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Mental Health, Religion & Culture
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Evaluating psychometric properties of the Muslim Daily Religiosity Assessment Scale (MUDRAS) in Indonesian samples using the Rasch model
Bambang Suryadi , Bahrul Hayat & Muhammad Dwirifqi Kharisma Putra
To cite this article: Bambang Suryadi , Bahrul Hayat & Muhammad Dwirifqi Kharisma Putra (2020): Evaluating psychometric properties of the Muslim Daily Religiosity Assessment Scale (MUDRAS) in Indonesian samples using the Rasch model, Mental Health, Religion & Culture To link to this article: https://doi.org/10.1080/13674676.2020.1795822
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Evaluating psychometric properties of the Muslim Daily
Religiosity Assessment Scale (MUDRAS) in Indonesian samples using the Rasch model
Bambang Suryadia, Bahrul Hayataand Muhammad Dwirifqi Kharisma Putrab
aFaculty of Psychology, UIN Syarif Hidayatullah Jakarta, Indonesia;bFaculty of Psychology, Universitas Gadjah Mada, Yogyakarta, Indonesia
ABSTRACT
This study aimed to validate the Indonesian version of the Muslim Daily Religiosity Assessment Scale (MUDRAS). This measure was tested on 766 Muslim college students aged 17–24 years (mean age = 20.01, SD = 1.4) who were students from six state Islamic universities and one private Islamic university in Indonesia. The data analysis technique used was the Partial Credit Model, which derived the polytomous Rasch model family. The results indicated that the MUDRAS has good psychometric characteristics for measuring religiosity in a sample of Indonesian Muslim students.
All assumptions of the Rasch model were fulfilled. The person separation reliability was .92 and Cronbach’s alpha was .93, indicating excellent internal consistency of the Indonesian MUDRAS. Confirmatory factor analysis revealed the higher order factor structure of the Indonesian MUDRAS. These findings provide thefirst Rasch model contribution to the MUDRAS and its first validation in a Muslim majority country.
ARTICLE HISTORY Received 25 March 2020 Accepted 8 July 2020
KEYWORDS
Adaptation; factor analysis;
MUDRAS; Muslim religiosity;
partial credit model; Rasch model
From prehistoric times to the present, religion has been a central part of human experi- ence and culture. Many experts see religion as a particularly important type of human activity, and all major religious traditions have developed philosophies on the nature of being human and our place in the world (Nelson,2009). Islam is the second largest religion in the world (Abu-Raiya et al., 2008). As Islam originated in the Asian continent, most Muslims are currently living in Asia, and the percentage of Muslims in Asia is about 27.5% of the total world Muslim population of 1.14 billion people. Additionally, 236 million Muslims are living in southeast Asia (Kettani, 2010). Indonesia is the world’s most populous Muslim nation (Webster, 2013), and 87.2% of Indonesians are Muslims (Government of Republic of Indonesia, 2020). Although Islam is the majority religion in Indonesia, Islam has also served as a unifying force for all religions in the country (Choi, 1996), in line with Pancasila– the Indonesian state ideology.
In the scientific study of religion, religiosity in its numerous manifestations has been researched for decades (Salam et al.,2019). Pioneering work on the psychology of religi- osity was done by Allport and Ross (1967), which examined the relationship between
© 2020 Informa UK Limited, trading as Taylor & Francis Group CONTACT Bambang Suryadi bambang.suryadi@uinjkt.ac.id
Supplemental data for this article can be accessed athttps://doi.org/10.1080/13674676.2020.1795822 https://doi.org/10.1080/13674676.2020.1795822
religious orientation and prejudice. Religiosity has been broadly studied in Indonesia using a variety of instruments (e.g., Brief Multidimensional Measure of Religiousness/
Spirituality and The Centrality of Religiosity Scale) that have been adapted to the Indo- nesian language (Cahyaningrum,2018; Purnomo & Suryadi,2017). This is not surprising, as religion has become a mandatory subject for all Indonesian undergraduate students.
However, there is a theoretical gap related to religiosity among these Indonesian adap- tations of the scales. This is because religiosity is a general concept, and the term as used is not specifically applicable for the Muslim population despite being tested in all-Muslim samples. Meanwhile, adaptations of measures developed in the West are not necessarily in line with Islamic values (Salam et al., 2019). However, the development of research on the Muslim context has been promising and rapid (Abu-Raiya & Hill,2014). Unfortu- nately, Indonesian versions of measures for Muslim religiosity are rare in the literature, especially in international peer-reviewed journals. There are also methodological gaps, as advances in psychometric methods such as the use of latent trait models in religiosity research (e.g., Abernethy & Kim, 2018; Schaap-Jonker et al., 2016) are rarely found in Indonesia.
Religiosity has been operationalised with different dimensions and has been measured in various ways. Muslim religiosity also has multiple conceptualisations. Although numer- ous studies have been conducted, the results are still inconclusive because of differences in the constructs of religiosity used (Abu-Raiya & Hill, 2014; Salam et al., 2019; Schaap- Jonker et al., 2016). As Abu-Raiya and Hill (2014) pointed out, from 1997 to 2013, there were a total of 17 religiosity measures rooted in Islam. They usedfive criteria to critically analyse religiosity measures, namely theoretical clarity, sample representation, reliability, validity, and cultural generalisability (Hill, 2013). The findings of their study indicated that the variety and scope of the instruments that have been developed are impressive.
Many of these instruments are promising, but others need refinement and further validation.
Another study by Mahudin et al. (2016) analysed twelve religiosity measures including one measure with Indonesian samples from Ji and Ibrahim (2007), although that measure was developed by a“derivative approach” (Abu-Raiya & Pargament,2011), which is associ- ated with some challenges (Abu-Raiya & Hill,2014). Moreover, due to the fact that Indo- nesia is a multicultural and multi-faith country, the use of Allport and Ross’s (1967) theory and religiosity instrument is not appropriate. (Hill & Dwiwardani, 2010). In a study by Salam et al. (2019) reviewing 39 measures of religiosity in an Islamic marketing context, none of them were validated in Indonesia.
In the Indonesian context, religiosity has a vital role in life in this multicultural society.
Indonesia has a rich diversity of cultures, religions, traditions, and local wisdom traditions.
The two most notable Islamic organisations are Persyarikatan Muhammadiyah and Nah- dlatul Ulama (Webster, 2013), which are also the two largest in the world (Marshall, 2018), and which are affiliated with higher education systems all across Indonesia (e.g., Muhammadiyah University and State Islamic University). Given these conditions, there is a need to have measures of religiosity grounded in Islam (see Abu-Raiya & Hill,2014, for a review). Such measures would be most appropriate because of Indonesia’s multicultur- ality and because Al-Qur’an is the central religious text of Islam that acts as a guide for all Muslims. One of the new Muslim religiosity measures is the Muslim Daily Religiosity Assessment Scale (MUDRAS) developed by Olufadi (2017).
The MUDRAS was developed based on Al-Qur’an as the central religious text of Islam and as a guide for all Muslims, tofill the gap related to limited references in the literature directed toward assessing Muslims’ daily actions and behaviours as advised in the Qur’an and the teachings of the Prophet Muhammad (Olufadi, 2017). Because the MUDRAS indicators were developed from the Holy Qur’an and the Hadith, the concept of Sunnah’ was included in this instrument. Another unique feature of the MUDRAS compared to other measures is that it covers behaviour and religious practices that are performed on a daily basis.
From a methodological perspective, in developing the MUDRAS, Olufadi (2017) employed exploratory and confirmatory factor analysis (EFA and CFA, respectively) to vali- date the construct. To date, in addition to CFA, there are modern latent trait models such as item response theory and Rasch models (e.g., Rasch, 1960; Samejima, 1969). Unlike factor analysis based methods, Rasch models have unique features of specific objectivity, parameter separation, and sufficiency (Wright & Masters,1982; Wright & Stone,1999). This feature means that a person’s trait level (e.g., religiosity) and item parameters can be sep- arated. Thus, it is possible to estimate a person’s level of the latent construct free of the distribution of the individual items and to estimate an item’s difficulty level free from the distribution of persons used in the sample (Andrich, 2010; DiStefano et al., 2019), and allows nonspecialists to use raw scores of the Indonesian MUDRAS. A unique feature of Rasch models is also highly related to cultural generalisability criteria (see Abu-Raiya & Hill, 2014; Hill, 2013), since these models have long been known as
“sample-free item analysis” (Rasch,1966; Wright & Panchapakesan,1969).
In thefield of psychology of religion and spirituality, the use of these latent trait models is recommended because they provide an invaluable resource for scale development.
These models, as advanced psychometric techniques, can provide more precise measures of religiosity (Schaap-Jonker et al.,2016), and provide a basis for potential refinement and adaptation of instruments for specific populations (Abernethy & Kim,2018). Rasch models can handle various item formats (e.g., dichotomous, polytomous, mixed, etc.).
The MUDRAS consists of 28 items with different numbers of response categories in some items. To analyse the MUDRAS, the Partial Credit Model (PCM; Masters,1982) can be used to handle Likert-type responses and can also accommodate these differences in response structure and produce results with an interval scale for person parameters (Wright & Masters, 1982). Therefore, PCM can contribute to validating the Indonesian MUDRAS, combined with CFA, which can provide a more detailed explanation of the psy- chometric characteristics of the measure, improving the reliability and validity criteria of this kind of measure (Abu-Raiya & Hill, 2014; Hill,2013). Additionally, this research can provide an example of the use of such data analysis methods when a scale has various numbers of response categories.
This article contributes to religiosity research in the following ways: (1) construct vali- dation of the MUDRAS for Indonesian samples in a multicultural context in Muslim majority country, (2) thefit of the MUDRAS items to the Rasch measurement model; and (3) the use of PCM to analyse an instrument with different numbers of response categories.
Adaptation of the Muslim Daily Religiosity Assessment Scale (MUDRAS) The MUDRAS was developed by Olufadi (2017); it contains 28 items and has three aspects, namely: sinful acts, recommended acts, and engaging in bodily worship of God. According to
the developers of the scale, only 21 items are included in the data analysis (sinful acts:
items 15, 18–21, 23–26, and 28; recommended acts: items 5–11; engaging in bodily worship of god: items 1–4). The MUDRAS was adapted into the Indonesian language through a process that complied with the standards set by the International Test Commis- sion Guidelines for Test Adaptation (International Test Commission, 2018). The original English version of the MUDRAS used in this study was translated into Bahasa Indonesian by two qualified translators from the Centre for Language Development who are Indone- sian and lecturers at Syarif Hidayatullah State Islamic University Jakarta. They arefluent in English and have doctoral degrees from Dutch and US universities.
Methods Participants
The sample of this study comprised 766 Indonesian Muslim university students (638 females, 128 males) using a nonprobability sampling technique. The sample were under- graduate students in various faculties of seven universities in Indonesia. The universities included six State Islamic Universities, namely: State Islamic University of North Sumatera, Medan (N = 91), Raden Fatah State Islamic University, Palembang (N = 93), Syarif Hidayatul- lah State Islamic University, Jakarta (N = 216), Maulana Malik Ibrahim State Islamic Univer- sity, Malang (N = 88), Sunan Ampel State Islamic University, Surabaya (N = 104), Alauddin State Islamic University, Makassar (N = 85), and one private Islamic university, namely Muhammadiyah University of Yogyakarta (N = 89).
The mean age of the sample was 20.01 (SD = 1.4), with a range of 17–24 years. The per- centage of participants within the four age bands of 17–18, 19–20, 21–22, and 23–24 was 12.9%, 51.3%, 31.7%, and 4.0%, respectively. The questionnaires were in paper-and-pencil format. Participation was voluntary and the purpose of the study was stated in a letter that accompanied the questionnaires. Participating persons were required to sign the informed consent form, which was also attached to the questionnaire.
Rasch model
The Rasch model (Rasch,1960) has revolutionised psychometrics (Mair,2018). This model allows measurement of persons and items on the same scale with equal interval properties of the scale and resulting linear measures (Wright & Stone,1999). When data arefitted to this model, item parameters can be estimated independently of the characteristics of the calibrating sample and person parameters can be freed from the difficulties of the items taken (Masters, 1982; Rasch,1966). Rasch models compute the probability of a certain response to each item given the level of the latent construct the individual possesses (i.e., the level of Muslim daily religiosity) and the relevant item’s difficulty of endorsement (DiStefano et al.,2019).
The PCM (Masters,1982) is a polytomous item response model belonging to the Rasch family that assumes ordered response categories as they exist in questionnaires, using uni- dimensional rating scales, which allow the number of response categories in each item to vary (de Ayala,2009; Embretson & Reise,2000). It follows that the PCM contains m (m + 1 being the number of response categories) threshold parameters. Each threshold
parameter marks a category intersection (Masters,1982). Threshold sometimes refers to
“step difficulty” or “step parameter” and illustrates the point on the latent trait continuum (e.g., level of Muslim religiosity) where a response in category k becomes more likely than a response in category k–1 (de Ayala,2009). The PCM provides scores for items, persons, and step parameters on a logit scale.
To implement a Rasch model, there are several assumptions that need to be fulfilled, namely: (1) unidimensionality of the latent trait, and (2) local independence (Embretson
& Reise,2000). To check the unidimensionality assumption, CFA was used and we also used Rasch Principal Component Analysis of Residuals (PCAR; Smith, 2002) to confirm the factor structure of the Indonesian MUDRAS. To check the local independence assump- tion, the Q3statistic was used (Yen,1984). After the assumptions were fulfilled, PCM was performed.
To check whether an itemfit the PCM, fit statistics can be used; two popular statistical tests are infit mean square (MNSQ) and outfit MNSQ, which describe the fit of the data to the PCM. The infit statistic places greater emphasis on unexpected responses that are close to the people and item location, and outfit is sensitive to unexpected responses that are far from the location (Bond & Fox,2015). The infit and outfit values are used to identify poten- tial unexpected response patterns. The expected value of infit or outfit for each item is 1.0, with a range of acceptable values ranging from .5 to 1.5. Values outside this boundary indi- cate a lack offit between items and models (DiStefano et al.,2019). In this study, we used the WINSTEPS program using Joint Maximum Likelihood Estimation to estimate item and person parameters of the Rasch model. To perform confirmatory factor analysis, we used the Mplus 8.4 program using a robust maximum likelihood (MLR) estimation.
Results
Factor structure
Factor analysis is commonly used to investigate whether item responses are unidimen- sional as required by Rasch analysis (Cook et al.,2009). In using CFA, we used several stat- istics and fit indices, namely, the root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker–Lewis index (TLI), and standardised root-mean- square residual (SRMR). Based on published criteria (Hu & Bentler,1999; Wang & Wang, 2019), the following standards for goodfit were used: CFI > .95, TLI > .95, RMSEA < .05, and SRMR < .08.
Before applying CFA, we excluded item 25 (“gambling”) because all of the respondents endorsed the lowest category (Never do this). Additionally, gambling is a crime in Indone- sia, especially for Muslim university students. The results of CFA, using MLR estimation, confirmed the second order factor model, in line with the original structure of the scale (see Olufadi,2017), because the values of the indices were above the acceptable threshold [χ2 (167) = 284.032, p < .001; RMSEA = .030 (90% CI = .024–.036), CFI = .983, TLI = .981, SRMR = .023], compared to the unidimensional model [χ2 (170) = 316.949, p < .001;
RMSEA = .034 (90% CI = .028–.039), CFI = .978, TLI = .976, SRMR = .023] and a 3-uncorre- lated-factors model [χ2(170) = 2427.628, p < .001; RMSEA = .132 (90% CI = .127–.136), CFI
= .669, TLI = .631, SRMR = .345]. Based on RMSEA, CFI, TLI, and SRMR, the results indicated that the model provided satisfactory representations of the underlying structure of the
Indonesian MUDRAS construct. All items loaded significantly (ranging from .535 to .817) in relation to eachfirst order factor, at a p < .01 significance level.
Unidimensionality
In testing the unidimensionality assumption of the Indonesian MUDRAS, besides using CFA, PCAR was performed (Chou & Wang, 2010). The results of this analysis confirmed that the PCM assumption of unidimensionality was met and that further analysis was worthwhile. According to PCAR, it can be concluded that a test only measures a dimen- sion when the minimum variance explained by the measure is > 50% (Linacre, 2018).
The PCAR showed unidimensionality, as values above 61.7% (eigenvalue of 32.2) of the variance explained by the measure were found. The measurement model of the MUDRAS proved to be unidimensional in line with second-order unidimensional factor structure from CFA.
Local independence
The Rasch model assumption of local independence requires that any set of items should not share any meaningful correlation, once the latent variable is accounted for (Edwards et al.,2018). After the assumption of unidimensionality was shown to have been met, the assumption of local independence was tested using the Q3 statistic (Yen, 1984). When using Q3statistic index criteria, in which it is specified that the raw residual correlation between pairs of items is never >.10 (Marais & Andrich,2008), no items were found to have local dependence. The items that had the highest raw residual correlations had nega- tive signs and no positive residual correlation. In other words, the assumption of local inde- pendence in this study was met.
PCM results: item measure,fit statistics, and step parameter
Table 1contains estimation results and thefit index model from each item of the Indone- sian version of the MUDRAS. As seen in the table, all MUDRAS items had infit and outfit statistics within an acceptable value (.5–1.5). No misfitting items were found and this means that the Indonesian version of the MUDRAS itemsfit with the Rasch PCM.
The estimates of item difficulty were between −1.36 and 1.51 on the logit scale. Based on the item discrimination index, which is analogous to classical test theory (item to-total- correlation), all the MUDRAS items have high discrimination values in a positive direction, with no values below .30 or negative values. This indicates that all items function well to distinguish persons with high versus low levels of religiosity. For each item, we examined the step parameter of category endorsements, and the statistics of each response for the items. All items, except item 8, followed the step ordering requirement. We found Item 8 (Step 1 =−.33, Step 2 = −.65, Step 3 = .98) experienced threshold disordering as the thresholds were not ordered from lowest to highest. However, none of the infit and outfit statistics for response categories were greater than 2. This finding indicated that col- lapsing categories was not necessary because the disordered threshold stillfit and did not violate the Rasch model (Linacre,2010;2018). Based on this information, we concluded that, in general, the MUDRAS itemsfit the Rasch PCM model.
Reliability
Wright and Masters (1982) developed reliability measures based on the Rasch measure- ment model, which have a different concept from classical test theory (e.g., Cronbach’s alpha). Reliability is estimated both for persons and items, by means of Person Separation Reliability (PSR). This is an estimate of how well this instrument can distinguish respon- dents on the measured variable. In parallel, Item Separation Reliability (ISR) is an indication of how well items are separated by the persons taking the test (Wright & Stone,1999). The cutoff of separation reliabilities is >.80 (Bond & Fox, 2015). The PSR of the Indonesian version of MUDRAS was .92, and the ISR was .99. The PSR and ISR were higher than the predefined criteria. We also computed Cronbach’s alpha, which was .93, which is higher than the Cronbach’s alpha of the original version (alpha = .89) (see Olufadi, 2017). Both alphas exceed the .70 cutoff value (Nunnally, 1978), indicating that the Indonesian version of the MUDRAS has excellent internal consistency.
Wright Map
The Wright Map, coined by Wilson and Draney (2002), is a map showing person measures and item calibration using the same scale. In the map, the overall results between persons and items can be compared easily. The Wright Map depicting the results of the Indonesian version of MUDRAS is shown inFigure 1.
FromFigure 1, it is clear that the least endorsed item was 28:“Mengganggu atau mel- anggar batas privasi atau ketentraman orang lain tanpa izin, seperti: memasuki rumah orang lain tanpa izin, dan lain sebagainya (Encroaching on others’ privacy (e.g., their houses, eavesdropping on their private conversations, etc.) without permission)”. In contrast, the most endorsed item was 11: “Ikhlas memohon ampunan-nya, dengan tidak mengulangi kesalahan atau dosa yang sama (Turn to God with sincere repentance, i.e., without return- ing to the sin)”. The mean of Muslim students’ daily religiosity of persons was 1.32 Table 1.Rasch item statistics and step parameter of the MUDRAS items: Item measure order.
Item Measure Infit Outfit PTMEA Step 1 Step 2 Step 3 Step 4 Step 5
Item-28 1.51 .89 .88 .76 −.51 −.31 .82
Item-18 1.01 .93 .92 .75 −1.04 .38 .66
Item-20 .99 1.31 1.32 .57 −1.48 −.79 2.27
Item-15 .98 .85 .81 .77 −.97 .03 .93
Item-9 .68 1.01 1.00 .69 −1.56 −.17 1.72
Item 2 .65 .82 .83 .81 −1.43 −.06 −.70 .15 2.04
Item-3 .52 .73 .75 .84 −1.98 −1.31 .70 .63 1.96
Item-24 .34 .83 .81 .76 −1.48 .46 1.02
Item-4 .30 .81 .82 .81 −1.49 −1.09 −.47 1.12 1.93
Item-26 .18 .96 .95 .66 −2.42 −.21 2.63
Item-10 −.09 1.15 1.20 .63 −1.36 .13 1.23
Item-7 −.19 1.11 1.17 .61 −2.11 .03 2.08
Item-19 −.47 1.11 1.15 .61 −1.14 −.23 1.37
Item-21 −.64 .96 .94 .64 −1.07 −.28 1.34
Item-5 −.69 1.09 1.14 .59 −.84 −.05 .89
Item-23 −.85 .95 .80 .65 −1.51 .74 .78
Item-8 −.89 1.06 .96 .57 −.33 −.65* .98
Item-6 −.93 1.08 .95 .58 −.81 .13 .68
Item-1 −1.06 1.19 1.15 .55 −1.41 .12 1.29
Item-11 −1.36 1.06 .78 .54 −.43 −.28 .71
Note: *Indicates disordered category.
Figure 1. Wright Map of MUDRAS representing direct comparsion of person dispersion and item distribution.
[standard deviation (SD) = 1.42], suggesting that the average Muslim student’s daily religi- osity was higher than the average level of item difficulty of the MUDRAS (zero). Further- more, the person distribution spread ranged from −2.80 to –4.84, which exceeded the item difficulty range (−1.36–1.51).
Discussion
The Indonesian MUDRAS was investigated using Rasch modelling with a PCM, resulting in a detailed item-level analysis as an addition to CFAfindings as a method for confirming factor structure. CFA results indicate that the Indonesian version of the MUDRAS has a second-order factor model, which is in line with the original factor structure (Olufadi, 2017). With this factor structure, users can have four-factor scores, which comprise one score for overall Muslim religiosity constructs as a higher-order factor, and three scores for each aspect of the MUDRAS (sinful acts, recommended acts, and engaging in bodily worship of God). We also found that a unidimensional CFA model had acceptable indices of goodfit.
In using PCM, we found that the unidimensionality and local independence assump- tions were fulfilled. All items of the Indonesian version of the MUDRAS fit very well with the Rasch PCM. All infit and outfit statistics were within acceptable criteria and all item had a high item discrimination index, indicating that the items were well-functioning.
These findings also pointed out a good construct validity evidence of Indonesian MUDRAS. Thesefindings allow users of the Indonesian version of the MUDRAS to report total scores and each aspect score based on the original scoring manual (see Olufadi, 2017).
Reliability coefficients from Rasch analysis indicated that the Indonesian version of the MUDRAS had high internal consistency (PSR = .92); thesefindings are in line with Cron- bach’s alpha of .93, which was higher than the original MUDRAS with an alpha of .89 (Olufadi,2017). Using criteria proposed by Hill (2013) and Abu-Raiya and Hill (2014), the Indonesian version of the MUDRAS was shown to have strong psychometric characteristics in terms of validity and reliability as a measure of Muslim religiosity, which also provide an alternative method to test them.
Regarding item content, the Rasch analysisfindings are interesting compared to CFA.
We identified the three most easily endorsed items that reflect Indonesian Muslim religi- osity. They are item-11 (“Turn to God with sincere repentance”), item-1 (“Aside from the recitations of the Quran during the five daily Obligatory prayers, how many times did you read the Quran today?”), and item-6 (“How many times did you spend anything on charity today?”). For item-11, which is related to “repentance”, findings from previous studies show that repentance means avoiding sins; there are debates about whether repentance is a traditional or modern concept (Fakhri & Nejad, 2013) From examining the Indonesian version of the MUDRAS, we find that this behaviour is “easiest” for the modern generation of Indonesian Muslim students.
With regard to item-1 (“How many times did you read the Quran today?”), the results of this study are fascinating and are characteristic of research samples from Indonesia. That is, one aspect of religiosity that the majority of Indonesian Muslims engage in is reading the Qur’an. For them, reading the Qur’an is part of their daily routine. No day passes without reading the Qur’an. One reason is that they believe that the Qur’an is a source of guidance
from Allah, and that reading the Qur’an is a psychological therapy that enables the reader to have peace of mind and tranquility. Thisfinding is very reasonable because, in Indone- sia, reading the Qur’an is taught from early childhood education to college, both through formal and non-formal education.
Regarding item-6,“charity”, we found this to be interesting because the behaviour is not obligatory as a Sunnah’. Thus it can be argued that the Indonesia Muslim population believes that Islamic charity, which is conceptualised as a way to gain wealth in this life, as it grounded in the belief that God will give back (Kailani & Slama,2020). Charity is also con- sidered a noble act in Islam, as reflected in the two Islamic foundational texts, the Qur’an and Hadith (Husein & Slama,2018), which is in line with the development of the MUDRAS (Olufadi,2017). For Indonesians, this behaviour is also related to social welfare and social justice (Fauzia,2017; Latief,2012). From the Indonesian version of MUDRAS, we know that this phenomenon also occurred in our sample, as this behaviour was“easy” for Muslim stu- dents. From these findings, we think that “charity” can be done not only by “wealthy”
people but also by anyone, within their means.
Conversely, we found the most challenging items to endorse were item-28 (“Encroach- ing on others’ privacy without permission”), item-18 (“Use intoxicants like alcohol whether drinking, selling, etc.”), item-20 (“Consult with soothsayers”). These findings are not surpris- ing, because as we expected, two of the most challenging items contain behaviour that are crimes in Indonesia (items 28 and 18), and since all respondents were university students, those two behaviours would rarely be endorsed in this sample. Regarding item-28, a pre- vious study used Qur’anic verses and Hadith with the same things used in the MUDRAS. In item-28, they found that this behaviour was worst in the context of digital media and tech- nology (e.g., social media or internet) (Lubis & Kartiwi,2013), and such behaviours are not covered in the Indonesian MUDRAS.
Regarding item-18 (“drinking alcohol”), drinking is an integral part of the indigenous culture in many local communities across Indonesia, and it often plays a significant role in social gatherings and is legal in Indonesia for people over 21-years old, except for one province (Muthia,2018). However, this behaviour was rarely endorsed by Indonesian Muslim university students samples who completed the MUDRAS. As a recommendation, previous studies have stated that less religious and less educated people should be con- sidered (Abu-Raiya et al.,2008), in addition to university students who are well-educated and studying in the large Islamic educational systems in Indonesia.
The results for Item-20 were interesting; the term“soothsayers” was translated as dukun (Choi,1996), which an ambiguous term and it is unclear which of its many meanings would be applicable (see Nourse,2013). Although Indonesia is referred to as a country of“mysti- cism” (Choi, 1996), soothsayers only exist in legends or myths rather than in real life, although the term may be understood to signify indigenous, traditional, and animist prac- tices (Geertz, 1976; Nourse, 2013), especially for young Islamic university students.
However, for Indonesians, the term “paranormal” is more common among urban popu- lations (Schlehe et al.,2013). We could notfind an “appropriate” term to use in the adap- tation process of the MUDRAS.
Based on the results, we also found an enormous potential use of the MUDRAS in regard to the development of new data analysis methods. As the MUDRAS assesses behav- iour that is performed on a daily basis, it can be a“bridge” to newly developing techniques that cover intensive longitudinal data (ILD; data with many measurements over time) (e.g.,
Dynamic Structural Equation Modelling; Asparouhov et al.,2018), rather than a longitudi- nal design, which takes a long time. In other words, we believe MUDRAS is a potential tool for exploring the dynamic process of Muslim religiosity, that is suitable for use as intensive longitudinal data in religious studies. This kind of research can occur following the suggestion about the use of longitudinal designs to learn more about Muslim reli- giosity or in relation to other variables such as well-being (Abdel-Khalek, 2011; Abu- Raiya et al.,2008).
Another potential use of the Indonesian version of the MUDRAS is highly related to the Indonesian culture, as Indonesia has an extensive Islamic higher educational system (e.g., State Islamic University and Muhammadiyah University), which were covered in this study.
We realised that Al-Qur’an (e.g., exegesis and reciting the Qur’an) and Hadith are included in the curriculum, for all majors and not only religious studies, and there are many experts in thisfield. That is why most of the few internationally indexed journals in Indonesia are about religious studies (e.g., Studia Islamika, Indonesian Journal of Islam and Muslim Societies, Journal of Indonesian Islam). Still, the use of methodology from social sciences is minimal; this article can make contributions to researchers of religious/Islamic studies in Indonesia about measurement derived from Al-Qur’an and Hadith. We also hope the Indonesian version of the MUDRAS can be analysed based on exegesis concerning the Qur’an and even their relation to broader Islamic culture in Indonesia.
Thus, we recognise that the present study has few limitations. First, while the goal was to assess the psychometric properties of the MUDRAS in Indonesian samples, we did not include another measure to be compared with the Indonesian version of the MUDRAS, such as an instrument derived from general concepts of religiosity (e.g., Cahyaningrum, 2018; Purnomo & Suryadi,2017). We believe that assessing the relationship of the Indone- sian version of the MUDRAS with another instrument can enhance the concurrent validity of aspects of the former measure. Second, although the sampled individuals were repre- sentative of the college student populations from which they were selected, the use of a nonprobability sampling approach may not provide an accurate representation of univer- sity students more broadly. The students were from Islamic universities only; hence, com- parison with students from public universities can enhance the generalisability of Indonesian samples using the Indonesian version of the MUDRAS. Future research should address these issues.
Conclusion
This article shows the value of analyzing a questionnaire that assess an Islamic religiosity construct by means of Rasch modelling. This study also provides additional psychometric information that was not provided with the original scale development of the MUDRAS, leading to more insight into the way in which the scales and items are used among samples from different cultures. In summary, the Indonesian version of the MUDRAS has adequate psychometric characteristics. More research with these adapted instruments is needed, especially on its relationship to other psychological constructs.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Ethics approval
Ethical approval was obtained from The Institute for Research and Community Service (LP2M), Syarif Hidayatullah State Islamic University, Jakarta, Indonesia. Participants con- sented to participate in the study and consented to the results being published according to the ethical approval.
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Appendix
Indonesian version of the MUDRAS
INSTRUKSI: Selain dari pertanyaan 1 sampai dengan 6, silahkan jawab pernyataan di bawah ini dengan angka terkait berapa kali anda melakukan atau terlibat dalam bentuk perilaku yang ada dalam pernyataan di bawah ini dengan menggunakan petunjuk sebagai berikut:
(1) Selain Al-Qur’an yang dibaca ketika anda melakukan shalat, jika di rata-ratakan dalam seminggu terakhir, berapa kali anda membaca Al-Qur’an dalam satu hari?
a Saya tidak bisa membaca Al-Qur’an
b Saya bisa membaca Al-Qur’an tetapi belakangan ini saya jarang membacanya c Saya membaca Al-Qur’an setiap hari
d Saya membaca Al-Qur’an dan terjemahannya, serta memahami isi atau makna dari ayat Al- Qur’an yang saya baca
(2) Berapa kali anda melaksanakan shalat setiap harinya?
a 0, b. 1, c. 2, d. 3, e. 4, f. 5
(3) Terdapat waktu tertentu yang telah ditetapkan untuk melaksanakan shalat 5 waktu, dan waktu yang paling baik untuk melaksanakan shalat adalah pada saat awal waktu shalat tersebut.
Berapa kali dalam sehari anda melaksanakan shalat tepat pada saat awal waktu shalat?
a 0, b. 1, c. 2, d. 3, e. 4, f. 5
(4) Allah telah memerintahkan kita untuk senantiasa meminta kepada-Nya terkait berbagai macam hal, baik itu yang berhubungan dengan dunia ataupun akhirat, dan Allah pun berjanju akan mengabulkan apa yang kita minta pada-Nya. Kemudian Allah juga menyebutkan bahwasanya, barangsiapa yang lebih mengutamakan kepentingannya dibanding Allah, maka tempatnya adalah di neraka. Berapa kali dalam kehidupan sehari-hari anda menempatkan Allah sebagai Yang Utama dibandingkan kepentingan anda?
a 0, b. 1, c. 2, d. 3, e. 4, f. lebih dari 5
(5) Terdapat istilah Nawaafil atau shalat sebelum dan sesudah shalat 5 waktu, yang sangat disaran- kan dan dicontohkan oleh Nabi Muhammad SAW. Berapa kali anda sudah melaksanakan Nawaafil tersebut dalam kegiatan sehari-hari anda?
a Tidak ada satu Nawaafil pun yang saya lakukan dalam sehari ini b Hanya satu Nawaafil yang saya lakukan dalam sehari ini
c 2-3 Nawaafil yang saya lakukan dalam sehari ini d Lebih dari 3 Nawaafil saya lakukan dalam sehari ini (6) Sudah berapa kali anda bersedekah dalam hari-hari anda?
Contohnya: memberikan uang sedekah, memberi makanan pada tetangga atau teman sejawat, mengajarkan atau berbagi ilmu yang anda ketahui kepada orang lain dan lain sebagainya.
a Saya tidak melakukan sedekah apapun belakangan ini b Hanya satu kali saya bersedekah dalam setiap hari
c 2-4 kali saya bersedekah dalam setiap hari
d Lebih dari 4 kali sedekah saya lakukan dalam sehari.
INSTRUKSI: Setelah selesai menjawab pertanyaan 1 sampai dengan 6, silahkan berikan penilaian ter- hadap pernyataan di bawah ini dengan tanda silang (×) pada kolom yang berisi opsi (Tidak pernah;
Pernah satu kali; Dua sampai tiga kali; Lebih dari tiga kali) terkait berapa kali anda melakukan atau terlibat dalam bentuk perilaku yang ada dalam pernyataan di bawah ini.
No. Pernyataan
7. Berkata jujur dalam keadaan apapun 8. Berbakti kepada orang tua 9. Menepati janji
10. Mendoakan kedua orang tua
11. Ikhlas memohon ampunan-Nya, dengan tidak mengulangi kesalahan atau dosa yang sama 12. Mengajak orang lain untuk berbuat kebaikan
13. Lebih mendekatkan diri kepada-Nya 14. Membunuh seseorang tanpa sebab
15. Melakukan segala macam tindak kecurangan atau berbuat tidak adil dalam berbagai macam bentuj, seperti:
mengambil harta milik orang lain yang bukan haknya, mencontek saat ujian dan lain sebagainya 16. Mendekati atau melakukan zina
17. Memberikan keterangan palsu
18. Mengkonsumsi barang haram, seperti minuman beralkohol, baik itu dalam bentuk meminum, menjual dan lain sebagainya.
19. Melakukan praktek Riba’ atau memakan harta Riba’ (melipat gandakan uang atau bunga bank) 20. Mempercayai ramalan
21. Memfitnah ataupun mendengar fitnah 22. Mengkhianati amanat yang telah dipercayakan
23. Berlaku mubazir atau berlebihan, baik itu dalam bentuk makanan ataupun uang 24. Berprasangka buruk kepada orang lain, seperti curiga
25. Berjudi
26. Memberikan sumpah palsu atas nama Allah 27. Memberikan sumpah kepada orang lain
28. Mengganggu atau melanggar batas privasi atau ketentraman orang lain tanpa izin, seperti: memasuki rumah orang lain tanpa izin, dan lain sebagainya
Prosedur skoring MUDRAS
Tidak seluruh item dalam MUDRAS diikutkan dalam proses skoring. Peneliti diharapkan untuk berhati-hati dalam memastikan bahwa item yang diikutkan dalam perhitungan skor sudah tepat.
Aspek 1: Sinful acts—Item 15, 18, 19, 20, 21, 23, 24, 25, 26 dan 28
Untuk seluruh Item, berilah skor berdasarkan jawaban responden, apabila Lebih dari tiga kali = 0;
Dua sampai tiga kali = 1; Pernah satu kali melakukan = 2; Tidak pernah melakukan = 3.
Setelah skor didapat dari hasil penjumlahan, jika skor seseorang sebesar 0-5 maka diberi kode 0, jika 6-10 diberi kode 1, jika 11-15 diberi kode 2, jika 16-20 diberi kode 3, jika 21-25 diberi kode 4, dan jika 26-30 diberi kode 5. Kode tersebut menggambarkan skor aspek sinful acts.
Aspek 2: Recommended acts—Item-5 sampai Item-11
Untuk item 5 dan 6, jika responden menjawab (a) maka berilah skor 0, jika menjawab (b) berilah skor 1, jika menjawab (c) berilah skor 2, jika menjawab (d) berilah skor 3.
Untuk item-7 hingga item-11, jika responden memilih jawaban lebih dari tiga kali = 0; Dua sampai tiga kali = 1; Pernah satu kali melakukan = 2; Tidak pernah melakukan = 3.
Setelah skor total didapat dari hasil penjumlahan, jika skor seseorang sebesar 0-5 maka diberi kode 0, jika 6-10 diberi kode 1, jika 11-15 diberi kode 2, jika lebih besar ataupun sama dengan 16 diberi kode 3. Kode tersebut menggambarkan skor aspek recommended acts.
Aspek 3: Engaging in bodily worship of Allah—Item-1 sampai Item-4
Untuk Item-1, jika responden menjawab (a) maka berilah skor 0, jika menjawab (b) berilah skor 1, jika menjawab (c) berilah skor 2, jika menjawab (d) berilah skor 3.
Untuk Item-2 hingga Item-4, jika responden menjawab (a) maka berilah skor 0, jika menjawab (b) berilah skor 1, jika menjawab (c) berilah skor 2, jika menjawab (d) berilah skor 3, jika menjawab (e) berilah skor 4, dan jika menjawab (f) berilah skor 5.
Setelah skor total didapat dari hasil penjumlahan, jika skor seseorang sebesar 0-6 maka diberi kode 0, jika 7-12 diberi kode 1, jika lebih besar ataupun sama dengan 13 diberi kode 2. Kode tersebut menggambarkan skor aspek engaging in bodily worship of Allah.
Untuk mendapatkan skor akhir dari MUDRAS, jumlahkanlah skor aspek sinful acts, skor aspek rec- ommended acts dan skor aspek engaging in bodily worship of Allah. Akan dihasilkan satu skor yang menggambarkan religiusitas untuk masing-masing responden.
