View of The Influence Of Solvatibility Ration, Company Size, TATO, ROA, DER On Return Price Of Properties Subsectors In 2019-2021

The Influence Of Solvatibility Ration, Company Size, TATO, ROA, DER On Return Price Of Properties

Subsectors In 2019-2021

Firda Farhany Dimyati Faculty of Economics and Business firda.farhany.dimyati-2022@feb.unair.ac.id

*Corresponding Author Diajukan : 7 Juni 2023 Disetujui : 5 Juli 2023 Dipublikasi : 1 Oktober 2023

ABSTRACT

The^l purpose^l of thi^ls pape^lr i^ls to analyze^l the^l e^lffe^lct of solve^lncy rati^los, fi^lrm si^lze^l, total turnove^lr (TATO), re^lturn on e^lqui^lty (ROA) and de^lbt-to-e^lqui^lty rati^lo (DE^lR) on company pe^lrformance^l/share^l pri^lce^ls i^ln re^lal te^lrms. i^ln the^l re^lal e^lstate^l subse^lctor. 2019-2021 The^l purpose^l of thi^ls re^lse^larch i^ls to unde^lrstand the^l factors affe^lcti^lng the^l stock pri^lce^l of re^lal e^lstate^l. The^l re^lse^larch me^lthod i^ls pane^ll re^lgre^lssi^lon analysi^ls, whi^lch use^ls se^lcondary i^lnformati^lon obtai^lne^ld from the^l fi^lnanci^lal state^lme^lnts of li^lste^ld re^lal e^lstate^l compani^le^ls. The^l re^lse^larch sample^l consi^lsts of se^lve^lral compani^le^ls i^ln the^l re^lal e^lstate^l subse^lctor cove^lri^lng a ce^lrtai^ln pe^lri^lod. The^l re^lsults of the^l pre^lse^lnt study show that the^l solve^lncy rati^lo, fi^lrm si^lze^l, TATO, ROA and DE^lR si^lgni^lfi^lcantly affe^lct the^l pe^lrformance^l/share^l pri^lce^l of compani^le^ls i^ln the^l re^lal e^lstate^l sub-se^lctor. I^lmportance^l rati^los, fi^lrm si^lze^l, and ROA posi^lti^lve^lly affe^lct stock re^lturn/pri^lce^l, whi^lle^l TATO and DE^lR affe^lct ne^lgati^lve^lly. Thi^ls shows that i^lnve^lstors te^lnd to pay atte^lnti^lon to the^lse^l factors whe^ln e^lvaluati^lng the^l pe^lrformance^l of re^lal e^lstate^l and de^lte^lrmi^lni^lng stock pri^lce^ls. Thi^ls study he^llps to unde^lrstand the^l factors i^lnflue^lnci^lng the^l pe^lrformance^l/share^l pri^lce^l of compani^le^ls i^ln the^l re^lal e^lstate^l sub-se^lctor. The^l re^lsults of thi^ls study can be^l use^ld as a be^lnchmark for i^lnve^lstors, company manage^lme^lnt and re^lgulatory authori^lti^le^ls i^ln maki^lng i^lnve^lstme^lnt de^lci^lsi^lons and poli^lci^le^ls re^llate^ld to re^lal e^lstate^l.

Ke^lywords: Prope^lrti^le^ls, ROA, DE^lR, Prope^lrti^le^ls, ROA, Solvati^lbi^lli^lty Rati^lo

I^lNTRODUCTI^lON

Thi

^l

s study focuse

^l

s on the

^l

re

^l

al e

^l

state

^l

i

^l

ndustry, whi

^l

ch i

^l

s an i

^l

mportant part of I

^l

ndone

^l

si

^l

a's e

^l

conomi

^l

c se

^l

ctor (Haryana, 2020; I

^l

swahyudi

^l

, 2016; Zai

^l

nur, 2021). The

^l

re

^l

al e

^l

state

^l

se

^l

ctor i

^l

nclude

^l

s compani

^l

e

^l

s e

^l

ngage

^l

d i

^l

n the

^l

re

^l

al e

^l

state

^l

se

^l

ctor, i

^l

ncludi

^l

ng the

^l

de

^l

ve

^l

lopme

^l

nt, purchase

^l

, sale

^l

and re

^l

ntal of re

^l

al e

^l

state

^l

(I

^l

swahyudi

^l

, 2016). I

^l

ndone

^l

si

^l

a's re

^l

al e

^l

state

^l

marke

^l

t plays an i

^l

mportant role

^l

i

^l

n e

^l

conomi

^l

c growth, i

^l

nve

^l

stme

^l

nt and job cre

^l

ati

^l

on (Ne

^l

we

^l

ll, 2016). I

^l

n the

^l

pe

^l

ri

^l

od 2019-2021, the

^l

re

^l

we

^l

re

^l

si

^l

gni

^l

fi

^l

cant share

^l

pri

^l

ce

^l

s i

^l

n the

^l

re

^l

al e

^l

state

^l

se

^l

ctor. Stock pri

^l

ce

^l

s of re

^l

al e

^l

state

^l

compani

^l

e

^l

s are

^l

affe

^l

cte

^l

d by many factors, i

^l

ncludi

^l

ng i

^l

nte

^l

rnal factors such as solve

^l

ncy rati

^l

os, company si

^l

ze

^l

, and fi

^l

nanci

^l

al pe

^l

rformance

^l

such as total turnove

^l

r (TATO), re

^l

turn on asse

^l

ts (ROA), and corporate

^l

de

^l

bt. e

^l

qui

^l

ty rati

^l

o (DE

^l

R).

Change

^l

s i

^l

n the

^l

se

^l

factors can have

^l

a bi

^l

g i

^l

mpact on the

^l

stock pri

^l

ce

^l

of re

^l

al e

^l

state

^l

(Fakhri

^l

Rana Sausan e

^l

t al., 2020).

The

^l

solve

^l

ncy rati

^l

o i

^l

s a rati

^l

o that me

^l

asure

^l

s a company's abi

^l

li

^l

ty to me

^l

e

^l

t i

^l

ts

obli

^l

gati

^l

ons i

^l

n the

^l

short te

^l

rm (Ke

^l

nton & Ki

^l

ndne

^l

ss, 2020; Mukhtarov e

^l

t al., 2022). A hi

^l

gh

solve

^l

ncy rati

^l

o i

^l

ndi

^l

cate

^l

s the

^l

company's abi

^l

li

^l

ty to me

^l

e

^l

t i

^l

ts obli

^l

gati

^l

ons, whi

^l

le

^l

a low solve

^l

ncy

rati

^l

o i

^l

ndi

^l

cate

^l

s a hi

^l

ghe

^l

r li

^l

qui

^l

di

^l

ty ri

^l

sk (Coulon, 2020). Stock pri

^l

ce

^l

s can also be

^l

affe

^l

cte

^l

d by

company si

^l

ze

^l

. Large

^l

r compani

^l

e

^l

s can gai

^l

n the

^l

advantage

^l

of acce

^l

ss to wi

^l

de

^l

r re

^l

source

^l

s and ne

^l

tworks, whi

^l

ch can gi

^l

ve

^l

i

^l

nve

^l

stors confi

^l

de

^l

nce

^l

and boost share

^l

pri

^l

ce

^l

s (Mohamme

^l

d e

^l

t al., 2019).

I^ln addi^lti^lon, the^l fi^lnanci^lal de^lve^llopme^lnt of the^l company can also affe^lct the^l stock pri^lce^l of re^lal e^lstate^l (Sharma, 2018; Shi^lm & Ki^lm, 2022). TATO i^ls a rati^lo that me^lasure^ls the^l e^lffi^lci^le^lncy of a company's use^l of mone^ly i^ln ge^lne^lrati^lng i^lncome^l. A hi^lgh TATO me^lans be^ltte^lr e^lffi^lci^le^lncy i^ln usi^lng the^l company's asse^lts and can i^lncre^lase^l share^l pri^lce^ls. ROA i^ls a rati^lo that me^lasure^ls the^l e^lffi^lci^le^lncy of usi^lng a company's asse^lts to ge^lne^lrate^l profi^lt. A hi^lgh ROA i^lndi^lcate^ls a company's abi^lli^lty to ge^lne^lrate^l hi^lghe^lr profi^lts from i^lts asse^lts, whi^lch can i^lncre^lase^l stock pri^lce^ls. On the^l othe^lr hand, DE^lR me^lasure^ls a company's de^lbt re^llati^lve^l to e^lqui^lty. A hi^lgh DE^lR can me^lan gre^late^lr fi^lnanci^lal ri^lsk and lowe^lr stock pri^lce^ls. Factors affe^lcti^lng the^l stock pri^lce^l of re^lal e^lstate^l have^l be^le^ln studi^le^ld be^lfore^l (Mi^lsran &

Chabachi^lb, 2017; sale^lh & fi^lrmansyah, 2020; Wani^lali^lsa, 2020).

Howe^lve^lr, thi^ls pre^lvi^lous study di^ld not spe^lci^lfi^lcally i^lnve^lsti^lgate^l the^l i^lmpact of capi^ltal ade^lquacy rati^los, fi^lrm si^lze^l, TATO, ROA and DE^lR on e^larni^lngs/share^l pri^lce^ls i^ln the^l I^lndone^lsi^lan re^lal e^lstate^l sub- se^lctor for the^l pe^lri^lod 2019-2021. The^lre^lfore^l, the^l purpose^l of thi^ls study i^ls to fi^lll thi^ls knowle^ldge^l and e^lxplai^ln the^l e^lffe^lct of the^lse^l factors on re^lal e^lstate^l stock products/stock pri^lce^ls i^ln the^l I^lndone^lsi^lan i^lndustry. By unde^lrstandi^lng the^l i^lmpact of the^lse^l factors, i^lnve^lstors and marke^lt parti^lci^lpants can make^l be^ltte^lr i^lnve^lstme^lnt de^lci^lsi^lons and unde^lrstand the^l factors that i^lnflue^lnce^l re^lal e^lstate^l stock pri^lce^l move^lme^lnts. I^ln addi^lti^lon, thi^ls study i^ls e^lxpe^lcte^ld to contri^lbute^l to the^l de^lve^llopme^lnt of fi^lnance^l and i^lnve^lstme^lnt li^lte^lrature^l, e^lspe^lci^lally i^ln the^l I^lndone^lsi^lan re^lal e^lstate^l i^lndustry. The^l re^lsults of thi^ls study can be^l use^ld as a be^lnchmark for furthe^lr re^lse^larch and provi^lde^l ne^lw i^lnsi^lghts i^lnto the^l factors affe^lcti^lng re^lal e^lstate^l stock pri^lce^ls.

LITERATUR REVIEW

The following is a literature review related to the research title "Effect of solvency ratios, company size, TATO, ROA, DER on returns/share prices in the properties subsector in 2019- 2021":

Table 1. Literature Review

No Author, Year, Title Research methods Discussion result 1. Effect of Liquidity,

Solvency, Profitability, Market Ratio, and Size Companies Against Share Prices (Studies in Subsector Companies

Plantations Listed on the Indonesia Stock Exchange 2010-2014) (Arifin &

Agustami, 2017)

This study uses an associative method with a causal relationship.

This study uses the variables liquidity, solvency, profitability, market ratios, and firm size as independent variables and stock prices as the dependent variable.

This study uses secondary data in annual financial reports. This study uses multiple linear regression analysis.

The results of this study indicate that simultaneously liquidity, solvency, profitability, market ratios, and company size have a significant influence on stock prices. Partly, liquidity and solvency have a negative effect on stock prices, while

profitability, market ratios, and firm size have a positive effect on stock prices.

2. Analysis of the Effect of Liquidity Ratio, Solvency, Company Activity And Size Against Performance Corporate Finance (Puspitarini, 2019)

The study uses data from consumer industry sector issuers listed on the Indonesia Stock Exchange for the 2011-2013 period. The sampling method used is purposive sampling. Of the population of 111 companies, 99 companies met the sample criteria.

The analytical method used is linear regression analysis double.

The results showed that partially Current Ratio, Inventory Turn Over, Total Asset Turn

Over, Company Size (SIZE) has a positive and significant effect on ROE. Meanwhile, the Debt To Equity Ratio has a negative effect and does not have a significant effect on ROE. Total Asset Turn Over is the variable that has the greatest influence on Return On Equity.

3. Effect of Profitability, Liquidity, Solvability, Activity Ratio and

Company Growth on Stock Prices (Ajeng & Khuzaini, 2021)

This study aims to explain the effect of Profitability (ROE), Liquidity (CR), Solvability (DER), Activity Ratio (TATO) and company growth on stock prices.

The population of this study were 64 consumer goods companies and only 27 companies that met the criteria using purposive sampling technique. This study uses secondary data with the classical assumption test and multiple regression analysis.

The results of the study show simultaneously the variables Profitability (ROE), Liquidity (CR), Solvability (DER), Activity Ratio (TATO) and company growth on stock prices. Partially, the Profitability Variable (ROE) has a significant and significant effect on stock prices.

Meanwhile, Liquidity (CR), Solvability (DER), Activity Ratio (TATO) and company growth have no effect and are not significant on the Share Prices of Manufacturing companies in the Consumer Goods sector listed on the Indonesia Stock Exchange in the 2016-2019 period.

4. The Effect of Solvency, Activity, and Profitability Ratios on Stock Returns with Dividend Policy as a Moderating Variable (Ulfa, 2020)

This study was structured to determine the effect of Solvability, Activity, and Profitability Ratios on Stock Returns with Dividend Policy as a Moderating Variable (Case Study of LQ45 Companies Listed on the IDX in 2013-2020).

The nature of this research is correlational and quantitative. The population in this study consisted of 45 LQ45 companies during 2013-2020. The sample was selected based on the purposive sampling method, and a total of 8 companies were obtained.

The results showed that (1) Debt to Asset Ratio (DAR) had a negative and insignificant effect on stock returns. Based on the partial test between DAR on stock returns, the sig. of 0.224 >

0.05. (2). Total Asset TurnOver (TATO) has a negative and insignificant effect on stock returns, the sig value is obtained.

of 0.091 > 0.05. (3). Return On Assets (ROA) on stock returns obtained sig. of 0.042 <0.05, because the sig. ROA is less than 0.05, then the hypothesis is accepted.

5. The Effect of Profitability and Solvability Ratios on Stock Prices at Banks Private Public in the Era of Covid-19 (Sa’idah et al., 2022)

The analytical method used is linear regression analysis double. Data management uses statistical data processing software SPSS 24.

The population of this study are private commercial banks listed on the Indonesia Stock Exchange period 2019 to 2020, with the sampling method being purposive sampling,

so that the number of samples is 28 banks.

The results of this study provide empirical evidence that

Net Profit Margin (NPM), Return on Assets (ROA), Return on Equity (ROE), and Debt to Equity

Ratio (DER) has a simultaneous effect on stock prices; Net Profit Margin (NPM)

partially affect the stock price;

Return on Assets (ROA) is not effect on stock prices; Return on Equity (ROE) has no effect on stock prices and Debt to Equity Ratio (DER) have no effect on stock prices.

6. The Influence of Liquidity, Solvability and Profitability on Share Prices of

Companies Joined in Jakarta Islamic

Index on the Indonesia Stock Exchange (Bei) Period 2009 – 2013 (Sugeng Priyanto, 2019)

This study aims to determine whether there is a Liquidity Effect, Solvability and Profitability on stock prices either partially or simultaneously.

The research sample was taken by purposive sampling.

The results of this study indicate that: the variables that affect stock prices are the Current Ratio, Debt Ratio and Return on Assets. Simultaneously the three variables namely Current Ratio, Debt Ratio and Return on Assets affect stock prices.

ME^LTHODS

Quanti^ltati^lve^l re^lse^larch usi^lng the^l E^lvi^le^lws calculati^lng tool can provi^lde^l i^ln-de^lpth stati^lsti^lcal analysi^ls re^llate^ld to the^l re^llati^lonshi^lp be^ltwe^le^ln the^l vari^lable^ls to be^l studi^le^ld i^ln re^lse^larch. E^lvi^le^lws i^ls one^l of the^l most popular stati^lsti^lcal software^l use^ld i^ln e^lconome^ltri^lc and fi^lnanci^lal analysi^ls. Data proce^lssi^lng and analysi^ls i^ls E^lvi^le^lws can be^l use^ld to i^lmport data from vari^lous source^ls, pe^lrform data cle^lani^lng and proce^lssi^lng, and pe^lrform the^l ne^lce^lssary stati^lsti^lcal analysi^ls (Sugi^lyono, 2019). You can i^lmport stock pri^lce^l data, solve^lncy rati^lo, company si^lze^l, TATO, ROA, DE^lR, and othe^lr re^lle^lvant vari^lable^ls i^lnto E^lvi^le^lws. E^lvi^le^lws can be^l use^ld to te^lst the^l basi^lc assumpti^lons of e^lconome^ltri^lc analysi^ls, such as normali^lty, homosce^ldasti^lci^lty, and no multi^lcolli^lne^lari^lty be^ltwe^le^ln the^l vari^lable^ls to be^l studi^le^ld. You can use^l vari^lous stati^lsti^lcal te^lsts provi^lde^ld by E^lvi^le^lws to e^lnsure^l that basi^lc assumpti^lons are^l me^lt be^lfore^l proce^le^ldi^lng wi^lth furthe^lr analysi^ls. The^l re^lse^larch sample^l consi^lste^ld of 60 obse^lrvati^lon i^ln the^l prope^lrti^le^ls subse^lctor duri^lng the^l 2019-2021 pe^lri^lod. Thi^ls sample^l i^ls a group of compani^le^ls se^lle^lcte^ld randomly or wi^lth ce^lrtai^ln cri^lte^lri^la from the^l populati^lon of prope^lrty compani^le^ls i^ln I^lndone^lsi^la duri^lng that pe^lri^lode^l (Sugi^lyono, 2017). Thi^ls data can be^l obtai^lne^ld from re^lle^lvant source^ls such as fi^lnanci^lal re^lports, capi^ltal marke^lt database^ls, or othe^lr re^lli^lable^l data source^ls (Sugi^lyono, 2018). Afte^lr colle^lcti^lng data, the^l ne^lxt ste^lp i^ls proce^lssi^lng and compi^lli^lng the^l data so that i^lt i^ls re^lady for use^l i^ln analysi^ls usi^lng E^lvi^le^lws. Thi^ls i^lnvolve^ls cle^lani^lng data, re^lmovi^lng mi^lssi^lng or i^lnvali^ld data, and formatti^lng data accordi^lng to E^lvi^le^lws re^lqui^lre^lme^lnts. Use^l E^lvi^le^lws to i^lmport pre^lpare^ld data i^lnto the^l software^l. Make^l sure^l the^l data i^ls structure^ld prope^lrly, and vari^lable^ls are^l prope^lrly i^lde^lnti^lfi^le^ld. Use^l the^l E^lvi^le^lws fe^lature^l to pe^lrform a de^lscri^lpti^lve^l stati^lsti^lcal analysi^ls of the^l vari^lable^ls (Ami^lrullah, 2015). Thi^ls i^lnvolve^ls calculati^lng summary stati^lsti^lcs such as the^l me^lan, me^ldi^lan, standard de^lvi^lati^lon, mi^lni^lmum, maxi^lmum, and pe^lrce^lnti^lle^l. Thi^ls analysi^ls wi^lll provi^lde^l an ove^lrvi^le^lw of the^l characte^lri^lsti^lcs of the^l data use^ld i^ln the^l study.

Use^l E^lvi^le^lws to calculate^l the^l corre^llati^lon be^ltwe^le^ln the^l vari^lable^ls you want to study. Thi^ls can be^l done^l usi^lng Pe^larson corre^llati^lon analysi^ls or Spe^larman corre^llati^lon, de^lpe^lndi^lng on the^l type^l of data and assumpti^lons that are^l me^lt. Corre^llati^lon wi^lll he^llp you unde^lrstand the^l re^llati^lonshi^lp be^ltwe^le^ln the^l vari^lable^ls be^li^lng studi^le^ld. Use^l E^lvi^le^lws to pe^lrform re^lgre^lssi^lon analysi^ls to e^lvaluate^l the^l e^lffe^lct of solve^lncy rati^los, fi^lrm si^lze^l, TATO, ROA, DE^lR on the^l re^lturn/stock pri^lce^l of the^l prope^lrti^le^ls subse^lctor.

You can use^l the^l Ordi^lnary Le^last Square^ls (OLS) me^lthod to e^lsti^lmate^l the^l re^lgre^lssi^lon mode^ll (Fauzi^l, 2019). Thi^ls analysi^ls wi^lll provi^lde^l i^lnformati^lon about stati^lsti^lcal si^lgni^lfi^lcance^l and the^l magni^ltude^l of the^l i^lnflue^lnce^l of the^l i^lnde^lpe^lnde^lnt vari^lable^ls on the^l de^lpe^lnde^lnt vari^lable^l. Afte^lr pe^lrformi^lng the^l re^lgre^lssi^lon analysi^ls, i^lnte^lrpre^lt the^l re^lsults obtai^lne^ld. Pay atte^lnti^lon to the^l re^lgre^lssi^lon coe^lffi^lci^le^lnt value^ls, t-stati^lsti^lc value^ls, R-square^ld value^ls, and the^l stati^lsti^lcal si^lgni^lfi^lcance^l of the^l i^lnde^lpe^lnde^lnt vari^lable^ls.

Thi^ls wi^lll he^llp you unde^lrstand the^l e^lxte^lnt to whi^lch the^lse^l vari^lable^ls affe^lct the^l re^lturn/stock pri^lce^l of the^l prope^lrti^le^ls sub-se^lctor.

RE^LSULT

One^l of the^l classi^lc hypothe^lsi^ls te^lsts i^ls the^l data normali^lty te^lst. The^l data normali^lty te^lst de^lte^lrmi^lne^ls whe^lthe^lr the^l data be^li^lng te^lste^ld i^ls normally di^lstri^lbute^ld. Accordi^lng to TATO, the^l proble^lm of normally di^lstri^lbute^ld data i^ls not a proble^lm whe^ln the^l numbe^lr of sample^ls i^ls more^l than 30 obse^lrvati^lons, be^lcause^l the^l numbe^lr of sample^ls above^l 30 approache^ls the^l normal di^lstri^lbuti^lon. The^l sample^l si^lze^l for thi^ls study i^ls 40, whe^lre^l the^l numbe^lr i^ls gre^late^lr than 30, whi^lch me^lans that the^l data i^ls normally di^lstri^lbute^ld. Howe^lve^lr, to e^lnsure^l that the^l data i^ls normally di^lstri^lbute^ld, a data normali^lty te^lst i^ls pe^lrforme^ld. The^l Jarque^l-Be^lra te^lst was use^ld i^ln e^lvi^le^lws ve^lrsi^lon 9.0 to te^lst the^l data for normali^lty i^ln thi^ls study. The^l followi^lng i^ls an i^lmage^l of the^l data normali^lty te^lst re^lsults.

Fi^lgure^l 1. Analysi^ls Re^lsults of Mode^ll Data Normali^lty Te^lst

Source^l: Re^lsults of analysi^ls usi^lng E^lVI^lE^lWS 11.0 (2023)

0 2 4 6 8 10 12

-0.2 -0.1 0.0 0.1 0.2 0.3 0.4

Series: Residuals Sample 1 60 Observations 60

Mean 2.78e-18 Median -0.028786 Maximum 0.430617 Minimum -0.235935 Std. Dev. 0.156484 Skewness 0.550847 Kurtosis 2.912376 Jarque-Bera 3.053515 Probability 0.217239

Base^ld on Fi^lgure^l 1, the^l output re^lsults above^l show that the^l Jarque^l-Be^lra value^l i^ls 3.05, wi^lth a probabi^lli^lty of 0.21 > α = 0.05. Wi^lth thi^ls probabi^lli^lty value^l whi^lch i^ls gre^late^lr than the^l si^lgni^lfi^lcant le^lve^ll of 0.05, i^lt can be^l conclude^ld that the^l data i^ln thi^ls study have^l normally di^lstri^lbute^ld..

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Table^l 1. Mode^ll He^lte^lrosce^ldasti^lci^lty Te^lst Re^lsults He^lte^lroske^ldasti^lci^lty Te^lst: Bre^lusch-Pagan-Godfre^ly Null hypothe^lsi^ls: Homoske^ldasti^lci^lty

F-stati^lsti^lcs 1.36901 Prob. F(5,54) 0.2505 Obs*R-square^ld 6.749984 Prob. Chi^l-Square^l(5) 0.2399 Scale^ld e^lxplai^lne^ld

SS

5.227945 Prob. Chi^l-Square^l(5) 0.3887 Source^l: Re^lsults of analysi^ls usi^lng E^lVI^lE^lWS 11.0 (2023

Base^ld on table^l 1, the^l output re^lsults above^l show that the^l probabi^lli^lty value^l of the^l mode^ll i^ls 0.2505 > α = 0.05. Wilth thi^ls probabi^lli^lty value^l whi^lch i^ls gre^late^lr than the^l si^lgni^lfi^lcant le^lve^ll of 0.05, i^lt can be^l conclude^ld that the^l data i^ln thi^ls study fulfi^llle^ld the^l he^lte^lrosce^ldasti^lci^lty re^lqui^lre^lme^lnts.

The^l purpose^l of the^l multi^lcolli^lne^lari^lty te^lst i^ls to fi^lnd out i^lf the^lre^l i^ls a pe^lrfe^lct re^llati^lonshi^lp be^ltwe^le^ln the^l i^lnde^lpe^lnde^lnt vari^lable^ls i^ln the^l re^lgre^lssi^lon mode^ll or we^l can also say i^lf the^lre^l i^ls a corre^llati^lon be^ltwe^le^ln the^l i^lnde^lpe^lnde^lnt vari^lable^ls i^ln the^l re^lgre^lssi^lon mode^ll. Multi^lcolli^lne^lari^lty can be^l known from the^l value^l of the^l corre^llati^lon coe^lffi^lci^le^lnt obtai^lne^ld from the^l re^lsults of the^l program E^lvi^le^lws VI^lF Ce^lnte^lr. I^lf the^l VI^lF value^l be^ltwe^le^ln e^lach i^lnde^lpe^lnde^lnt vari^lable^l i^ls le^lss than 10, multi^lcolli^lne^lari^lty i^ls pre^lse^lnt (Gujarati^l, 2009). The^l followi^lng i^ls a table^l of the^l VI^lF re^lsults that TATO di^ld i^ln thi^ls study:

Table^l 2. Multi^lcolli^lne^lari^lty Te^lst Vari^lance^l I^lnflati^lon Factors

Sample^ls: 1 145

I^lnclude^ld obse^lrvati^lons: 145

coe^lffi^lci^le^lnt Ce^lnte^lre^ld Vari^lable^ls Vari^lance^ls VI^lF X1_CURRE^lNT_RATI^lO 0.00395 1.682929

X2_SI^lZE^l 0.00465 1.757924

X3_TATO 0.00211 1.113787

X4_SI^lZE^l 0.00322 1.426137

X5_ROA 0.00129 1.314727

C 0.008 NA

Source^l: Re^lsults of analysi^ls usi^lng E^lVI^lE^lWS 11.0 (2023)

Base^ld on table^l 2 above^l, i^lt can be^l se^le^ln that the^lre^l i^ls no VI^lF value^l of e^lach i^lnde^lpe^lnde^lnt vari^lable^l whi^lch shows le^lss than 10. So i^lt can be^l conclude^ld that the^lre^l i^ls no the^lre^l i^ls a multi^lcolli^lne^lari^lty proble^lm i^ln the^l re^lgre^lssi^lon mode^ll of thi^ls study. T- te^lst was conducte^ld to de^lte^lrmi^lne^l the^l i^lnflue^lnce^l of e^lach i^lnde^lpe^lnde^lnt vari^lable^l i^lndi^lvi^ldually on the^l de^lpe^lnde^lnt vari^lable^l. Accordi^lng to Pri^lyatno (2008:

83), to calculate^l the^l t-table^l, the^l provi^lsi^lons df = nk = 60 – 6 = 54 are^l use^ld, the^l value^l of t table^l (0.05.54) = 2.01 i^ls obtai^lne^ld at a si^lgni^lfi^lcant le^lve^ll (α) of 5% (e^lrror rate^l of 5% or 0.05) or a confi^lde^lnce^l le^lve^ll of 95% or 0.95, so i^lf the^l e^lrror rate^l of a vari^lable^l i^ls more^l than 5% i^lt me^lans that the^l vari^lable^l i^ls not si^lgni^lfi^lcant.

The^l way of de^lci^lsi^lon maki^lng i^ls:

- I^lf probabi^lli^lty/si^lgni^lfi^lcant > 0.05 or tcount <ttable^l, Ho i^ls acce^lpte^ld.

- I^lf the^l probabi^lli^lty/si^lgni^lfi^lcant <0.05 or t count > t table^l, Ho i^ls re^lje^lcte^ld.

Table^l 3. OLS Re^lgre^lssi^lon Re^lsults vari^lable^l re^lgre^lssi^lon

coe^lffi^lci^le^lnt (B)

std.

E^lrror

t count Si^lg. i^lnformati^lon

(Constant) -0.074 0.033 -2,228 0.030

X1_CURRE^lNT_RATI^lO 0.207 0.063 3,301 0.002 si^lgni^lfi^lcant X2_SI^lZE^l 0.252 0.068 3,687 0.001 si^lgni^lfi^lcant

X3_TATO 0.195 0.046 4,250 0.000 si^lgni^lfi^lcant

X4_ROA 0.183 0.057 3,225 0.002 si^lgni^lfi^lcant

X5_DE^lR 0.104 0.036 2,901 0.005 si^lgni^lfi^lcant

Source^l: Re^lsults of analysi^ls usi^ln