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Bagus Setiawan
Departemen Klinik, Reproduksi, dan Patologi Fakultas Kedokteran Hewan Institut Pertanian Bogor, Bogor
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Journal : Building of Informatics, Technology and Science

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Analisis Sentimen Ulasan Aplikasi Identitas Kependudukan Digital Menggunakan Algoritma Logistic Regression dan K-Nearest Neighbor Setiawan, Bagus; Baihaqi, Kiki Ahmad; Nurlaelasari, Euis; Handayani, Hanny Hikmayanti
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5389

Abstract

The government has launched the latest innovation in data collection in the realm of population data which relies on digital technology through mobile applications using photos or QR codes which aims to reduce the use of physical prints of identity cards and the availability of blank KTPs with the aim of simplifying the administrative process and no longer requiring population documents. printing or saving in physical format such as an KTP file. In implementing the population identity application, some people feel anxious due to limited internet access, lack of knowledge about the application, as well as concerns about the security and privacy of identity data in digital format. This research aims to conduct sentiment analysis on reviews of digital population identity applications by comparing logistic regression and k-nearest neighbor algorithms. The dataset was taken using the Google Play Scraper library in Python which got 1700 raw data taken from 12-February to 26 March 2024 and then pre-processed and got 1108 clean data. The results of this research show that the comparison between the logistic regression algorithm and k-nearest neighbor algorithm shows that the k-nearest neighbor algorithm is better than the logistic regression algorithm with an accuracy result of 80.43%, a difference of 3.60% compared to k-nearest neighbor. So it can be concluded that the digital population identity application is still considered poor in its use because it has a negative sentiment of 73.9% and it can be seen in this research that the comparison results of the k-nearest neighbor algorithm prove that its performance is better than logistic regression
Co-Authors Agus Riyanto Aisyah, Nadia Al-Khalifi, Melisa Ref’ni Ali, Fachri Fadillah Andriani, Mega Arrahman, Muhammad Fiqri Arthur Daniel Limantara, Arthur Daniel astina, ria Astuti, Sri Hartini Juni Ayu Fitriani, Prilia Nurdiah Baihaqi, Kiki Ahmad Bramastha, Gusti Rajhu bustan, novita Didik SULISTYANTO Dwi Aries Himawanto Echwan, Chairul Ekasari, Natasya Putri Eko Prasetyo Budiana, Eko Prasetyo Eny Fuskhah Erminawati Erwanto, Angga Faiz, Achmad Nur Fitria, Saripatul Fitriani, Endah Hafifah, Hafifah Hanny Hikmayanti Handayani Hendra Pratama, Hendra Heri, Rif’at Reza Ramadhan Imam Kamaluddin Ira Puspita Dewi, Ira Puspita Iva Khoiril Mala Jakiyudin, Ahmad Havid Karno Kartika Senjarini Laily, Dwi Yanti Laksono, Judo Lia Lia M. Irfa'i Mahyunis Mariana Syamsudin Marzuki Marzuki Mecca Arfa, Mecca Muhamad Azrino Gustalika Muhammad Syahdan Muharir Nadela, Nadela Nasruddin Nasruddin Ningsih, Dinah Zahra Restia Nurdiana Nurdiana Nurhalisa, Nurhalisa Nurhayati Nurhayati Nurjannah Nurjannah Nurlaelasari, Euis Nuruddaroini, M. Ahim Sulthan Osijo, Immanuel Ustradi Pahrurraji, Pahrurraji Paramitha, Nina Pradana Ananda Raharja Pramita, Cindi Pratiwi, Arum Dyah purwadi joko widodo Purwani, Desy Putri, Vania Santika Rahman, Muhammad Raisa Fitri Raissa Amanda Putri Ramadani, Noor Fatjriansyah Rianda, Rianda Safrizal Safrizal Samsudin, Samsudin Saputra, Ibra Ganie Satriyo Satriyo Saufiah, Saufiah Solichin, Much. Riyadus Sudarmiatin Sutrisno, Franky Tamsir Ariyadi Warsito, Kabul Wenty Dwi Yuniarti, Wenty Dwi Yopanggi, Randi Zulfikar Ali Zulkifli Lubis Zulmi, Muhammad Nizar Zurrahmi Wirda