This Author published in this journals
All Journal SMATIKA
Heris Pamuntjar
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Sistem Inferensi Fuzzy Mamdani Untuk Penunjang Keputusan Penentuan Potensi Desa Di Kabupaten Malang Kukuh Yudhistiro; Heris Pamuntjar
SMATIKA JURNAL Vol 9 No 01 (2019): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.911 KB) | DOI: 10.32664/smatika.v9i01.244

Abstract

The profiles of Kelurahan are the comprehensive of data collection that can accommodate the information needs for the utilization of their regional data. However, there are still obstacles to data collection and information processing needed to produce the potentioal value of a village. The constraints are such as the data distribution, data collecting, data acquisition, human resources as well as manual data collection and the unavailability of automation systems and databases that function as backups and evaluations. Therefore, to solve these problems, it is necessary to build a system that can help the implementing parties and decision makers in processing data in determining village potential. In this case the use of the mamdani fuzzy inference method as a decision-making will be the basis of decision maker for a village/Kelurahan’s profile assessment system. In this paper, processing profile survey data for all villages (390 villages) in Malang Regency where the assessment criteria will be used as fuzzy input variables, then the output of the processing is used as a dataset for the formation of fuzzy rules in the system created, will produce assessment recommendations the potential of the village that matches the conditions or criteria determined by the Malang Regency Government. From total of 390 villages, 300 will be used as data and 90 other villages to prove the accuracy of the recommendations from assessing village potential with collected datasets. The accuracy achieved by using this system reached 90%. The cause that affects accuracy is the diversity of the village conditions.