TY - JOUR

T1 - A Discrimination Index Based on Jain's Fairness Index to Differentiate Researchers with Identical H-index Values

AU - Rochim, Adian Fatchur

AU - Muis, Abdul

AU - Sari, Riri Fitri

N1 - Funding Information:
This research was financially supported by the Ministry of Research and Technology, Republic of Indonesia through Fundamental Research Grant No. 225-98/UN7.6.1/PP/2020.
Publisher Copyright:
© 2020 2020 Adian Fatchur Rochim et al., published by Sciendo.

PY - 2020

Y1 - 2020

N2 - This paper proposes a discrimination index method based on the Jain's fairness index to distinguish researchers with the same H-index. A validity test is used to measure the correlation of D-offset with the parameters, i.e. H-index, the number of cited papers, the total number of citations, the number of indexed papers, and the number of uncited papers. The correlation test is based on the Saphiro-Wilk method and Pearson's product-moment correlation. The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset (D-offset), with a range of D-offset from 0.00 to 0.99. The result of the correlation value between the D-offset and the number of uncited papers is 0.35, D-offset with the number of indexed papers is 0.24, and the number of cited papers is 0.27. The test provides the result that it is very unlikely that there exists no relationship between the parameters. For this reason, D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index. The H-index for researchers can be written with the format of "H-index: D-offset". D-offset is worthy to be considered as a complement value to add the H-index value. If the D-offset is added in the H-index value, the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.

AB - This paper proposes a discrimination index method based on the Jain's fairness index to distinguish researchers with the same H-index. A validity test is used to measure the correlation of D-offset with the parameters, i.e. H-index, the number of cited papers, the total number of citations, the number of indexed papers, and the number of uncited papers. The correlation test is based on the Saphiro-Wilk method and Pearson's product-moment correlation. The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset (D-offset), with a range of D-offset from 0.00 to 0.99. The result of the correlation value between the D-offset and the number of uncited papers is 0.35, D-offset with the number of indexed papers is 0.24, and the number of cited papers is 0.27. The test provides the result that it is very unlikely that there exists no relationship between the parameters. For this reason, D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index. The H-index for researchers can be written with the format of "H-index: D-offset". D-offset is worthy to be considered as a complement value to add the H-index value. If the D-offset is added in the H-index value, the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.

KW - D-offset

KW - Discrimination index

KW - Jain's fairness index

KW - Validity

UR - http://www.scopus.com/inward/record.url?scp=85089671353&partnerID=8YFLogxK

U2 - 10.2478/jdis-2020-0026

DO - 10.2478/jdis-2020-0026

M3 - Article

AN - SCOPUS:85089671353

VL - 5

SP - 5

EP - 18

JO - Journal of Data and Information Science

JF - Journal of Data and Information Science

SN - 2096-157X

IS - 4

ER -