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Journal : Journal of Data Science and Its Applications

Mapping Organization Knowledge Network and Social Media Based Reputation Management Andry Alamsyah; Maribella Syawiluna
Journal of Data Science and Its Applications Vol 1 No 1 (2018): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/jdsa.2018.1.3

Abstract

Knowledge management are important aspects in an organization, especially in ICT industry. Having more control of it is essentials for the organization to stay competitive in the business. One way to assess the organization knowledge capital is by measuring employee knowledge network and their personal reputation in social media. Using this measurement, we see how employee build relationship around their peer networks or clients virtually. We also able to see how knowledge network support organization performance. The research objective is to map knowledge network and reputation formulation in order to fully understand how knowledge flow and whether employee reputation have higher degree of influence in organization knowledge network. We particularly develop formulas to measure knowledge network and personal reputation based on their social media activities. As case study, we pick an Indonesian ICT company which actively build their business around their employee peer knowledge outside the company. For knowledge network, we perform data collection by conducting interviews. For reputation management, we collect data from several popular social media. We base our work on Social Network Analysis (SNA) methodology. The result shows that employees knowledge is directly proportional with their reputation, but there are different reputations level on different social media observed in this research.
Understanding Public Attitude towards Political Candidate through Conversational Network in West Java Regional Election Rimba Pratama Putra; Hanif Fakhrurroja; Andry Alamsyah
Journal of Data Science and Its Applications Vol 2 No 2 (2019): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/jdsa.2019.2.21

Abstract

Social media is a very important part of the political campaign strategy. By using information about various policies as well as public opinion, will provide rich information in political issues during elections. The problem is how political attitudes in social media relate to the results of the election winners. In this paper, we proposed a methodology of social network analysis to measure conversational network activity. As a case study, we select the Pilkada Jawa Barat 2018 for the reason most populous province in Indonesia. We get the conversation in online social network service Twitter and collected 70335 tweets from June 20 to June 26, 2018. Our findings indicate that the network properties of each candidate is in accordance to the real count and the candidate that appear most often are "@ridwankamil", the name of the winner of the regional elections in the Pilkada Jawa Barat 2018. We summarize all the conversations of each candidate and our results show there are high correlations with the results of the election winners. Because the higher the conversations network of each candidate, the greater the possibility of winning the election.