Výsledky vyhledávání - "Mayumi Puspita"

Akademický článek

Enhancing classification rate of electronic nose system and piecewise feature extraction method to classify black tea with superior quality

Autor: Kombo Othman Kombo, Nasrul Ihsan, Tri Siswandi Syahputra, Shidiq Nur Hidayat, Mayumi Puspita, Wahyono, Roto Roto, Kuwat Triyana

Publikováno v: Scientific African, Vol 24, Iss , Pp e02153- (2024)

This study introduced a metal-oxide-semiconductor (MOS) based electronic nose (E-nose) to perform on-the-spot classification of superior-quality black tea. A piecewise feature method based on a line-fitting model was introduced to extract comprehensi

Externí odkaz: https://doaj.org/article/3706d889e6c54182b89c764ee02befea

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Akademický článek

Rapid analysis of meat floss origin using a supervised machine learning-based electronic nose towards food authentication

Autor: Linda Ardita Putri, Iman Rahman, Mayumi Puspita, Shidiq Nur Hidayat, Agus Budi Dharmawan, Aditya Rianjanu, Sunu Wibirama, Roto Roto, Kuwat Triyana, Hutomo Suryo Wasisto

Publikováno v: npj Science of Food, Vol 7, Iss 1, Pp 1-15 (2023)

Abstract Authentication of meat floss origin has been highly critical for its consumers due to existing potential risks of having allergic diseases or religion perspective related to pork-containing foods. Herein, we developed and assessed a compact

Externí odkaz: https://doaj.org/article/0d07bdcdabc44552ad46dd4440f0b2ef

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Validation of Early Infection Markers for Ganoderma in Oil Palm at Three Endemic Ganoderma Locations

Autor: Galuh Wening Permatasari, Mayumi Puspita, Irma Kresnawaty, Agustin Sri Mulyatni, Deden Dewantara Eris, Happy Widiastuti, Kuwat Triyana, Priyono Priyono

Publikováno v: Jurnal Penelitian Kelapa Sawit. 31:1-12

A serious disease that affects the viability of the oil palm industry is basal stem rot, which is caused by Ganoderma. The current level of disease can be viewed as unmanageable, given that the palms were growing in an unfavorable or unsuitable clima

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8df58c368d65a2e3ae5f8b064e823022
https://doi.org/10.22302/iopri.jur.jpks.v31i1.195

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Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose

Autor: Shidiq Nur Hidayat, Trisna Julian, Agus Budi Dharmawan, Mayumi Puspita, Lily Chandra, Abdul Rohman, Madarina Julia, Aditya Rianjanu, Dian Kesumapramudya Nurputra, Kuwat Triyana, Hutomo Suryo Wasisto

Publikováno v: Artificial intelligence in medicine. 129

Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7ed5de412176386fe5662808dad011f
https://pubmed.ncbi.nlm.nih.gov/35659391

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