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All Journal Journal Software, Hardware and Information Technology MDP Student Conference Jurnal Software Engineering and Computational Intelligence Journal of Intelligent Systems and Information Technology Jurnal Sistem Informasi Komputer dan Teknologi Informasi
Firza Septian
Universitas Serelo Lahat
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Unlocking Communication Wonders: Exploring Transmitter and Receiver Concepts with p5.js Septian, Firza
Journal Software, Hardware and Information Technology Vol 4 No 2 (2024)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v4i2.123

Abstract

This research presents comprehensive results in various forms such as images, graphs, tables, etc., to facilitate a profound understanding of the developed transmitter-receiver simulation using p5.js. Each component, including setting the canvas, dynamic display, user interaction, binary conversion, transmitter and receiver objects, simulation reset, and testing and evaluation, is thoroughly discussed in separate subsections. A comparative analysis with previous studies is incorporated for enhanced context. The testing phase not only validates the simulation's functionality and accuracy but also emphasizes its role as a potent educational tool. The successful execution of the experiment attests to the codebase's robustness, confirming its ability to effectively illustrate digital communication fundamentals. The visualization of binary signals enhances the project's educational dimension, transforming intricate concepts into an accessible, interactive learning experience. Future testing and refinements present exciting opportunities to augment user experience and extend simulation capabilities. This positive outcome establishes a solid foundation for the program's educational utility, making it a valuable resource for imparting digital communication knowledge. In conclusion, the validated transmitter-receiver simulation marks a significant milestone, combining functionality, visual representation, and potential enhancements. Positioned as an innovative educational technology, it fosters curiosity and understanding in learners exploring digital communication nuances.
Utilization of the Whale Optimization Algorithm in Finite State Automata Design for Advanced Pattern Recognition Systems Septian, Firza; Prakarsya, Agustian
Jurnal Software Engineering and Computational Intelligence Vol 2 No 02 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i02.4844

Abstract

This research explores the application of the Whale Optimization Algorithm (WOA) in designing Finite State Automata (FSA) for advanced pattern recognition systems. Pattern recognition plays a crucial role in various fields, requiring high accuracy and efficiency. Traditional approaches to FSA design often face limitations in adaptability and optimization. By integrating WOA, a nature-inspired metaheuristic algorithm, this study aims to optimize FSA structures to improve recognition capabilities. The research process involves implementing WOA within the FSA design framework, testing it on multiple artificial pattern recognition tasks to assess effectiveness, and comparing results with other optimization methods. The findings reveal that after 10 iterations, the WOA achieved a best score of 14.01% error, indicating initial progress but room for further improvement. At 50 iterations, the performance plateaued, maintaining a score of 9.43% error, suggesting a need for additional exploration of the parameter space. However, by 100 iterations, the WOA produced a significantly improved score of 0.0022% error, demonstrating a highly optimized solution as the parameters converged closely to their target values. After 100 iterations, the error value did not decrease any further, indicating that the effective iteration count for optimization is 100 iterations. These results highlight the effectiveness of WOA in enhancing FSA performance, showcasing its potential as a robust solution for complex pattern recognition needs. This study contributes to the development of intelligent recognition systems, advancing the state of the art in pattern recognition technology.
ALGORITMA OPTIMISASI WHALE UNTUK DIAGNOSTIK MEDIS: REVIEW LITERATUR SECARA SISTEMATIS Septian, Firza; Utami, Ema
SISKOMTI: Jurnal Sistem Informasi Komputer dan Teknologi Informasi Vol. 4 No. 2 (2022): Agustus 2022
Publisher : Universitas Lembah Dempo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54342/tb9k1278

Abstract

A lot of factors, including noise, have a harmful impact on the health of people from all walks of life, including unborn children. In the medical field, grouping research utilizing WOA was required. Data is gathered from a number of reliable sources, including IEEE and Scopus. Practical applications serve as a "Laboratory" in the action research methodology for testing theories. on items that have been synthesized. Regarding WOA for medicinal purposes, there are three basic concepts. The plan calls for the use of WOA for medical diagnostic. A population-based method called the Whale Optimization Method (WOA) uses a randomized collectivist humpback whale sample to improve prospective solutions. Three of the 74 journals gathered satisfied the predetermined criteria.
A Systematic Literature Review Of Mental Health Diagnostic Using K-Nearest Neighbour - Whale Optimization Algorithm Septian, Firza; Kusrini , Kusrini; Hidayat, Tonny
SISKOMTI: Jurnal Sistem Informasi Komputer dan Teknologi Informasi Vol. 5 No. 1 (2023): Februari 2023
Publisher : Universitas Lembah Dempo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54342/ptc0pb11

Abstract

People including unborn infants are negatively impacted by a number of things, such as noise. Noise and the others aspect could affect somebody mental health. Mental health as natural problem might be easier detected using metaheuristic algorithm, K-Nearest Neighbour - Whale Optimization Algorithm (KNN-WOA) is one of them. A variety of trustworthy sources, including IEEE and Scopus, are used to collect the data. In the action research technique, practical applications work as a "Laboratory" for testing hypotheses on synthesized products. There are three fundamental ideas in regard to using WOA for medical purposes. KNN will be used according to the plan for medical diagnostics. WOA, a population-based approach, uses a randomized collectivist humpback whale sample to enhance potential solutions as feature selection while KNN as the main algorithm. Only three of the 94 journals collected met the set standards.
Pemanfaatan Mit App Inventor Dalam Pengembangan AplikasiKamus Bahasa Ogan Dengan Algoritma Levenshtein Distance Prakarsya, Agus; Nurmala Sari, Yusi; Septian, Firza
SISKOMTI: Jurnal Sistem Informasi Komputer dan Teknologi Informasi Vol. 7 No. 1 (2025): Februari 2025
Publisher : Universitas Lembah Dempo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54342/332bmn91

Abstract

Sumatera Selatan mempunyai beberapa bahasa daerah, salah satunya adalah bahasa Ogan. Dimana penggunaan bahasa Ogan dalam komunikasi sehari-hari mengalami penurunan dikarenakan banyak masyarakat mengutamakan bahasa gaul. Oleh karena itu, perlunya membuat sebuah aplikasi yang dapat memenuhi keinginan setiap pengguna akan pengganti buku yang bersifatportabel yang bisa pakai kapan saja dan di mana saja. Media aplikasi kamus dapat menjadi solusi untuk mengenalkan bahasa Ogan kepada masyarakat luas. Tujuan dari penelitian ini ialah membuat kamus bahasa ogan dengan Pemanfaatan MIT App Inventor dalam Pengembangan Aplikasi Mobile untuk mempermudah proses pembelajaran bahasa daerah Ogan secara efektif dan efisien. aplikasi kamus bahasa. Metode levenshtein distance yang digunakan pada penelitian ini sedangkan untuk pengembangan perangkat lunaknya menggunakan model waterfall.Aplikasi ini dibuat dengan menggunakan MIT App Inventor. Hasil dari aplikasi ini dapat menjadi media yang bermanfaat untuk pembelajaran, pelestarian dan pengembangan bahasa daerah untuk tetap dilestarikan sebagai kekayaan bahasa.
Prediksi GDP dengan RF dan XGBoost Berdasarkan Aspek Sosial, Ekonomi, dan Lingkungan Mubarok, M. Husni; Septian, Firza
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11206

Abstract

This study aims to analyze Gross Domestic Product (GDP) prediction using Random Forest and XGBoost algorithms by considering social, economic, and environmental variables. The dataset was obtained from Kaggle and includes 22 independent variables influencing GDP. The model was developed with Whale Optimization Algorithm (WOA) optimization to improve prediction accuracy. Experiments were conducted on the Google Colab platform, and evaluation metrics included Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-Squared (R²). The results show that XGBoost with WOA optimization achieves higher prediction accuracy compared to Random Forest. Key factors influencing GDP were identified through feature correlation analysis. In conclusion, the combination of machine learning and metaheuristic-based optimization methods enhances GDP prediction accuracy, providing valuable insights for economic policymakers.
Identification of Determinants of Inclusive Economic Growth Using the Metaheuristic Whale Optimization Algorithm Approach Septian, Firza; Putriani, Nina Dwi
Jurnal Software Engineering and Computational Intelligence Vol 3 No 01 (2025)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v3i01.5396

Abstract

Inclusive economic growth demands the identification of key factors that drive equitable improvements in regional welfare. However, the complex interrelationships among social, economic, and demographic variables make traditional approaches insufficient for handling high-dimensional data. This study introduces an innovative approach by combining the Whale Optimization Algorithm (WOA) for feature selection with a Random Forest Regressor model to predict Gross Regional Domestic Product (GRDP) per capita as the main indicator of regional prosperity. The dataset consists of 210 regional observations and 18 independent variables. Feature selection using WOA was guided by minimizing the mean squared error (MSE), resulting in the identification of the 8 most relevant features. The retrained Random Forest model on the selected features achieved a high prediction performance, with an R² value of 0.9938 and a low RMSE. Furthermore, GRDP values were categorized into three regional welfare classes (Low, Medium, High), and the classification yielded 97.92% accuracy with high precision, recall, and F1-scores across all classes. These findings demonstrate that combining metaheuristic optimization and machine learning enables efficient and accurate identification of the key determinants of inclusive economic growth. The results provide valuable insights for formulating more targeted regional development policies.
Build Up Aplikasi Verifikasi Kemurnian Balok Karet dengan Whale Optimization Algorithm Septian, Firza; Sulkhan Nurfatih, Muhammad
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 Mediansyah, Iski; Septian, Firza; Zikry, Arief
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.
Performance Optimization of Document Clustering for Harry Potter Series Comments using Cosine Similarity Septian, Firza; Zikry, Arief; Dwi Putriani, Nina
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.
Co-Authors Dwi Putriani, Nina Ema Utami Iski Mediansyah Kusrini , Kusrini Mubarok, M. Husni Muhammad Sulkhan Nurfatih Prakarsya, Agus Prakarsya, Agustian Putriani, Nina Dwi TONNY HIDAYAT Yusi Nurmalasari