Infolitika Journal of Data Science
Vol. 1 No. 1 (2023): September 2023

ANFIS-Based QSRR Modelling for Kovats Retention Index Prediction in Gas Chromatography

Idroes, Rinaldi (Unknown)
Noviandy, Teuku Rizky (Unknown)
Maulana, Aga (Unknown)
Suhendra, Rivansyah (Unknown)
Sasmita, Novi Reandy (Unknown)
Muslem, Muslem (Unknown)
Idroes, Ghazi Mauer (Unknown)
Jannah, Raudhatul (Unknown)
Afidh, Razief Perucha Fauzie (Unknown)
Irvanizam, Irvanizam (Unknown)



Article Info

Publish Date
07 Sep 2023

Abstract

This study aims to evaluate the implementation and effectiveness of the Adaptive Neuro-Fuzzy Inference System (ANFIS) based Quantitative Structure Retention Relationship (QSRR) to predict the Kovats retention index of compounds in gas chromatography. The model was trained using 340 essential oil compounds and their molecular descriptors. The evaluation of the ANFIS models revealed promising results, achieving an R2 of 0.974, an RMSE of 48.12, and an MAPE of 3.3% on the testing set. These findings highlight the ANFIS approach as remarkably accurate in its predictive capacity for determining the Kovats retention index in the context of gas chromatography. This study provides valuable perspectives on the efficiency of retention index prediction through ANFIS-based QSRR methods and the potential practicality in compound analysis and chromatographic optimization.

Copyrights © 2023






Journal Info

Abbrev

ijds

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Description

Infolitika Journal of Data Science is a distinguished international scientific journal that showcases high caliber original research articles and comprehensive review papers in the field of data science. The journals core mission is to stimulate interdisciplinary research collaboration, facilitate ...