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All Journal Jurnal Software Engineering and Computational Intelligence Journal of Intelligent Systems and Information Technology
Firza Septian
Universitas Serelo Lahat
Computer Science & IT Engineering

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Performance Optimization of Document Clustering for Harry Potter Series Comments using Cosine Similarity Firza Septian; Arief Zikry; Nina Dwi Putriani
Journal of Intelligent Systems and Information Technology Vol. 1 No. 1 (2024): January
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v1i1.30

Abstract

This research delves into the distinctive realm of comment clustering, focusing on the extensive discourse generated by the Harry Potter series. Leveraging a dataset from Kaggle, the study aims to optimize document clustering using cosine similarity within the K-Means algorithm. The research addresses the nuanced dynamics of sentiment and preferences within the Harry Potter fan community. A comprehensive methodology involves data collection, preprocessing, TF-IDF initialization, K-Means clustering with varying distance metrics, and result evaluation. The dataset of 491 respondents unveils diverse gender, geographical, and age distributions, adding complexity to the analysis. The K-Means clustering results highlight predominant positive sentiment, emphasizing the enduring popularity of the series. The study's originality lies in its focus on the Harry Potter cultural phenomenon, contributing to sentiment analysis and fan engagement discourse. The implications extend to researchers, practitioners, and enthusiasts seeking a deeper understanding of online discussions surrounding iconic media franchises.
Exploring the Performance of Whale Optimization Algorithm on Rosenbrock's Function Firza Septian
Journal of Intelligent Systems and Information Technology Vol. 1 No. 2 (2024): July
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v1i2.35

Abstract

Optimization of complex and nonlinear functions is essential across various domains, from engineering and finance to artificial intelligence and machine learning. Rosenbrock's function stands as a fundamental benchmark for evaluating optimization algorithms due to its highly nonlinear and multimodal nature. Among the multitude of optimization algorithms, the Whale Optimization Algorithm (WOA) has garnered attention for its inspiration from the social behavior of humpback whales. However, its performance on Rosenbrock's function remains relatively unexplored. This paper aims to investigate the effectiveness of the WOA specifically on Rosenbrock's function through rigorous experimentation and analysis. By evaluating convergence speed, solution accuracy, and robustness, this study sheds light on WOA's behavior when confronted with the challenges posed by Rosenbrock's function. Comparative analysis with other optimization algorithms further elucidates WOA's adaptability and scalability. The findings contribute valuable insights for selecting suitable optimization algorithms in real-world applications and advance understanding of optimization algorithms' behavior in challenging landscapes.
Build Up Aplikasi Verifikasi Kemurnian Balok Karet dengan Whale Optimization Algorithm Firza Septian; Muhammad Sulkhan Nurfatih
Jurnal Software Engineering and Computational Intelligence Vol 2 No 01 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i01.4146

Abstract

The rubber industry requires precise quality control of rubber blocks to maintain product consistency and customer satisfaction. This study develops an application to verify the purity of rubber blocks using the Whale Optimization Algorithm (WOA). The application aims to provide an accurate, efficient, and automated solution for detecting impurities. Inspired by the bubble-net hunting strategy of humpback whales, WOA is effective in solving complex optimization problems. In this research, WOA optimizes parameters for impurity detection, enhancing verification accuracy. The application integrates image processing techniques and machine learning algorithms. Images of rubber blocks are captured and processed to extract relevant features, which are then analyzed using WOA to identify impurities. Extensive testing demonstrated that the application achieves high accuracy in impurity detection, outperforming traditional methods. The use of WOA significantly reduces processing time, making the application suitable for real-time industrial verification. This study highlights the potential of the Whale Optimization Algorithm to improve quality control processes in the rubber industry. The developed application offers a reliable and efficient tool for ensuring rubber block purity, thereby enhancing product quality and operational efficiency.
Penerapan Whale Optimization Algorithm dalam Pengoptimalan Portofolio Investasi Menggunakan Model Prediktif Artificial Intelligence Iski Mediansyah; Firza Septian; Arief Zikry
Jurnal Software Engineering and Computational Intelligence Vol 2 No 01 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i01.4147

Abstract

The optimization of investment portfolios has become a primary focus in the management of dynamic financial markets. The Whale Optimization Algorithm (WOA) and Artificial Intelligence (AI) have emerged as potential solutions to tackle market complexities. WOA offers an efficient approach to finding optimal solutions, while AI models such as Artificial Neural Networks (ANN) and Machine Learning (ML) algorithms are effective in predicting market behaviors. The integration of WOA and AI holds promise for better outcomes in optimizing investment portfolios by considering complex factors and market volatility. However, the development of this technology requires interdisciplinary collaboration, increased financial and technological literacy, and consideration of social and environmental aspects. With a sustainable, inclusive, and responsible approach, we can create a more sustainable financial future that positively impacts society and the environment.
Co-Authors Arief Zikry Iski Mediansyah Muhammad Sulkhan Nurfatih Nina Dwi Putriani