An Integration of Machine Learning with e-government: Challenges and Future Trends

Shareef M Shareef

doi:10.58777/ise.v2i1.191

Authors

Shareef M Shareef Salahaddin University, Eribl Kurdistan-Iraq

DOI:

https://doi.org/10.58777/ise.v2i1.191

Keywords:

Smart government, E-government, Technology challenges, Citizen satisfaction

Abstract

The tremendous rise of data and information and the increase in computer processing in e-governments has significantly changed how the government makes decisions relying on advanced technologies. This number will grow dramatically, and there is a prominent direction that institutions are considering the use of advanced technology to assist in delivering services and making daily decisions. The use of developed technologies, such as Machine Learning (ML), is believed appropriate in an effort to turn the massive amount of information in this extend of data into a meaningful one, and ease of analysis. Machine Learning is a technology that can handle huge data and classification for statistics or even more complex purposes, such as data analysis and decision making. The applications of ML are being used to improve the current state of e-government services by reducing processing times, lowering costs, and increasing citizen satisfaction. However, this technology still confronts a number of obstacles that obstruct its use in e-government applications, both for improving e-government systems and for increasing e-government-citizen interactions. This paper aims to address and analyse the impact of the use of ML in e-government, and also to see the feasibility of this technology in the e-services provision in developing countries, the Kurdistan Region of Iraq (KRI) in particular. In addition, it highlights the challenges that impact the integration of advanced technology with e-government and discourses on future trends. The main contribution of this paper is that it helps organizations better understand their approaches to machine learning, allowing them to make more informed decisions about how to employ developed technology in the e-government system.

Peningkatan data dan informasi yang luar biasa dan peningkatan pemrosesan komputer di e-government telah secara signifikan mengubah cara pemerintah membuat keputusan dengan mengandalkan teknologi canggih. Machine Learning (ML) adalah teknologi yang dapat menangani data besar dan klasifikasi untuk statistik atau bahkan tujuan yang lebih kompleks, seperti analisis data dan pengambilan keputusan. Aplikasi ML digunakan untuk meningkatkan status layanan e-government saat ini dengan mengurangi waktu pemrosesan, menurunkan biaya, dan meningkatkan kepuasan warga. Namun, teknologi ini masih menghadapi sejumlah kendala yang menghambat penggunaannya dalam aplikasi e-government, baik untuk meningkatkan sistem e-government maupun untuk meningkatkan interaksi e-government-citizen. Makalah ini bertujuan untuk mengatasi dan menganalisis dampak penggunaan ML dalam e-government, dan juga untuk melihat kelayakan teknologi ini dalam penyediaan layanan elektronik di negara-negara berkembang, Wilayah Kurdistan Irak (KRI) pada khususnya. Selain itu, menyoroti tantangan yang berdampak pada integrasi teknologi canggih dengan e-government dan wacana tentang tren masa depan. Kontribusi utama dari makalah ini adalah membantu organisasi lebih memahami pendekatan mereka terhadap pembelajaran mesin, memungkinkan mereka untuk membuat keputusan yang lebih tepat tentang bagaimana menggunakan teknologi yang dikembangkan dalam sistem e-government.

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