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All Journal INFOKAM Sisforma: Journal of Information Systems Journal of Information Systems and Informatics Journal of Computer and Information Systems Ampera Journal of Business and Technology International Journal of Artificial Intelligence and Science Computing and Information System Journal
Albertus Dwiyoga Widiantoro
Information System Department, Computer Science Faculty Soegijapranata Catholic University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Social Sciences Other

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Implementing CryptoWoo as a Cryptocurrency Payment Gateway on the Contemporary Curiosities Online Store Kurniawan, Margareta Sheryl; Widiantoro, Albertus Dwiyoga; Harnadi, Bernardinus
SISFORMA Vol 12, No 1: May 2025
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24167/sisforma.v12i1.13174

Abstract

This study aims to implement the CryptoWoo payment gateway and analyse its implementation on WordPress as a cryptocurrency payment gateway for the Contemporary Curiosities online store. The online store is built using WordPress with additional plugins such as WooCommerce, CryptoWoo, Super Socializer, and Tawk.to. The development of the online store follows the waterfall method, while testing is conducted using black box testing through in-depth interviews. This study evaluates ease of use, functionality, and user acceptance. The results show a positive potential for CryptoWoo as a cryptocurrency payment gateway. Support and acceptance from representatives of the cryptocurrency trading platform Indodax, application development partners, and students as potential consumers of the Contemporary Curiosities online store indicate a positive response.
Analisis Efektifitas Machine Learning Pada Saham PT. Adaro Energy: SVM, NN, K-NN Dan RL Dengan Rapidminer Thobibuddin, Firstiawan Fadhil; Widiantoro, Albertus Dwiyoga
Computing and Information System Journal Vol. 1 No. 1 (2025): Technological Innovation for System Automation and Efficiency
Publisher : IndoCompt Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research investigates the effectiveness of four machine learning models in predicting the stock prices of PT Adaro Energy Tbk. The models evaluated include Support Vector Machine, Neural Network, K-Nearest Neighbors, and Linear Regression. Daily stock price data was collected from the period of June 3, 2019, to May 31, 2024, then processed and trained using preprocessing techniques to ensure the quality of the analyzed data. Each model was evaluated using prediction accuracy metrics and Root Mean Squared Error on a separate test dataset. The experimental results show that LR provides the best performance with the lowest RMSE value, followed by SVM, KNN, and LR. These findings indicate that LR can be an optimal choice for predicting the stock prices of PT Adaro Energy Tbk in this context.
BBCA Stock Price Prediction Using Linear Regression Method Saputra, Shannon Dominique; Widiantoro, Albertus Dwiyoga
International Journal of Artificial Intelligence and Science Vol. 1 No. 1 (2024): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v1.i1.7

Abstract

This study focuses on predicting the stock price of Bank Central Asia (BBCA) using linear regression techniques, a widely utilized statistical method in financial forecasting. Stock price prediction is critical for investors, particularly in volatile markets like Indonesia. This research analyzes the relationship between key variables, such as adjusted closing prices and trading volume, based on historical data. The methodology includes data collection, preprocessing, model construction, and evaluation using metrics like Root Mean Square Error (RMSE) to assess the model's accuracy. The results indicate that linear regression can effectively predict BBCA stock prices with reasonable accuracy, providing a practical and interpretable tool for investors. These findings contribute to financial forecasting by demonstrating the utility of linear regression in stock price prediction, particularly in emerging markets.
Co-Authors Agus Cahyo Nugroho Anastasia Widiastuti Andre Kurniawan Pamudji Bernadinus Harnadi Bernardinus Harnadi Bernardinus Harnadi Chandrawati, T. Brenda Chrismastuti, Agnes Advensia Christianto Gunadi Eddy Sukamto Elisa Purnamasari Erdhi Widyarto Evangeline Eunike Evania Chrestella Albertina FX Hendra Prasetya FX Hendra Prasetya Gregorius Alvin Raditya Santoso Hardayani, Bernadheta Dinar Koen Hartono, Pieter Chang Helarius Panji Aruna Hendra Prasetya Hendra Prasetya JImmy Wiyanto Khoirul Fikri Shona Kurniawan, Margareta Sheryl Lydia Natalia Kristiani Maximiliano, Oeij Dominic Aldrich Muljanto, Yehuda Joy Namudani, Ninggar Nugroho, Agus Cahyo pieter santoso hadi Ridwan Sanjaya Saputra, Shannon Dominique Stefanus Lintang Timur Aji Pamungkas Steven Wisnu Cahya Putra T Brenda Chandrawati Thobibuddin, Firstiawan Fadhil Vania Wahyu Febriani Victorio Almers Chrisetya Putra Yuvisan, Evaditus Kresna