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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika SAGA: Journal of Technology and Information Systems
Ramadhan, Duta Pramudya
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science

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Enhancing Cable News Network Comprehension: Text Rank Integrated Natural Language Processing Summary Algorithm Ramadhan, Duta Pramudya; Hindarto, Djarot
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.13600

Abstract

In the online news space, timely content delivery has become essential due to the unavoidable information overload. This study investigates the use of Python-based text summarizing techniques on news sites, promoting the combination of Natural Language Processing approaches with the Text Rank summarization algorithm. The primary objective is to deliver automatic news article summaries while preserving pertinent information, this is confirmed by means of experimental testing. This study uses the Text Rank technique on a news platform to enhance summaries' readability and information absorption capacity. To test the Text Rank algorithm's capacity to provide enlightening summaries, two news stories from the Cable News Network were chosen for the experiment. The word "Trump" obtained the highest score of 16.52 when sentence scores were calculated using the Text Rank algorithm. "Former" came in second with a score of 1.95, "McCarthy" was third with a score of 1.31, and "President" and "Republican" were each awarded a score of 1.03. Furthermore, the terms "CNN" and "Establishment" received scores of 0.79 and 0.58, respectively, for "DeSantis" and "Endorsements." Reader accessibility and convenience can be improved by using a news summary algorithm on a Python-based platform to swiftly retrieve important information. This research emphasizes the critical role that summary algorithm technology plays in enabling efficient and easily accessible information consumption in the digital age, in addition to creating automated tools for news summaries.
Jakarta Air Quality Classification Based On Air Pollutant Standard Index Using C4.5 And Naïve Bayes Algorithms Ramadhan, Duta Pramudya; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 2 No. 4 (2024): November 2024 (IN PRESS)
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i4.395

Abstract

Increasing air pollution in DKI Jakarta has become an increasingly pressing environmental issue, which has a direct impact on public health and environmental sustainability. Therefore, it is very important to have a system that manages data-based air pollution levels. The purpose of this research is to classify air quality in DKI Jakarta through Air Pollutant Standard Index (ISPU) data. This data consists of parameters such as dust particles (PM10, PM2.5), sulfur dioxide (SO2), carbon monoxide (CO), surface ozone (O3), and nitrogen dioxide (NO2), as well as two classification algorithms used, namely C4.5 and Naïve Bayes. This research also seeks to compare the effectiveness of the two algorithms based on ISPU data collected in 15 Jakarta areas. The approach used in this research is to divide the data using three ratio scenarios, namely 70% : 30%, 80% : 20%, and 90%: 10%. In addition, performance assessment is carried out using accuracy, precision, recall and f1 score metrics. The experimental results showed better performance of C4.5, with an average accuracy of 95%, precision of 99%, recall of 94% and f1-score of 97%. In contrast, Naïve Bayes recorded an average accuracy of 81%, precision of 93%, recall of 73% and f1-score of 82%. These findings corroborate the validity of the C4. 5 algorithm is more effective in air quality classification based on ISPU, thus making it a reliable resource for air quality monitoring and management in DKI Jakarta, as well as supporting decision-making in air pollution control policies.
Co-Authors Agung Triayudi Hindarto, Djarot