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Ahmad Haidar Mirza

Gunadarma University

Author-ID : 320637

Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Poverty Data Model as Decision Tools in Planning Policy Development Mirza, Ahmad Haidar
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14022

Poverty is the main problem in a country both in developing countries to the developed countries, both in structural poverty, cultural and natural. That is, poverty is no longer seen as a measure of the failure of the Government to protect and fulfill the fundamental rights of its citizens but as a challenge of the nation to realize a fair society, prosperous and dignified sovereign. Various efforts have been made in determining government policy measures in an effort to overcome poverty, one of them by conducting a survey to assess the poor. The results of the survey of the various activities of the organization obtained a variety of database versions poverty to areas or locations. The information generated from the poverty database only includes recapitulation of poor people to the area or location. One step is to process the data on poverty in a process of Knowledge Discovery in Databases (KDD) to form a data mining poverty. Data mining is a logical combination of knowledge of data, and statistical analysis developed in the knowledge business or a process that uses statistical techniques, mathematics, artificial intelligence, artificial and machine-learning to extract and identify useful information for the relevant knowledge from various large databases.

Poverty Data Model as Decision Tools in Planning Policy Development Mirza, Ahmad Haidar
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14022

Poverty is the main problem in a country both in developing countries to the developed countries, both in structural poverty, cultural and natural. That is, poverty is no longer seen as a measure of the failure of the Government to protect and fulfill the fundamental rights of its citizens but as a challenge of the nation to realize a fair society, prosperous and dignified sovereign. Various efforts have been made in determining government policy measures in an effort to overcome poverty, one of them by conducting a survey to assess the poor. The results of the survey of the various activities of the organization obtained a variety of database versions poverty to areas or locations. The information generated from the poverty database only includes recapitulation of poor people to the area or location. One step is to process the data on poverty in a process of Knowledge Discovery in Databases (KDD) to form a data mining poverty. Data mining is a logical combination of knowledge of data, and statistical analysis developed in the knowledge business or a process that uses statistical techniques, mathematics, artificial intelligence, artificial and machine-learning to extract and identify useful information for the relevant knowledge from various large databases.

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