a strong waalaikum warahmatullahi wabarokatuh happy to see you again with the statistics tutorial Mrs. statistics thousands of pages. On this occasion, we are sharing experience knowledge about the latest smokeless PS4 application. It has Bread from all versions to version 3 and now it has become a small pellet version 4 so that all can be downloaded in uh smartfresh channel Yes And we use the student version of Smart On this occasion we will share about how to read the output of the reflective measurement model yes Complete reflective measurement model starting from convergent validity convergent validity to very light SLR pellets and Palace predictions we will discuss everything in Smartfren Mrs. statistic 1700 pages that we wrote OK, don't forget to subscribe to our channel statistics Mother 1 stick 1000 pages yes our channel Don't forget to subscribe, yes it will give you the benefits of our channel this is our research file namely empowerment and lusita allegedly affecting motivation and satisfaction, yes local government Yes, and this test also affects motivation and job satisfaction, yes. There are 100% of the respondents. Our research building is like this. Before buying, statistical friends must look for this journal, then read this journal . use plsm When do we use vlsm and how do we report pls-sem yes this is very complete and very detailed yes in our opinion this journal will be a guide for all of us How exactly do we use pls eban analysis When do we measure what statistics Yunus reports in the research report pls Okay then we spill it From this journal into our analysis in the mother we have Hi guys the first is the evolution of the measurement model for the reflective measurement model we see the first is the evaluation of the measurement model not from a loading factor above 0 .70 then composite reabi affective value and close loading are familiar and hate MT yes then proceed with evaluating the structural model seen from inner Afif below 5 then the significance of the model testing is then carried out evaluating the suitability and goodness of the model from R square square smr then pls.pdf and linearity Okay we go straight into to the small pellet application , we open the Smart application like this, the first step is to click New Project, then give the project name, for example, research, hi, okay, then we import the data on the left. the data has been drawn then click back then kriyet model we choose plsm here pls-sem yes then we give it a name for example reflective model Already click Hi today is the day to draw first we click Klaten this gold variable click here we make empowerment told big small knife which the second is religiosity the third is motivation Hai the fourth is job satisfaction, satisfaction, my love, then for the vegetables, we click connect to connect our hypothesis according to the building of the research model, we make a key like this. the next step, we move the measurements to the ground by dragging and dropping on the blog, then we drag like this, drag felicity, then motivation , then work satisfaction Hi . look here we move it to the left we move it to the left No move it to the left it's already neat all that remains is the cycle ok this is neat just the first cycle is to evaluate the measurement model first in Perez yes this is a loading factor above 0.70 Ok we will if it's skin BLSM Don't forget to Open, bother clicking Spike, this already has results The first step is to evaluate the loading factor. This low European vector product, we throw it away later . on the left and on this list it looks red, yes, motive one, then empowerment one and empowerment two, then we throw it away first because we use hair, yes, use hair e-toll 2019 0.70 friends can use cin, yes, if the limit is cin, yes, Cin 1998 The loading factor is above 0.60, yes. It's possible, but we're using hair, we're going back to Hi. Our research model, let's throw it away first, OK? Empowerment 12 and motive one , we click back, then we throw it away. We just delete one motif one and empowerment two is wasted, OK? let's tidy it up again, we 've tidied it up. That reflects variable measurements. We can see here the output is autoloading this type of matrix. Yes, we can move this to excel by way of a blog, then copy it, then move it to XL. Yes, for the student version, you can't. The student version can't be exported. to Excel but how to export the KSLN on the blog on the blog then Right Click then we move it to Excel. Yes, we can move it to XL without the first autor loading already above 0.70 yes it meets the validity level requirements Then the second is CR with what composite reliability with AV here is the third muscle discriminant validity here there is hate MT then we can see here later Cross loading then fornel and make up good we see at the output in our mother this is outdoor loading yes otology for as much motivation as above 0.70 then also empowerment then Hi, satisfaction is also reality. What does outdoor learning mean, let's see what the motivations are ot loading 0.76 point 76 is greater than 0.70 which means that every time the item that the item motives is invalid measures the motivational variable every change in motivation will be reflected in motivation2 of 55,000 so every change in a teacher's motivation will be reflected or represented in item number 2 of 55-60, which means then we continue with the reliability composite meaning 0.89 and AV the meaning of this reliability composite is overall satisfaction motivation empowerment and obesity have a level of reliability at the level of an acceptable variable yes or or each measurement item that measures the whole item measurement item satisfaction measures consistent or reliable satisfaction, yes No, this is then the AV value. What is the HP value of 0.96, so the final value is 0.5 96. satisfied 6 contained by that variable is 59.60 Saint so b the magnitude of the variation in the kumite measurement variation contained in the satisfaction variable is 59.60 Saint fulfills a good convergent validity evaluation , minimum 50%, the next step is TMT, we saw earlier in my abcd ATM output, this is the minimum ATM seen by this MP is 0.4 simum 0.90 to say a good level of discriminant validity where the value is 0.90 here, okay, we moved it to our mother, the cell phone value. If you look at the mv, it should be below 0.90, for example, HTM is satisfaction with motivation , right? This is below 0.90, it means that the convert discriminant validity has been reached, yes in 9 politics it has been reached. Okay, it means what is cemented paliti bavarians divided by the variable which is greater for items than it is divided for other items? -toll that this KTP is more recommended than for new and a record compared to the loading process so you have recently been in the journal journal l Internationally it's reported, yes, because HTM has a better level of sensitivity and accuracy in measuring discriminant validity compared to for new and like and cross loading, but short circuit and fornever, we will also report this, this is Fortnite, yes, the output already has a smart flash, we can see here, formal and reckless this is the output key let's see Hi satisfaction slash this Latitude is going to AV 0.77 2771 8138 11 this is Raffi this transverse line this diagonal line so that AV we bolt thick this is carve any variable must be greater than the correlation between constructions it can be read that fire satisfaction is 0.77 two greater than motivation greater than empowerment is greater than the correlation with a density of 0.98 this shows that the discriminant validity for the satisfaction variable is fulfilled Likewise with motivation look down and to the left side yes this is greater than 7 one from downward and 71 greater than the correlation with motivation this shows n Avenue roots show that discriminant validity is met, then the loading short circuit is the evaluation of the measurement model at the item level, for example, here the motives for the measurement items, the motives must still be higher with 746 motivation, right ? We can see here that all motivational items 2-6 correlate more strongly with the variable it measures, namely motivation, which is motivational and lower than other Palembang. with empowerment and satisfaction, yes, you can compare each with a stronger correlation with the variable being measured. Okay, cross loading creates higher creativity with shaving items. this texture then returns to all the pellets back B Oh yes come here then we if our skin is bootstrap Okay we choose 5000 then we select BCA B corrective accelerative then we select Open hassle click Open bother Okay this is IDR 5,000 then we'll wait already this is we can we can just choose the setting value or t-statistic, yes, we can see here that empowerment has a significant effect on motivation, it is also significant, the felicity is not significant, the value is above 0.05, this empowerment is significant for this motivation, then also reality is also significant for motivation, the full output is in here okay This is a fashion line Yep efficiency Magnitude of influence While this is the significance on the right this is the t-statistics okay before evaluating the structural model the first step we have to do is this this review this review he yes satisfaction and inner motivation the effect is below five ok This Below five. Whether there is multicollinearity is not assessed, it must be below li ma Okay the value below means that there is no multicollinearity between variables that affect satisfaction, continue then we just click call it stretch and we have described the result earlier . we can see that increasing job satisfaction here the variable affecting satisfaction is empowerment motivation and from the situation yes from when we can see these variables here that the most influencing it is motivation yes 364 empowerment 0.4 empowerment yes empowerment has the highest and greatest influence on satisfaction compared to motivation and recitation while the ricity is not significant we can see here so when there is a policy from the school principal regarding motivation for empowerment and resitas waqf the highest teacher satisfaction is empowerment the second is motivation while ricity is not significant ifik Ok this is here Hi already the next step is this evaluation the complete interval is 95% we also report it in international journals we have also started doing this we can read here the motivation for satisfaction this is lower this is over confidence 95% meaning in a confidence interval of 95% The influence of motivation on satisfaction lies between 0.14 eight to 0.56 eight. Yes, this means that once again in a long dive 90%, the effect of motivation on satisfaction lies between 0.14 8-0 568, meaning that if the principal implements policies that related to increasing teacher motivation, the effect on motivation will increase until the highest is 0.56 8 key , followed by the mediation test, how about the mediation test here, the specific indirect effect, we can see recently, the contents of the bag and motivations affect satisfaction means motivation mediates the influence of the lesitta after satisfaction is here can we here significant n yes okay empowering is also significant we can see that reality does not directly affect satisfaction not directly earlier yes we can see here reality does not directly affect satisfaction here but through the mediation of motivation later policies must be taken by the Principal in increasing satisfaction from resitas is to make programs from situations that encourage motivation yes make density programs that encourage motivation when the motivation grows then the satisfaction will be sing when we saw it here earlier yes Sis Hi this key this rositas has a significant indirect effect on satisfaction by motivation of 0.1 80 to the next eighth is evaluating the goodness and suitability of this model the last part is SWT SquarePants Where's rMR and artalink RCTI prediction pellets OK the first is M Square we're back again to smokeless we're back like then we're Randy the first part earlier yes share first there's appsquare here Edward here r-square first Let's look at the square Here Kya Aap Square Let's open it first M Square forms a matrix Here's the heart yes this Square this r-square is already here then this is the goodness-of- fit yes it's here okay srm ring is here Kya Translate appsquare the effect of variables at the structural level Yes we might want to know whether the effect is low moderate or moderate and high yes how to calculate this experiment is by entering the variables into the model and eliminating the variables in the model then compares the M Square of the two events, yes, for example, the motivational variable is removed from the model, what is the score, then the motivational variable is included in the F model, what is the score , then how to calculate R Square, we immediately see that the r-square value is divided into three, namely 0.020 1500 and 0.35 is high, we can see that the effect of motivation on satisfaction is 0.31, that's right ti at a low level but towards Moderate many approaching medium 0.51 empowerment influences satisfaction at a moderate structural level yes above zero point 15 while reality has a low effect empowerment and resilience have an influence on empowerment motivation at a moderate level while Russia is a high level bicycle yes it is very high above 0.35 we can see that if there are programs with satisfaction the principal makes a policy regarding the reality satisfaction improvement program yes sorry about the risk then he will encourage very strong motivation yes this is 0.38 so it has a very strong influence very high at the structural level r-square R Square Hai satisfaction value 5903 means that the magnitude of the influence of empowerment and motivation on satisfaction is 5903 percent and according to this measure Water is included in the muter influence or moderate influence so these three variables have a moderate influence together in influencing Mr.'s hospital satisfaction is 0.09 five, yes 0.09 5 we translate here according to hair 0.09 5 is considered not good, I'm not a good driver, but we use a reference from a luxurious screen share fabric, OK ? 0.10 is still acceptable, if it's less than zero point 10, it's still acceptable, this is 0.09. The last 5 about pls Dik, right? Because we use the student version or not, we back it up and then there are credit pellets. We use the student version. We can't use the professional version. Okay, let's see the output here, enter the skin click, then select plsv here . satisfaction yes 0.49 4 this is relatively moderate Yes he's the cake is the level of prediction accuracy Yes qwerty i This can also be called the level of prediction accuracy according to hair if the chi-square value is above 0.25 above 0.50 it is considered high, it means that we can see here, this includes satisfaction, this is high 0.94 which is close to 0.50, this motivation is considered high. yes so every change that bag production and empowerment is able to predict every motivational change yes the level of prediction accuracy is high if satisfaction is close to high yes this is yes at a height of 0.94 above Hi Okay this is the output earlier pls predict yes This is also reported in each pls analysis research is one of the same prediction-based ones to test the theory of models that are more oriented towards predictions. Therefore, the news prediction pellets must be what the name is stated in making a report about PLS, yes, how to read it is by comparing the PRS model with the PRS model. regression Does the PRS model have what is called accuracy, power, yes, predictive power, yes, predictive power f the predictive power is very good or not, according to Hairbath, by comparing the PL PRS model with the right-hand regression model, the regression model, yes, we can see here that all items of satisfaction and motivation are endogenous variables, the RMSE value and the noodles. root mean Square error and this is mint absolutely the error must be smaller the PNS model must be smaller than the regression model once again the PRS model must be smaller than the regression model yes the trick is the pls model must be smaller which is lower yes the rmse value and play is greater lower than the linear regression model we can see for item 21 it turns out that the lower regression model is satisfied2 pls lower this one pls lower yes satisfied 1234 this PRS model is lower 935 than one legend pellet 886 lower than this lower which we blog red this shows Perez is taller but if we add up these black ones 123456789 10 11 1 2 13 14 yes the black one uh the front one is red so there are more PRS models lower than the Legacy Okay, let's see here Hi most of the indicators there are 14 out of 20 uran pls have a lower rmse and May value than this modern er eyes PNS models have medium predictive power which has a predictive medium Al Okay maybe that's all we can say about the model pls hopefully Saba statistics all benefit from our presentation If there is a statistic patient everyone is interested in having Ibuk statistics 1700 pages we have updated 1700 pages about SPSS real-world flash Smartfren Had Amos dance Tata, please Japri to our cell phone number God willing, we will help and once bought free for life it's enough to have 1700 pages of statistical bugs, we'll update it forever, it's free as long as we update, our mothers don't have to give anymore, so one time buy is free forever Thank you salamualaikum Sule barakatuh I hope