:32Z
dc.date.issued2020-12
dc.description.abstractThe development of digital image processing science makes it possible to sort and sort the maturity level of oil palm fruit with the help of image processing applications. Image processing techniques are another form of visual observation. Currently, the process of determining mortality is still using traditional methods, namely looking at the number of loose fruit and falling from the fruit bunches and the color of the fruit on the bunches. This study aims to design a system using the perceptron method, measure the accuracy of the system and measure the correlation between the color of the oil palm fruit and the level of maturity. The data used is a digital image in JPG format by extracting the RGB and HSV values. The sample used was palm fruit which presented 2 levels of maturity which were grouped into 5 fractions, namely F00, F0 categorized as raw fruit, F1, F2 and F3 categorized as ripe fruit. The amount of input data used amounted to 50 palms then processed using the single layer perceptron method and using the sigmoid bipolar and maximal epoh activation functions used were 30 where 10 data were for the training process and 30 data were for the testing process. The output produced is raw and ripe palm fruit. The success rate in experiment 1 using flash was 55% and the success rate in experiment 2 without flash resulted in an accuracy of 80%en_US
dc.description.sponsorshipJurusan Ilmu Komputer Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10188
dc.language.isoenen_US
dc.subjectPalm fruiten_US
dc.subjectRGBen_US
dc.subjectHSVen_US
dc.subjectPerceptronen_US
dc.subjectArtificial Neural Networken_US
dc.subjectPythonen_US
dc.titleKLASIFIKASI KEMATANGAN BUAH SAWIT DENGAN JARINGAN SYARAF TIRUAN METODE PERCEPTRONen_US
dc.typeArticleen_US

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