The Importance of Information Integrity: In a Data-Driven World, Unreliable and Inaccurate Information Can Lead to Bad Decision-Making

What is information integrity? It is the trustworthiness and dependability of information. The credibility of information depends on whether we are getting it from sources we can trust. After all, the value of information to the decision-maker and problem-solver consists first in its integrity, and then in its usefulness and usability. Why? Because, even the best chef knows that you can\u27t make a good omelet out of bad eggs! Consider the emerging trend of big data (see Big Data on page 34). According to IBM, people create 2.5 quintillion bytes of data every day (a quintillion is 1 followed by 18 zeroes), and research from International Data Corp. suggests that the world\u27s data volume is doubling every two years. So what are organizations going to do about this unfathomable data accumulation

Big Data Transformation in Agriculture: From Precision Agriculture Towards Smart Farming

[EN] Big data is a concept that has changed the way to analyse data and information in different environments such as industry and recently, in agriculture. It is used to describe a large volume of data (structured or unstructured data), which are difficult to obtain, process or parse using conventional technologies and tools like relational databases or conventional statistics, in a reasonable time for their insight. However, Big Data is applied differently in each area to take advantage of its potential and capabilities. Specially in agriculture that presents more demanding conditions due to its inherent uncertainty, so Big Data methods and models from other environments cannot be used straight away in this area. In this paper, we present a review/update of term Big Data and analyse the evolution and the role of Big Data in agriculture outlined the element of collaboration.All authors acknowledge the partial support of Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015; and the project "Development of an integrated maturity model for agility, resilience and gender perspective in supply chains (MoMARGE). Application to the agricultural sector." Ref. GV/2017/025 funded by the Generalitat Valenciana. This first author was supported by the Aid Programme of Research and Development of Universitat Politecnica de Valencia [PAID-01-18].Rodríguez-Sánchez, MDLÁ.; Cuenca, L.; Ortiz Bas, Á. (2019). Big Data Transformation in Agriculture: From Precision Agriculture Towards Smart Farming. 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Using Stock Prices as Ground Truth in Sentiment Analysis to Generate Profitable Trading Signals

The increasing availability of "big" (large volume) social media data has motivated a great deal of research in applying sentiment analysis to predict the movement of prices within financial markets. Previous work in this field investigates how the true sentiment of text (i.e. positive or negative opinions) can be used for financial predictions, based on the assumption that sentiments expressed online are representative of the true market sentiment. Here we consider the converse idea, that using the stock price as the ground-truth in the system may be a better indication of sentiment. Tweets are labelled as Buy or Sell dependent on whether the stock price discussed rose or fell over the following hour, and from this, stock-specific dictionaries are built for individual companies. A Bayesian classifier is used to generate stock predictions, which are input to an automated trading algorithm. Placing 468 trades over a 1 month period yields a return rate of 5.18%, which annualises to approximately 83% per annum. This approach performs significantly better than random chance and outperforms two baseline sentiment analysis methods tested.Comment: 8 pages, 6 figures. To be presented at IEEE Symposium on Computational Intelligence in Financial Engineering (CIFEr), Bengaluru, November 18-21, 201

STRATEGI KOMUNIKASI MARKETING PUBLIC RELATIONS OHS (OH SEMMY) MAKE-UP DALAM MEMBANGUN BRAND AWARENESS MELALUI SOCIAL MEDIA.

OHS Make-up Artist is one of the male make-up artists in Malang City. It becomes a big challenge for a man to compete in the world of the Make-up Artists which women dominate. Therefore, we need a marketing strategy that can increase sales volume from time to time.  The purpose of this study was to analyze the marketing public relations strategy of OHS Make-up Artists in building brand awareness through social media. This is descriptive qualitative research. This study uses observation, interviews, and documentation as data collection techniques with the target population of the general public in the city of Malang aged between 18 to more than 30 years.  The result of the study indicates that OHS Make-up Artist uses a push strategy, namely, using social media (Whatsapp & Instagram) as a medium of communication and information. It also uses Advertising on Instagram stories, as well as being a sponsor for some photoshoot events. At the same time, the pull strategy is in the form of collaboration with beauty products and influencers as promotion (re-branding) and portfolio enhancement. At the brand awareness level, OHS Make-up Artist is in the Brand Recognition position because people still need a stimulus to get to know OHS Make-up Artist's service products