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All Journal METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Pendidikan Ekonomi (JURKAMI) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Indonesian Journal of Social and Educational Studies Economics and Business Journal Open Community Service Journal Journal of Economic Education and Entrepreneurship Studies SAGA: Journal of Technology and Information Systems Seminar Nasional Hasil Penelitian LP2M UNM Amal: Jurnal Ekonomi Syariah
Najib, Marhawati
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Religion Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Journal : SAGA: Journal of Technology and Information Systems

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Sentiment Analysis on Erspo Jersey in X Using Machine Learning Algorithms Andi Asrida Reskinah. D; Najib, Marhawati; Muhammad Ashdaq
SAGA: Journal of Technology and Information System Vol. 2 No. 3 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i3.334

Abstract

This research conducts a sentiment analysis on Erspo jerseys using machine learning algorithms on the X platform. The objective is to identify the public's sentiment and compare the performance of three algorithms: Naïve Bayes, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Data was collected through web scraping of tweets between January and September 2024, containing keywords related to Erspo. Using a lexicon-based approach, the preprocessing steps involved cleaning, tokenizing, normalizing, and labeling data into positive, negative, and neutral sentiments. Results show that the Naïve Bayes algorithm provided the highest accuracy in sentiment classification, followed by SVM and KNN. Positive sentiment primarily centered on product loyalty, while negative sentiment largely criticized jersey design and quality. The findings offer important insights for Erspo stakeholders to refine marketing strategies and product improvements. This study highlights the potential of machine learning in analyzing consumer opinions at scale, making it a valuable tool for real-time consumer feedback analysis.
Implementation of Fundamental Analytical Dashboard and Stock Price Forecasting of ADRO, ANTM, INCO with Arima Approach Najib, Marhawati; Nur Aulia Cahyani; Syamsu Alam
SAGA: Journal of Technology and Information System Vol. 2 No. 3 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i3.335

Abstract

This study aims to compare the financial performance of ADRO, ANTM, and INCO and project the stock prices using fundamental analysis and the ARIMA approach. The background of this study is based on the phenomenon of herding behavior and overconfidence of investors who often ignore fundamental analysis in making investment decisions. This study adopts a quantitative method using financial ratio data and historical stock prices and a qualitative method through visualization in the form of an analytical dashboard. The results of the study show that ADRO has an advantage in terms of profitability, INCO stands out in liquidity, and ANTM experiences fluctuations in financial performance. The ARIMA model can project the stock prices of the three companies by showing a positive trend for INCO and ANTM, while ADRO tends to be stable. The analytical dashboard developed helps investors understand financial performance and stock price projections, thus supporting more accurate investment decision-making.
Co-Authors Afrinda Andi Asrida Reskinah. D Andi Sawe Ri Esso Andi Tenri Ampa Chaerunnisa Najib esso, andi sawe ri Fitri, Ade Fuad, M. Fikri Nur INANNA Irwandi Miftahul Jannah Mubarak, Muhammad Fadel Muhammad Ashdaq Muhammad Asiz Muhammad Hasan Muhammad Ilyas Thamrin Tahir Muhammad Jufri MUSTARI Mustari Mustari Novita Nur Aulia Cahyani Nuralisa, Nuralisa Nurhalim Nurjannah Nurjannah Nur’Aeni, Nur’Aeni Rahmatullah Rajab, Nurjannah Ratna Sri Astuty Subur, Hikmayani Syam, Agus Syamsu Alam Syamsu Rijal Tadampali, Andi Caezar To Tuti Supatminingsih Valentino Aris, Valentino Wahyu Hidayat M WULAN PURNAMASARI, WULAN Zulistnayarti, Andi