International Lecture with Dr Kemal Kilic, Univ Sabanci Turkey, and Dr Ismail Fahmi, Director Media Kernels Indonesia (Drone Emprit): Data Analysis for Business Sector

News of UNAIR Postgraduate School, 3 Jun 2021 – Postgraduate School of Universitas Airlangga (UNAIR) held an international webinar on Thursday, June 3, 2021. The webinar was entitled CREATING BUSINESS VALUE WITH DATA ANALYTIC. Present as speakers are Dr. Kemal Kilic from the Faculty of Engineering & Natural Science, Sabanci University in Turkey, and Ismail Fahmi Ph.D. as a Director of Media Kernel Indonesia. Also present Ira Puspitasari, S.T., M.T., Ph.D. from UNAIR Postgraduate School as moderator.

Kemal states that complex problems require complex solutions. To produce optimal research results, data on statistics need to be analyzed. Therefore, data analysis is divided into 4 stages, namely descriptive, diagnostic, predictive, and determining. In the first stage, namely description, the type of data is described and sorted by type. Then enter the diagnosis stage, a research hypothesis is made before the data is processed. Entering the prediction stage, the data is analyzed with appropriate software and scientific theories, so that the results can be predicted. Entering the determination stage, the results are determined whether significant to a particular object and determined whether it can be used to solve a problem or not.

Meanwhile, Ismail emphasized the importance of big data processing for companies to be able to analyze market sentiment and trends. From the data that can be analyzed, it can also become a company decision, with the opportunity to be able to reduce various costs up to 8%. Company decisions can be more strategic in business through big data processing. For startups, there is no need to prepare the infrastructure to store and process data, because they can take advantage of cloud data available from Google or a company that offers could service to the public by paying a rental fee. Ismail also believes that big data analysis can also be used in the agricultural sector. By collecting rainfall conditions, weather humidity, contours, and soil conditions, optimal data processing for the appropriate distribution of plantings can be applied. For Indonesia, due to the limitations of available digital facilities, the provision of big data for the agricultural sector has experienced many obstacles and is inadequate. The Indonesian government can provide data that is available through public institutions. The public can use it to predict economic activity or social phenomena that can be used for their benefit.

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