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All Journal Knowledge Engineering and Data Science Jurnal Praksis dan Dedikasi Sosial Bulletin of Social Informatics Theory and Application
Hammad, Jehad A.H
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Computer Science & IT Engineering Environmental Science Social Sciences Other

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Blocking pornography sites on the internet private and university access ; Irawan, Ninon Oktaviani; Nurfadila, Piska Dwi; Ristanti, Putri Yuni; Hammad, Jehad A.H
Bulletin of Social Informatics Theory and Application Vol. 3 No. 1 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v3i1.161

Abstract

Promoting Covid-19 vaccination with Instagram Fahmi, Ahmad Maulanal; Azizah, Hanifah Nur; Mahendra , I Putu Arda; Fatkhiatin , Irma; Hammad, Jehad A.H
Bulletin of Social Informatics Theory and Application Vol. 5 No. 1 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v5i1.408

Abstract

The COVID-19 Vaccination Program is essential information during this pandemic. Information about COVID-19 vaccination is disseminated through social media, one of which is Instagram. During the COVID-19 pandemic, the Ministry of Health's Instagram accounts in various countries provided much information about COVID-19, including vaccinations. This research was made to determine the role of Instagram as a media to promote the invitation to vaccinate for COVID-19 by using the calculation of engagement rates in each post category on the Instagram account of the Ministry of Health of Indonesia, Malaysia, the United States, and Australia. The results obtained in this study are that these accounts have implemented the right strategy in COVID-19 vaccination, and several strategic refinements need to be done.
Ransomware detection: patterns, algorithms, and defense strategies Amro, Manar Y; Dwieb, Mohamed; Hammad, Jehad A.H; Wibawa, Aji Prasetya
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.689

Abstract

In the contemporary digital landscape, rapid technological advancements present unprecedented challenges for developers in the hardware and software realms. The ubiquitous presence of the Internet, the Internet of Things (IoT), and widespread digital solutions bring numerous benefits and escalating risks. This study investigates the pervasive threat of ransomware attacks, a daily menace that imperils the operational and security dimensions of the digital sphere for enterprises and individuals. The research objective is to identify the most effective algorithm for detecting ransomware viruses, a persistent and evolving threat that significantly challenges institutions, companies, and governmental organizations. The dynamic nature of ransomware necessitates robust detection mechanisms to safeguard sensitive data. To achieve this goal, we conducted a comparative analysis of four prominent algorithms recognized for their efficacy in combating and detecting viruses. Emphasis was placed on the algorithm exhibiting the most promising results. A detailed examination of its impact on existing data involved comprehensive analysis and a comparative assessment against previous studies. Results, derived from extensive studies and experiments on a diverse dataset, illuminate the critical role of ransomware detection algorithms and underscore their effectiveness. The findings contribute valuable insights to the ongoing discourse on cybersecurity strategies, providing a foundation for enhanced ransomware defense measures.
PREDICTION OF SEA LEVEL MEASUREMENT IN PANGPANG BAY FOR SEAPLANE LANDING SEAPLANE LANDING USING ID CONVOLUTIONAL NEURAL NETWORK Setiawan, Ariyono; Islam, Fajar; Efendi, Efendi; Globalisasi, Safitri Era; Hammad, Jehad A.H
Jurnal Praksis dan Dedikasi Sosial Vol. 7 No. 2 (2024)
Publisher : Universitas Negeri Malang

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This research investigates the relationship between sea level height and various environmental factors in Pangpang Bay, Indonesia, using Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) modeling techniques. Daily data on sea level height, weather, and oceanography were collected from April 1 to April 15, 2024. An analysis was conducted on the factors affecting sea level height and the evaluation of predictive model performance. The findings reveal historical patterns of sea level height changes influenced by the variability of meteorological and oceanographic conditions. Although ANN and CNN models have varying degrees of accuracy, both show potential in predicting sea level height by considering environmental factors. Recommendations include the development of more advanced predictive models, deeper data observation, integration of multidisciplinary information, continuous environmental monitoring, and stakeholder collaboration. This research is expected to contribute to the understanding and management of environmental risks related to sea level height in Pangpang Bay.
A Review of Accessing Big Data with Significant Ontologies Sleeman, Jumah Y.J; Hammad, Jehad A.H
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new query; (ii) mapping rewriting the query that obtained from previous step reformulating it over the data sources using mapping assertions. In this survey, we aim to study the earlier works done by other researchers in the fields of ontology, mapping and query answering over data sources.
Co-Authors Aji Prasetya Wibawa Amro, Manar Y Azizah, Hanifah Nur Dwieb, Mohamed Efendi Efendi Fahmi, Ahmad Maulanal Fatkhiatin , Irma Globalisasi, Safitri Era Irawan, Ninon Oktaviani Islam, Fajar Larasati, Khoirunnisa Mahendra , I Putu Arda Mubarok, Ahmad Nurfadila, Piska Dwi Ristanti, Putri yuni Setiawan, Ariyono Siswahyudi, Dwi Sleeman, Jumah Y.J Tri Kuncoro Wibowo, Untung Lestari