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All Journal Knowledge Engineering and Data Science Journal of Economic, Bussines and Accounting (COSTING)
Larasati, Khoirunnisa
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Computer Science & IT Economics, Econometrics & Finance Engineering

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Random Forest Algorithm to Measure the Air Pollution Standard Index Setiawan, Ariyono; Wibowo, Untung Lestari; Mubarok, Ahmad; Larasati, Khoirunnisa; Hammad, Jehad A.H
Knowledge Engineering and Data Science Vol 7, No 1 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v7i12024p86-100

Abstract

This study uses the Random Forest algorithm to measure and predict the Air Pollution Standard Index (APSI) at Blimbing Banyuwangi Airport. Air pollution data, including concentrations of O3, CO, NO2, SO2, PM2.5, and PM10, were collected from air monitoring stations at the airport from April 15-30, 2024. APSI measurement followed established formulas by relevant authorities. Data analysis utilized statistical approaches and computational algorithms. The findings reveal that air quality at the airport is generally "Moderate," with occasional "Good" days. The Random Forest algorithm effectively predicts APSI based on existing pollution data. These results provide insights for improving air pollution management at the airport and surrounding areas, emphasizing the need for continuous air quality monitoring. Days classified as "Moderate" suggest health risks for sensitive groups, indicating the need for targeted mitigation strategies. Recommendations include increasing green spaces, optimizing flight schedules to reduce peak pollution, and raising public awareness about air quality. The effectiveness of the Random Forest algorithm suggests its potential application in other airports for proactive air quality management. Future research could integrate real-time data and advanced machine learning models for more accurate and timelier APSI predictions.
THE EFFECT OF DIGITALIZATION OF HR MANAGEMENT ON EMPLOYEE PRODUCTIVITY IN THE ERA OF TECHNOLOGY-BASED ECONOMY Iswahyudi, Prasetyo; Larasati, Khoirunnisa; Wardana, Miko Andi
Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 6 (2025): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/qmsfkc40

Abstract

The development of a technology-based economy encourages organizations to undertake digital transformation across various aspects, including human resource management (HR). This study aims to analyze the influence of digitalization of HR management on employee productivity in the era of a technology-based economy. The research method used is a qualitative approach within the library research type. Research data were obtained from various reputable scientific literature, especially from Scopus-indexed international journals published in the last five years. The results of the study show that the digitization of HR management through the implementation of HR Information Systems, e-recruitment, e-learning, HR analytics, and digital-based performance management systems has a positive impact on increasing employee productivity. Digitization of human resources can improve the efficiency of work processes, enhance decision-making quality, and encourage innovative work behavior and employee engagement. However, the effectiveness of human resource digitalization is greatly influenced by organizational readiness factors, employee digital competence, leadership support, and a work culture that is adaptive to technology. This study concludes that the digitalization of HR management is an essential strategy for increasing employee productivity, but its success requires careful implementation planning and sustainable HR capacity-building.
Co-Authors Hammad, Jehad A.H iswahyudi, Prasetyo Mubarok, Ahmad Setiawan, Ariyono Wardana, Miko Andi Wibowo, Untung Lestari