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All Journal Jurnal Informatika Jurnal Infra Seminar Nasional Informatika (SEMNASIF) JOIV : International Journal on Informatics Visualization Indonesian Journal of Artificial Intelligence and Data Mining International Journal of Engineering, Science and Information Technology Jurnal Pengabdian Masyarakat Bangsa Bulletin of Social Informatics Theory and Application
Agustinus Noertjahyana
Program Studi Teknik Informatika Universitas Kristen Petra
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation

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Comparative Analysis of Support Vector Regression and Linear Regression Models to Predict Apple Inc. Share Prices Pangestu, Resza Adistya; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Noertjahyana, Agustinus
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.28594

Abstract

Stock price prediction is a complex and important challenge for stock market participants. The difficulty of predicting stock prices is a major problem that requires an approach method in obtaining stock price predictions. This research proposes using machine learning with the Support Vector Regression (SVR) model and linear regression for stock price prediction—the dataset used in the daily Apple Inc historical data from 2018 to 2023. The hyperparameter tuning technique uses the Grid Search method with a value of k = 5, which will be tested on the SVR and Linear Regression methods to get the best prediction model based on the number of cost, epsilon, kernel, and intercept fit parameters. The test results show that the linear regression model with all hyperparameters k = 5 with the average taken performs best with a True intercept fit value. The resulting model can get an excellent error value, namely the RMSE value of 0.931231 and MSE of 0.879372. This finding confirms that the linear regression model in this configuration is a good choice for predicting stock prices.
Strategic Recommendations in Increasing Gen Z User Engagement towards Gamification Elements with Fuzzy AHP and Octalysis Approaches Marisa, Fitri; Istiadi, -; Ahmad, Sharifah Sakinah Syed; Handajani, Endah Tri Esti; NoerTjahyana, Agustinus; Maukar, Anastasia L
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.3324

Abstract

Generation Z (Gen Z), often referred to as the "digital native" generation, interacts extensively with digital technology and social media. E-commerce companies need to adopt the right strategies, such as gamification, to increase user engagement among Gen Z. However, there is limited research evaluating which gamification elements are most effective in engaging Gen Z users. This study addresses this gap by identifying the most impactful gamification elements that enhance Gen Z user engagement and providing strategic recommendations for e-commerce designers and developers. Using the Fuzzy AHP method and Octalysis approach, this study evaluates five gamification elements: Point, Reward, Referral, Leaderboard, and Level across four key parameters: Motivation, Engagement, User Experience, and Retention. The Fuzzy AHP results indicate that the "Reward" element ranks highest with a score of 1.0, followed by "Level" with a score of 0.829. "Leaderboard" comes in third with a score of 0.669, while "Point" and "Referral" score 0.606 and 0.220, respectively. The low score of "Referral" suggests its limited effectiveness in fostering social connectedness among Gen Z users. The Octalysis analysis reveals that "Reward" has the most significant influence on core drives such as "Development and Accomplishment" and "Scarcity and Impatience," with an average score of 7.25, followed by "Level" with a score of 7.125. These findings underscore the importance of prioritizing "Reward" and "Level" to optimize user engagement for Gen Z. The practical implications of this study suggest that e-commerce platforms should integrate these gamification elements to create more engaging and interactive shopping experiences for Gen Z users, aligning with their preferences and motivations.
Co-Authors A.A. Ketut Agung Cahyawan W Agus Setiawan Suhariono Agustinus Darmawan Andilolo Ahmad, Sharifah Sakinah Syed Albert Halim, Albert Alexander Setiawan Alvin Assianto Leiman Anastasia Lidya Maukar Andreanus Agung Andreas Handojo Andrey Hariyanto Anik Vega Vitianingsih Anita Nathania Purbowo Che Pee, Ahmad Naim Daniel Satriautama, Daniel Daniel Wilhenson Kuntani, Daniel Wilhenson David Harjowinoto, David Della Nova Ongkodjojo Denissa Alfiany Luhulima Devi Christiani Angir, Devi Christiani Endhy, Kezia Tiatira Fanny Febriani Santoso, Fanny Febriani Fujianto - Genadiarto, Anthony Sutera Go David Gunawan Gregorius Satia Budhi Handajani, Endah Tri Esti Handojo, Steven Halim Hartanto Rusli Heinrich Wiradinata Hendy Santoso Henry Novianus Palit Ibnu Gunawan Istiadi Justinus Andjarwirawan Kabzar, Vladimir Kartika Gunadi Kevin Darmawan Limantoro Leo Willyanto Santoso M Zainal Arifin, M Zainal Machael Cahyadi, Machael MARIFANI FITRI ARISA Maukar, Anastasia L Maulana, Sandy Yunan Michael Christian Wibisono Mohamed Asghaiyer, Asghaiyer Natanael, Theodorus Nico Hartono, Nico Ocky Mahendra Alim, Ocky Mahendra Osbert Tjitro Sampurna Palit, Henry N Pangestu, Resza Adistya Paul Agustinus Praseptiawan, Mugi Raymond Adrian Hardha, Raymond Adrian Regina, Gladys O Renardi Dewanto Cahyadi, Renardi Dewanto Richard Pangalila, Richard Rosaline Debora Kusuma Rudy Adipranata Sandy Sulistio Shandy Widjaya, Shandy Silvia Rostianingsih Slamet Kacung, Slamet Stien Tjiangdiono, Stien Surjo, Gregorius Maria Vianny Novita, Vianny Vincentius Aditya Nugraha Widya Ongels, Widya William Andi Pattera Yulia Yulia Zakaria, Mohd Hafiz