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Tensor Pure and Applied Mathematics Journal
Article . 2022 . Peer-reviewed
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Analisis Pendapatan Menggunakan Metode Weighted Least Square (Wls) dengan Fungsi Pembobot Huber

Authors: Gabriela Haumahu; Indriana Umul Mu'minin; Abraham Z Wattimena; Jefri Radjabaycolle;

Analisis Pendapatan Menggunakan Metode Weighted Least Square (Wls) dengan Fungsi Pembobot Huber

Abstract

The Weighted Least Square (WLS) method is a development of the OLS method which will provide a more accurate solution than the OLS method when outliers are identified in the data. It is possible that the model generated by the OLS method still contains outliers, while the WLS method minimizes outliers in the data. The income result determined using the OLS method is less than the income result using the WLS method, which means that if a fixed value is given (according to the standard) for each result of the factors that affect the income result in the OLS method, the average fisherman income is IDR 2,225 .220. While the average income of fishermen using the WLS method is Rp. 1,015,840. There were two outliers identified using the OLS method and after using the WLS method there were no outliers.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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