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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Inferensi SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Jurnal Pengabdian pada Masyarakat
Muhammad Fikri
Statistics Department, Faculty Of Mathematics And Natural Sciences, Universitas Tanjungpura, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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EFEKTIVITAS PELATIHAN POWER BI DALAM MENINGKATKAN LITERASI DATA ADMIN SATU DATA KALIMANTAN BARAT Neva Satyahadewi; Evy Sulistianingsih; Shantika Martha; Nurfitri Imro'ah; Hendra Perdana; Wirda Andani; Ray Tamtama; Yuyun Eka Pratiwi; Muhammad Fikri; Pitriani; Annisa Auliarahmi; Nazwa Nursyifa; Yohanna Gabriel Richsita; Louis Putra Jaya; Jessica Audrey Valeria
Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat Vol 3 No 1 (2026): Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat
Publisher : LPPM Universitas Panca Bhakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54035/dianmas.v3i1.626

Abstract

This Community Service Program (PKM) aimed to enhance data literacy and information visualization skills among Satu Data administrators of local government agencies (OPD) through Microsoft Power BI training at the West Kalimantan Provincial Communication and Information Agency (Diskominfo). The program was implemented through preparation, face-to-face training, and evaluation stages using pre-test and post-test instruments. The training covered fundamental concepts of data analysis, data visualization techniques, and hands-on dashboard development using regional sectoral data. The results of the paired sample t-test analysis indicated a statistically significant improvement between participants’ pre-test and post-test scores, demonstrating the effectiveness of the training. Furthermore, analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that training material quality had a positive and significant effect on participants’ learning outcomes, while other supporting factors such as training duration, facilitator performance, and technical aspects did not show significant effects. These findings highlight that well-structured and relevant training materials play a critical role in improving participants’ competencies. Overall, the program contributed to strengthening analytical skills and supporting the implementation of the Satu Data Indonesia policy toward transparent and evidence-based data governance
Technology Integration in Community Service: Empowering IDX Employees with Data Visualization Skills Wirda Andani; Hendra Perdana; Nurfitri Imro'ah; Evy Sulistianingsih; Neva Satyahadewi; Ray Tamtama; Shantika Martha; Yuyun Eka Pratiwi; Pitriani Pitriani; Annisa Auliarahmi; Muhammad Fikri
SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Vol. 7 No. 1 (2026)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/spekta.v7i1.15922

Abstract

Background: The rapid growth of digitalization in the capital market requires the Indonesia Stock Exchange (IDX) to deliver transparent, accurate, and understandable information through data visualization. However, employees at the IDX West Kalimantan Representative Office rarely process and visualize data, even though it is essential for carrying out daily tasks. Contribution: This study fills the gap in technology-based community service programs that rarely integrate infographic training with information literacy enhancement in capital market education. The novelty of this study lies in the evaluation of the community service program, which not only measures the effectiveness of the training but also employs CB-SEM to identify the factors influencing participants’ learning outcomes. Method: The Statistics Study Program, Untan, conducted a training workshop combining theory and practice with real data. A situational analysis with IDX representatives was first carried out to identify needs and design the program. Effectiveness was evaluated using pre-tests, post-tests, and satisfaction surveys. Results: The paired t-test results at the 5% significance level demonstrating the effectiveness of infographic training in enhancing data visualization skills. In addition, CB-SEM analysis revealed that the module variable was the dominant factor, highlighting the importance of structured and relevant training materials in supporting participants’ learning outcomes. Conclusion: The training effectively enhanced the knowledge and skills of IDX West Kalimantan Representative employees in data processing and visualization.
Remodeling and Application of Stock Option Price Based on Skewed Laplace Distribution Approach Evy Sulistianingsih; Ferdi Afrizal; Muhammad Fikri; Pitriani -
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.44222

Abstract

This paper proposed a new model to price a stock option based on the Skewed Laplace distribution approach (SLOP). The approach was considered to provide a better option price than Black Scholes Option Price (BSOP) because Skewed Laplace distribution (SL) has a shape parameter that can capture excess skewness and kurtosis frequently found in stock return underlying the option price. In this study, SL’s shape parameter was estimated using a mixture of the Moment Method and Fourth-Order Taylor Series approach. The estimator was different from the majority of prior SL’s shape parameter that was obtained by Maximum Likelihood Estimation (MLE). The proposed shape parameter was easier to obtain relative to the prior parameter because it did not require a Likelihood Function (LH) and the maximization of LH where involved a complicated numerical method. The performance of SLOP was applied to eleven different enterprises that trade stock options at several strike prices. According to the empirical results in this research, it can be summarized that the SL approach yields a better option price model rather than Black Scholes (BS).
TEXT ANALYTICS AND LASSO REGRESSION FOR STOCK PRICE MOVEMENTS Muhammad Fikri; Shantika Martha; Evy Sulitianingsih; Wirda Andani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2885-2900

Abstract

This study investigates the impact of news events on stock price movements in the IDX Kompas 100 index (JKKM100) by combining machine learning-based text analytics with event study analysis using LASSO regression. News data from January 1, 2019 to July 22, 2024 were collected via web scraping and used as training data for text classification. The trained model was then applied to classify news events in the period from January 1, 2024 to April 30, 2025, which were subsequently used in the event study analysis. Stock price data for the same period (January 1, 2024 to April 30, 2025) were collected to ensure consistency between predictor and response variables. Due to class imbalance, the synthetic minority over-sampling technique (SMOTE) was applied. Several machine learning algorithms were evaluated, and XGBoost achieved the highest accuracy of 72.22%, improving to 79% after hyperparameter tuning. Using weighted abnormal returns as predictors and stock closing prices as response variables, the LASSO regression results show that 13 out of 180 news events significantly influenced stock price movements. The model explains 48.17% of the variance with an RMSE of approximately 5% of the average stock price. Industry-related news contributed the most (43.20%), followed by PESTEL (3.97%) and Investment (1.00%). This study demonstrates that integrating text analytics with LASSO-based event study provides an effective framework for analyzing the impact of news on stock price movements.
Stock Portfolio Optimization Based on Financial and Risk–Return Clustering and TOPSIS with MVEP–MAD Weighting Wirda Andani; Shantika Martha; Evy Sulistianingsih; Muhammad Fikri; Cinta Priscillia Maharani; Rifki Pebriyandi
Inferensi Vol 9 No 2 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i2.9906

Abstract

This research aims to construct an optimal stock portfolio from the Kompas100 index using stock performance indicators, fundamental indicators, K-Means, TOPSIS, and portfolio optimization. Of the 100 stocks, only 22 were suitable as candidates for portfolio formation. From these 22 stocks, 4 portfolio candidates were identified through K-means analysis and 7 through TOPSIS analysis. The next step was to determine the investment proportion for each stock in the portfolio using MVEP and MAD. Performance evaluation results show that Portfolio 4, consisting of PTRO and WIFI stocks, consistently yields the highest Sharpe Ratio under both weighting methods: 0.19 using MVEP and 0.21 using MAD. Portfolio 4’s performance was then re-evaluated using data from April through December 2025, resulting in a higher Sharpe ratio for both the MAD and MVEP. Overall, this study demonstrates that the combination of the K-Means Clustering, TOPSIS, MVEP, and MAD methods can be used to assist in the stock selection process and the formation of an optimal portfolio that is more efficient than investing in a single stock because it provides a better balance between return and risk through investment diversification, while remaining stable for the next nine months.
Co-Authors Annisa Auliarahmi Annisa Auliarahmi Cinta Priscillia Maharani Evy Sulistianingsih Evy Sulistianingsih Evy Sulitianingsih Ferdi Afrizal Hendra Perdana Hendra Perdana Jessica Audrey Valeria Louis Putra Jaya Nazwa Nursyifa Neva Satyahadewi Neva Satyahadewi Nurfitri Imro'ah Nurfitri Imro’ah Pitriani Pitriani - Pitriani Pitriani Ray Tamtama Rifki Pebriyandi Shantika Martha Shantika Martha Shantika Martha Tamtama, Ray Wirda Andani Wirda Andani Wirda Andani Yohanna Gabriel Richsita Yuyun Eka Pratiwi