Hammam Riza

Followers

Following

Co-author

Public Views

Judith L Green

University of California, Santa Barbara

Andreas Treske

Bilkent University

David Seamon

Kansas State University

Simon Darcy

University of Technology Sydney

Merve Ayyüce Kızrak, Ph.D.

Bahcesehir University

Mariia Protsiuk

University of Wroclaw

Rigas Kotsakis

Aristotle University of Thessaloniki

Vania V Estrela

UFF - Universidade Federal Fluminense

Jane Chin Davidson

California State University, San Bernardino

Sheena Baburaj

Cochin University of Science and Technology

Interests

Uploads

Papers by Hammam Riza

Inovasi Teknologi Melawan Covid-19 : Bunga Rampai Kajiterap BPPT Membangun Inovasi Karya Anak Bangsa

Feature Variations on the Cartesian 3D Print Machine Using Vibration and Sound Signal Readings

Proceedings of the 2nd International Conference on Experimental and Computational Mechanics in Engineering

Advancing Flood Disaster Mitigation in Indonesia Using Machine Learning Methods

2020 International Conference on ICT for Smart Society (ICISS)

The fourth industrial revolution essential components which include cloud computing technology, a... more The fourth industrial revolution essential components which include cloud computing technology, artificial intelligence, big data, and the internet of things has also been affecting the flood disaster mitigation strategy worldwide. This is also true for Indonesia where the flood disaster event has increased almost three times during the past fifteen years. In this literature review, the advancement of the application of artificial intelligence, in particular, machine learning in flood mitigation in Indonesia is studied. Based on this study, the future possible improvement of flood mitigation has also been given. The study revealed that machine learning has not yet been applied extensively in flood disaster mitigation in Indonesia. Some applications are for rainfall, river water level, and discharge level predictions, and to a lesser degree for flood forecasting and early warning. The future prospective advancement of flood disaster mitigation is the application of machine learning methods in an integrated flood prediction and early warning that covers rainfall, river water level, river discharge, and flood predictions as well as estimated spatial flooding area, and early warning dissemination using the internet of things.

Evaluation of Synset Assignment to Bi-lingual Dictionary

Abstract. This paper describes an automatic WordNet synset assignment to the existing bi-lingual ... more Abstract. This paper describes an automatic WordNet synset assignment to the existing bi-lingual dictionaries of languages having limited lexicon information. Generally, a term in a bi-lingual dictionary is provided with very limited information such as part-of-speech, a set of synonyms, and a set of English equivalents. This type of dictionary is comparatively reliable and can be found in an electronic form from various publishers. In this paper, we propose an algorithm for applying a set of criteria to assign a synset with an appropriate degree of confidence to the existing bi-lingual dictionary. We show the efficiency in nominating the synset candidate by using the most common lexical information. The algorithm is evaluated against the implementation of Thai-English, Indonesian-English, and Mongolian-English bi-lingual dictionaries. The experiment also shows the effectiveness of using the same type of dictionary from different sources.

Hammam Riza

Related Authors

Uploads

Papers by Hammam Riza

Log In