Introduction
Marriage for Muslims is not only a religious but also social activity because Islamic marriage contains a civil contract (mu‘amalah) and ritual acts (ibadah) (Fauzi, 2019). Moreover, the believers may also perceive that marrying off their children is their duty as parents and the sunnah of the Prophet Muhammad (Susilo et al., 2021). This phenomenon can also be found in Indonesia, one of the biggest countries with a Muslim community (Hadiati et al., 2022). The marriage process and registration in Indonesia are different between Muslims and citizens of other religions as described in the previous studies, which interested readers can visit, as these differences are not discussed further in this study (Fauzi, 2019; Grijns & Horii, 2018; Julianto et al., 2022).
However, the readiness for marriage in Islam is determined by the signs of puberty (aqil baligh), not by particular age (Rofiah et al., 2022; Samuri et al., 2022b). Therefore, once the individual shows physical change because of puberty (having sex dreams for men and menarche for women), the person is perceived as an adult and deemed ready for marriage. This understanding is mainly coming from the interpretation of the hadith of the Prophet Muhammad married Aishah [Aisyah] when she was 6 years old (Rofiah et al., 2022; Samuri et al., 2022a).
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Consequently, the number of child marriages in Islamic communities or countries is relatively high. In Indonesia, it was found that one in nine girls had married in 2018, which made Indonesia one of the highest child marriage numbers in the world (Subchi et al., 2021; Susilo et al., 2021). In particular, the impact of religion on child marriage was found to be stronger in the villages than in the urban or city areas through the patriarchy and religious leaders’ influence (Hadiati et al., 2022; Putri et al., 2021; Ratnaningsih et al., 2022; Rofiah et al., 2022; Sutriyatmi et al., 2023; Widyastari et al., 2020). Readers are encouraged to read an ethnographic report by Platt (2017) if they are interested in understanding more about the marital experiences of Muslim Indonesian women from an anthropological perspective.
The child marriage phenomenon was also found in the neighboring Islamic country, Malaysia, where child marriage among Muslims may be allowed through the Sharia court’s permission (Samuri et al., 2022a). Moreover, child marriages were also found to be prevalent in Muslim communities or countries worldwide (Samuri et al., 2022b). For example, Muslim women in Bangladesh were nearly two times more likely to be married at an early age compared to non-Muslim women (Saleheen et al., 2021). It was also found that child marriage was more prevalent among Muslim women in six South Asian countries (Afghanistan, Bangladesh, India, Maldives, Nepal, and Pakistan) compared to non-Muslim women in those countries (Kamal & Ulas, 2021).
However, the use of hadith in justifying child marriage has been challenged by other Islamic scholars (Adawiyah et al., 2022; Rofiah et al., 2022). For example, scholars of the Kongres Ulama Perempuan Indonesia (KUPI, the Indonesian Women's Ulama [Scholars] Congress) rely on the Qur’an (al-Baqarah, 2: 195) when arguing that child marriage should be prevented because it causes multiple harms (madharat), particularly for the children (Satibi et al., 2023). A similar movement was also found in Malaysia, where some scholars argued that the hadith of Aishah should not be interpreted literally and the forced application of this hadith in the current lifetime could be only to fulfil sexual desire (Samuri et al., 2022a).
On the other hand, the minimum legal age limit for brides and grooms in Indonesia is 19 years after a long battle of 45 years to increase the brides’ minimum age limit from 16 years (Grijns & Horii, 2018; Julianto et al., 2022). As consistently found in previous studies, child marriage negatively affects the children who are involved because it could violate their basic rights (Grijns & Horii, 2018). In particular, girls would be affected more than boys by gender-based violence, cessation of education, teenage pregnancy, and maternal mortality (Miedema et al., 2020; Rofiah et al., 2022).
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However, despite the minimum age for the brides has been raised, Muslim people in Indonesia still could apply for a marriage dispensation if the broom and/or bride are under 19 years by submitting their applications to the [Islamic] Religious Court (Pengadilan Agama [Islam]) before the couple can do their marriage at [Islamic] Religious Affairs Office (Kantor Urusan Agama/KUA [Islam]) (Grijns & Horii, 2018). A previous study in Palu Religious Court from 2018 to 2020 found one of the primary factors of parents submitting underage marriage dispensation applications for their children was avoiding slander from the society (Marzuki et al., 2021). These parents were worried when seeing their children in a relationship and acting against the social norms.
The condition was worsened during the COVID-19 pandemic because the number of marriage dispensation applications steadily increased, which happened not only in Indonesia but globally (Alqahtani & Alqahtani, 2022; Arshad, 2020; Bachtiar et al., 2021; Julianto et al., 2022; Subchi et al., 2021). A study among Bangladeshi, Rohingya, Jordanians, and Syrians found that these refugee girls were having a higher risk to be married than local girls or the host community, which mainly because of the curbing policy and the impacted family’s economic situation (Baird et al., 2022). Furthermore, the United Nations International Children’s Emergency Fund (UNICEF) predicted that the COVID-19 pandemic will significantly add to the number of child marriages worldwide through education interruption, economic crisis, health care interruption, orphanages, and disruption to child marriage prevention programs (Alqahtani & Alqahtani, 2022; Kidman et al., 2022).
Therefore, this study aimed to investigate factors associated with the applications of child marriage dispensation submitted to the Religious Courts during the COVID-19 pandemic in Indonesia, particularly between 2019 and 2021. By understanding these factors, the stakeholders can design effective programs to slow down the child marriage numbers when entering the endemic period as was done in a previous study post-natural disaster (Dewi & Dartanto, 2019).
Methodology
This quantitative study utilized data from the Supreme Court of The Republic of Indonesia (Mahkamah Agung). In particular, for the main variable, we used the number of child marriage dispensation cases from 2019 to 2021 from 29 provincial [Islamic] Religious High Courts (Pengadilan Tinggi Agama/PTA [Islam]). Five provinces of total 34 provinces in Indonesia were not included in this study because they have no PTA, including Papua Barat/West Papua, Sulawesi Barat/West Sulawesi, Bali, Kepulauan Riau/Riau Islands, and Kalimantan Utara/North Kalimantan provinces. There is no PTA in these provinces might be because of the small numbers of Muslims or logistical issues (i.e., new province), which could be outliers for this study. The complete description from 34 provinces has been reported elsewhere (Julianto et al., 2022).
This study also used socioeconomic variables that were extracted from Badan Pusat Statistik/BPS (Central Agency on Statistics) and COVID-19-related variables from the COVID-19 task force. In addition, the divorce cases were also included where they were two types of divorce recorded by the [Islamic] Religious Courts: cerai talak (Arabic: talaq, means to release) and cerai gugat (sue, judicial divorce) (Nainggolan, 2022). Cerai talak is simply understood as a form of divorce under Islamic law initiated by the husband who repudiates the marriage [wife] by saying “talaq” three times and then proceed at the Religious Court. On the other hand, cerai gugat under Islamic law is basically understood as a form of divorce initiated by the wife who makes a petition to the Religious Court to be divorced from her husband. The summary of these variables is presented in Table 1 below.
Table 1
Description and source of variables included in the study
Variable | Description | Source |
|---|---|---|
Child marriage | The application numbers of child marriage dispensation in 2019, 2020, and 2021 | The Supreme Court of The Republic of Indonesia |
Poverty rate | The number of poor populations, which is defined as people with a monthly average per capita expenditure below the poverty line | |
Jobless rate | The percentage of open unemployment, including those who (1) are unemployed and looking for work; (2) do not have a job and are preparing a business; (3) do not have a job and are not looking for work, because they feel it is impossible to get a job; and (4) already have a job, but have not started working | |
Junior high school completion rate | The junior high school completion rate | |
Senior high school completion rate | The senior high school completion rate | Ditto |
Cerai talak | The total numbers of cerai talak applications | Collated from the BPS website at province level, for example, Central Java province: https://jateng.bps.go.id/statictable/2020/07/20/1880/jumlah-perceraian-menurut-faktor-dan-kabupaten-kota-di-provinsi-jawa-tengah-2019.html |
Cerai gugat | The total numbers of cerai gugat applications | Ditto |
COVID-19 positive cases | The numbers of COVID-19 confirmed cases | |
COVID-19 death cases | The numbers of deaths by COVID-19 | Ditto |
Data were first analyzed descriptively (i.e., mean [M] and standard deviation [SD]) for each year and the difference between 2021 and 2019 by calculating the change. Second, the differences between 2021 and 2019 were analyzed using the repeated measures analysis of variance (ANOVA, F) for all variables except two variables related to the COVID-19 pandemic (total positive cases and total death numbers), which were analyzed using the paired t-test (t). Third, the relationship between variables was analyzed using the Pearson product-moment correlation coefficient (r). Finally, hierarchical multiple regression (F)1 with entering method was used to determine the predictors of the number of child marriage dispensation cases in years 2019, 2020, and 2021; and the change from 2019 to 2021.
Variables were included in the regression based on the results of correlational tests and multicollinearity screenings that included poverty and jobless rate in Block 1, cerai talak and cerai gugat in Block 2, and COVID-19 positive cases and COVID-19 death cases (only in years 2020 and 2021) in Block 3. Standard coefficients (β) and confidence intervals (95% CI) were computed to compare the relative importance of each variable in the equation. for each possible. The R-squared (R2) and change of R-squared (Δ R2) were examined to determine the goodness of fit of a regression model. All analyses were conducted using Statistical Package for the Social Sciences (SPSS) version 28.
Results
New dispensation underage marriage applications (Table 2) from 29 provinces in 2019, 2020, and 2021 were 24,457 (M = 843, SD = 1519), 63,391 (M = 2186, SD = 4085), and 62,167 (M = 2144, SD = 4058), respectively. The repeated measures ANOVA (Greenhouse-Geisser) showed that the dispensation underage marriage application number was significantly different within 3 years, F(1.0, 28.6) =7.63, p = .01. The posthoc pairwise comparisons indicated that the differences were significant between year 2019 and 2020 (p = .03) as well as between year 2019 and 2021 (p = .03). On the other hand, the dispensation underage marriage applications between year 2020 and 2021 were not significantly different (p = .99). These dispensation application numbers in all 3 years were consistently to be found positively correlated with poverty rate, jobless rate, cerai talak, cerai gugat, COVID-19 positive cases, and COVID-19 death cases (Table 3). In addition, all negative correlations between the percentage of high school completion rate and the dispensation underage marriage applications in 2019, 2020, and 2021 were found to be non-significant.
Table 2
Underage marriage dispensation applications, socioeconomic variables, and COVID-19-related variables in 29 provinces (2019–2021)
No | Province | A | B | C | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I | II | III | IV | I | II | III | IV | I | II | III | IV | ||
1 | DI Aceh | 229 | 963 | 956 | 727 | 809,760 | 833,910 | 850,260 | 40,500 | 148,474 | 166,600 | 158,857 | 10,383 |
2 | Bangka Belitung | 159 | 265 | 261 | 102 | 67,370 | 72,050 | 69,700 | 2,330 | 26,063 | 38,756 | 37,176 | 11,113 |
3 | Banten | 192 | 504 | 357 | 165 | 641,420 | 857,640 | 852,280 | 210,860 | 489,825 | 661,061 | 562,310 | 72,485 |
4 | Bengkulu | 325 | 961 | 1,098 | 773 | 298,000 | 306,000 | 291,790 | -6,210 | 33,793 | 43,801 | 38,745 | 4,952 |
5 | Jawa Tengah | 5,451 | 13,683 | 14,073 | 8,622 | 3,679,400 | 4,119,930 | 3,934,010 | 254,610 | 818,276 | 1,214,342 | 1,128,223 | 309,947 |
6 | Kalimantan Tengah | 310 | 901 | 839 | 529 | 131,240 | 141,780 | 141,030 | 9,790 | 55,473 | 63,309 | 63,874 | 8,401 |
7 | Sulawesi Tengah | 286 | 600 | 462 | 176 | 404,030 | 403,740 | 381,210 | -22,820 | 46,993 | 59,381 | 59,371 | 12,378 |
8 | Jawa Timur | 6,167 | 17,576 | 17,567 | 11,400 | 4,056,000 | 4,585,970 | 4,259,600 | 203,600 | 835,130 | 1,301,145 | 1,281,395 | 446,265 |
9 | Kalimantan Timur | 538 | 1,255 | 1,195 | 657 | 220,910 | 243,990 | 233,130 | 12,220 | 106,960 | 124,884 | 126,186 | 19,226 |
10 | Nusa Tenggara Timur | 34 | 81 | 92 | 58 | 1,129,460 | 1,173,530 | 1,146,280 | 16,820 | 84,874 | 121,884 | 109,928 | 25,054 |
11 | Gorontalo | 388 | 918 | 1,090 | 702 | 184,710 | 185,310 | 184,600 | -110 | 22,382 | 25,410 | 17,959 | -4,423 |
12 | DKI Jakarta | 296 | 600 | 401 | 105 | 362,300 | 496,840 | 498,290 | 135,990 | 339,402 | 572,780 | 439,899 | 100,497 |
13 | Jambi | 301 | 1,016 | 1,021 | 720 | 273,370 | 288,100 | 279,860 | 6,490 | 71,212 | 93,990 | 93,754 | 22,542 |
14 | Lampung | 280 | 776 | 717 | 437 | 1,041,480 | 1,091,140 | 1,007,020 | -34,460 | 175,657 | 209,568 | 210,632 | 34,975 |
15 | Maluku | 17 | 56 | 69 | 52 | 319,510 | 322,400 | 295,970 | -23,540 | 54,400 | 63,489 | 59,589 | 5,189 |
16 | Sulawesi Utara | 289 | 890 | 909 | 620 | 188,600 | 195,850 | 186,550 | -2,050 | 73,413 | 90,248 | 85,540 | 12,127 |
17 | Sumatera Utara | 380 | 874 | 868 | 488 | 1,260,500 | 1,356,720 | 1273,070 | 12,570 | 399,262 | 507,805 | 475,156 | 75,894 |
18 | Papua | 67 | 167 | 184 | 117 | 900,950 | 912,230 | 944,490 | 43,540 | 65,143 | 75,658 | 64,996 | -147 |
19 | Riau | 385 | 1,059 | 1,053 | 668 | 483,920 | 491,220 | 496,660 | 12,740 | 180,661 | 203,837 | 145,669 | -34,992 |
20 | Sulawesi Tenggara | 146 | 378 | 343 | 197 | 299,970 | 317,320 | 323,360 | 23,390 | 46,017 | 61,860 | 54,134 | 8,117 |
21 | Kalimantan Selatan | 561 | 1,462 | 1,383 | 822 | 190,290 | 206,920 | 197,760 | 7,470 | 89,269 | 103,648 | 109,968 | 20,699 |
22 | Sulawesi Selatan | 2,224 | 4,197 | 4,289 | 2,065 | 759,580 | 800,240 | 765,460 | 5,880 | 196,779 | 269,817 | 252,349 | 55,570 |
23 | Sumatera Selatan | 618 | 1,498 | 1,626 | 1,008 | 1,067,160 | 1,119,650 | 1,116,610 | 49,450 | 190,204 | 238,363 | 219,199 | 28,995 |
24 | Jawa Barat | 3,106 | 8,530 | 7,054 | 3,948 | 3,375,890 | 4,188,520 | 4,004,860 | 628,970 | 1,929,515 | 2,533,076 | 2,430,147 | 500,632 |
25 | Kalimantan Barat | 506 | 1,253 | 1,216 | 710 | 370,470 | 370,710 | 354,000 | -16,470 | 111,257 | 151,561 | 153,307 | 42,050 |
26 | Nusa Tenggara Barat | 378 | 913 | 1,160 | 782 | 705,680 | 746,040 | 735,300 | 29,620 | 85,501 | 113,430 | 82,495 | -3,006 |
27 | Sumatera Barat | 340 | 1,031 | 1,077 | 737 | 343,090 | 364,790 | 339,930 | -3,160 | 144,349 | 190,609 | 179,948 | 35,599 |
28 | DI Yogyakarta | 468 | 947 | 756 | 288 | 440,890 | 503,140 | 474,490 | 33,600 | 71,482 | 101,846 | 106,432 | 34,950 |
29 | Maluku Utara | 16 | 37 | 51 | 35 | 87,180 | 87,520 | 81,180 | -6,000 | 27,874 | 29,997 | 28,133 | 259 |
Total | 24,457 | 63,391 | 62,167 | 37,710 | 24,093,130 | 26,783,200 | 25,718,750 | 1,625,620 | 6,919,640 | 9,432,155 | 8,775,371 | 1,855,731 | |
M (SD) | 843 (1,519) | 2,186 (4,085) | 2,144 (4,058) | 1,300 (2,555) | 830,797 (1,050,999) | 923,559 (1,220,348) | 886,853 (1,152,171) | 56,056 (131,727) | 238,608 (387,959) | 325,247 (532,812) | 302,599 (509,047) | 63,991 (128,387) | |
F/t (p) | 7.63 .01 | 6.56 .01 | 8.67 ** | - | |||||||||
df1, df2 | 1.0, 28.6 | 1.1, 31.5 | 1.1, 29.8 | ||||||||||
p I vs II | .03 | .04 | .01 | ||||||||||
p I vs III | .03 | .09 | .04 | ||||||||||
p II vs III | .99 | .04 | .01 |
No | Province | D | E | F | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I | II | III | IV | I | II | III | IV | I | II | III | IV | ||
1 | DI Aceh | 89.50 | 90.92 | 93.43 | 3.93 | 69.96 | 70.07 | 74.36 | 4.40 | 1,567 | 1,536 | 1,469 | -98 |
2 | Bangka Belitung | 77.96 | 81.91 | 80.99 | 3.03 | 53.84 | 56.74 | 63.98 | 10.14 | 593 | 553 | 577 | -16 |
3 | Banten | 87.40 | 86.70 | 90.63 | 3.23 | 56.94 | 64.24 | 66.90 | 9.96 | 3,186 | 3,121 | 3,323 | 137 |
4 | Bengkulu | 85.13 | 87.68 | 89.94 | 4.81 | 61.47 | 62.73 | 62.46 | 0.99 | 875 | 928 | 912 | 37 |
5 | Jawa Tengah | 85.47 | 89.00 | 88.44 | 2.97 | 49.79 | 55.82 | 59.9 | 10.11 | 21,202 | 19,244 | 18,799 | -2,403 |
6 | Kalimantan Tengah | 81.01 | 84.83 | 89.76 | 8.75 | 50.01 | 60.77 | 61.04 | 11.03 | 879 | 776 | 810 | -69 |
7 | Sulawesi Tengah | 82.23 | 82.79 | 85.42 | 3.19 | 52.00 | 57.68 | 61.16 | 9.16 | 839 | 907 | 940 | 101 |
8 | Jawa Timur | 86.21 | 89.98 | 90.30 | 4.09 | 57.74 | 63.53 | 66.33 | 8.59 | 27,277 | 25,000 | 25,110 | -2,167 |
9 | Kalimantan Timur | 86.98 | 92.40 | 95.34 | 8.36 | 64.74 | 71.63 | 74.26 | 9.52 | 2,278 | 1,964 | 1,996 | -282 |
10 | Nusa Tenggara Timur | 74.31 | 78.81 | 78.83 | 4.52 | 43.85 | 50.65 | 44.88 | 1.03 | 161 | 170 | 135 | -26 |
11 | Gorontalo | 80.60 | 80.10 | 81.22 | 0.62 | 50.87 | 55.35 | 53.73 | 2.86 | 512 | 476 | 524 | 12 |
12 | DKI Jakarta | 93.02 | 94.57 | 95.00 | 1.98 | 84.35 | 85.67 | 84.98 | 0.63 | 4,329 | 3,685 | 3,960 | -369 |
13 | Jambi | 84.40 | 86.31 | 89.00 | 4.60 | 56.87 | 63.66 | 64.51 | 7.64 | 1,109 | 1,066 | 1,147 | 38 |
14 | Lampung | 84.08 | 86.66 | 89.46 | 5.38 | 54.87 | 57.59 | 60.09 | 5.22 | 2,814 | 2,922 | 3,119 | 305 |
15 | Maluku | 88.43 | 88.04 | 93.08 | 4.65 | 67.82 | 70.55 | 68.12 | 0.30 | 192 | 198 | 212 | 20 |
16 | Sulawesi Utara | 85.67 | 86.69 | 91.05 | 5.38 | 67.58 | 73.79 | 68.56 | 0.98 | 424 | 486 | 440 | 16 |
17 | Sumatera Utara | 88.26 | 91.63 | 91.35 | 3.09 | 65.21 | 70.39 | 72.81 | 7.60 | 3,172 | 3,183 | 3,555 | 383 |
18 | Papua | 59.31 | 65.75 | 66.06 | 6.75 | 27.44 | 30.92 | 32.95 | 5.51 | 545 | 489 | 514 | -31 |
19 | Riau | 84.97 | 86.84 | 87.11 | 2.14 | 58.78 | 66.62 | 68.94 | 10.16 | 2,922 | 2,893 | 3,198 | 276 |
20 | Sulawesi Tenggara | 85.46 | 89.18 | 90.88 | 5.42 | 64.26 | 68.28 | 70.65 | 6.39 | 836 | 839 | 868 | 32 |
21 | Kalimantan Selatan | 82.77 | 82.48 | 84.06 | 1.29 | 59.52 | 63.05 | 63.59 | 4.07 | 1,766 | 1,520 | 1,543 | -223 |
22 | Sulawesi Selatan | 83.74 | 85.08 | 88.18 | 4.44 | 60.97 | 66.22 | 69.43 | 8.46 | 3,534 | 3,489 | 3,406 | -128 |
23 | Sumatera Selatan | 83.40 | 85.02 | 87.68 | 4.28 | 58.23 | 65.42 | 67.20 | 8.97 | 2,321 | 2,193 | 2,474 | 153 |
24 | Jawa Barat | 85.53 | 88.17 | 88.18 | 2.65 | 57.46 | 63.56 | 64.89 | 7.43 | 24,172 | 23,756 | 23,971 | -201 |
25 | Kalimantan Barat | 72.78 | 80.88 | 79.65 | 6.87 | 49.29 | 55.23 | 54.27 | 4.98 | 1,038 | 1,042 | 1,126 | 88 |
26 | Nusa Tenggara Barat | 88.64 | 89.91 | 92.19 | 3.55 | 57.60 | 64.66 | 65.71 | 8.11 | 2,034 | 2,048 | 2,040 | 6 |
27 | Sumatera Barat | 84.07 | 87.12 | 89.49 | 5.42 | 60.32 | 67.11 | 70.06 | 9.74 | 2,272 | 2,187 | 2372 | 100 |
28 | DI Yogyakarta | 92.34 | 92.36 | 94.94 | 2.60 | 84.54 | 87.99 | 90.12 | 5.58 | 1,529 | 1,447 | 1,467 | -62 |
29 | Maluku Utara | 84.07 | 87.12 | 89.49 | 7.86 | 59.13 | 66.52 | 66.95 | 7.82 | 358 | 351 | 391 | 33 |
Total | NA | NA | NA | NA | NA | NA | NA | NA | 114,736 | 108,469 | 110,398 | -4,338 | |
M (SD) | 83.72(6.46) | 86.17(5.48) | 87.97(6.07) | 4.34(2.01) | 58.81(10.92) | 64.02(10.36) | 65.27(10.62) | 6.46(3.35) | 3,956(7,137) | 3,740(6,674) | 3,807(6,662) | -150(614) | |
F/t (p) | 69.76*** | 85.15*** | 3.03.09 | ||||||||||
df1, df2 | 1.9, 54.8 | 1.7, 47.5 | 1.1, 30.4 | ||||||||||
p I vs II | *** | *** | |||||||||||
p I vs III | *** | *** | |||||||||||
p II vs III | *** | *** |
No | Province | G | H | I | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I | II | III | IV | I | II | III | IV | I | II | III | IV | ||
1 | DI Aceh | 4,515 | 4,547 | 4,972 | 457 | 0 | 8,752 | 29,684 | 29,684 | 0 | 358 | 1,708 | 1,708 |
2 | Bangka Belitung | 1,908 | 1,717 | 1,900 | -8 | 0 | 2,337 | 49,971 | 49,971 | 0 | 35 | 1,424 | 1,424 |
3 | Banten | 11,689 | 11,235 | 12,346 | 657 | 0 | 18,154 | 114,787 | 114,787 | 0 | 518 | 2,165 | 2,165 |
4 | Bengkulu | 2,423 | 2,560 | 2,934 | 511 | 0 | 3,603 | 19,432 | 19,432 | 0 | 112 | 360 | 360 |
5 | Jawa Tengah | 61,061 | 56,514 | 56,761 | -4,300 | 0 | 82,860 | 404,370 | 404,370 | 0 | 3,609 | 26,665 | 26,665 |
6 | Kalimantan Tengah | 2,782 | 2,594 | 2,678 | -104 | 0 | 9,866 | 35,900 | 35,900 | 0 | 198 | 1,233 | 1,233 |
7 | Sulawesi Tengah | 2,830 | 2,849 | 3,019 | 189 | 0 | 3,360 | 43,485 | 43,485 | 0 | 106 | 1,519 | 1,519 |
8 | Jawa Timur | 65,311 | 60,983 | 63,126 | -2,185 | 0 | 84,084 | 315,656 | 315,656 | 0 | 6,367 | 23,334 | 23,334 |
9 | Kalimantan Timur | 6,547 | 5,951 | 6,006 | -541 | 0 | 26,581 | 131,149 | 131,149 | 0 | 747 | 5,172 | 5,172 |
10 | Nusa Tenggara Timur | 315 | 330 | 301 | -14 | 0 | 2,193 | 65,368 | 65,368 | 0 | 67 | 1,304 | 1,304 |
11 | Gorontalo | 1,860 | 1,825 | 1,894 | 34 | 0 | 3,839 | 8,632 | 8,632 | 0 | 102 | 356 | 356 |
12 | DKI Jakarta | 12,588 | 11,100 | 12,058 | -530 | 0 | 184,318 | 754,435 | 754,435 | 0 | 5,150 | 11,339 | 11,339 |
13 | Jambi | 3,544 | 3,413 | 3,853 | 309 | 0 | 3,227 | 26,580 | 26,580 | 0 | 56 | 1,019 | 1,019 |
14 | Lampung | 9,802 | 10,667 | 11,916 | 2,114 | 0 | 7,563 | 40,295 | 40,295 | 0 | 274 | 3,630 | 3,630 |
15 | Maluku | 456 | 557 | 547 | 91 | 0 | 5,722 | 9,071 | 9,071 | 0 | 70 | 193 | 193 |
16 | Sulawesi Utara | 1,444 | 1,500 | 1,445 | 1 | 0 | 15,818 | 20,237 | 20,237 | 0 | 302 | 831 | 831 |
17 | Sumatera Utara | 12,256 | 12,501 | 13,718 | 1,462 | 0 | 18,129 | 87,563 | 87,563 | 0 | 677 | 2,208 | 2,208 |
18 | Papua | 1,342 | 1,245 | 1,324 | -18 | 0 | 13,153 | 20,953 | 20,953 | 0 | 157 | 428 | 428 |
19 | Riau | 8,785 | 8,672 | 9,528 | 743 | 0 | 24,966 | 104,602 | 104,602 | 0 | 583 | 3,475 | 3,475 |
20 | Sulawesi Tenggara | 2,640 | 2,616 | 2,955 | 315 | 0 | 8,203 | 11,965 | 11,965 | 0 | 146 | 380 | 380 |
21 | Kalimantan Selatan | 6,105 | 5,648 | 6,039 | -66 | 0 | 15,303 | 54,255 | 54,255 | 0 | 1,383 | 1,803 | 1,803 |
22 | Sulawesi Selatan | 12,682 | 12,090 | 12,172 | -510 | 0 | 30,955 | 84,838 | 84,838 | 0 | 592 | 1,648 | 1,648 |
23 | Sumatera Selatan | 7,928 | 7,466 | 8,717 | 789 | 0 | 11,837 | 47,965 | 47,965 | 0 | 599 | 2,482 | 2,482 |
24 | Jawa Barat | 73,645 | 71,537 | 74,115 | 470 | 0 | 90,286 | 618,248 | 618,248 | 0 | 1,446 | 13,133 | 13,133 |
25 | Kalimantan Barat | 4,023 | 4,126 | 4,099 | 76 | 0 | 3,118 | 38,553 | 38,553 | 0 | 25 | 1,036 | 1,036 |
26 | Nusa Tenggara Barat | 6,735 | 6,626 | 6,946 | 211 | 0 | 5,664 | 22,143 | 22,143 | 0 | 261 | 557 | 557 |
27 | Sumatera Barat | 6,391 | 6,206 | 7,003 | 612 | 0 | 23,464 | 66,589 | 66,589 | 0 | 525 | 1,628 | 1,628 |
28 | DI Yogyakarta | 4,179 | 4,320 | 4,173 | -6 | 0 | 12,155 | 144,856 | 144,856 | 0 | 259 | 5,006 | 5,006 |
29 | Maluku Utara | 845 | 867 | 882 | 37 | 0 | 2,771 | 9,334 | 9,334 | 0 | 89 | 215 | 215 |
Total | 336,631 | 322,262 | 337,427 | 796 | 0 | 722,281 | 3,380,916 | 3,380,916 | 0 | 24,813 | 116,251 | 116,251 | |
M (SD) | 11,608(19,481) | 11,113(18,423) | 11,635(18,904) | 27(1,096) | 0 | 24,906(39,167) | 116,583(181,658) | 116,583(181,658) | 0 | 856(1,536) | 4,009(6,563) | 4,009(6,563) | |
F/t (p) | 4.83.02 | -3.41** | -3.20** | ||||||||||
df1, df2 | 1.5, 41.5 | ||||||||||||
p I vs II | .11 | ||||||||||||
p I vs III | .99 | ||||||||||||
p II vs III | *** |
Table 3
Correlatio ns between variable
2019 | A | B | C | D | E | F | G | |||
A | Underage marriage dispensation applications | 1 | .91*** | .68** | .13 .51 | −.09 .65 | .93*** | .91*** | ||
B | Poverty rate | 1 | .82*** | .06 .76 | −.17 .37 | .95*** | .95*** | |||
C | Jobless rates | 1 | .18 .35 | −.01 .97 | .87*** | .92*** | ||||
D | Junior high school completion rate | 1 | .87*** | .17 .37 | .18 .34 | |||||
E | Senior high school completion rate | 1 | −.05 .81 | −.05 .81 | ||||||
F | Cerai talak | 1 | .99*** | |||||||
G | Cerai gugat | 1 | ||||||||
2020 | A | B | C | D | E | F | G | H | I | |
A | Underage marriage dispensation applications | 1 | .91*** | .74*** | .20 .29 | −.07 .72 | .94*** | .91*** | .51** | .76*** |
B | Poverty rate | 1 | .88*** | .15 .42 | −.14 .47 | .96*** | .96*** | .52** | .66*** | |
C | Jobless rates | 1 | .25 .20 | .03 .89 | .92*** | .95*** | .63*** | .56** | ||
D | Junior high school completion rate | 1 | .87*** | .25 .19 | .25 .18 | .39 .04 | .35 .06 | |||
E | Senior high school completion rate | 1 | −.03 .89 | −.02 .90 | .33 .09 | .21 .27 | ||||
F | Cerai talak | 1 | .99*** | .60*** | .72*** | |||||
G | Cerai gugat | 1 | .60*** | .67*** | ||||||
H | COVID-19 cases | 1 | .85*** | |||||||
I | Number of deaths by COVID-19 | 1 | ||||||||
2021 | A | B | C | D | E | F | G | H | I | |
A | Underage marriage dispensation applications | 1 | .89*** | .70*** | 0.08 .69 | −.02 .93 | .91*** | .87*** | .49** | .91*** |
B | Poverty rate | 1 | .89*** | .01 .98 | −.09 .63 | .96*** | .96*** | .61** | .87*** | |
C | Jobless rates | 1 | .10 .59 | .05 .78 | .93*** | .95*** | .74*** | .74*** | ||
D | Junior high school completion rate | 1 | .87*** | 0.11 .56 | 0.11 .55 | 0.23 .24 | 0.17 .37 | |||
E | Senior high school completion rate | 1 | 0.04 .84 | 0.04 .83 | 0.31 .10 | 0.13 .50 | ||||
F | Cerai talak | 1 | .99*** | .68*** | .89*** | |||||
G | Cerai gugat | 1 | .70*** | .87*** | ||||||
H | COVID-19 cases | 1 | .73*** | |||||||
I | Number of deaths by COVID-19 | 1 | ||||||||
2021–2019 | A | B | C | D | E | F | G | H | I | |
A | Underage marriage dispensation applications | 1 | .54 ** | .83*** | −.14 .46 | .26 .17 | −.92*** | −.74*** | .46 .01 | .90*** |
B | Poverty rate | 1 | .87*** | −.28 .15 | .18 .36 | −.43 .02 | −.30 .11 | .76*** | .65*** | |
C | Jobless rates | 1 | −.21 .27 | .19 .34 | −.70*** | −.49 .01 | .72*** | .85*** | ||
D | Junior high school completion rate | 1 | .16 .42 | .11 .57 | .05 .78 | −.34 .07 | −.23 .22 | |||
E | Senior high school completion rate | 1 | −.17 .37 | −.15 .45 | −.02 .90 | .21 27 | ||||
F | Cerai talak | 1 | .91*** | −.49 .01 | −.91*** | |||||
G | Cerai gugat | 1 | −.41 .03 | −.76*** | ||||||
H | COVID-19 positive cases | 1 | .73*** | |||||||
I | Number of deaths by COVID-19 | 1 |
The multiple regression analysis for the dispensation underage marriage applications in year 2019 was statistically significant, F(4,24) = 178.53, p < .001 (Table 4). The final model (Model 2) was able to account for 97% of variance in new dispensation underage marriage applications (R2 = .97). However, only jobless rate (β = −0.95, 95% CI = −0.01–0.01, p < .001) and cerai gugat (β = 1.82, 95% CI = 0.06–0.22, p < .01) were significantly and uniquely contributed in predicting the 2019 dispensation applications. For every 387,959 more on jobless rate, a reduction of 1443 dispensation was applied, which this interpretation is true only if the effects of other variables are held constant. For every 19,481 more on cerai gugat, an extra 2765 dispensations were applied, which this interpretation is true only if the effects of other variables are held constant. The economic variables (poverty and jobless rates) in Model 1 could explain 84% of variance in 2019 new dispensation underage marriage applications, which increased by 13% when cerai talak and cerai gugat were entered in Model 2.
Table 4
Hierarchical multiple regression results
Variable/year | β | 95% CI | p | β | 95% CI | p | β | 95% CI | p |
|---|---|---|---|---|---|---|---|---|---|
2019 | I—Model 1 | I—Model 2 | |||||||
Block 1 | |||||||||
Poverty rate | 1.06 | 0.00–0.01 | *** | 0.06 | 0.00–0.01 | 0.64 | |||
Jobless rate | −0.19 | −0.01 to 0.01 | 0.18 | −0.95 | −0.01 to 0.01 | *** | |||
Block 2 | |||||||||
Cerai talak | −0.10 | −0.20 to 0.15 | 0.80 | ||||||
Cerai gugat | 1.82 | 0.06–0.22 | ** | ||||||
F (df1, df2) | 66.06 (2, 26) | *** | 178.53 (4, 24) | *** | |||||
R2, Adjusted R2 | 0.84, 0.82 | *** | 0.97, 0.96 | *** | |||||
Δ R2 | - | 0.13 | |||||||
2020 | II—Model 1 | II—Model 2 | I—Model 3 | ||||||
Block 1 | |||||||||
Poverty rate | 1.18 | 0.00–0.01 | *** | 0.09 | −0.01–0.00 | 0.48 | 0.06 | −0.01–0.00 | 0.64 |
Jobless rate | −0.30 | −0.01 to 0.00 | 0.07 | −0.87 | −0.01 to 0.00 | *** | −0.78 | −0.01 to 0.00 | *** |
Block 2 | |||||||||
Cerai talak | 1.22 | 0.33–1.16 | ** | 0.77 | −0.12 to 1.06 | 0.11 | |||
Cerai gugat | 0.43 | −0.09 to 0.28 | 0.31 | 0.76 | −0.05 to 0.39 | 0.12 | |||
Block 3 | |||||||||
COVID-19 positive cases | −0.11 | −0.04 to 0.01 | 0.36 | ||||||
Deaths by COVID-19 | 0.18 | −0.31 to 1.29 | 0.22 | ||||||
F (df1, df2) | 77.20 (2, 26) | *** | 241.40 (4, 24) | *** | 161.83 (6, 22) | *** | |||
R2, Adjusted R2 | 0.86, 0.85 | 0.98, 0.97 | 0.98, 0.97 | ||||||
Δ R2 | - | 0.12 | 0.00 | ||||||
2021 | III—Model 1 | III—Model 2 | III—Model 3 | ||||||
Block 1 | |||||||||
Poverty rate | 1.26 | 0.00–0.01 | *** | 0.19 | 0.00–0.01 | 0.19 | 0.06 | −0.01–0.00 | 0.70 |
Jobless rate | −0.42 | −0.01 to 0.00 | 0.03 | −1.13 | −0.02 to 0.01 | *** | -0.73 | −0.01 to 0.00 | 0.02 |
Block 2 | |||||||||
Cerai talak | 1.18 | 0.24–1.20 | ** | 1.18 | 0.24–1.20 | ** | |||
Cerai gugat | 0.60 | −0.09 to 0.35 | 0.23 | 0.21 | −0.20 to 0.29 | 0.71 | |||
Block 3 | |||||||||
COVID-19 positive cases | -0.17 | −0.01 to 0.00 | 0.13 | ||||||
Deaths by COVID-19 | 0.29 | −0.07 to 0.42 | 0.15 | ||||||
F (df1, df2) | 61.87 (2, 26) | *** | 168.86 (4, 24) | *** | 115.67 (6, 22) | *** | |||
R2, Adjusted R2 | 0.83, 0.81 | 0.97, 0.96 | 0.97, 0.96 | ||||||
Δ R2 | - | 0.14 | 0.00 | ||||||
2021–2019 | IV—Model 1 | IV—Model 2 | IV—Model 3 | ||||||
Block 1 | |||||||||
Poverty rate | −0.77 | −0.02 to (−0.01) | *** | -0.29 | −0.01 to 0.00 | 0.02 | −0.18 | −0.01 to 0.00 | 0.10 |
Jobless rate | 1.51 | 0.02–0.04 | *** | 0.63 | 0.01–0.02 | ** | 0.65 | 0.01–0.02 | *** |
Block 2 | |||||||||
Cerai talak | −0.82 | −5.09 to 1.75 | *** | −0.55 | −4.43 to (−0.11) | 0.04 | |||
Cerai gugat | 0.24 | −0.15 to 1.25 | 0.12 | 0.11 | −0.39 to 0.91 | 0.42 | |||
Block 3 | |||||||||
COVID-19 positive cases | −0.29 | −0.01 to 0.00 | ** | ||||||
Deaths by COVID-19 | 0.27 | −0.05 to 0.26 | 0.19 | ||||||
F (df1, df2) | 68.12 (2, 26) | *** | 117.85 (4, 24) | *** | 117.62 (6, 22) | *** | |||
R2, Adjusted R2 | 0.84, 0.83 | 0.95, 0.94 | 0.97, 0.96 | ||||||
Δ R2 | - | 0.11 | 0.02 | ||||||
The multiple regression analysis for the dispensation underage marriage applications in year 2020 was statistically significant, F(6,22) = 161.83, p < .001 (Table 4). The final model (Model 3) was able to account for 98% of variance in new dispensation underage marriage applications (R2 = .98). However, only jobless rate (β = −0.78, 95%CI = −0.01–0.00, p < .001) was significantly and uniquely contributed in predicting the 2020 dispensation applications. For every 532,812 more on jobless rate, a reduction of 3186 dispensation was applied, which this interpretation is true only if the effects of other variables are held constant. The economic variables (poverty and jobless rates) in the original Model 1 could explain 86% of variance in 2020 new dispensation underage marriage applications, which increased by 12% when cerai talak and cerai gugat were entered in Model 2. Two COVID-19 variables were not adding a unique contribution in explaining the variance in Model 3.
The multiple regression analysis for the dispensation underage marriage applications in year 2021 was statistically significant, F(6,22) = 115.67, p < .001 (Table 4). The final model (Model 3) was able to account for 97% of variance in new dispensation underage marriage applications (R2 = .97). However, only jobless rate (β = −0.73, 95% CI = −0.01–0.00, p = .02) and cerai talak (β = 1.18, 95% CI = 0.24–1.20, p < .01) were significantly and uniquely contributed in predicting the 2021 dispensation applications. For every 509,047 more on jobless rate, a reduction of 2,962 dispensation was applied, which this interpretation is true only if the effects of other variables are held constant. For every 6,662 more on cerai talak, an extra 4,788 dispensations were applied, which this interpretation is true only if the effects of other variables are held constant. The economic variables (poverty and jobless rates) in the original Model 1 could explain 83% of variance in 2021 new dispensation underage marriage applications, which increased by 14% when cerai talak and cerai gugat were entered in Model 2. Two COVID-19 variables were not adding a unique contribution in explaining the variance in Model 3.
The multiple regression analysis for the change of dispensation underage marriage applications in the pandemic and before (years 2021–2019) was statistically significant, F(6,22) = 117.62, p < .001 (Table 4). The final model (Model 3) was able to account for 97% of variance in new dispensation underage marriage applications (R2 = .97). However, only jobless rate (β = 0.65, 95% CI = 0.01–0.02, p < .001), cerai talak (β = −0.55, 95% CI = −4.43–(−0.11), p = .04), and COVID-19 positive cases (β = −0.29, 95% CI = −0.01–0.00, p < .01) were significantly and uniquely contributed in predicting the change of dispensation applications from 2021 and 2019. For every 128,387 more on jobless rate, a reduction of 1,661 dispensation was applied, which this interpretation is true only if the effects of other variables are held constant. For every 614 more on cerai talak, an extra 1,405 dispensations were applied, which this interpretation is true only if the effects of other variables are held constant. For every 181,658 more on COVID-19 positive cases, an extra of 741 dispensation was applied, which this interpretation is true only if the effects of other variables are held constant. The economic variables (poverty and jobless rates) in Model 1 could explain 68.12% of variance in the changes of new dispensation underage marriage applications, which increased by 11% when cerai talak and cerai gugat were entered in Model 2. Two COVID-19 variables were adding 2% more unique contribution in explaining the variance in Model 3.
Discussion
This study aimed to investigate factors associated with the applications of child marriage dispensation submitted to the [Islamic] Religious Courts in Indonesia between 2019 and 2021 during the peak of COVID-19 pandemic. Islam gradually entered Indonesia and spread across the archipelago mainly through trading in the thirteenth century. Although Indonesia is the world’s most populous Muslim-majority country, with approximately 241 million adherents or around 87% of the population in 2022 (Kementerian, 2022), it is a secular democratic country where the constitution guarantees the freedom of worship according to an individual’s religion or belief (Ropi, 2017). Nowadays, in order to manage the practices of Muslims in Indonesia, the Government established the Majelis Ulama Indonesia (MUI, Indonesian Council of Religious Scholars) in 1975, which is not discussed in detail in this study, but interested readers can read the history of Islam in Indonesia in other references (Liow, 2016; Ropi, 2017).
This current study found that the application numbers increased three times between the years, especially from 2019 to 2020. This nationwide result confirmed previous local studies that also found the increase of child marriage dispensation applications, including in Nusa Tenggara Barat (West Nusa Tenggara) (Rahiem, 2021), Jawa Tengah (Central Java) (Supriyadi & Suriyati, 2022), and Jawa Timur (East Java) (Susilo et al., 2021). Moreover, this study supported the global phenomenon regarding the rise of child marriage numbers during the COVID-19 pandemic, including in Africa and South Asia regions (Bachtiar et al., 2021; Kidman et al., 2022; Wahab, 2022). In particular, the rising child marriage numbers in other Muslim-majority countries might be caused by the (mis) interpretation of the hadith of Aishah in patriarchy societies like in Indonesia (Adawiyah et al., 2022), which religion is embedded in Indonesia’s culture and norm as well as people’s daily lives (Grijns & Horii, 2018; Liem, 2020). However, the misconception of the hadith of Aishah has been eradicated by the Indonesian women’s ulama who are committed to gender equality (Rofiah et al., 2022; Satibi et al., 2023).
As found in previous studies (Handayani et al., 2021; Putri & Sutrisno, 2022), the increasing of child marriage applications in Indonesia from 2019 to 2021 was consistently correlated in a positive direction with the economic factors, which were represented by the poverty and jobless rates. However, unlike jobless status, the regression analysis found that poverty rate could not significantly predict the increasing numbers of child marriage applications in the long run during the pandemic situation. Interestingly, the jobless rate was actually reducing the numbers of child marriage applications. It might be because the parents lost their financial stability by being laid off or losing their business and savings so they might hire their children as laborers in doing home industry to alleviate the economic burden on their family. This argument of child labors during the COVID-19 pandemic has also been found in a global study (Washburn et al., 2022).
Moreover, in Islamic tradition, the groom must prepare and give the mahar/mas kawin (dowry) to the bride, which the Indonesian Compilation of Islamic Law stated that mahar is not always money but can also be in the form of goods, animals, and services (Ratnaningsih et al., 2022). However, a previous study in Indonesia found that nearly 80% of mahar was given in the form of jewelry and money (Aini, 2014). It is assumed that the unemployed status of the people and their inadequate financial situation would prevent them from providing this mahar and proposing to their future wives. This assumption is supported by the previous study in Sulawesi that found dowry significantly contributed to child marriage acceptance (Ratnaningsih et al., 2022). Another speculation is that these unemployed young people then migrate internally to another province to find work and prevent them from getting married.
Our study also found the divorce rates were consistently correlated with the child marriage application numbers every year during the pandemic. However, in the long run, it was only cerai talak (husband initiated the divorce under Islamic law) that significantly contributed in predicting the numbers of child marriage applications. We argue that these divorces might impose women into socioeconomic disadvantages, which were supported by the significant correlations between poverty rate and cerai talak numbers from 2019 to 2021 in our analysis. Furthermore, based on the Indonesian Compilation of Islamic Law, custody of a child after divorce is given to the mother if the child has not reached mumayyiz (having a good judgement to tell good from bad) or under 12 years of age (Imami & Hayatudin, 2022). This challenging situation might drive the family to marry their children where the decision could also be forced by the extended family members like grandparents of the child. In addition, women’s voice is usually heard less in the patriarchy society so the mothers could not do much even though they might disagree with marrying the child, which was relatively same with findings among some ethnic groups in Indonesia (Handayani et al., 2021).
The rising of child marriage application numbers could also be predicted through the numbers of COVID-19 positive cases. It might happen because the family has to take care of the members who are infected by coronavirus, which might leave the parents with a caregiving burden. In addition, poverty was positively correlated with the COVID-19 total cases, which it could be interpreted that family who cares for their ill members might then experience financial hardship. Consequently, they might perceive marrying their children as one of the strategies to ease the situation. This phenomenon was also observed in Bangladesh, Brazil, Ethiopia, India, and Nigeria where economic shocks could accumulate in a long term (Yukich et al., 2021).
Implications
Findings from this study could be used by the stakeholders (e.g., local Government, the Ministry of Women’s Empowerment and Child Protection, Child Protection Commission, and non-governmental organizations focus on child’s welfare) as a reference to prevent and decrease the numbers of child marriage, particularly during the COVID-19 pandemic. As economic factors were found significantly in predicting the child marriage dispensation applications, social intervention should prioritize family from low and middle socioeconomic backgrounds. Additionally, the welfare and safety of children with parents who lost their jobs during the pandemic should be monitored because they might be at risk of being exploited as child labores.
Special consideration should also be given for children whose parents are divorcing. The wellness of the child must be protected and the judges should also assess how the parents will care for the child and assure they will not marry the child. A previous study in Nusa Tenggara Barat and Jawa Barat found that not all Religious Court judges asked about or considered the educational and reproductive health needs of children after marriage (Sutriyatmi et al., 2023), which in fact contradicted the Supreme Court Regulation Number 5 of 2019 on the Guidelines for the Trials of Applications for the Dispensation of Marriage/PERMA No. 5/2019 (Mahkamah Agung Republik Indonesia, 2019). Therefore, it is strongly suggested that all Religious Court judges be certified for PERMA No. 5/2019 and its implementation be monitored to ensure that children’s testimonies are heard in court in order to prevent violations of children’s rights in the determination of marriage settlements.
Due to the communal or strong-ties culture in Indonesia (Balmores-Paulino et al., 2023), the judges of divorce cases should also involve the parents of the divorcing couples about child’s wellness and ask their commitment for protecting it, including avoiding child marriage practice. Furthermore, psychosocial supports for women who are divorced and child-bearing should be provided by the Government. For example, a social worker could do a home visit to assist the transition period and monitor the condition of mother and child. Also, because religious leaders are highly respected and Pondok Pesantren (Islamic boarding schools) are common in Indonesia, they can be empowered to prevent child marriage, as a previous study in a religious area in Indonesia found (Amberi, 2023).
Lastly, during pandemic or other crisis situations, family with children should be supported especially when the breadwinner in the family is affected by situations that threaten the family’s financial security. Financial assistance could be given to ease the economic burden due to the loss of income or to pay the medical expenses. Homecare visit or caregiving assistance could also be given in alleviating the caregiving impacts that might be experienced by the parents. In addition, voluntary education tutor could also assist families who are affected by the crisis so the children in these households could be assisted related to their homework and educational material.
Conclusion
Using national data on the numbers of child marriage dispensations from 2019 to 2021, our study found the significant rise within these years. Economic factors, divorce applications, and COVID-19 positive cases were found to be variables that could predict these elevation numbers during the pandemic. Collaborative multi-sectors works are needed to decrease these numbers and findings from this study could be used by the stakeholders in preventing the similar phenomenon in the future crisis situation.
Acknowledgements
The authors thank Alivia Khairunnisa, Elvira Hidayati Afifah, Dr. Drs. H. Abdul Ghani, SH., MH (Deputy Register for Religious Civil Cases at Supreme Court of The Republic of Indonesia) for their support in data collection and analysis.
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Competing interest
The authors declare no competing interests.
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