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All Journal Elkom: Jurnal Elektronika dan Komputer
Widi Afandi
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PENERAPAN METODE SUPPORT VECTOR MACHINE ANALISIS SENTIMEN TWEET PERGANTIAN LOGO HALAL DI INDONESIA Widi Afandi; Tri Ginanjar Laksana; Nia Annisa Ferani Tanjung
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.964

Abstract

The Halal Product Assurance Agency (BPJPH) is an agency under the auspices of the Ministry of Religion with the task of ensuring the halalness of products in Indonesia. BPJPH has become a public concern after establishing the new halal logo. On February 10, 2022 the new halal logo was ratified by the Head of BPJPH, Muhammad Aqil Irham. This has become a topic of public discussion either directly or through social media, one of which is social media twitter. The number of opinion tweets about the change of the halal logo can be used as a data source to obtain information about public opinion on the change of the halal logo through sentiment analysis. Sentiment analysis can be done by machine learning approach, one of these is the SVM algorithm . In this research, oversampling and undersampling are applied to handle data that has an unbalanced sentiment class. The results showed that the Support Vector Machine (SVM) model using oversampling training data got the highest accuracy, recall, precision, and f1-score, namely 71% accuracy, 67% precision, 61% recall, and 61% f1-score while training using undersampling training data has the lowest performance, namely getting 56% accuracy, 51% precision, 57% recall, and 52% f1-score.
PENERAPAN METODE SUPPORT VECTOR MACHINE ANALISIS SENTIMEN TWEET PERGANTIAN LOGO HALAL DI INDONESIA Widi Afandi; Tri Ginanjar Laksana; Nia Annisa Ferani Tanjung
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.964

Abstract

The Halal Product Assurance Agency (BPJPH) is an agency under the auspices of the Ministry of Religion with the task of ensuring the halalness of products in Indonesia. BPJPH has become a public concern after establishing the new halal logo. On February 10, 2022 the new halal logo was ratified by the Head of BPJPH, Muhammad Aqil Irham. This has become a topic of public discussion either directly or through social media, one of which is social media twitter. The number of opinion tweets about the change of the halal logo can be used as a data source to obtain information about public opinion on the change of the halal logo through sentiment analysis. Sentiment analysis can be done by machine learning approach, one of these is the SVM algorithm . In this research, oversampling and undersampling are applied to handle data that has an unbalanced sentiment class. The results showed that the Support Vector Machine (SVM) model using oversampling training data got the highest accuracy, recall, precision, and f1-score, namely 71% accuracy, 67% precision, 61% recall, and 61% f1-score while training using undersampling training data has the lowest performance, namely getting 56% accuracy, 51% precision, 57% recall, and 52% f1-score.
PENERAPAN METODE SUPPORT VECTOR MACHINE ANALISIS SENTIMEN TWEET PERGANTIAN LOGO HALAL DI INDONESIA Widi Afandi; Tri Ginanjar Laksana; Nia Annisa Ferani Tanjung
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.964

Abstract

The Halal Product Assurance Agency (BPJPH) is an agency under the auspices of the Ministry of Religion with the task of ensuring the halalness of products in Indonesia. BPJPH has become a public concern after establishing the new halal logo. On February 10, 2022 the new halal logo was ratified by the Head of BPJPH, Muhammad Aqil Irham. This has become a topic of public discussion either directly or through social media, one of which is social media twitter. The number of opinion tweets about the change of the halal logo can be used as a data source to obtain information about public opinion on the change of the halal logo through sentiment analysis. Sentiment analysis can be done by machine learning approach, one of these is the SVM algorithm . In this research, oversampling and undersampling are applied to handle data that has an unbalanced sentiment class. The results showed that the Support Vector Machine (SVM) model using oversampling training data got the highest accuracy, recall, precision, and f1-score, namely 71% accuracy, 67% precision, 61% recall, and 61% f1-score while training using undersampling training data has the lowest performance, namely getting 56% accuracy, 51% precision, 57% recall, and 52% f1-score.
Co-Authors Nia Annisa Ferani Tanjung Tri Ginanjar Laksana Tri Ginanjar Laksana