Putra, Muhamad Faiq Purnomo (2019) Analisis Sentimen Masykarakat Indonesia Terhadap Gatra Ekonomi Ketahanan Nasional Menggunakan Fuzzy Ontology-Based Semantic Knowledge. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kampanye diantara dua kubu acap kali meramaikan media sosial yang telah menjadi target kampanye dimana total pengguna media sosial di Indonesia telah mencapai 130 juta pengguna. Memanfaatkan momentum ramainya media sosial pada tahun pemilu dan kampanye, penulis mencoba menggali sentimen masyarakat melalui Twitter terhadap gatra ekonomi dalam konsepsi ketahanan nasional menggunakan Fuzzy ontology-based semantic knowledge. Ontologi pada biasanya dianggap tidak terlalu efektif dalam mengekstrak informasi dari tweets, sehingga digunakanlah konsep Fuzzy-ontology based semantic knowledge.
Fuzzy ontology-based semantic knowledge merupakan salah satu cara analisis sentimen menggunakan pendekatan gabungan lexicon-based, ontologi, dan fuzzy logic untuk menghasilkan apakah suatu tweet dapat dikategorikan sebagai strong negative, negative, netral, positive, maupun strong positive.
Pada akhirnya, ontologi biasa tidak dapat mengklasifikasikan masuk kedalam sentimen apa sebuah tweet jika tweet tersebut memiliki lebih dari satu nilai SentiWord. Dari 2032 tweet bersentimen, terdapat 205 tweet yang memiliki lebih dari satu
nilai SentiWord sehingga diperlukan penerapan FuzzyDL untuk memecahkan permasalahan tersebut. Dengan menggunakan metode ini, didapatkan akurasi 78%, dengan tingkat presisi 93%, recall 73%, dan function measure 82%.
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The campaign between the two camps often enlivened social media which has become the target of the campaign where the total number of social media users in Indonesia has reached 130 million users. Utilizing the momentum of the hectic social media in the election year and campaign, the author tries to explore the public sentiment through Twitter on gatra economy in the concept of national resilience using Fuzzy ontology-based semantic knowledge. Ontology is usually considered to be not very effective in extracting information from tweets, so the concept of Fuzzy-ontology based semantic knowledge is used. Fuzzy ontology-based semantic knowledge is one method of sentiment analysis using a combined approach of lexicon- based, ontology, and fuzzy logic to produce whether a tweet can be categorized as strong negative, negative, neutral, positive, or strong positive.
In the end, ordinary ontologies cannot classify what sentiment is a tweet if the tweet has more than one SentiWord value. Of the 2032 sentiment tweets, there are 205 tweets that have more than one SentiWord value, so FuzzyDL is needed to solve these problems. By using this method, an accuracy of 78% is obtained, with a precision level of 93%, a recall of 73%, and a function measure of 82%.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSI 658.403 801 1 Put a-1 2019 |
| Uncontrolled Keywords: | analisis sentimen, ontologi, sentiword, fuzzy logic, gatra ekonomi, ketahanan nasional, Twitter. |
| Subjects: | T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T58.62 Decision support systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.88815 Semantic Web |
| Divisions: | Faculty of Information and Communication Technology > Information Systems > 57201-(S1) Undergraduate Thesis |
| Depositing User: | Muhamad Faiq Purnomo Putra |
| Date Deposited: | 25 May 2023 07:27 |
| Last Modified: | 25 May 2023 07:27 |
| URI: | http://repository.its.ac.id/id/eprint/64511 |
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