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John Kennedy
Universitas Bengkulu
Engineering

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Automation Mangrove Identification with Case Based Reasoning Process Arie Vatresia; Asahar Johar; Rendra Regen; John Kennedy
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 16 No. 2 (2022)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v16i2.1470

Abstract

Mangroves are ecosystems with unique functions in the environment. Because of its physical properties, mangroves are able to play a role as a wave retardant as well as retaining intrusion and abrasion of the sea. Mangroves themselves have various types of species that are spread throughout Indonesia and not yet widely known to people in general. In identifying the mangrove species itself cannot be done arbitrarily, it requires an expert who truly understands the mangrove species. This research was conducted with the aim of adopting the knowledge of mangrove experts to identify mangrove species into expert systems. The method used is case based reasoning method using the KNN algorithm which is used to calculate the similarity value between cases that will be applied to the expert system to identify mangrove species found in Taman Wisata Alam Pantai Panjang dan Pulau Baai Kota Bengkulu. This system is built using HTML, CSS, Javascript, Php, and Mysql programming languages and is designed using UML diagrams. The results of this study itself are, it has been successfully applied the case based reasoning method in the expert system to identify mangrove species found in Taman Wisata Alam Pantai Panjang dan Pulau Baai Kota Bengkulu
Co-Authors Arie Vatresia Asahar Johar Rendra Regen