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Journal : SinkrOn

APPLICATION OF SIMPLE ADDITIVE WEIGHTING METHOD FOR DETERMINATION OF TODDLER NUTRITION STATUS Badrul, Mohammad; Rusdiansyah, Rusdiansyah; Budihartanti, Cahyani
SinkrOn Vol 4 No 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v4i1.10145

Abstract

The nutritional status of children under five is measured by age, weight and height. The weight and height variables are presented in the form of three anthropometric indicators namely weight by age, height by age, and weight by height. By using these indicators the Cipadu-Kreo health center sometimes determines the nutritional status of children under five years of age. Therefore the simple additive weighting (SAW) method is able to decide the nutritional status of toddlers by adding a toddler's body mass index variable, so as to produce the right and valid decision. Then from 20 samples of toddlers categorizing by age group. Obtained the nutritional status results there are 1 toddler get a SAW value of 0.44 with poor nutritional status, 3 toddlers with undernourished status, 8 toddlers with excess nutrition status and 8 toddlers with a balanced nutrition status with the highest SAW value with a value
DIABETES MELLITUS DIAGNOSIS EXPERT SYSTEM WITH WEB-BASED FORWARD CHAINING Rusdiansyah, Rusdiansyah; Setiawan, Santoso; Badrul, Mohammad
SinkrOn Vol 3 No 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v3i2.10055

Abstract

Diabetes Mellitus Diagnosis Expert System with Web-Based Forward Chaining Method. An expert system is one branch of artificial intelligence technology that combines the knowledge of an expert with tracing data to solve problems that are normally carried out by an expert. The development of information technology now makes it possible to access information from anywhere and anytime. So the role of information technology is increasingly useful to be able to develop in various fields including in the health sector. One of them is the system used to diagnose diabetes mellitus. Diabetes Mellitus is one of the most common diseases in the world. The inability of the pancreas to produce insulin normally becomes one of the reasons a person has this disease. In this research, the method used is Forward Chaining which sorts all data obtained before getting the final conclusion. The final results obtained from this study is an expert system application for diagnosing diabetes with a forward chaining method, where the user answers questions based on perceived symptoms, then the results obtained in the form of disease and explanation of the disease.
PENERAPAN DATA MINING PENJUALAN PIZZA DENGAN MENGGUNAKAN METODE APRIORI Rusdiansyah, Rusdiansyah; suharyanti, Nining; Triningsih, Triningsih; Murniyati, Murniyati
SinkrOn Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v4i2.10500

Abstract

Pizza is a processed food originating from Italy and has been spread in various other countries including one of them in Indonesia. Pizza is a processed food that is currently sought after by various groups of people so as to make the pizza business opportunity very profitable, if it is run in a food business. Currently the pizza business has very favorable prospects when compared to other businesses. Moreover, the targeted target can be from all walks of life from children to adults. Pizza sales transactions that produce sales data every day, have not been able to maximize the use of sales data. Sales data is only stored as an archive, so it becomes a pile of data. Therefore the use of data mining is used to solve this problem. A priori algorithm is a data mining method by using minimum support parameters, minimum confidence and will analyze in the period of every month of sales transactions. This study produces data on the results of the process of association rules from the data collection of sales transactions. From the association rules it can be concluded that the pattern of pizza sales, where consumers more often buy Meatzza and Cheese Mania, as evidenced by the results of calculations using Apriori Algorithm and Rapidminer 5.3, with support of 30% and 60% confidence.