Article Per Year (5 Year)
p-Index From 2021 - 2026
1.937
P-Index
This Author published in this journals
All Journal Desimal: Jurnal Matematika Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Indonesian Journal of Education and Mathematical Science Community Development Journal: Jurnal Pengabdian Masyarakat ALACRITY : Journal Of Education Journal Of Human And Education (JAHE) METAL : Jurnal Sistem Mekanik dan Termal BATIK: Jurnal Pengembangan dan Pengabdian Masyarakat Multikultural INTAN CENDEKIA: JURNAL PENGABDIAN MASYARAKAT Journal of Mathematics, Computation and Statistics (JMATHCOS)
Sarmada, Sarmada
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Desimal: Jurnal Matematika

 1 
Comparison of quantile regression and censored quantile regression methods in the case of chicken consumption Sarmada, Sarmada; Yanuar, Ferra; Devianto, Dodi
Desimal: Jurnal Matematika Vol. 6 No. 2 (2023): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v6i2.18949

Abstract

The censored quantile regression method is a parameter estimation method that can be used to overcome censored data and BLUE (Best Linear Unbiased Estimator) assumptions that are not met. This research aims to compare the quantile regression method and the censored quantile regression method on data on chicken consumption cases in West Sumatra. The smallest RMSE (Root Mean Square Error) is an indicator of the goodness of the model. This research proves that the censored quantile regression method tends to produce smaller RMSE values than the quantile regression method. So it is concluded that the censored quantile regression method is the appropriate method for estimating parameters with censored data.
Co-Authors Affan, Affan Alfan Ekajati Latief Alim, Khairul Devianto, Dodi Fajrin, Dirani Amaris Gusri, Lailal Irawan, Randi Irfan, Laode Mochamad kholijah, gusmi M. Yogi Riyantama Isjoni Mardhotillah, Bunga Multahadah, Cut Multhadah, Cut Prianto, Ramdan rarasati, niken S., Adimas Prasetyo S., M. Pramuda Nugraha Safitri, Yuliana Shahadah, Nabilah Sherly, Issaura Sormin, Corry Tasya, Anisya Yanova, Shally Yanuar, Ferra Yurinanda, Sherli Yurinanda, Sherly Yusnidar Yusnidar Z, Gusmanely Z, Gusmanely. Zurweni Zurweni