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Lunardi, Lidya
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Optimizing Convolutional Neural Networks with Particle Swarm Optimization for Enhanced Hoax News Detection Hermawan, Aditiya; Lunardi, Lidya; Kurnia, Yusuf; Daniawan, Benny; Junaedi
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 1 (2025): February
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.1.53-64

Abstract

Background: The global spreading of hoax news is causing significant challenges, by misleading the public and undermining public trust in media and institutions. This issue is worsened by the rapid spreading of misinformation which is facilitated by digital platforms, triggering social unrest and threatening national security. To overcome this problem, reliable and robust method is essential to adapt to the evolving tactics of misleading information spreading. Objective: This study aimed to improve the accuracy of hoax news detection tools by evaluating the effectiveness of Deep Learning methods enhanced with Convolutional Neural Networks (CNNs) using Particle Swarm Optimization (PSO). Methods: The dataset was processed by tokenization, stopword removal, and stemming. CNNs were trained with default parameters, due to their potential as one of the effective methods for text classification. Furthermore, PSO was used to optimize the main parameters such as filters, kernel sizes, and learning rate, which was refined iteratively based on validation accuracy. Results: The optimized CNNs+PSO was further tested by data training to show its effectiveness in detecting hoax news and misleading articles. The result showed that the optimized CNNs+PSO model had high effectiveness, by achieving accuracy rate of 92.06%, precision 91.6%, and recall 96.19%. These values validated the model’s ability to classify hoax news in Indonesian accurately. Conclusion: This study showed that the optimized CNNs+PSO method was highly effective in detecting hoax news and misleading articles by achieving impressive accuracy, precision, and recall rate. The integration showed the potential of CNNs+PSO to mitigate the impacts of hoax news, enhance public awareness, and promote people to critically believe the news Keywords: Convolutional Neural Networks, Deep Learning, Hoax, Particle Swarm Optimization, Text Mining
PROTOTIPE SISTEM OTOMASI SMART OFFICE DENGAN MENGGUNAKAN LOCK DOOR, MOTION SENSOR, DAN LCD BERBASIS ARDUINO UNO Dwiyanthi Kusuma, Ellysha; Ignatius Tarunay, Oliver; Lunardi, Lidya; Andika
RUBINSTEIN Vol. 1 No. 2 (2023): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v1i2.2094

Abstract

Perkembangan teknologi diera digital ini sangat lah pesat khususnya pembuatan perangkat otomasi telah berkemkembang sangat cepat dan telah mengalami banyak sekali kemajuan dalam berbagai bidang yaitu dalam bidang perkantoran, kesehatan, keamanan, transportasi dan ekonomi. Pada penelitian ini komponen yang di gunakan untuk pembuatan sistem otomasi dengan menggunakan perangkat berbasis Arduino Uno. Permasalahan ini Berfokus dari sebuah perusahaan adalah dengan cara meminimalisir kesalahan dan efisiensi pengeluaran.Sedangkan tujuan utama dari sebuah perusahaan adalah memaksimalkan laba dengan menekan biaya seminimal mungkin. Barometer keberhasilan sebuah perusahaan dapat ditentukan berdasarkan kemampuan sebuah perusahaan untuk mendapatkan profit. Profit dihasilkan setelah dilakukan pengurangan terhadap biaya produksi yang dilakukan. Penelitian ini melakukan pembuatan tempat smart office menggunakan sensor  RFID scanner  telah dilakukan dengan tujuan untuk mengembangkan sistem yang dapat mempermudah mempermudah karyawan dalam melaksanakan kegiatan di dalam kantor.  
Pengaruh Streamer Attractiveness, Content Marketing, dan Hedonic Shopping Motive terhadap Impulsive Buying dengan Utilitarian Value sebagai Pemoderasi Lunardi, Lidya; Alexander; Tambun, Sihar
RUBINSTEIN Vol. 4 No. 1 (2025): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v4i1.4040

Abstract

This study investigates the impact of streamer attractiveness (SA), content marketing (CM), hedonic shopping motive (HSM), and utilitarian value (UV) on impulsive buying (IB) in the context of Indonesian e-commerce live streaming. It also examines how UV moderates the relationships between these factors and IB. A quantitative approach was adopted, using purposive sampling of 209 respondents who had previously participated in live shopping broadcasts. Data analysis was performed with Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings show that SA, CM, HSM, and UV all have a significant positive effect on IB, with HSM identified as the most dominant factor influencing impulsivity. Furthermore, UV moderates the relationship between SA and IB, but does not significantly enhance the effect of CM or HSM on IB. These results suggest that emotional drivers such as enjoyment and attractiveness are key catalysts for impulsive purchasing behavior. However, functional product value still plays a strategic role in driving purchase decisions. The study emphasizes the need for a balanced approach in content strategy, combining both emotional appeal and functional information to maximize consumer engagement and conversion. Marketers are encouraged to integrate hedonic (emotional) and utilitarian (practical) elements in their offerings to foster impulsive buying behavior. Additionally, future research should explore longitudinal and qualitative methods to capture the evolving nature of impulsive buying behavior, as well as the deeper psychological mechanisms driving consumer decisions in live commerce environments. Such research will help further uncover the dynamics of consumer decision-making in online shopping and improve understanding of the broader implications for e-commerce strategies.
Co-Authors Aditiya Hermawan alexander ANDIKA Daniawan, Benny Dwiyanthi Kusuma, Ellysha Ignatius Tarunay, Oliver JUNAEDI Sihar Tambun Yusuf Kurnia, Yusuf