Claim Missing Document
Check
Articles

Pengaruh Pengembangan Aplikasi Web Deteksi Clickbait Pada Judul Berita Online Berbahasa Indonesia Menggunakan Metode Naïve Bayes Classifier Muhammad Ro’is Misbakhul Munir; Budi Hartono; Eko Siswanto
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 6 No. 2 (2026): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v6i2.11521

Abstract

This study aims to develop a web-based application for detecting clickbait in Indonesian online news headlines using the Naïve Bayes Classifier method, with case studies on Kompas.com and Detik.com. The problem underlying this research is the widespread use of sensational headlines that may mislead readers. The system is developed as a web application using XAMPP as the local server environment, Apache as the web server, and MySQL as the database. The system process begins with users entering news headlines, followed by text preprocessing, which includes tokenization, filtering, and word weighting before classification is performed using the Naïve Bayes algorithm. The application also provides model training and search history features that run in the local XAMPP environment to store previous detection results. The testing results show that the system can automatically classify news headlines into clickbait and non-clickbait categories with a fast processing time. The implementation of the Naïve Bayes method is considered effective because it is simple, lightweight, and suitable for short text classification, such as news headlines. However, the system’s accuracy is still influenced by the amount of training data used. This application is expected to help users identify clickbait news headlines, improve public digital literacy, and support more objective and reliable information consumption.
Pemanfaatan Teknologi Internet of Things untuk Monitoring Kualitas Air Sungai di Wilayah Perkotaan Danang Danang; Nuris Dwi Setiawan; Eko Siswanto
Journal of New Trends in Sciences Vol. 2 No. 1 (2024): Februari: Journal of New Trends in Sciences
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jnts.v2i1.784

Abstract

The rapid urbanization and industrialization of cities have significantly contributed to the rising pollution levels, especially in urban rivers, where water quality is often compromised. Monitoring water quality in real-time is essential for mitigating the adverse effects of water contamination. This research aims to design and implement an Internet of Things (IoT)-based system for real-time monitoring of water quality in urban rivers, focusing on the continuous collection and analysis of environmental data. The system utilizes a range of sensors to measure critical water quality parameters, including pH, temperature, dissolved oxygen (DO), turbidity, and various contaminants, all of which transmit data wirelessly to a central server for further processing. The study evaluates the accuracy, reliability, and efficiency of the IoT system in detecting water pollution and its ability to deliver real-time insights. Findings demonstrate that the IoT system offers a higher level of precision and faster detection compared to conventional monitoring methods, making it an effective tool for real-time pollution detection and decision-making. Additionally, the integration of the IoT system with a user-friendly visualization platform enhances the accessibility of the data for stakeholders, enabling them to monitor the water quality effectively. The study suggests that IoT-based water quality monitoring systems present a sustainable long-term solution for urban water management, offering cost and time savings. Moreover, the research highlights the importance of cross-sector collaboration to support the development and deployment of IoT technologies and recommends further advancements in sensor technologies to monitor additional water quality parameters.