Melola Discovery

← Melola Discovery

Akses terbuka Jurnal SINTA 1

A contest of sentiment analysis: k-nearest neighbor versus neural network

IAES International Journal of Artificial Intelligence · Vol. 14 No. 2 (2025) · hlm. 1625–1633

DOI
10.11591/ijai.v14.i2.pp1625-1633
ISSN
2252-8938, 2089-4872
Terbit
2025-04-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Discourse about public matters often encompasses sentences that address topics emerging within societal contexts, including issues related to Islamophobia. Debates surrounding this subject frequently evoke support and opposition within digital platforms and interpersonal interactions. Categorizing such dialogic expressions within online media facilitates an evaluation of their negative and positive implications. This study employs two distinct methodologies, specifically deep learning and machine learning techniques, to visualize the findings by implementing dual algorithms. According to the comparative analysis, deep learning achieves a higher accuracy rate of 78%, whereas machine learning achieves a rate of 71%. Thus, deep learning is a better method for textual data classification.

Kata kunci

Jaringan kolaborasi para penulis

17 penulis · 43 tautan kepenulisan bersama · 23 lintas organisasi

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • Universitas Islam Negeri Maulana Malik Ibrahim
  • Institut Agama Islam Negeri Pontianak
  • University of Technology Malaysia
  • Universitas Islam Negeri Sayyid Ali Rahmatullah Tulungagung
  • University of Malaya
  • Institut Pendidikan Guru Kampus Perempuan Melayu
  • Universitas Alma Ata
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Rifqy Rosdiyah IlmiUniversitas Islam Negeri Maulana Malik Ibrahim1
Sri HariniUniversitas Islam Negeri Maulana Malik Ibrahim1
Samsul SusilawatiUniversitas Islam Negeri Maulana Malik Ibrahim1
Ahmad YasinUniversitas Islam Negeri Maulana Malik Ibrahim1
Zaidatun TasirUniversity of Technology Malaysia1
Rika Inggit AsmawatiUniversitas Islam Negeri Maulana Malik Ibrahim1
Abdulloh ChakimUniversitas Islam Negeri Sayyid Ali Rahmatullah Tulungagung1
Abd. Rahman Ambo’ DalleUniversitas Islam Negeri Maulana Malik Ibrahim1
Zawawi IsmailUniversity of Malaya1
Nurwaina RasitInstitut Pendidikan Guru Kampus Perempuan Melayu1
Sumin SuminInstitut Agama Islam Negeri Pontianak1
Sukino SukinoInstitut Agama Islam Negeri Pontianak1
Erwin MahrusInstitut Agama Islam Negeri Pontianak1
Ahmad SalimUniversitas Alma Ata1
Imron MuttaqinInstitut Agama Islam Negeri Pontianak1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (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-US">A contest of sentiment analysis: k-nearest neighbor versus neural network</dc:title>
	<dc:creator>Kurniawan, Fachrul</dc:creator>
	<dc:creator>Supriyatno, Triyo</dc:creator>
	<dc:subject xml:lang="en-US">Machine Learning &amp; Deep Learning</dc:subject>
	<dc:subject xml:lang="en-US">Classification; Deep learning; K-nearest neighbor; Machine learning; Neural network</dc:subject>
	<dc:description xml:lang="en-US">Discourse about public matters often encompasses sentences that address topics emerging within societal contexts, including issues related to Islamophobia. Debates surrounding this subject frequently evoke support and opposition within digital platforms and interpersonal interactions. Categorizing such dialogic expressions within online media facilitates an evaluation of their negative and positive implications. This study employs two distinct methodologies, specifically deep learning and machine learning techniques, to visualize the findings by implementing dual algorithms. According to the comparative analysis, deep learning achieves a higher accuracy rate of 78%, whereas machine learning achieves a rate of 71%. Thus, deep learning is a better method for textual data classification.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2025-04-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/25567</dc:identifier>
	<dc:identifier>10.11591/ijai.v14.i2.pp1625-1633</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 14, No 2: April 2025; 1625-1633</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v14.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/25567/14503</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>