Skripsi

KLASIFIKASI EMOSI PADA TEKS BAHASA INDONESIA MENGGUNAKAN K - NEAREST NEIGHBOR

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Penilaian

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As social beings, humans can communicate in two ways, namely verbal and non-verbal. One way of non-verbal communication is to use text. However, communication using text cannot show one's emotions. Therefore, it is necessary to classify texts in Indonesian. The first step in classifying text is to preprocess the data which consists of casefolding, tokenizing, filtering, stemming, then weighting the words using TF-IDF. In this study, text classification was carried out on conversational texts using the K - Nearest Neighbor method to classify words into four classes, namely, happy, sad, angry, afraid. The test was carried out on 20 test data and obtained an accuracy of 45.0%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002619	T54341	T543412021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T543412021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xv, 65 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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