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dc.contributor.advisorHizriadi, Ainul
dc.contributor.advisorSeniman
dc.contributor.authorPasaribu, Claudia Demita
dc.date.accessioned2025-07-17T06:19:09Z
dc.date.available2025-07-17T06:19:09Z
dc.date.issued2025
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/105688
dc.description.abstractSalak with the scientific name Salacca zalacca is a type of plant classified in the Arecaceae tribe or palms with edible fruits. Salak plays an important role in increasing Indonesia's foreign exchange. In addition to being marketed in the local market, , salak fruit has also been exported to various countries in Asia. In 2018, salak exports reached 1,233 tons, 28% increase from the previous year. This number continued to increase in 2019 to 1,698 tons and made salak the fourth most exported fruit in Indonesia. The selection of the quality of salak fruit is very important and needs to be done carefully so that the distribution of salak fruit for long-distance delivery and export destinations can be carried out effectively. Producers and sellers of salak fruit must be able to produce and market good quality salak fruit so that it can satisfy consumer needs. The determination of the quality of salak fruit is still done manually with the sense of sight so this will require precision and will take longer. The existence of a difference perception of subjective quality assessment can cause obstacles in the salak fruit distribution process. In this research, there are 5 qualities of salak fruit that will be classified, namely good quality, semi-ripe, tear defects, dent defects and rotten defects using the Faster R-CNN algorithm. The study used 535 images which were divided into training data, data validation and data testing. After conducting the research, it can concluded that Faster R-CNN can classify 5 different classes with 92% accuracy value.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectSalaken_US
dc.subjectSalak Fruit Qualityen_US
dc.subjectFaster R-CNNen_US
dc.subjectDigital Image Processingen_US
dc.titleKlasifikasi Kualitas Buah Salak Menggunakan Algoritma Faster R-CNN Berbasis Androiden_US
dc.title.alternativeQuality Classification of Salak Fruit Using Android Based Faster R-CNN Algorithmen_US
dc.typeThesisen_US
dc.identifier.nimNIM181402019
dc.identifier.nidnNIDN0127108502
dc.identifier.nidnNIDN0025058704
dc.identifier.kodeprodiKODEPRODI59201#Teknologi Informasi
dc.description.pages93 Pagesen_US
dc.description.typeSkripsi Sarjanaen_US
dc.subject.sdgsSDGs 4. Quality Educationen_US


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