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All Journal Letters in Information Technology Education (LITE) International Journal of Robotics and Control Systems
Chuttur, Mohammad Yasser
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Control & Systems Engineering Education Electrical & Electronics Engineering

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Requirements for an Online Automated Project Allocation System in Higher Education Institutions – A Case Study Khurwolah, Mooneerah; Chuttur, Mohammad Yasser
Letters in Information Technology Education (LITE) Vol 3, No 2 (2020)
Publisher : Universitas Negeri Malang

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Abstract

This paper presents the requirements gathered for an online automated project allocation system that can be used to assign final year projects to students registered in Higher Education Institutions (HEIs). The requirements are gathered for a well-known University in Mauritius. This research is motivated by several issues encountered with the current manual system in place at the studied institution and the need for adopting online systems following the COVID-19 outbreak. Following document analysis and a survey, important functional and non-functional requirements for an online automated project allocation system were uncovered. Gathered requirements also helped in determining a recommended workflow that can be adopted as best practice for final year project allocation. We posit that requirements presented in this paper can help develop a system that can be very useful and ultimately streamline the process for allocating projects typically important for Higher Education Institutions and other similar training institutions.
Exploring the Role of Deep Learning in Forecasting for Sustainable Development Goals: A Systematic Literature Review Utama, Agung Bella Putra; Wibawa, Aji Prasetya; Handayani, Anik Nur; Chuttur, Mohammad Yasser
International Journal of Robotics and Control Systems Vol 4, No 1 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i1.1328

Abstract

This paper aims to explore the relationship between deep learning and forecasting within the context of the Sustainable Development Goals (SDGs). The primary objective is to systematically review 38 articles published between 2019 and 2023, following PRISMA guidelines, to understand the current landscape of deep learning forecasting for SDGs. Using data from 2019-2023 allows capturing the latest developments in deep learning forecasting for Sustainable Development Goals (SDGs), while excluding data before 2019 and after 2023 is based on the desire to avoid including potentially less relevant or unpublished research and to maintain focus on the most current and contextually relevant literature. The methodological approach involves analyzing the application of deep learning methods for forecasting within various SDG fields and identifying trends, challenges, and opportunities. The literature review results reveal the popularity of LSTM models, challenges related to data availability, and the interconnected nature of SDGs. Additionally, the study demonstrates that deep learning models enhance forecast accuracy and computational performance, as measured by Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and R-squared (R2). The findings underscore the importance of advanced data preparation techniques and the integration of deep learning with SDGs to improve forecasting outcomes. The novelty of this research lies in its comprehensive overview of the current landscape and its valuable insights for researchers, policymakers, and stakeholders interested in advancing sustainable development goals through deep learning forecasting. Finally, the paper suggests future research directions, including exploring the potential of hybrid forecasting models and investigating the impact of emerging technologies on SDG forecasting methodologies. Innovative methods for imputing missing values in deep learning forecasting models could be further explored to enhance predictive accuracy and robustness.
Co-Authors Aji Prasetya Wibawa Anik Nur Handayani Asif Faroqi Iswanti, Usmanur Dian Khurwolah, Mooneerah Ridwandono, Doddy Utama, Agung Bella Putra