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All Journal JOIN (Jurnal Online Informatika) IJAIT (International Journal of Applied Information Technology)
Ibrahim, Adamu Abubakar
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Computer Science & IT

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Social Network Analysis: Identification of Communication and Information Dissemination (Case Study of Holywings) Aditiawarman, Umar; Lumbia, Mega; Mantoro, Teddy; Ibrahim, Adamu Abubakar
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.911

Abstract

Social media especially Twitter has been used by corporation or organization as an effective tool to interact and communicate with the consumers. Holywings is one of the popular restaurants in Indonesia that use social media as a tool to promote and disseminate information regarding their products and services. However, one of their promotional items has gone viral and invited public protests which turned into a trending topic on Twitter for a couple of weeks. Holywings allegedly improperly promoted their products by using the most honorable names, “Muhammad” and “Maria”. Social network analysis of Twitter data is conducted to identify and examine information circulating among the users, which leads to wider public attention and law enforcement. In this study, we focused on the conversation about Holywings on Twitter from 24 June to 31 July 2022. The analysis was carried out using Python to retrieve data and Gephi software to visualize the interactions and the intensity of the network group in viewing the spread of information. The findings reveal the centrality account that caused the news to go viral are the CNN Indonesia (@CNNIndonesia) news media account and Haris Pertama (@knpiharis), with a centrality of 0.161 and 0.282, respectively. There are also 121 groups involved in the conversation with modularity of 0.821.
IWDSA: A Hybrid Intelligent Water Drops with a Simulated Annealing for The Localization Improvement in Wireless Sensor Networks Gumaida, Bassam; Ibrahim, Adamu Abubakar
IJAIT (International Journal of Applied Information Technology) Vol 08 No 01 (May 2024)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v8i1.6456

Abstract

Improving localization accuracy and reducing development costs are pivotal keys and main issues in managing and administrating wireless sensor networks (WSNs). This paper considers a modern and qualified algorithm that leverages advanced optimization techniques to localize nodes deployed in outdoor environments. The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). IWD is a qualified stochastic optimization tool adept at minimizing objective functions. In IWDSA, SA is integrated to enhance solution quality and prevent IWD from getting trapped in local minima. This paper ensures that internal distances between nodes are calculated using Received Signal Strength Indicator (RSSI) measurements. The paper aims to achieve two primary goals. First, it addresses the challenge of low accuracy in RSSI measurements by employing IWDSA. Second, it aims to achieve highly accurate localization of unknown sensor nodes in WSNs. IWDSA enhances localization precision due to its flexible implementation of IWD and SA, combined with the cost-free utilization of RSSI. Simulation results demonstrate the reliable performance of the proposed algorithm in solving the low accuracy of RSSI measurements and localizing unknown nodes with high accuracy. Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. This exceptional performance is evident across various evaluation metrics, including localization error, localization rate, and simulation runtime.
Co-Authors Gumaida, Bassam Lumbia, Mega Teddy Mantoro Umar Aditiawarman