Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Teknik Informatika (JUTIF)

PREDICTION OF 2024 PRESIDENTIAL ELECTION USING K-NN WITH METRIC APPROACHES CHEBYSHEV AND EUCLIDEAN BASED ON TWITTER DATA INVESTIGATION Darmawan, Steven Ryan; Fatchan, Muhamad; Maulana, Donny
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1720

Abstract

The potential difference between the popularity of presidential candidates on social media and in the general public poses a serious challenge in predicting the outcome of the 2024 presidential election. Technical constraints in collecting, cleaning and analyzing dynamic and large-scale social media data can threaten the accuracy and validity of predictions. To overcome this problem, careful steps and in-depth understanding are needed. Therefore, this study aims to predict the winner of the 2024 presidential election from the popularity of presidential candidates Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto on Twitter. The K-Nearest Neighbor (K-NN) method with the Both Metric approach (Euclidean and Chebyshev) was used to analyze 51,192 tweet data through the Knowledge Discovery in Database (KDD) stage using Orange software. The evaluation results show almost the same performance, with AUC values of 0.725 for Euclidean and 0.720 for Chebyshev. The CA result was 55.6% for Euclidean and 55.4% for Chebyshev. Although F1, precision, and recall were almost the same, overall, the Euclidean metric was better. The prediction shows Prabowo Subianto as the most popular candidate on Twitter. Nonetheless, these results need to be interpreted with caution and strengthened with further analysis and additional data to get a more comprehensive conclusion. This research shows that K-NN with both metrics can provide predictions above 50%, reliable enough to be able to predict the most popular candidates on Twitter.
Co-Authors Abdul Halim Anshor Abdurrafi, Alfin ADI FITRA Aditiya, Febri Aditya Nugroho Widiadi Afriantoro, Irfan Agung Nugroho Agus Suwarno, Agus Amali Amali, Amali Aminurdin, Majid Andri Firmansyah Anggi Muhammad Rifa’i Aning Risky Montana Anwar, M. Syaibani ARIF SUSILO Asep Muhidin Auliyah, Risma Barokah, Awalina Budiarto, Eko Darmawan, Steven Ryan Daspar Daspar Edora Edora, Edora Edy Widodo Ferawati, Eva Fitria Hermiati, Novi Gatot Tri Pranoto Halim Anshor, Abdul Hardianti, Fazrin Putri Hariyono Hartati, Nani Huda, Miftakul Ikhsan Romli Indah Wahyu Puji Utami, Indah Wahyu Indradewa, Rhian Ira Restu Kurnia Isarianto, Isarianto Ismamudi Ismamudi Ismamudi, Ismamudi Juluw, Sephia Maharani Niki Karsito Kartini, Tri Mulyani Kinanti, Aning Aning Kurniadi, Nanang Tedi Lisa Kustina Majid, Annisa Maulana Maulana Majid, Annisa Miftahul Huda Miftakul Huda Miharja, Muhammad Najamuddin Dwi Muhamad Fatchan Muhtajuddin Danny Nawangsih, Ismasari Nisawati, Inna Nugroho, Agung Nur Ilman Ilyas Nurhidayanti, Nisa Pupung Purnamasari Purwanti purwanti, purwanti Putra, Fibi Eko Putra, Maha Putri, Isria Miharti Mahaerni Rachman, Nazwa Aulia Rahardjo, Sugeng Budi Retno Purwani Setyaningrum Rismawati Rismawati Rismawati sanjay, sanjay Sellina, Sesri Sihombing, Veronika Rustiani Dame Simanjuntak, Antonius Sunita Dasman Suratman Suratman Suriyanti Surojudin, Nurhadi Tedi, Nanang Tri Ngudi Wiyatno Tri Sasongko, Ananto Turmudi Zy, Ahmad Umah, Rani Nur Wiyanto Wulandari , Anna Yansyah, Hamdi Yoga Religia