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Journal : Journal of Applied Data Sciences

Classification of Political Party Conflicts and Their Mediation Using Modified Recurrent Convolutional Neural Network Riyadi, Slamet; Suradi, Muhamad Arief Previasakti; Damarjati, Cahya; Chen, Hsing-Chung; Al-Hamdi, Ridho; Masyhur, Ahmad Musthafa
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.513

Abstract

The rapid proliferation of political information on the internet has exacerbated conflicts within political parties, including elite disputes, dualism, candidate controversies, and management issues, which can undermine political stability and public trust. To address these challenges, this study introduces the Modified Recurrent Convolutional Neural Network (M-RCNN), an enhanced RCNN model designed to improve classification accuracy and mitigate overfitting by incorporating additional layers and dropout mechanisms. The primary objective of this research is to provide an efficient and accurate framework for classifying political conflicts and mediation strategies, overcoming the limitations of traditional methods, particularly in handling imbalanced datasets and intricate data patterns. Using a dataset of 1,106 Indonesian news articles categorized into four conflict types—elite disputes, management, presidential, and legislative candidate conflicts—and four mediation strategies—leadership decisions, deliberation, legal channels, and none—the data underwent extensive preprocessing, tokenization, and an 80:20 training-testing split. The M-RCNN achieved a conflict classification accuracy of 98.0%, a precision of 99.0%, and a loss of 0.03, significantly outperforming baseline models, including CNN (85.0% accuracy), RNN with LSTM (88.0%), and standard RCNN (85.0%). For mediation strategy classification, the model demonstrated exceptional performance with an accuracy of 99.0%, a precision of 99.0%, and a loss of 0.01, highlighting its robustness and scalability. This study’s novelty lies in its ability to process imbalanced and complex datasets with unparalleled precision and efficiency, providing a practical framework for automated political conflict analysis and mediation. The findings underline the potential of the M-RCNN model to revolutionize political science applications by delivering reliable, fast, and accurate tools for analyzing and resolving political conflicts, thereby contributing to the advancement of artificial intelligence in promoting political stability and fostering public trust.
Co-Authors AA Sudharmawan, AA Achmad Nurmandi Adibah Dhivani Gusmi Ahmad Syukri . Akbar, Ali - Alfian Nurochman Ali - Akbar Alim Bubu Swarga Anawati, Dyah Mely Annida Ulfah Annisa Risky Ramadan Arfan Ashari Saputra Arissy Jorgi Sutan Astri Candra Dewi Awang Darumurti, Awang Bachtiar Dwi Kurniawan, Bachtiar Dwi Bambang Eka Cahya Widodo Banggu, Masni Cahya Damarjati Chen, Hsing-Chung Danang Kurniawan, Danang David Efendi Dewanti, Mike Diah Riski Hardiana Diah Riski Hardiana Dimas Subekti Dyah Mely Anawati Elis Nugraha Septiana Erna Trianggorowati Erna Trianggorowati Gusmi, Adibah Dhivani Haedar Nashir Halimah Abdul Manaf Halimah Halimah Hardiana, Diah Riski Heriansyah Anugrah Indar Surahmat Indriyani, Nessa Rizky Ismed Kelibay Karmila Zahrani Al Hayati Khabir, Muhammad Hazim Kharisma Purwandani Kurnia, Rahmat Kahfi Kurniasari, Lenny Kurniawati, Nawang Laras Lingganingrum Mahmud, Ramli Masyhur, Ahmad Musthafa Moch. Rifqi Mei Redha Muhamad Iqbal Muttaqin Muhammad Eko Atmojo, Muhammad Eko Naprathansuk, Non Nawang Kurniawati Nawang Kurniawati Non Naprathansuk Nur Hayati, Neni Nur Sofyan Nuryani, Najli Aidha Pahlevi, Moch Edward Trias Rahmat, Al Fauzi Resky Sirupang Kanuna Sahrul Pora Sakir Sakir Sakir Sakir, Sakir Sakti, Andi Muhammad Sary Septiana, Elis Nugraha Siti Maharani Chumairah Slamet Riyadi Sri Agustiningsih Suradi, Muhamad Arief Previasakti Suranto Suranto Suswanta Swarga, Alim Bubu Tanto Lailam Tanto Lailam Tri Oka Putra Laksana Trianggorowati, Erna Trianisa, Krisma TUNJUNG SULAKSONO Tyas Hadi Angesti Vindhi Putri Pratiwi Widiyastuti Setiabudi WIDODO, BAMBANG