Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Pilar Nusa Mandiri Jurnal Penelitian dan Pengabdian Masyarakat
Maysas Yafi Urrochman
Institut Teknologi dan Bisnis Widya Gama Lumajang
Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
PERFORMANCE COMPARISON OF RANDOM FOREST REGRESSION, SVR MODELS IN STOCK PRICE PREDICTION Urrochman, Maysas Yafi; Asy'ari, Hasyim; Hizham, Fadhel Akhmad
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6072

Abstract

The stock market is characterized by high volatility and complexity, making it an intriguing and challenging subject for researchers and practitioners. This study aims to predict stock prices by comparing the performance of two machine learning models: Random Forest Regression and Support Vector Regression (SVR). These models were selected for their ability to handle complex data and high volatility. The dataset used in this study consists of BNI stock data over the last five years (2019–2024), comprising a total of 1,211 data points. Testing was conducted using a cross-validation approach, and model performance was evaluated based on several metrics, including MSE, R², RMSE, MAPE, MAE, and Score. The results indicate that Random Forest Regression outperforms SVR. The model achieved an MAE of 17.766, an RMSE of 22.376, and an R² of 0.997. These findings suggest that Random Forest Regression is more effective in predicting stock prices, particularly in unstable market conditions. This study recommends Random Forest Regression as a reliable model for stock price prediction, with potential applications in other stock markets with similar characteristics.
Digital Transformation of School Administration through Human Resource Information System Implementation Masyhuri Masyhuri; Maysas Yafi Urrochman
Jurnal Penelitian dan Pengabdian Masyarakat Vol. 4 No. 3 (2026): August 2026 In Press
Publisher : Yayasan Pondok Pesantren Sunan Bonang Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61231/10g2dk18

Abstract

This community service program aims to improve administrative management effectiveness through the implementation of a web-based information system at SMK Al-Maliki Sukodono Lumajang. The main problem faced by the schools was the use of manual recording systems, which resulted in low efficiency, high risk of data errors, and limited access to information. The methods employed included needs analysis, system design, implementation, as well as user assistance and evaluation. The results indicate that the developed system successfully improved work efficiency, data organization, and reporting processes. User evaluation revealed a very high level of satisfaction, with 73% of respondents being very satisfied with the system’s benefits, 67% with access speed, and 60% with ease of use. In addition, the system encouraged a shift toward technology- and data-driven work practices. Therefore, the implementation of the web-based information system is proven effective in enhancing school administrative governance and has strong potential to be replicated in other educational institutions with similar characteristics.
Co-Authors Asy'ari, Hasyim Hizham, Fadhel Akhmad Masyhuri Masyhuri