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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Research trends in spatial modeling of PM2.5 concentration using machine learning: a bibliometric review Wahyuni, Retno Tri; Hanafi, Dirman; Tomari, M. Razali; Sihabudin Sahid, Dadang Syarif
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 2: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i2.pp1317-1327

Abstract

Spatial modeling is commonly used to map research variables, including particulate matter 2.5 (PM2.5) concentrations, in specific areas. The article that surveys publications on the application of machine learning in spatial modeling of PM2.5 using bibliometric methods has not been identified yet. This paper aims to analyze trends in applying machine learning in the spatial modeling of PM2.5 using bibliometric methods. The review was conducted on publications indexed in the Scopus database over the decade (2014–2023) comprising 335 articles. The analysis included co-authorship and co-occurrence using VOSviewer. From the two stages of analysis, it can be concluded that research on this topic has constantly increased over the past 10 years, with the highest productivity coming from researchers in China. This research topic is multidisciplinary, with most publications appearing in environmental science. The research also shows a very high collaboration rate of 0.98. A deeper examination of the keywords reveals the most commonly used machine learning techniques by researchers. The random forest method is the most frequently found in the analyzed documents, followed by deep learning, long short-term memory (LSTM), extreme gradient boosting (XGBoost), and ensemble model.
Study of design thinking and software engineering integration in education and training Zul, Muhammad Ihsan; Mohd. Yasin, Suhaila; Sahid, Dadang Syarif Sihabudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1384-1398

Abstract

Integrating design thinking (DT) with software engineering (SE) is widely applied in industry, serving as a reference for SE in education and training. The industry has various integration models, but researchers and educators mainly adapt them for education. A clear understanding of DT-SE integration models is essential to figuring out their implementation. This study examines existing DT-SE integration models, challenges, and integration methods using Kitchenham’s framework in education and training. The paper was collected from ScienceDirect, IEEEXplore, Scopus, ACM, SpringerLink, and Google Scholar, yielding 593 initial publications, with 43 selected for in-depth analysis. Findings indicate that the d.school model is the most widely adopted DT model. Key challenges include team dynamics, process management, complexity, and cultural factors. DT is integrated into requirements engineering (RE) due to its user-centered nature, though only two studies explicitly describe DT-SE integration models, both applied early in SE processes. These findings suggest educational practices align with industry trends in model adoption and integration focus. Educators and practitioners can use these insights to design or adapt integration models suitable for education and training by shaping curricula that emphasize user-centered design, collaboration, and the extension of DT practices beyond RE-strengthening its impact for education and training.