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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Yohanssen Pratama
Del Institute of Technology
Computer Science & IT

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The Addition Symptoms Parameter on Sentiment Analysis to Measure Public Health Concerns Yohanssen Pratama; Puspoko Ponco Ratno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 3: September 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i3.4711

Abstract

Information about public health has a very important role not only for health practitioners, but also for goverment. The importance of health information can also affect the emotional changes that occur in the community, especially if there is news about the spread of infectious disease (epidemic) in particular area at the time, such as case of outbreaks Ebola disease or Mers in specific area. Based on data obtained from Semiocast, Indonesia is the country with fifth largest number of Twitter users in the world, where every topic that lively discussed will also influence a global trending topic. This paper will discuss the measurement of public health concern (Degree of Concern) level by using sentiment analysis classification on the twitter status. Sentiment data of the tweets were analyzed and given some value by using a scoring method. The scoring method equation (Kumar A. et al., 2012) will be tested with new additional parameters, ie symptoms parameters. The value of any twitter user sentiment is determined based on adjectives, verbs, and adverbs that contained in the sentence. The method that we used to find the semantic value of adjectives is corpus-based method. While for finding the semantic value of the verb and adverb we used a dictionary-based method.
Cassava Quality Classification for Tapioca Flour Ingredients by Using ID3 Algorithm Yohanssen Pratama; Hadi Sutanto Saragi
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 3: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i3.pp799-805

Abstract

Cassava is one of the main foods consumed by Indonesian people and main ingredients to make tapioca flour. In North Sumatera there is factory that produced tapioca flour to fulfill consumer demand.  To be able to meet the needs of consumers and seize market share, the product must have a good quality. Product specifications are a reference for product quality and measured with 7 parameters. The seven parameters include whiteness, moisture content, spotness, ash content, thinness, residual screen, pH flour, which meets the Indonesian National Standard. In this research we use two parameters (whiteness and spotness) to determine the quality of cassava and help the factory to maintain their product quality. In here we use blob and edge detection method in image processing to detect spot and after that classified the cassava by using an ID3 algorithm. 
Co-Authors Hadi Sutanto Saragi Puspoko Ponco Ratno