English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Research about sound processing by computer using fuzzy logic has been known since 1970. One of approach logic fuzzy method is fuzzy mamdani method. Fuzzy mamdani method is the method to give conclusion from groupof rules of fuzzy. There have to be minimum of two rules, input rule and output rule. Sound processing in canaries bierd’s chirp quality can be explained as measurement standar for canary’s bird’s chirp to the point of song variant and volume. The background of this research is to create a sound identification system that uses dynamic data, the pattern of canary’s bird’s chirp obtained from dynamic data.Dynamic data is difficult to approach with certain formulas. The purpose of this research is to create indentification system to measure Canaries bird’s chirp quality pre-contest. The method used in this research was statistic analysis, sound analysis and fuzzy Mamdani method. Statistic analysis was used to look for important features from Canarie’s chirp sample. This analysis results Max amplitude variable, Min amplitude variable, Root-mean square. Then sound analysis results Autocorrelation time, Zero cross and Energy. Then those values were used as the input in fuzzy Mamdani method process. As for the output variables were the judges score result about the quality of bird’ chirp. The results from identification system of bird’s chirp quality from 6 samples are (1). Accuration level 81,67%. (2) Error sytemrate 18,33%. (3). Based on system performance and error rate that have been known can be concluded that the system can indentifyCanarie’s chirp quality well.

Identification of Canaries Bird’s Chirp Quality Using Statistic Analysis, Sound Analysis and Fuzzy Mamdani Method