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Journal : Journal of Machine Learning and Soft Computing

Intelligent Software for Classification of Regional Inequality in Banten Province Using the Williamson Index Tubagus Rachmat Hidayat; Harsiti Harsiti; Zaenal Muttaqin; Maya Selvia Lauryn
Journal of Machine Learning and Soft Computing Vol. 1 No. 1 (2019): Volume 1, Nomor 1, Maret 2019
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jlmsc.v1i1.1672

Abstract

The process of development in some areas occur quickly, but several areas experienced a very slow process. In this case, the local government has some problems in the process of implementing of local development, whether in policy making or proposing a strategy for local development, as well as improving the environment in order to support the development of their region's economy. Banten Province is a province located at the west of Java. The administrative conditions which is directly bordered with Jakarta as a capital city and West Java province makes Banten province become the most strategic regions. Based on economic growth data of Banten Province in 2010 - 2015, it can be seen that economic growth of Banten Province is increasing positively in five years. Although the growth of economic development in Banten province tend to be positive, it can be seen significantly that there is still a level of development that has an index of inequality  in some districts or cites in Banten. In the process of identification the inequality level among the districts in Banten province, the government usually analyze the case by using manual calculations to determine the policy that should be taken in addressing the inequality that occur in those districts. This process takes quite a long time to take the policy in structuring regional areas. In determining the area of inequality, the government requires Gross Regional Domestic Product (GRDP) data and the data of the population which can be calculated by using several inequality area methods. The method that often used is the Shift Share, Index Gain, Williamson Index and Klassen Typology. In some cases, Williamson index is often used in calculating the inequality between regions or territories. Several studies that had used Williamason index in identifying inequality development usually used the data analysis without particular tools such as software. It complicates the process of inequality analysis if the amount of the data is quite big. Therefore, this study aims to develop the software as a supporting tool for the identification of inequality development using Williamson index. The application is based-website to make it easier for the identification process.
Expert System for Diagnosing Types of Diseases in Human Intestine Organs Using the Certainty Factor Method Elis Nurhayatmi; Zaenal Muttaqin; Ahmad Sugiyarta; Ryan Naufal Hay’s
Journal of Machine Learning and Soft Computing Vol. 1 No. 2 (2019): Volume 1 Nomor 2, July 2019
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jlmsc.v1i2.1676

Abstract

Intestine is one of the organs of the digestive system in the human body which is shaped like pipes and act as gatekeeper food system for our bodies. Many people do not noticed his intestines health because they are too busy with his activity, or lazy to go to the doctor, even when hospital were many visitors there is also felt a lot of to waste time to queue up because they want to get their turn to be checked and a lot of costs to be incurred. This research discusses about creating expert system to diagnose intestinal diseases using certainty factor method.  Applications developed with Visual Basic programming language with MySQL as its database. The results of this research able to do early diagnosis of the symptoms that is felt system users, and provide diagnostic results such as type of disease suffered, prevention and its information.