KLASIFIKASI EMOSI PADA TEKS BAHASA INDONESIA MENGGUNAKAN K - NEAREST NEIGHBOR

RIZKYTAMI, PRILLY and Rini, Dian Palupi and Yusliani, Novi (2021) KLASIFIKASI EMOSI PADA TEKS BAHASA INDONESIA MENGGUNAKAN K - NEAREST NEIGHBOR. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Teks, Klasifikasi Emosi, K – Nearest Neighbor
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Prilly Rizkytami
Date Deposited:	21 Sep 2021 02:33
Last Modified:	21 Sep 2021 02:33
URI:	http://repository.unsri.ac.id/id/eprint/54341

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