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All Journal Jurnal Ilmiah FIFO Network Engineering Research Operation [NERO] International Journal of New Media Technology Journal of Business and Applied Management Jurnal Teknologi Informasi dan Terapan (J-TIT) JURNAL TEKNIK Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Algoritma, Logika dan Komputasi J-Intech (Journal of Information and Technology) Formosa Journal of Multidisciplinary Research (FJMR) Media Abdimas Jurnal Satya Informatika Jurnal Karya untuk Masyarakat (JKuM)
Destriana Widyaningrum
Universitas Bunda Mulia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : Jurnal Ilmiah FIFO

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Sentimen Analisis Mengenai Polusi Udara Menggunakan Algoritma Support Vector Machine dan Random Forest Hakim, Lukman; Dalimunthe, Muhammad Variansjah; Danuputri, Chyquitha; Widyaningrum, Destriana
Jurnal Ilmiah FIFO Vol 15, No 2 (2023)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2023.v15i2.001

Abstract

Air pollution is the contamination of indoor or outdoor environments with chemical, physical, or biological substances that change the natural properties of the atmosphere. Domestic incinerators, cars, motorbikes, combustion products from factory processing, waste burning, and forest fires are common sources of air pollution. In Indonesia, there is no doubt that air pollution occurs because of the many forest fires in Indonesia. As a result of this case, many people's opinions differ. Various sentiments occur in cyberspace, one of which is Twitter. Twitter is the social media that accommodates the most various kinds of positive, negative and neutral opinions. Therefore, researchers want to solve the problem by implementing the SVM and Random Forest algorithms. The dataset was obtained from scrapping results using tweet harvest. The data obtained was 5545 tweets. By dividing the dataset model by 80% and 20%, the results showed that the accuracy of the SVM algorithm was better than the Random Forest algorithm. The accuracy of the SVM algorithm is 83% while the Random Forest algorithm is 81%.
Co-Authors Chiquitha Danuputri Chyquitha Danuputri Dalimunthe, Muhammad Variansjah Danuputri, Chyquitha Deny Setiawan Wijaya Ester Lumba Ginting, Jusia Amanda Hakim, Lukman Herlina Herlina, Herlina Lukman Hakim Lumba, Ester Maya Cendana, Maya Sinata, Frans Suryantara, I Gusti Ngurah Teady Matius Surya Mulyana, Teady Matius Thenata, Angelina Pramana Waworuntu, Alexander Wijaya, Agustinus Fritz