Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning

Webinar of E-Goverment Transformation Toward Smart System
Pekan Ilmiah Fakultas Teknik Universitas Widyagama

5 March, 2020 [Online]

https://pilfatek2021.widyagama.ac.id

Transcript

1. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho March 5, 2021 Presented in Webinar of E-Government Transformation Toward Smart System
2. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
3. Talk Outline 1. Artificial intelligence vs. machine learning vs. deep learning ▪ How is traditional programming different from machine learning? 2. How machine learning is changing e-government? ▪ E-government in Indonesia ▪ Automatic text classification ▪ Automatic number plate recognition ▪ Handwritten text recognition ▪ Potential benefits of machine learning 3. Challenges of Using Machine Learning in Government Text Preprocessing Pipeline for Bahasa using Python: Concept, Steps, Tools, and Examples Kuncahyo Setyo Nugroho | Present in PyCon ID 2020
4. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
5. Artificial Intelligence vs. Machine Learning vs. Deep Learning: What’s the Difference? Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
6. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
7. How is traditional programming different from machine learning? Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Use case: How can a computer recognize and separate apples and oranges?
8. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Traditional Programming if pixel[5][8] is red & pixel[2][8] is red: if pixel[9][4][3] is green & …: return ‘apple’ … … … else: return ‘orange’ input output Rules Answer Data
9. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Traditional Programming: How About This?
10. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Machine Learning input output Apple Apple Apple Oranges Answer Data Rules
11. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Machine Learning ? Apple Machine Learning Rules “Field of study that gives computers the ability to learn without being explicitly programmed” (Arthur Samuel, 1959)
12. How Machine Learning is Changing e-Government? Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
13. Online government services to exchange of information and services electronically with citizens, businesses, and other arms of government. (United Nations, 2006) Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 E-Government
14. E-Government in Indonesia 1. Instruksi Presiden Republik Indonesia Nomor 3 Tahun 2003 tentang Kebijakan dan Strategi Nasional Pengembangan E-Government. 2. Peraturan Menteri Pendayagunaan Aparatur Negara dan Reformasi Birokrasi Nomor 5 Tahun 2018 tentang Pedoman Evaluasi Sistem Pemerintahan Berbasis Elektronik. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
15. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 E-Government in Indonesia
16. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
17. Automatic Text Classification Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Hardaya, I. S., Dhini, A., & Surjandari, I. (2017, October) https:/ /monkeylearn.com/blog/customer-complaint-classification
18. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Manwatkar, P. M., & Singh, K. R. (2015, January) Handwritten Text Recognition
19. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Intel® OpenVINO™ Toolkit Automatic Number Plate Recognition Onnyx Electronisys Pvt. Ltd.
20. Potential Benefits of Machine Learning Efficiency Digital information age further leads to the generation of big data as well as big government data, at a faster rate, thus making manual data analysis and interpretation impossible. ML does not only automate the analysis of big government data but also can provide data-driven answers. Accuracy The results of ML systems, irrespective of the used techniques, are more accurate, since ML can process big government data and no intervention from either knowledge engineers or domain experts is required. Performance & Process Simplification Easier and faster way for automated classification to analyse data when compared to manual process which would consume a significant amount of time and effort by reducing the cost. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
21. Challenges of Using Machine Learning in Government Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021
22. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Challenges of Machine Learning Privacy & Ethical Issues In many cases (e.g. healthcare) the collection of personal data, the ownership of personal data and the benefits of their processing leads to privacy and ethical issues. Quality & Quantity of Data Lack of data (e.g. geographical data) or even accessed data may not be representative and, in cases of predictions, barriers can be found decreasing the quality and quantity of the ML system. Heterogeneity of Data Heterogeneity of data (e.g. writing styles or different vocabularies) is a challenge for ML because it can lead to wrong results. Availability of Data Difficulties of gaining regulatory approval of accessing data (for instance in healthcare), or even lack of data (geographical data) in order for a ML system to be properly trained for quality results.
23. Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021 Challenges in Indonesia 1. Readiness of regulations governing ethics of use 2. Readiness of the workforce 3. Infrastructure readiness and supporting data 4. Readiness of industry and the public sector in adopting artificial intelligence innovations.
24. Thank you! Would love to connect, feel free to reach out. Discussion, any question? https:/ /ksnugroho.site https:/ /linkedin.com/in/ksnugroho https:/ /github.com/ksnugroho Automating E-Government Services with Artificial Intelligence: Extensive use of Machine Learning Kuncahyo Setyo Nugroho | Presented in Webinar of E-Government Transformation Toward Smart System 2021