S udies Managemen and Finance Economics, o Jou nal
0504-2644 (online): ISSN 0490,-2644 (p in ): ISSN
5202 No embe 11 Issue 80 Volume
8.317 Fac o : Impac ,33-i11-10.47191/je ms/ 8 DOI: A icle
4507-7438 No: Page
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7438
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking
Sec o
Kaleb Solaiman1, Bah ia Usman2, Adle Haymans Manu ung3
1Ph.D S uden a T isak i Uni e si y in Indonesia
2P o esso o Finance a T isak i Uni e si y in Indonesia
3P o esso o Capi al Ma ke and Banking a Bhayangka a Uni e si y Jaka a Raya
ABSTRACT: This esea ch aims o explo e se e al a iables ha a ec p ice o book alue mode a ed by size in Indonesia's banking
sec o . This esea ch used a panel da a model o he pe iod 2015 o 2024. This s udy ound ha he noise a iable s a is ically
signi ican ly a ec s he p ice- o-book alue a iable. The noise a iable consis en ly signi ican ly a ec s p ice- o-book alue
wi hou including size as a mode a ing a iable, as well as when including size as a mode a ing a iable. Size is conside ed a
mode a ing a iable because he in e ac ion be ween size and noise signi ican ly a ec s p ice- o-book alue.
KEYWORDS: P ice o Book Value, In e es Ma gin, Loan o Deposi s Ra io, En e p ise In o ma ion Technology, Noise, Size
I. INTRODUCTION
Banks, as inancial business ins i u ions, ha e he ask o collec ing unds om su plus uni s and dis ibu ing hem o de ici
uni s, ea ning a ma gin o hese ope a ions. Banks can channel hese unds h ough c edi o in es men o consume
pu poses. Based on A icle 1 o Law No. 7 o 1992 conce ning banking, which was amended by Law No. 10 o 1998, which was
also in luenced by Job C ea ion Law No. 11 o 2020, i is s a ed ha banks ha e he concep o "Ins i u ions ha collec unds om
he public, in o m hem abou sa ings o deposi s o accoun s, and hen channel hem o o he ins i u ions h ough c edi o
o he o ms o imp o e he s anda d o li ing o he communi y. Bank in es men s a e a ac i e o ob aining g ea e capi al and
p o iding op imal e u ns. The ollowing shows in es men s in banking s ocks since Decembe 2024. Financial s ock indices a e
highly ola ile and can p o ide p o i s o in es o s, as can be seen in he image below.
Figu e 1.1: Banking S ock Index since Decembe 2024
Sou ce: h ps://id. ading iew.com/cha /?symbol=IDX%3AIDXFINANCE
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7439
Table 1.1 below shows banking pe o mance om 2017 o 2024. A he end o 2024, he e we e 105 banks, down om 115
banks in 2017. The banking index luc ua ed om 2017 o 2024. To al banking asse s in Indonesia amoun ed o IDR 7,387.6
illion in 2017 and inc eased o IDR 12,460.967 illion in 2024, ep esen ing an a e age g ow h o 7.75% pe yea du ing ha
pe iod. The e u n a e in 2017 had he highes e u n a e o 46.73% and he lowes o - 10.91% in 2024. The inancial sec o
expe ienced signi ican luc ua ions, while BCA sha es expe ienced he highes posi i e luc ua ions, app oaching he inancial
sec o 's indus y
e u n a e, and he lowes a 5.18% in 2024. BBTN's e u n a e was 109.64% in 2017 and he lowes a -5.34% in 2024.
The a e o e u n on a ious s ocks is shown by luc ua ing alues and becomes an op ion o in es men . This a e o e u n is
measu ed by he annual e u n on sha es. Table 1.1 shows ha he a e o e u n on sha es a ies conside ably and can a exceed
he ma ke .
P e ious explana ion ega ding in es men decisions o pu chase banking s ocks on he Indonesia S ock Exchange (IDX). Banking
s ocks a e usually pu chased using he P ice o Book Value measu e (Manu ung e .al, 2023). The use o P ice o Book Value as a
measu e o pu chasing banking s ocks is due o he na u e o bank s ocks, whe e asse s a e owned as a esul o public us in
banks o deposi hei unds in he banks conce ned. Based on his PBV measu e, in es o s ha e a desi e o de e mine how much
hey a e willing o pay o he book alue o he bank. The book alue is he accumula ion o e ained ea nings o he bank in
ques ion. Based on he o mula de eloped by Manu ung e al. (2025c), PBV is a unc ion o Re u n on Equi y (ROE), Di idend
Payou Ra io (DPO), di idend g ow h (g), and expec ed e u n ( ).
Table 1.1 Banking Pe o mance and Re u n Ra es o Se e al Bank S ocks
Kine ja Pe bankan
Indika o
2017
2018
2019
2020
2021
2022
2023
2024
Jumlah Bank
115
115
110
109
107
106
105
105
Ase
7.387,63
7.913,49
8.562,97
9.177,89
10.112,30
11.113,32
11.765,84
12.460,96
K edi
4.781,93
5.358,01
5.683,76
5.547,62
5.820,64
6.497,62
7.186,94
7.942,95
DPK
5.289,38
5.630,45
5.998,65
6.665,39
7.479,46
8.153,59
8.457,93
8.837,24
Laba Be sih
131,14
150,01
156,49
104,72
140,21
201,82
243,33
255,20
ROA
2,45
2,55
2,47
1,59
1,85
2,45
2,74
2,69
NIM
5,32
5,14
4,91
4,45
4,63
4,80
4,81
4,62
CAR
23,18
22,97
23,40
23,89
25,66
25,62
27,65
26,69
LDR
90,04
94,78
94,43
82,54
77,49
78,98
83,83
88,57
NPL
2,56
2,37
2,53
3,06
3,00
2,44
2,19
2,08
BOPO
78,64
77,86
79,39
86,58
83,55
78,70
78,92
81,30
Ase Likuid
18,56
14,96
15,51
18,91
19,57
15,90
13,29
11,27
Indeks Finansial
900,64
910,52
1.033,43
993,40
1.031,02
1.150,98
1.269,55
1.130,96
Re u n Indeks Finansial
0,467318
0,01097
0,134989
-0,03874
0,0378699
0,1163508
0,1030166
-0,1091647
BCA
3723,93
4.469,36
5.816,58
6.010,52
6.593,96
7.872,04
8.869,75
9.386,19
Re u n BCA
0,428939
0,200173
0,301435
0,033343
0,0970698
0,1938259
0,126741
0,05822487
Mandi i
2728,36
2.581,07
2.772,93
2.400,59
2.757,25
4.081,20
5.229,53
5.178,97
Re u n Bank Mandi i
0,416403
-0,05398
0,074334
-0,13428
0,1485718
0,4801705
0,2813707
-0,0096682
BRI
2289,99
2.372,94
2.954,13
2.908,92
3.229,89
4.036,05
4.970,78
3.856,24
Re u n Bank BRI
0,611205
0,036223
0,244924
-0,0153
0,1103399
0,2495936
0,2315952
-0,2242183
BNI
3732,6
3.412,67
3.117,21
2.526,24
2.782,69
3.873,18
4.708,12
3.992,38
Re u n Bank BNI
0,848874
-0,08571
-0,08658
-0,18958
0,1015145
0,3918834
0,2155696
-0,1520225
DANAMON
5132,58
5.734,99
3.026,80
2.643,32
2.006,45
2.385,98
2.533,34
2.417,47
Re u n Bank Danamon
0,914327
0,11737
-0,47222
-0,12669
-0,240936
0,189155
0,0617608
-0,045738
CIMB NIAGA
820,62
569,74
616,68
689,24
696,75
930,41
1.456,99
1.584,76
Re u n Bank CIMB
Niaga
0,597656
-0,30572
0,082388
0,117662
0,0108961
0,335357
0,5659655
0,08769449
J-TRUST
50,00
50,00
50,00
700,00
206,00
174,00
120,00
187,00
Re u n Bank J-T us
0
0
0
13
-0,705714
-0,15534
-0,3103448
0,55833333
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7440
BBTN
2634,83
1.903,82
1.624,02
1.324,20
1.328,04
1.181,93
1.133,42
1.072,89
Re u n Bank BBTN
1,096426
-0,27744
-0,14697
-0,18462
0,0028999
-0,110019
-0,041043
-0,0534047
MAYBANK
212,97
170,39
174,89
302,50
292,75
205,45
225,51
201,75
Re u n Bank Maybank
-0,21026
-0,19993
0,02641
0,729659
-0,032231
-0,298207
0,0976393
-0,1053612
Sumbe : Bank Indonesia dan OJK
Ma gin (o en e e ed o as in e es ma gin o Ne In e es Ma gin) in a bank is a e y impo an inancial a io. This ma gin is
he main sou ce o income o a bank. This ma gin is he di e ence be ween he in e es ea ned by he bank in i s lending
ac i i ies, so he ma gin is he in e es ecei ed minus he in e es paid as a esul o he lending ac i i ies ca ied ou by he
bank conce ned. In e es ma gin is insepa able om bank policy and p e ailing in e es a es (F eixas and Roche , 2008). The
highe he in e es ma gin, he highe he bank's going conce n. Howe e , he highe he in e es ma gin, he lowe he loans
disbu sed. Hasan e al. (2020) ound ha he in e es ma gin has a posi i e e ec on ROA and ROE. Manu ung e al. (2020) also
s a ed ha NIM has a posi i e e ec on bank pe o mance as measu ed by RAROC. Widyas u i e al. (2017) also s a ed ha he
in e es ma gin has a posi i e e ec on bank p o i abili y in Indonesia. F eddy and Toni (2020) s a ed ha he Ne In e es
Ma gin g ea ly a ec s he P ice o Book Value. The e o e, he in e es ma gin is used as an independen a iable in his
disse a ion esea ch.
The Loan o Deposi s Ra io (LDR) is a a io o loans (c edi ) g an ed wi h hi d-pa y unds (DPK). This a io is conside ed a a io
ha desc ibes banks as in e media ies in he Indonesian economic sys em. As a a io, banks mus no exceed 92% (Manu ung,
2017). Banks wan o ha e his a io because hey also ha e o und in e bank ansac ions, o eign exchange ansac ions, and
in es men s in bonds. Resea ch on he e ec o LDR on PBV and in es men decisions is s ill e y limi ed. Lubis e al. (2019)
conduc ed esea ch on he e ec o LDR on ROA. Abdu ohman e al. (2020) conduc ed esea ch on he e ec o LDR on ROA.
Tan owi and Simanjun ak (2020) also conduc ed esea ch on he e ec o LDR on ROA. Fanesha e al. (2021) s udied he e ec o
LDR on ROA. Se ianingsih e al. (2023) s udied he e ec o LDR on ROA.
The EITSP (En e p ise In o ma ion Technology S a egic Plan) is a p og am ha is always included in he bank's annual planning
because echnology is e y impo an o banking oday. I a bank does no ha e one o he in o ma ion echnologies in banking,
i will all behind in se ice. The 2017 PWC Repo (PWC, 2017) s a es ha he banking indus y in Indonesia is unde going a
signi ican ans o ma ion d i en by digi al echnology/in o ma ion echnology. Bank Indonesia Regula ion (PBI) No.
9/15/PBI/2007 conce ning he implemen a ion o isk managemen in he use o in o ma ion echnology by banks and PBI No.
12/21/PBI/2010 conce ning bank business plans equi e all banks o comply and submi hei bank business plans and he
implemen a ion o isk managemen in he use o IT by banks o Bank Indonesia on ime e e y yea . The esponsibili y o he
Boa d o Di ec o s and all pa ies (business uni s and suppo uni s) o he Bank o ganiza ion ha use high in o ma ion
echnology can inc ease inancial s abili y (Flamini e al., 2009).
Acco ding o Beccalli (2007), banking p oduc s and se ices ha e used in o ma ion and communica ion echnology (ICT), now
e e ed o as digi al echnology (DT), in he p oduc ion and deli e y p ocesses o achie e e ec i e and e icien ways o
gene a ing cus ome sa is ac ion and expe ience. Compu e s a e p esen in all ields, bu hei p esence does no inc ease
p oduc i i y (Solow, 1987). In ac , Roach (1994) s a es ha he p oduc i i y pa adox is a phenomenon cha ac e ized by a gap
be ween he in es men alloca ed o in o ma ion echnology and he o al ou pu p oduced. Kusumaning um e al. (2021)
discuss in es men decisions and di idend policies on he Indonesia S ock Exchange o banking s ocks. Simo angki (2025)
s a es ha in o ma ion echnology is e y impo an o banking and is measu ed by expendi u e on in o ma ion echnology.
In he con ex o inance, noise is always associa ed wi h i ele an o misleading in o ma ion, andom luc ua ions, o sho -
e m p ice mo emen s ha cause con usion o in es o s in making in es men decisions. This noise is always measu ed by s ock
ola ili y (Feng e al., 2014). Resea ch on noise in ela ion o PBV and in es men decisions is s ill e y limi ed. T uemann (1988)
s a es ha in es o s a e e y ond o ading s ocks i he e is ading noise on hose s ocks. Ye and Tan (2021) s a e in hei
esea ch esul s ha noise ading o en occu s in he Chinese s ock ma ke and ha ma ke e u ns a e mo e ola ile in good
ma ke s han in bad ma ke s. Gao and Ladley (2021) discuss he exis ence o noise ading and ma ke s abili y. Khasawneh and
Abdel (2017) discuss noise ading in small ma ke s such as he Amman S ock Exchange.
This s udy co e s he pe iod om 2015 o 2024. This pe iod includes he COVID-19 pandemic. The exis ence o his pe iod
means ha he s udy mus include a dummy pe iod o he COVID-19 pe iod. Nega i e news abou COVID-19 had a huge impac
on a ious indus ies and businesses, causing a sha p decline in in es men ma ke p ices and nega i ely a ec ing s ock
pe o mance and e u ns (Neog and Rakshi , 2022). The COVID-19 pandemic a iable was used as a dummy a iable in his
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7441
disse a ion esea ch. Sulli an and Widoa modjo (2021) discuss his pandemic pe iod in he inancial sec o , especially banks.
Hidayan i and Cahyono (2023) discuss ac o s ha in luence inancial dis ess du ing he COVID-19 pe iod. Cio i e al. (2020)
discuss COVID-19 in he heal h sec o . Rino ah e al. (2022) s udied he ac o s ha in luence he po en ial o bank up cy du ing
he COVID-19 pandemic pe iod. Nguyen e al. (20224) discussed he COVID-19 pandemic and he manu ac u ing sec o . E diaw-
Kwasie (2023) discussed he impac o he COVID-19 pe iod on he pe o mance o small companies.
The in e nal and ex e nal a iables o he bank need o be mode a ed by o he a iables. Manu ung (2019a) s a es ha
mode a ing a iables can s eng hen o weaken he ela ionship be ween independen and dependen a iables. The
mode a ing a iable used in his s udy is bank size. Nodeh e al. (2016) used company size as a mode a ing a iable in examining
he e ec o bank di ec o s uc u e on he inancial pe o mance o banks in Malaysia. Bada a (2016) also conduc ed esea ch
using bank size as a mode a ing a iable o Nige ia. Abbasi and Malik (2015) used company size as a mode a ing a iable in
in luencing company inancial pe o mance. Hapsa i (2018) conduc ed esea ch on banking and used bank size as a mode a ing
a iable o examine he e ec o LDR and NPL on banking pe o mance. The e o e, his a iable will also be used in his s udy as a
mode a ing a iable. Fi i e al. (2018) conduc ed esea ch on banking pe o mance using company size as a mode a ing a iable.
Size as a mode a ing a iable has been p oposed and used by p e ious esea che s. Howe e , mode a ing a iables can be
media ing a iables, as s a ed by Sha ma e al. (1981), namely, "I a speci ic a iable is linked o a c i e ion a iable and/o a
p edic o a iable bu does no in e ac wi h he p edic o a iable." In his s udy, bank asse s a e included as a mode a ing
a iable ha ac s as a media ing a iable. Si o us (2017) used bank asse s as an in e ening a iable o in luence bank
p o i abili y. Ap ilia e al. (2018) conduc ed esea ch on banking using Re u n On Asse as an in e ening a iable.
II. THEORETICAL REVIEW
In his s udy, company o bank pe o mance is one o he ac o s in luencing in es men decisions, and his a iable is
placed as an in e ening a iable. Company pe o mance is he abili y o a company o gene a e alue, which has inc eased.
The abili y o company managemen o manage he company has caused he company's alue o inc ease. The inc ease in he
company's sha e alue is indica ed by he company's sha e p ice on he s ock exchange. Fo he banking indus y,
pe o mance is measu ed by P ice o Book Value (Manu ung, 2025c; Pin o, 2010), because banks a e se ice ins i u ions and
hi d-pa y unds, and he c edi disbu sed is a ool o banks o inc ease company alue. Jamil (2017) in es iga ed he
ac o s ha in luence PBV.
Wilcox (1984) has shown ha he P/B-ROE (Re u n On Equi y) model appea s o be supe io o he p ice-ea nings
a io alua ion model. Fama and F ench (1991) showed ha he book- o-ma ke a io explains e u n di e ences be e
han be a, and hough ha size and book- o-ma ke a ios a e p oxies o o he undamen als. Ka mawan and Dewi
(2025) s udied he ac o s ha in luence P ice o Book Value. Fa ikhah and Gin ing (2025) conduc ed esea ch on he in luence
o DER, ROE, and Cu en Ra io on P ice o Book Value. Nawawi (2024) s a ed ha P ice o Book Value is s ill in luenced by
key ac o s such as ROA and so on. Rahayu e al. (2023) discuss ha in es men decisions, he DER a io, and di idend policy
simul aneously in luence PBV. Rahayu and U ami (2020) discuss he in luence o in es men decisions, p o i abili y, and size
on PBV.
Banking as an in e media y ins i u ion o collec unds om su plus uni s and channel hem o de ici uni s. Banks pay
in e es o su plus uni s a a lowe a e han he in e es hey ecei e om de ici uni s. This in e es di e ence is known as
he in e es ma gin o Ne In e es Ma gin (NIM). Ne In e es Ma gin (NIM) is a inancial a io in banks as a measu e o
pe o mance. NIM is he di e ence in in e es ea ned by banks as a esul o dis ibu ing unds and paying in e es o hi d
pa ies. This in e es ma gin gene ally anges om 3% o 6% (Manu ung, 2020). The e o e, ne in e es ma gin can be
w i en in a ma hema ical equa ion (Manu ung and Dezme coledi, 2013 and Manu ung, 2025). Ho and Saunde s (1981)
discuss he de e minan s o ne in e es ma gin in heo y and in p ac ice in he Uni ed S a es. And os and Chang (2021)
discuss inno a i e app oaches o managing in e es ma gins wi h economics and s a is ical analysis o comme cial bank
esou ces.
Ne in e es ma gin is always ela ed o in e es a e heo y, whe eby an inc ease in in e es a es will inc ease
in la ion and dec ease company ne p o i s (Do nbusch and Fische , 2017). Dumicic and Ridzak (2013) discuss he
de e minan s o he ne in e es ma gin o banks in Eu ope. Doy an (2013) in es iga es he ela ionship be ween ne in e es
ma gin and i m pe o mance in de eloping coun ies. Les a i (2021) discusses he ac o s ha in luence in e es a es o
Indonesian banks.
The Loan o Deposi s Ra io (LDR) is a a io used by banks o measu e hei in e media y capabili ies. Howe e ,
Manu ung (2020) s a es ha banks can dis ibu e hei unds so ha his LDR a io should no exceed 92%, because banks
mus p o ide unds o o he banking ac i i ies such as o eign exchange ansac ions, in es men s in bonds, und ans e
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7442
ansac ions, e c. Resea ch on LDR a ies g ea ly, bu he ela ionship be ween his a io and in es men decisions is e y
limi ed. Resea ch on LDR in ela ion o o he ac o s a ies g ea ly. Lubis e al. (2019) conduc ed esea ch on he e ec o
LDR on ROA. Abdu ohman e al. (2020) conduc ed esea ch on he e ec o LDR on ROA. Pu i and Sua dikha (2019)
discussed he e ec o LDR on bank p o i abili y. Tan owi and Simnajun ak (2020) also conduc ed esea ch on he e ec o
LDR on ROA. Fanesha e al. (2021) s udied he e ec o LDR on ROA. Se ianingsih e al. (2023) s udied he e ec o LDR on
ROA. Ugli (2025) discussed he ac o s ha in luence he Loan o Deposi Ra io.
Nowadays, banks a e compe ing o se e hei cus ome s, who ha e adi ionally been cen e ed on b anch o ices,
and he e has been a change in cus ome se ice. This ac ion is insepa able om he de elopmen o echnology, namely
h ough he echnology owned by cus ome s, namely mobile elecommunica ions. Laudon and Laudon (2004) de ine
in o ma ion echnology as a combina ion o ha dwa e, so wa e, and ne wo ks ha collec , s o e, p ocess, and ansmi
in o ma ion elec onically. Acco ding o Wilkinson and Ce ullo (1997), in o ma ion echnology in es men is he amoun o
company unds used o in es in in o ma ion echnology, bo h ha dwa e and so wa e. In o ma ion echnology has he
abili y o mee he in o ma ion needs o he business wo ld quickly, imely, ele an ly, and accu a ely. Schniede jans e al.
(2010) s a e ha in o ma ion echnology in es men is a decision o in es in alloca ing all esou ces (ha dwa e, so wa e,
so wa e applica ions, and human esou ces) o manage in o ma ion sys ems. Zana ia (2017) s a es ha he u iliza ion o
in o ma ion echnology is wha in o ma ion sys em use s expec o do hei jobs o he beha io hey exhibi when using
echnology a wo k. Halim e al. (2020a) discuss EITSP wi h bank pe o mance.
Halim e al. (2020b) conduc ed esea ch on he o EITSP wi h bank pe o mance in Indonesia mode a ed by size. S i as a
and Jain (2024) s udied he in luence o in o ma ion echnology assessmen on in es men decision choices. Abu-Taleb &
Nilson (2021) discussed he in luence o social media on in es men decisions. Sup iyadi e al. (2023) discussed he in luence
o Financial Technology (Fin ech) on Banking P o i abili y in Indonesia.
Noise on he s ock exchange can be de ined as in e e ence o noise ha occu s on he exchange when an in es o
decides o buy o sell ce ain s ocks. This noise is caused by he la ge amoun o in o ma ion en e ing he exchange, which
con uses in es o s when conduc ing s ock ansac ions, causing hem o sell when hey ac ually wan o buy, o ice e sa,
buying s ocks when hey should be selling. Noise was i s in oduced by Black (1981). This noise is always measu ed by s ock
ola ili y (Feng e al., 2014). Resea ch on his noise in ela ion o PBV and in es men decisions is s ill e y limi ed. T uemann
(1988) s a es ha in es o s a e e y ond o ading s ocks when he e is ading noise on hose s ocks. Ye and Tan (2021)
s a ed in hei esea ch esul s ha noise ading o en occu s in he Chinese s ock ma ke and ha ma ke e u ns a e mo e
ola ile in good ma ke s han in bad ma ke s. Gao and Ladley (2021) discussed he exis ence o noise ading and ma ke
s abili y. Khasawneh and Abdel (2017) discussed noise ading in small ma ke s such as he Amman S ock Exchange. Dai e
al. (2025) discuss he ac ions ha mus be aken so ha noise ade s can su i e in he ma ke in he long e m, e en hough
p e ious indings indica e ha noise ade s canno su i e in he long e m. He e e al. (2019) discuss he in luence o noise
ade s and sma in es o s on s ock e u ns and ola ili y.
Size is a a iable ha indica es he size o a company wi hin a g oup o companies. Size became a a iable ha was
aken in o accoun in inancial esea ch a e Banz (1981) published his esea ch on size as measu ed by a company's ma ke
capi aliza ion. Size is o en used as an independen a iable o a mode a ing a iable. In his pape , size is used as a
mode a ing a iable in he esea ch amewo k. Amelinda e al. (2023) in es iga ed he ole o size as a mode a ing a iable
in inancial esea ch. Mahmood e al. (2019) conduc ed esea ch on he e ec o mode a ing a iables o company size and
le e age on wo king capi al in China. Bada a (2016) in es iga ed he mode a ing e ec o company size on he ela ionship
be ween boa d s uc u e and bank inancial pe o mance. Muigai and Mu ii h (2017) conduc ed a s udy on he mode a ing
e ec o company size on capi al s uc u e and co po a e inancial dis ess. Mahanani & Ka ika (2022) discussed he
in luence o size on company alue. P ase yo e al. (2024) discuss he e ec o size on p ice o book alue o Indonesian banks.
Rahayu and U ami (2020) discuss in es men decisions, p o i abili y, and size on p ice o book alue.
III. METHODOLOGY
This sub-sec ion will explain he me hod used in his esea ch. This sub-sec ion comp ises Panel Da a Model, Ope a ional
Va iables, and Sou ces o Da a.
MODEL
This esea ch uses h ee models whe e he dependen a iable is P ice o Book Value (PBV). The i s model is he PBV model
in luenced by independen a iables wi hou mode a ing a iables. The second model includes he mode a ing a iable Size
wi hou conside ing i s in e ac ion. The hi d model is a comple e model ha shows he in e ac ion o mode a ing a iables wi h
independen a iables so ha mode a ing a iables can be s a ed. The comple e model is as ollows:
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7443
PBVi, = a0 + b1 NIMi, + b2 LDRi, + b3 EITSPi, + b4 NOISEi, + b5 SIZEi, + b6 PDMC
+b8 (SIZEi, *NIMi, ) + b9 (SIZEi, *LDRi, ) + b10 (SIZEi, *EITSPi, )
+ b11 (SIZE(i, ) *NOISE(i, ) )+ ε (1)
Panel Da a Model
This esea ch uses a Panel Da a Model o es ima e he ela ionship be ween some independen a iables o de e mine P ice o
Book Value as a dependen a iable wi h Ma gin In e es , Loan o Deposi s Ra io (LDR), En e p ise In o ma ion Technology,
Noise, COVID, and Size as mode a ion a iables. The Panel Da a Model is app op ia e o small da a, which is a sho ime se ies,
and small companies as samples. Besides ha , he panel da a model also shows ime and c oss-sec ion as samples. Guja a i
(2003), Woold idge (2002), G eene (2008), Bio n (2017), Sul (2019), and Manu ung (2024b) s a ed ha he panel da a model is as
ollows:
Judge (1982), Woold idge (2002), Bio n (2017), Sul (2019), and Manu ung (2024b) s a ed ha how we choose FEM o REM is as
ollows:
When T ( he numbe o ime se ies da a poin s) is la ge and N ( he numbe o c oss-sec ional uni s) is small, FEM may be
p e e able. When N is la ge and T is small, i we s ongly belie e ha he indi idual, o c oss-sec ional, uni s in ou sample a e
no andom d awings om a la ge sample, FEM is app op ia e. I he c oss-sec ional uni s in he sample a e ega ded as
andom d awings, he REM is app op ia e. When indi idual e o componen εiand one o mo e eg esso s a e co ela ed,
FEM is
an unbiased es ima o . REM es ima o s a e mo e e icien han FEM es ima o s when N is la ge and T is small and i he
assump ions unde lying REM hold.
IV. RESEARCH DATA
The uni o analysis in his esea ch is elecommunica ions companies lis ed on he Indonesia S ock Exchange. The e a e 17
bank companies ha we e pu posi ely selec ed as he uni o analysis, wi h annual epo s om 2015 o 2024. The da a was
collec ed om se e al sou ces. Mos o he da a is on a yea ly basis o he pe iod 2015 o 2024. All da a was collec ed om he
websi es o he banks and he Indonesia S ock Exchange.
This esea ch will p esen desc ip i e analysis and causal analysis, which will be explained la e .
V. FINDINGS AND DISCUSSION
Desc ip i e Analysis
The cen al alues o his disse a ion esea ch a e he minimum, maximum, a e age, skewness, ku osis, and Ja que
Be a alues. This in o ma ion can be seen in Table 1 below.
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7444
TABLE 1 : CENTER VALUE OF RESEARCH VARIABLE.
PBV
NIM
LDR
EITSP
Noise
Minimum
0.188653
0.4700
32.680
0.001215
0.0400
Maximum
16.75218
9.3000
135.46
0.93362
1.3014
A e age
1.247769
4.8089
83.878
0.206077
0.4092
S anda d
De ia ion
1.554493
1.7876
13.109
0.170549
0.2055
Skewness
6.331868
-0.1833
-0.5943
1.554399
1.6118
Ku osis
58.54315
0.1157
3.4528
3.288146
3.5499
Ja que Be a
22,988.33
59.8775
11.4596
69.04584
75.7460
Sou ce: P ocessed by he esea che
In his s udy, he main dependen a iable used is in es men decision, whe e a alue o ze o indica es no buying sha es and a
alue o one indica es buying bank sha es. The e o e, he cen al alue o his a iable does no need o be analyzed because i
does no p o ide any u he meaning.
The in e media e a iable is bo h an independen and dependen a iable in his s udy. The in e media e a iable in his s udy,
P ice o Book Value, is a a iable ha ep esen s company pe o mance and is also used o pu chase bank sha es. The minimum
alue is 0.1886x; he maximum alue is 16.75x, he a e age is 1.248x, and he s anda d de ia ion is 155.45%. This igu e
indica es ha he PBV alue a ies g ea ly o he 17 esea ch samples and he a e age is e y close o he minimum alue. The
Ja que Be a alue is e y high and i can be s a ed ha he PBV a iable has a no mal dis ibu ion.
The NIM a iable is a a iable ha indica es he pe o mance and p o i abili y o he bank conce ned. The minimum alue is
0.47%; he maximum alue is 9.3%, he a e age is 4.81%, and he s anda d de ia ion is 178.76%. This igu e indica es ha he
NIM alue a ies g ea ly o he 17 esea ch samples, and he a e age is he cen al alue o in he middle o he minimum and
maximum alues. The Ja que Be a alue is e y high, and i can be s a ed ha he NIM a iable has a no mal dis ibu ion.
The LDR a iable is a a iable ha indica es a bank's abili y o ac as an in e media y be ween su plus ins i u ions o uni s and
de ici ins i u ions o uni s. LDR is he a io o loans g an ed o cus ome s o he amoun o unds collec ed by he bank. This a io
is expec ed o be a maximum o 100%, bu p e ious s udies ha e shown ha his a io only anges a ound 90% due o o he
ac i i ies. The minimum alue is 32.68%; he maximum alue is 135.46%, he a e age is 83.878%, and he s anda d de ia ion is
13.109%. These igu es indica e ha he LDR alue a ies g ea ly o he 17 esea ch samples, and he a e age is he expec ed
LDR a io alue, which ends o a y a ound he expec ed LDR alue. The Ja que Be a alue is e y high, indica ing ha he LDR
a iable has a no mal dis ibu ion.
The EITSP a iable is a a iable alue ha indica es bank spending on in o ma ion echnology. Banks a e cu en ly highly
dependen on in o ma ion echnology, and almos all banks ha e in o ma ion echnology o se e hei cus ome s. As desc ibed,
his expendi u e alue is di ided by o al asse s because i is adjus ed o he alue o he independen a iable (in e media e
a iable), which is he bank's pe o mance a io and also he p o i abili y o he bank conce ned. The minimum alue is 0.12%;
he maximum alue is 93.36%, he a e age is 20.61%, and he s anda d de ia ion is 17.05%. These igu es indica e ha he EITSP
alue a ies g ea ly o he 17 esea ch samples, and he a e age is a alue ha anges a ound he minimum alue. The Ja que
Be a alue is e y high and i can be s a ed ha he EITSP a iable has a no mal dis ibu ion.
The Noise a iable is a a iable ha indica es s ock ac i i y on he exchange, whe e he e is a lo o in o ma ion and con usion
when making in es men decisions on hese bank s ocks. The measu emen o his noise in o ma ion uses he s anda d de ia ion
alue o s ock p ices on he exchange. The minimum alue is 4%; he maximum alue is 130.14%, he a e age is 40.92%, and he
s anda d de ia ion is 20.55%. These igu es indica e ha he Noise alue a ies g ea ly o he 17 esea ch samples, and he
a e age is e y close o he minimum alue. The Ja que Be a alue is e y high and i can be s a ed ha he Noise a iable has a
No mal dis ibu ion.
Bank size is used as a mode a ing a iable in his disse a ion esea ch. Bank size is measu ed using he size in oduced by Bank
Indonesia, which has unde gone changes h ough a Bank Indonesia Ci cula Le e . I u ns ou ha he bank size in his esea ch
sample a ies g ea ly because la ge banks can be coun ed on one hand, and bank size 3 is also balanced wi h size 4, while he es
is ep esen ed by banks wi h sizes 2 and 1. Howe e , his bank size canno be said o be a bank wi h a no mal dis ibu ion.
In his s udy, he COVID-19 a iable was included as an independen a iable o dis inguish be ween he pe iods when
COVID-19 was p esen and when i was no , symbolized by 0 and 1. As a esul , cen al da a analysis was no necessa y in his
s udy.
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7445
Causal Analysis
This sub-chap e discusses he a iables ha in luence he PBV (p ice o book alue) a iable, which is an in e media e a iable
in his s udy. The esea ch model was c ea ed wi h and wi hou mode a ion. The esea ch mode a ion used is he size o he
bank cu en ly using his capi al. The esea ch model always uses he Fixed E ec s Model (FEM), which is one o he panel da a
models. This ac ion was aken because he da a was collec ed pu posi ely wi h an emphasis on in o ma ion echnology
expendi u e da a, which amoun ed o 17 companies. The independen a iables in his s udy a e NIM, LDR, EITSP, Noise, and
COVID-19, and a a iable size as a mode a ing a iable. Equa ion (4.1) is a ma hema ical model o PBV in luenced by NIM, LDR,
EITSP, Noise, and COVID-19.
PBVi, = 0.2969 - 0.01897 NIMi, + 0.0039 LDRi, + 0.7128 EITSPi, + 1.3454 NOISEi,
(0.6663) (0.3957) (0.283) (0.00)
+ 0.0481 COVID-19(i, ) (1)
(0.5535)
R2 = 33.92%, F = 9.7574, Numbe s in pa en heses a e p obabili y alues
The coe icien o de e mina ion is 0.3392 o 33.92%, which s a es ha he a iables NIM, LDR, EITSP, NOISE, and COVID-19
oge he in luence PBV luc ua ions by 33.929%, wi h he emainde in luenced by o he ac o s. The F alue o 9.7574 indica es
ha his alue
is g ea e han he F( able) alue and leads o he conclusion ha model (1) is highly sui able
and can be used o
examine he e ec o independen a iables on he dependen a iable PBV. As desc ibed ea lie , he i s model analyzed was he
e ec o he a iables NIM, LDR,
Noise, EITSP, and COVID-19 on PBV. This model is shown in Equa ion 4.1. In equa ion (4.1), he Noise a iable signi ican ly and
posi i ely a ec s PBV a a signi icance le el o 1%. I Noise inc eases by 1 uni , PBV also inc eases by 1.3454 uni s. This esul is
almos he same as equa ion (1). I PBV con inues o inc ease, he e is a possibili y ha in es o s will no buy he sha es o he
company conce ned. The inc ease in luc ua ing s ock p ices is indica ed by an inc ease in noise as measu ed by he ola ili y o
he s ock. As a esul , he sha es in ques ion a e decided no o be pu chased because he sha e p ice has inc eased. On he o he
hand, equa ion (1) shows ha he a iables NIM, LDR, EITSP, and COVID-19 do no signi ican ly a ec PBV a a signi icance le el
o 10%. The esul s o his s udy suppo p e ious s udies, namely Ha ini e al. (2023), Su ismi e al. (2023), and Jamil (2017),
Ka mawan and Dewi (2025), Fa ikhah and Gin ing (2025), Nawawi (2024), Rahayu e al. (2023), and Rahayu and U ami (2020).
Fu he mo e, he Size a iable was included as an independen a iable because he size a iable will be es ed as a mode a ing
a iable in his s udy. The model is shown in equa ion (4.2) as ollows:
PBVi, = 0.6989 - 0.0313 NIMi, + 0.0035 LDRi, + 0.4825 EITSPi, + 1.3282 NOISEi,
(0.4968) (0.4403) (0.5139) (0.00)
- 0.016 COVID-19i, – 0.0841 SIZEi, (2)
(0.8684) (0.3632)
R2 = 33.94%, F = 8.6158, Numbe s in pa en heses a e p obabili y alues
The coe icien o de e mina ion is 0.3394 o 33.94%, which s a es ha he a iables NIM, LDR, EITSP, NOISE, and COVID-19
oge he in luence PBV luc ua ions by 33.94%, wi h he emainde in luenced by o he ac o s. The F alue = 8.6158 indica es
ha his alue
is g ea e han he F( able) alue and leads o he conclusion ha model (2) is highly sui able o can be decla ed a
model and can be used o see he e ec o independen a iables on he dependen a iable PBV.
The p e ious desc ip ion shows ha he second model analyzed is he e ec o he a iables NIM, LDR, Noise, EITSP, COVID-19,
and size on PBV. This model is shown in Equa ion (2). In equa ion (2), he Noise a iable signi ican ly and posi i ely a ec s PBV a
a signi icance le el o 1%. I Noise inc eases by 1 uni , PBV also inc eases by 1.3282. This coe icien alue is smalle han he
coe icien alue in equa ion (1). I PBV con inues o inc ease, he e is a possibili y ha in es o s will no buy he sha es o he
company conce ned. The inc ease in luc ua ing s ock p ices is indica ed by an inc ease in noise as measu ed by he ola ili y o he
s ock. As a esul , he s ock in ques ion is decided no o be pu chased because he s ock p ice has inc eased. On he o he hand,
equa ion (2) shows ha he a iables NIM, LDR, EITSP, and COVID-19, as well as he a iable Size, do no signi ican ly a ec PBV a
a signi icance le el o 10%.
Then, PBV is also es ima ed and he in luence o he a iables NIM, LDR, Noise, EITSP and COVID-19 is obse ed, while including
size as a mode a ing a iable and es ing he size a iable as a mode a ing a iable. The esul s a e shown in equa ion (3) below.
PBVi, = 0.269 - 0.0156 NIMi, - 0.0081 LDRi, + 0.485 EITSPi, + 3.9000 NOISEi,
Noise A ec P ice o Book Value Mode a ed by Size in Indonesia’s Banking Sec o
JEFMS, Volume 08 Issue 11 No embe 2025 www.ije m.co.in Page 7446
(0.8968) (0.5997) (0.8261) (0.0)
+ 0.007382 SIZEi, + 0.1108 PDMC – 0.0376 (SIZEi, *NIMi, )
(0.9901) (0.2205) (0.3927)
+ 0.0085 (SIZEi, *LDRi, ) – 0.0711 (SIZEi, *EITSPi, ) –
(0.123) (0.9287)
- 1.3836 (SIZEi, *NOISEi, ) (3)
(0.0)
R2 = 38.21%, F = 14.247, Numbe s in pa en heses a e p obabili y alues
In Model (3), he coe icien o de e mina ion (R2) is 38.21% and he Fob alue is 14.247.
The coe icien alue o 38.21% indica es
ha all a iables oge he explain 38.219% o he luc ua ions in he PBV a iable, wi h he emainde being explained by o he
ac o s. This esul is qui e good, as he e a e s ill o he ac o s ha explain i . This ai ly la ge alue indica es ha model (3) is
e y sui able o he model. Finally, he e ec o each a iable (NIM, LDR, Noise, EITSP, and COVID-19) on PBV, known as pa ial
a iable analysis, is discussed. The Noise a iable posi i ely and signi ican ly a ec s he PBV a iable a a 1% signi icance le el.
This esul is he same as he esul s o equa ions (1) and (2). I he noise a iable inc eases by one uni , i will inc ease he PBV
a iable by 3.900 uni s. This s udy suppo s p e ious s udies. As desc ibed ea lie , he size a iable is included as a mode a ing
a iable.
Consequen ly, his s udy examines he mode a ing e ec o he size a iable. The in e ac ion be ween size and he independen
a iable se es as a benchma k o examining he e ec o size as a mode a ing a iable. The in e ac ion be ween size and noise
has a nega i e e ec on PBV. This in e ac ion indica es ha size weakens he ela ionship be ween noise and PBV. The size
a iable becomes a pu e mode a ing a iable because size does no signi ican ly a ec PBV (Sha ma, 1981 and Manu ung, 2024).
The in e ac ion be ween size and Co id-19 has a posi i e e ec on he dependen a iable PBV. The size a iable becomes a pu e
mode a ing a iable o PBV because he size a iable does no signi ican ly a ec PBV (Sha ma, 1981 and Manu ung, 2024).
This size mode a ing a iable s eng hens he ela ionship be ween Co id-19 and PBV.
In model (2), i was ound ha he NIM a iable did no signi ican ly a ec he dependen a iable PBV a a signi icance le el o
10%. The independen a iable LDR also did no signi ican ly a ec he dependen a iable PBV a a signi icance le el o 10%. The
independen a iable IETSP also does no signi ican ly a ec he dependen a iable PBV a a signi icance le el o 10%. The
a iable size as a mode a ing a iable also does no signi ican ly a ec he dependen a iable PBV a a signi icance le el o 10%.
The insigni icance o he independen a iable size a ec ing he dependen a iable PBV will p o ide a s a emen ha he
signi ican in e ac ion es will p o e o be a pu e mode a ing a iable. The esul s o his s udy suppo p e ious s udies, namely
Ha ini e al. (2023), Su ismi e al. (2023), and Jamil (2017), Ka mawan and Dewi (2025), Fa ikhah and Gin ing (2025), Nawawi
(2024), Rahayu e al. (2023), and Rahayu and U ami (2020).
VI. CONCLUSION
This s udy ound ha he noise a iable s a is ically signi ican ly a ec s he P ice o Book Value a iable. The Noise a iable
consis en ly signi ican ly a ec s P ice o Book Value wi hou including Size as a mode a ing a iable, as well as when including he
Size a iable asa mode a ing a iable. Size is conside ed a mode a ing a iable because he in e ac ion be ween size
and Noise signi ican ly a ec s P ice o Book Value.
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[3].
2) Al-Tamimi, H. A. H. (2006). Fac o s in luencing indi idual in es o beha io : an empi ical s udy o he UAE inancial
ma ke s. The Business Re iew, 5(2), 225-233.
3) Ani a, I., Tampubolon, J. F. And A.A. Rachman (2021), Fac o s A ec ing he In es men decision on S ock In es o
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