Luhulima, YugoYudansha (2013) Sentiment Analysis pada Review Barang Berbahasa Indonesia dengan Metode K-Nearest Neighbor (K-NN). Sarjana thesis, Universitas Brawijaya.
Abstract
Analisis sentimen merupakan domain Text Mining atau penggalian data berupa teks, yang diantaranya terdapat proses mengolah dan mengekstrak data tekstual secara otomatis untuk mendapatkan informasi. Manfaat analisis sentimen dalam dunia usaha antara lain untuk melakukan pemantauan terhadap sebuah produk. Analisis sentimen dapat digunakan sebagai alat bantu untuk melihat respon konsumen atau masyarakat terhadap suatu produk tertentu, sehingga dapat segera diambil langkah-langkah strategis berikutnya. Proses pada analisis sentimen diawali dengan preprocessing , dilanjutkan dengan pembobotan kata, kemudian penghitungan cosine similarity, dan klasifikasi. Preprocessing terdiri dari beberapa tahap yaitu Cleaning, Casefolding, stopword removal, dan stemming . Metode pembobotan kata yang digunakan pada skripsi ini adalah Term Frequecny – Inverse Document Frequency (TF-IDF) dan menggunakan K-Nearest Neighbor (KNN) sebagai metode klasifikasinya. K-Nearest Neighbor (KNN) adalah suatu metode pengklasifikasian berdasarkan mayoritas dari kategori. Metode ini bertujuan untuk mengklasifikasi objek baru berdasarkan atribut dan training sample . Pengujian akurasi dari analisis sentimen pada review barang berbahasa Indonesia dengan metode K-Nearest Neighbor (KNN) menghasilkan rata-rata akurasi sebesar 59,160 % dan nilai tertinggi akurasi sebesar 76,19048 %.
Item Type: | Thesis (Sarjana) |
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Identification Number: | SKR/FTIK/2013/99/051306929 |
Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data |
Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
Depositing User: | Endang Susworini |
Date Deposited: | 21 Aug 2013 14:09 |
Last Modified: | 20 Oct 2021 03:16 |
URI: | http://repository.ub.ac.id/id/eprint/145885 |
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