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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Klabat Journal of Management DIGIBE: Digital Business and Entrepreneurship Journal
Irawan Wingdes, Irawan
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Perbandingan Metode Pengujian Teori TAM Pada Penerimaan Teknologi E-Money di Pontianak Wingdes, Irawan; Kosasi, Sandy; Yuliani, I Dewa Ayu Eka
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 11, No 1 (2021): Volume 11 Nomor 1 Tahun 2021
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol11iss1pp26-33

Abstract

As a researcher, one could analyze Technology Acceptance Model (TAM) by utilizing several methods. Such methods are summated scales regression, factor analysis score regression, covariance-based SEM, and PLS-based SEM. However, there exists less effort to compare the difference in estimates of these methods in a single dataset. The differing estimates could therefore lead to type I statistical errors. This research purpose was to compare these methods objectively with a single dataset. The dataset tested was derived from e-money research in Pontianak, with 280 data collected at refueling stations during May, June, July 2020. This research contributes to proofing how method choices will produce a differing interpretation even though tested on the same dataset. Summated scale regression and PLS-based SEM produced similar estimation results but differed from factor analysis score regression and covariance-based SEM. Further testing implies that the different estimates are due to the elimination of indicators, which is method-specific. Therefore, method justification, completeness of research report, and research context are crucial for accounting limitation of the method chosen. PLS-based SEM was a suitable method for data utilized with 50,3% variability in usefulness, 58% variability in intention to use is accounted for from the research model.  
SHORT VIDEO APPLICATION USAGE AND FLOW EFFECT ON IMPULSE BUY Wingdes, Irawan; Luwuk, Yosua Markoliano
Klabat Journal of Management Vol 4 No 2 (2023): Klabat Journal of Management
Publisher : Faculty of Economics and Business, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60090/kjm.v4i2.1027.163-172

Abstract

Mobile Short Video Applications (MSA), offering short video content and often including referral and commercial features, have attracted a substantial user base, appealing to marketers. However, previous research has not specifically focused on how the use of MSA can influence impulsive buying. Therefore, this research aims to fill this gap by integrating the concept of flow (intense engagement with an activity) into the Stimulus-Organism-Response (SOR) Model. In this context, the utilization of MSA serves as the Stimulus, while flow is divided into enjoyment, concentration, and time distortion, acting as the Organism. The observed Response is impulsive buying. A survey-based questionnaire research method was employed, with a sample of 190 university students. Structural equation modeling (SEM) techniques were used to examine the relationships among the constructs, complemented by qualitative analysis. The research findings indicate that the use of MSA significantly influences the experience of flow, which, in turn, affects impulsive purchasing behavior. Flow (enjoyment) exerts the strongest influence on impulsive buying (0.459 correlation), compared to concentration (0.204) and time distortion (0.212). Enjoyment also mediates the relationship between MSA usage and impulsive purchasing. Users tended to engage in spontaneous and unplanned impulsive purchases when they were in a heightened state of flow, predominantly triggered by enjoyment while using MSA, as opposed to concentration or time distortion. The testing model is valid and reliable within a statistical confidence level exceeding 90%, explaining 29.5% of the variance in impulse buying. Keywords: MSA usage, SOR model, flow, impulse buy
Perencanaan Strategis Electronic Social Customer Relationship Management untuk Peningkatan Keterlibatan Pelanggan Callista, Marlline; Kosasi, Sandy; Wingdes, Irawan; Syarifudin, Gusti; Yuliani, I Dewa Ayu Eka
Jurnal Ilmiah IT CIDA Vol 8 No 2: Desember 2022
Publisher : STMIK AMIKOM Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55635/jic.v8i2.162

Abstract

Perubahan perilaku pada konsumen menciptakan kebutuhan akan keterlibatan pelanggan. Namun, penggunaan media sosial yang belum maksimal dan akses informasi yang masih terbatas, membuat vihara kesulitan dalam memonitor dan merespon umatnya secara menyeluruh. Penelitian bertujuan merancang strategis e-SCRM dalam rangka meningkatkan keterlibatan umat dalam vihara. Metode penelitian menggunakan Design Science Research (DSR). Metode perencanaan strategis e-SCRM menggunakan Model Strategis SI/TI, serta RAD (Rapid Application Development) untuk perancangan artefak penelitian. Hasil pengujian menunjukkan perencanaan strategis e-SCRM mendapatkan nilai keterlibatan sebesar 112,56% dengan kategori Engagement Rate Value Range yaitu High Engagement Rate untuk akun dibawah 5000 pengikut, yang menunjukkan bahwa perencanaan strategis e-SCRM efektif dan memiliki potensi untuk digunakan meningkatkan keterlibatan umat vihara. 
MODELING PRICE REVERSALS IN THE INDONESIAN EQUITY MARKET USING SUPERVISED MACHINE LEARNING Wingdes, Irawan; Ferdi
Digital Business and Entrepreneurship Journal Vol. 3 No. 2 (2025): Digital Business and Entrepreneurship Journal
Publisher : FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS KUNINGAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/digibe.v3i2.323

Abstract

This study aims to develop a classification model using the random forest approach to identify mean reversion events in stock prices within the Indonesian capital market, which applies a long-only trading system and prohibits short selling. A mean reversion event is defined as a condition in which the price deviates from the average—specifically, the 50-period Simple Moving Average (SMA)—and subsequently moves back toward the average within a certain timeframe. The model is trained on historical data from three of the most liquid stocks in the financial sector: BBCA, BMRI, and BBNI. The features used include technical indicators such as SMA, Relative Strength Index (RSI), oscillators, and price autocorrelation. Two models were developed with variations in parameters including the reversal window, number of estimators, maximum depth, class weight, threshold, and classification probability. Evaluation was conducted using the Receiver Operating Characteristic (ROC) curve and precision-recall metrics, and further tested on out-of-sample data from cross-sector stocks to assess the model’s generalization capability across various market conditions. In addition, the buy-sell strategy was tested through simulations and validated using Monte Carlo methods to evaluate the model’s robustness in actual trading conditions and under random data variations. The results indicate that mean reversion events can be effectively modeled, yielding high reliability—particularly in models that are more selective or less responsive to short-term price fluctuations. The model also demonstrated strong simulation performance, especially when implemented with appropriate filtering methods.
Co-Authors Callista, Marlline Ferdi Gusti Syarifudin, Gusti I Dewa Ayu Eka Yuliani Luwuk, Yosua Markoliano Sandy Kosasi