scholarly journals DESIGN OF PEOPLE PROFILING AND MODELING REPUTATION COMPUTATION BASED ON SENTIMENT ANALYSIS

SINERGI ◽  
2019 ◽  
Vol 23 (1) ◽  
pp. 1
Author(s):  
Ahmad Mafazi Damanhuri ◽  
Zhang Huaping
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Decision Support ◽  
Sentiment Analysis ◽  
Poor People ◽  
Famous People ◽  
Access Information

The number of popular people is still growing because of the easiness to access information technology. Every time people upload things and let people watch it and give it a like or comment. People who can impress other people will grow their popularity and fame. Some famous people make influences, help poor people with powers, and others are causing troubles. Community these days drives people perspective by share their thoughts on social media. They spread information and makes others want to see things they are talked about. Troublesome popular people defended by their fan base and attacked by other communities. By these cases, the research tried to gather information on social media and used it for calculation and profiling. The method that proposed to rely on this information is based on sentiment analysis to look up someone’s record and listing them into top 10 best got from DBpedia. This system shows the list of people and contains all important record about that person which can be used for decision support for a policy or rewarding people. The results have successfully visualized the output in the list of people with any further details following by clicking their names.

scholarly journals Social Media Based Decision Support Model To Solve Indonesian Waste Management Problem: An Improved Version

2021 ◽  
Vol 11 (10) ◽  
pp. 1-12
Author(s):  
Christopher Michael ◽  
◽  
Ditdit Nugeraha Utama
Keyword(s):  
Social Media ◽  
Decision Support ◽  
Waste Management ◽  
Sentiment Analysis ◽  
Environmental Issues ◽  
Management Problem ◽  
Decision Support Model ◽  
Management Quality ◽  
Research Decision ◽  
Support Model

Twitter is a commonly used social media and can sometimes picture an entire situation especially environmental issues like waste management. Machine learning and sentiment analysis tools have also been used in many cases around the world and has produced useful results to assist decision making models. In this research Decision Support Model (DSM) and Sentiment Analysis with the help of Naïve Bayes Theorem was used to analyze the waste management case in Indonesia and find out how much improvement is needed in the current situation. The research has found that severe improvements in all of the 5 aspects analyzed is needed to elevate the waste management quality to the next level, especially with a low overall score of 45.29.

scholarly journals Using IOT to Improve Indian Agriculture

2021 ◽  
Vol 10 (11) ◽  
pp. 47-53
Author(s):  
Ajay Kumar ◽  
Anmol Swaroop
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Decision Support ◽  
Internet Of Things ◽  
Agent Based ◽  
Agriculture Sector ◽  
Indian Agriculture ◽  
The World ◽  
Use Of Social Media ◽  
Use Of Internet

The use of Internet of Things (IoT) may provide the boost which is required to improve the productivity of Indian agriculture system which is well below the world average and may help in improving the income and conditions of Indian farmer. The present paper presents the efforts done by the researchers in this direction to promote the use of Information technology in general and IoT in particular in Indian agriculture sector. The areas in which IoT helps are, robotics, decision support systems, smart irrigation, precision farming, use of social media for the benefit of Indian farmers. The use of agent based systems in Indian Agriculture scenario has also been discussed in this paper.

scholarly journals Analisis Pro Kontra Vaksin Covid 19 Menggunakan Sentiment Analysis Sumber Media Sosial Twitter

2021 ◽  
Vol 2 (1) ◽  
pp. 34-42
Author(s):  
I Wayan Desta Gafatia ◽  
Novri Hadinata
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Clinical Trials ◽  
Sentiment Analysis ◽  
Rapid Growth ◽  
Government Policies ◽  
Bayes Method ◽  
Basic Emotions ◽  
Opinion Analysis ◽  
Twitter Users

The development of information technology today has experienced very rapid growth. One of the developments in information technology, namely social media such as Twitter, Facebook, and Youtube, are some of the most popular communication media in today's society. Twitter is often used to express emotions about something, either praising or criticizing in the form of emotion. Human emotions can be categorized into five basic emotions, namely love, joy, sadness, anger, and fear. Twitter users' emotional tweets can be known as opinion or sentiment analysis (opinion analysis or sentiment analysis). Sentiment analysis is also carried out to see opinions or tendencies towards a problem or policy, whether they tend to have negative or positive opinions. The COVID-19 vaccine has become one of the discussions with a fairly high intensity on social media. Vaccine-related tweets have increased as government policies evolve. The responses of netizens also varied, ranging from clinical trials of vaccines, free vaccines, vaccine effectiveness, halal vaccines, to the implementation of vaccinations. This research produces a system that can analyze tweet sentiment related to the covid 19 vaccine in Indonesia where the tweet is obtained using the Twitter API. This system uses the Multinominal Naive Bayes method for the classification process.

INSTAGRAM SEBAGAI SOCIAL MEDIA MARKETING DALAM MEMBANGUN BRAND AWARENESS FAKULTAS EKONOMI DAN BISNIS ISLAM

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Oktaria Ardika Putri
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Qualitative Analysis ◽  
Educational Institution ◽  
Social Media Marketing ◽  
Brand Awareness ◽  
Educational Institutions ◽  
Business People ◽  
Marketing Tool

Instagram is a social media application that is currently very popular in the community, especially among artist, politicians, and business people. Companies or advanced business must quicly adapt to the advancement of information technology in the form of social media as a marketing tool. Instagram social media also necessary to developing educational institutions. One of the educational institution that ae currently developing is the newly established Faculty of Economics and Business Islam (FEBI) at the Kediri State Islamic Institute (IAIN Kediri). This writing aims to examine the importance of Instagram as social media marketing to building FEBI IAIN Kediri Brand Awareness. Instagram social media is considered more effectives to embrace students and the community, so it is expected to facilitate marketing and communication between FEBI IAIN Kediri with the students or other agencies. The method of this reasearch is a qualitative analysis which reference libraries are used as a basis. Keywods:  Instagam,  social media, Faculty of Economics and Business Islam, IAIN Kediri

scholarly journals Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic

2021 ◽  
Vol 13 (7) ◽  
pp. 3836
Author(s):  
David Flores-Ruiz ◽  
Adolfo Elizondo-Salto ◽  
María de la O. Barroso-González
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Cost Savings ◽  
Mass Scale ◽  
Tourism Sector ◽  
The Social ◽  
Analytical Tools ◽  
Media Data

This paper explores the role of social media in tourist sentiment analysis. To do this, it describes previous studies that have carried out tourist sentiment analysis using social media data, before analyzing changes in tourists’ sentiments and behaviors during the COVID-19 pandemic. In the case study, which focuses on Andalusia, the changes experienced by the tourism sector in the southern Spanish region as a result of the COVID-19 pandemic are assessed using the Andalusian Tourism Situation Survey (ECTA). This information is then compared with data obtained from a sentiment analysis based on the social network Twitter. On the basis of this comparative analysis, the paper concludes that it is possible to identify and classify tourists’ perceptions using sentiment analysis on a mass scale with the help of statistical software (RStudio and Knime). The sentiment analysis using Twitter data correlates with and is supplemented by information from the ECTA survey, with both analyses showing that tourists placed greater value on safety and preferred to travel individually to nearby, less crowded destinations since the pandemic began. Of the two analytical tools, sentiment analysis can be carried out on social media on a continuous basis and offers cost savings.

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