Melola Discovery

← Melola Discovery

Jurnal

Analisis Sentimen Survei Regsosek pada Twitter Menggunakan Algoritma K-Nearest Neighbor (K-NN)

ESTIMASI: Journal of Statistics and Its Application · Vol. 4 No. 2 (2023) · pp. 196–207

DOI
10.20956/ejsa.v4i2.25522
ISSN
2721-379X, 2721-3803
Published
2023-08-04
Publisher
Hasanuddin University
Language
en

Abstract

Indonesia in 2022, will experience a shift in adaptation to recovery from the pandemic as well as rising global commodity prices due to the impact of the Ukraine-Russia war. The government in its efforts to deal with this situation, one of which is by transforming data into one data through the 2022 Social Economic Registration (Regsosek) as a requirement for social protection system reform. However, in practice, Research and Research has become quite a public concern, where the content is almost the same as previous surveys conducted by BPS, which raises questions about the effectiveness of this survey. This study aims to determine the sentiments of each opinion on social media Twitter regarding 2022 Social Security. This research implements the K-Nearest Neighbor (K-NN) method to analyze sentiment in tweets. Data obtained from Twitter by scrapping. The polarity percentage results from the tweets obtained are dominated by negative opinions. The best application of the K-Nearest Neighbor (K-NN) algorithm is using the parameter k = 3. The model built shows very good performance with an accuracy of 96%, a recall of 100%, and a precision of 0,96%.

Keywords

Collaboration network of the authors

15 authors · 28 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Muhammadiyah Semarang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Prizka Rismawati ArumAffiliation unknown3
Laily HimmaturrohmahAffiliation unknown1
Indah Manfaati NurAffiliation unknown1
Nun Maulida Suci AyomiAffiliation unknown1
Anita Retno IndrianiAffiliation unknown1
Rochdi WasonoAffiliation unknown1
Yulia FitriAffiliation unknown1
Rahmad Putra GautamaAffiliation unknown1
Muhammad Sam’anUniversitas Muhammadiyah Semarang1
Wulan SariAffiliation unknown1
Fatkhurokhman FauziAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Analisis Sentimen Survei Regsosek pada Twitter Menggunakan Algoritma K-Nearest Neighbor (K-NN)</dc:title>
	<dc:creator xml:lang="en">Ayuningrum, Bunga</dc:creator>
	<dc:creator xml:lang="en">Haqq, Hilma Hanna Mahanna</dc:creator>
	<dc:creator xml:lang="en">Lestari, Suci Mega Puji</dc:creator>
	<dc:creator xml:lang="en">Haris, M Al</dc:creator>
	<dc:subject xml:lang="en">K-Nearest Neighbor</dc:subject>
	<dc:subject xml:lang="en">Regsosek</dc:subject>
	<dc:subject xml:lang="en">Sentimen analysis</dc:subject>
	<dc:subject xml:lang="en">Twitter</dc:subject>
	<dc:description xml:lang="en">Indonesia in 2022, will experience a shift in adaptation to recovery from the pandemic as well as rising global commodity prices due to the impact of the Ukraine-Russia war. The government in its efforts to deal with this situation, one of which is by transforming data into one data through the 2022 Social Economic Registration (Regsosek) as a requirement for social protection system reform. However, in practice, Research and Research has become quite a public concern, where the content is almost the same as previous surveys conducted by BPS, which raises questions about the effectiveness of this survey. This study aims to determine the sentiments of each opinion on social media Twitter regarding 2022 Social Security. This research implements the K-Nearest Neighbor (K-NN) method to analyze sentiment in tweets. Data obtained from Twitter by scrapping. The polarity percentage results from the tweets obtained are dominated by negative opinions. The best application of the K-Nearest Neighbor (K-NN) algorithm is using the parameter k = 3. The model built shows very good performance with an accuracy of 96%, a recall of 100%, and a precision of 0,96%.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2023-08-04</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/25522</dc:identifier>
	<dc:identifier>10.20956/ejsa.v4i2.25522</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 4, No. 2, Juli, 2023 : Estimasi; 196-207</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/25522/10210</dc:relation>
</oai_dc:dc>