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All Journal Techno.Com: Jurnal Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika International Journal of Informatics and Computation Jurnal Informatika Ekonomi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Journal Automation Computer Information System (JACIS) Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Joong-Ki : Jurnal Pengabdian Masyarakat Jurnal Informasi Sains dan Teknologi (ISAINTEK) SMART Management Journal STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Indonesian Research Journal on Education Journal Of Informatics And Busisnes VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Komputer dan Teknologi (JUKOMTEK) SAINTEK Jurnal Media Akademik (JMA) Joong-Ki Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan SISFOTENIKA Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Expert Net: Exploration Journal of Technological Education Trends Joong-Ki Jurnal Rekayasa Teknologi Nusa Putra Jejak digital: Jurnal Ilmiah Multidisiplin Jurnal Cakrawala Akademika
Elkin Rilvani
Universitas Pelita Bangsa
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Journal : International Journal of Informatics and Computation

 1 
Sentiment Analysis on Canva Reviews Using Naive Bayes Method Faiza Muhammad Julianto; Ahmad Turmudi Zy; Elkin Rilvani
International Journal of Informatics and Computation Vol. 7 No. 1 (2025): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v7i1.107

Abstract

Sentiment analysis for user review is a growing research topic in digital applications. In this study, we analyze user reviews from the Google Play Store to classify sentiments as positive or negative. The primary objective of this research is to evaluate the performance of the Naive Bayes classifier in sentiment classification. The methodology involves comprehensive data preprocessing, model training, and evaluation using performance metrics such as accuracy, precision, recall, and F1-score. The results indicate that the proposed model achieves an accuracy = 92%, precision = 85%, recall = 88%, and F1-score= 86%, respectively. These findings show the effectiveness of the proposed method that can extract valuable insights from user reviews to increase user satisfaction.
Co-Authors Abdul Rokim Abid Lu’ay Raihan Taufik Agung Nugroho Ahmad Budi Trisnawan Ahmad Turmudi Zy Al Ayubi, Muhammad Din Aldi Patria Nugraha Alfian Saputra, Ricky Alfiana Erlangga, Dafa Alif Nur Fathlii Amarta Amar Agung Subekti An-nisa Fitriani Andhika Aziz Bachtiar Andi Setyawan Anindha Latiefa Zahra Apik Aminah Aries Widyantoro ARIF SUSILO Arif Susilo Arya Saepul Hakim Asep Muhidin Asep Saepuloh Baehaqi Bagoes Ramadhan Baihaqi Asa’ari Lubis Bayu Nugroho Butsianto, Sufajar Candra Naya Catur Pranomo Dimas Adi Nugraha Dina Amalia Putri Diska Kurnia Azzahra Putra Dito Ridwansyah, Rizjky Dzaky Alaudin Malik Edi Tri Wibowo Edora Erikasari, Vivie Zuliani Ermanto Ermanto Ermanto Fachrial Banyu Asmoro Fadhlurohman Fatikh Navintino Faisal Arya Yudanto Faiza Muhammad Julianto Faqih Irianto Fazri Albadawi Fikr, Muhammad Fiqhy Faradisa Al Bina Fitakwim Fitakwim Galih Pangestu Gilar Sumilar Hadi Putra Hardiansyah, Andi Henri Caesar Bimantara Hilman Ihza Amrullah Hizkia Vincent Hrenysa Ikhsan Romli Indry Widiyani Khaerunnisa Isnaeni Lestari Khairunnisa Nasution Lili Fadli Muhamad Ma'ruf Setiadi2 Maharani , Tyanshi Firli Mikael Rivaldo Mochammad Rahmat Faisal Monika Pakpahan Muhamad Daffa Maulana Arrasyid Muhamad Fatchan Muhammad Akmal Ar Rasid Muhammad Albedri MUHAMMAD ARIFIN Muhammad Farhan Fahreza Muhammad Nur Falah Muhammad Rifki Febrianto Muhammad Rizal Mantofani Muhammad Rizky Raka muhidin, asep Muhtajuddin Danny Nabilla Kusuma Wijaya Nadia tul umah Naya, Candra Naza Sefti Prianita Novant Nanda Pradana Novianto Andi Hardiansyah Nugroho, Agung Nur Hasim Nur Hidayati Nurkholik Safrudin Ovi Marzuki Panji Anwar Sanusi Pardede, Debora Hizkhia Prakoso, Indra Priasnyomo Prima Santoso Putra, Aan Fadillah Rafi Maulana Firdaus Ramadhan Ardi Iman Prakoso Rio Rinto Saki Rizki Fahrizal Rizky Juniarko Taruna Putra Roana, Roana Saiful Muktiali Sela, Mosses Ara’al De Setyawan, Wisnu Shanti Cahyaningtyas Sifa Setiyani Silvi Fara Dita Siswandi, Arif Siti Yasmin Nurcholifah Soejarminto, Yos Sukmana Wibowo, Mohamad Hegar Surojudin, Nurhadi Suryadi Putra Suryadi, Dikky Suryana, Syahro Tatia Deswita Anggraeni Taufik Eka Albani Tia Mulyani Tri Ngudi Wiyatno Weni Purnomo1 Widodo , Edy Wisnu Ikhwansyah Saputra Wisnu Setyawan Yoga Pratama, Evan Yudha Purnama Putra Zacky Rafian Fawwauzy Zalfa Dewi Zahrani