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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar
Mardin, Aslam
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Computer Science & IT

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Ethical Analysis of Online Media Journalistic Photos Worth Publishing Based on Images Using the Convolutional Neural Network Method Rijal, Syamsul; Mardin, Aslam; Anas, Anas; Sharif, Tirta Chiantalia; Sunardi, Sunardi
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11349

Abstract

This study aims to develop and test a Convolutional Neural Network (CNN)-based artificial intelligence model to analyze and classify online media journalistic photos based on ethical criteria for publication suitability (suitable or unsuitable). In the context of digital journalism, the process of filtering sensitive visual content that potentially violates the code of ethics is often time-consuming and prone to subjectivity. Therefore, a CNN model is proposed as an automated solution to identify images containing visual elements deemed unethical. An annotated image dataset was used to train and test the CNN model. The model test results showed effective and robust performance in classifying the ethical suitability of photos. The model achieved a weighted average accuracy of 0.86 (86%) and a weighted average F1 - score of 0.86. Specifically, the model performed very well in identifying "suitable" photos with precision, recall, and F1- score values ranging from 0.88 to 0.89. Performance in the "Unsuitable" class was also relatively strong with an F1 - score of 0.81. Overall, these results confirm that the CNN method has great potential as an efficient and objective decision support system in the visual content editing process. Implementing this model not only speeds up the editorial process but also improves online media's adherence to journalistic ethical standards by minimizing the risk of publishing potentially unethical photos.
Perancangan Dan Implementasi Sistem Informasi Monitoring Respon Netizen Terhadap Universitas Al Asyariah Mandar Berbasis Web Mardin, Aslam; Muslihan, Muslihan; Syarli, Syarli
JURNAL ILMU KOMPUTER Vol 10 No 2 (2024): Edisi September
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v10i2.379

Abstract

Media sosial menjadi sarana bagi masyarakat untuk menyampaikan pendapat dan memberikan penilaian terhadap berbagai isu, termasuk terhadap institusi tertentu. Banyaknya respon dan opini yang tersebar di media sosial menyebabkan proses pemantauan secara manual menjadi sulit dilakukan. Oleh karena itu, penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Monitoring Respon Netizen Berbasis Web guna mengetahui penilaian netizen berdasarkan kata kunci tertentu. Metode penelitian yang digunakan adalah metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Sistem dikembangkan menggunakan bahasa pemrograman PHP dan memanfaatkan API Twitter sebagai sumber pengambilan data. Data tweet dikumpulkan berdasarkan kata kunci “UNASMAN”, “Sulbar”, dan “Polewali”, kemudian dianalisis untuk mengelompokkan respon netizen ke dalam kategori positif, netral, dan negatif. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan berhasil terhubung dengan API Twitter dan mampu menampilkan informasi tweet berdasarkan kata kunci secara terstruktur melalui media web. Sistem ini dapat membantu pengguna dalam memantau respon netizen serta menjadi bahan evaluasi dan pendukung pengambilan keputusan.
Co-Authors Anas Anas, Anas Muslihan, Muslihan Sharif, Tirta Chiantalia Sunardi Sunardi Syamsul Rijal Syarli, Syarli