Amalina, Mely (2021) Analisa Sentimen Penilaian Produk pada Shopee Berdasarkan Rating Menggunakan Metode K-NN. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT Marketplace is an online application that is very popular with the public, one of which is Shopee. Shopee sells a wide variety of products including electronic products. Electronic products are one of the superior products in the Shopee marketplace that are in demand by many customers. The increasing number of electronic products offered by Shopee to its customers makes customers recommend the best recommendations regarding electronic product information that these customers want. Product recommendations are also very influential in terms of products so that customers become wiser buyers and can be more careful in considering before buying electronic products on the Shopee market. Therefore, as a problem-solving solution, the authors create a program that can analyze and help process product performance more quickly and effectively. The process carried out is to return electronic products in the Shopee marketplace by becoming test data and training data, then providing variables to be used as parameters in the calculation process using the K-NN method. The K-NN method is used in analyzing the sentiment of an electronic product in the Shopee market. The variables used are the variable rating, price, and sold / the number of goods sold from an electronic product in shopee. These three variables are used to calculate the distance in the K-NN calculation process, where in this system the distance formula used is the euclidean distance formula in the KNN algorithm with vector representation data from electronic products as the data used in the calculation of the system which is made mostly to produce accuracy 93 %. Keywords: Marketplace, Product Appraisal, Shopee, K-NN Method
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 26 Mar 2021 06:43 |
| Last Modified: | 26 Mar 2021 06:43 |
| URI: | http://eprints.uty.ac.id/id/eprint/7151 |
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