Firstly, descriptive analysis was applied to quantitatively describe and summarize the socio-demographic characteristics of the respondents and the research variables (knowledge, perception, and attitude). Lastly, cross-tabulation and path analysis were conducted to examine the relationship between knowledge, perception, and attitude to determine the level of public acceptance of a coastal flooding early warning system.
3.1. The Respondents’ Socio-Demographic Characteristics
The respondents’ socio-demographic characteristics are shown in Figure 3
, Figure 4
, Figure 5
and Figure 6
. The respondents were grouped into five age groups. The results showed that the age group with the most respondents was the 31–40-year-old group (35%), and the group with the least was in the >60-year-old group (1.25%) (Figure 3
Regarding sex, most respondents were male (70.5%), and the remaining respondents were female (29.5%) (Figure 3
Based on the level of education, most respondents (55.75%) had an education level of senior high school/equivalent (local term: SLTA) and at least 1.75% of them were academy graduates (Figure 4
Based on the type of occupation, most respondents (67.25%) worked as entrepreneurs/self-employed, and no respondents were working as Indonesian Military Soldiers or Police Officers (local term: TNI or POLRI) (Figure 4
Based on citizenship status, most respondents (97%) were permanent residents according to the distribution area of the questionnaire, while the remaining 3% were residents with a national government ID card (local term: KTP) from outside of Jakarta Province (Figure 5
Based on the management of RT/RW (the Indonesian term for the lowest administrative area neighborhood consisting of 10–50 families), RW is one level higher than RT, but lower than a village; most respondents (89.25%) were not RT/RW administrators. The remaining 10.75% of the respondents were active members of the local RT/RW management (Figure 5
). This indicates that the survey carried out has been evenly distributed to both residents and local stakeholders.
Based on total income, most respondents (49%) had an income of between Rp. 3,501,000 and 6,000,000 (Rp. is similar to IDR, the currency of Indonesia), and the smallest number of respondents (3.25%) had an income of <Rp. 500,000 (Figure 6
The questionnaire results regarding the capacity of the respondents to face coastal flooding and the responses regarding coastal flooding early warnings are provided in Appendix B
. In addition, the results indicated that most respondents had lived in coastal areas for more than 20 years, with the majority being native residents, where their residence or houses were mostly privately owned property.
From the survey, the largest proportion of people living in coastal areas were married with 4–6 people living in the same house, followed by 1–3 people in the same house. Based on the questions asked in the questionnaire, most respondents knew the causes and impacts of coastal flooding (i.e., sea level rise and poor drainage channels (gutters)). Based on the answers of the respondents, coastal flooding (local term: Rob—flood due to sea level rise) events occur at uncertain times according to most respondents, with a frequency of 1–3 times per month, each with a duration of 2–3 h and 0–30 cm depth.
Most respondents said that the dissemination of information related to flooding was rare by the head of the local RT/RW, as they did not participate in associations or organizations related to flood disasters. Some efforts have been made to deal with flooding, such as house reconstruction efforts like elevating the ground floor of houses as the most impact felt due to flooding is property damage (houses, vehicles, household utensils). Many respondents stated that the reason for living in the location where they are currently living is because they have lived there for a long time, even though when viewed from the survey results, it was found that the drainage conditions (waterways and/or gutters) in the neighborhood where most respondents were located could properly flow, but some of the drainage systems were clogged with mud and/or trash.
According to most respondents, there was no flood warning system in the neighborhood where they lived, and they commonly obtained the information/news related to flood disasters that occurred (including flood predictions) from news sources such as newspapers, television, or the internet. When they were questioned about where to go to save themselves when a flood occurs, they generally answered that they would remain at home as the modes of transportation mostly used to evacuate during such an emergency were motorbikes.
When they were asked about the type of fund allocation that is available, 69% of respondents said they did not have any funds allocated for flood disasters due to the low-income level in coastal areas. Moreover, according to most respondents, there was no financial assistance during or after flood disasters. The government provided aid during and after flood disasters; the assistance provided was mostly in the form of food supplies, followed by the provision of body protection such as clothes and blankets.
Previous research [36
] suggested that the information needs of local residents and access to information are integral components in the process of public understanding. This theory was tested out for the government mitigation scheme.
Based on the answers to these questions, the capacity of coastal communities to deal with coastal flooding was observed. Of note, three-fourths of the respondents already knew the causes and impact of coastal flooding. However, the community rarely received information from the head of the RT/RW. This information is important because it impacts the lack of community participation in coastal flooding management. There is no early warning coastal flooding system, even though the questionnaire results showed that the government provides the most assistance to the community, both in terms of funding for disaster management and repairing drainage systems in coastal areas. It can be concluded that a large amount of government involvement makes the dissemination of the coastal flooding early warning system very critical for improving the level of public acceptance based on existing capacities.
3.2. Descriptive Analysis of Research Variables
This section describes the dynamics and distribution of the respondents’ answers to the questions determining the variables of knowledge, perceptions, and attitudes. Recapitulation was performed to determine the average score of each variable, which was then compared, observed, and analyzed based on the sub-district. Referring to the minimum and maximum values described in Section 2.2
, the existing median value for the knowledge variable was 2, and the value for the perception and attitude variables was 3.
shows that Warakas village had the lowest knowledge, with an average score value of 2.30. The highest average score value was in Koja Utara village (3.00). This indicated that the average community on the coast of North Jakarta had little knowledge about coastal flooding and the early warning of coastal floods in the community area.
Based on the context of public perception about the coastal flooding early warning information system, Kali Baru village had the lowest average score (2.44) compared to other urban villages, while the highest average score was in Warakas village (3.59). In addition, according to the average score for each village, the coastal communities of North Jakarta had a common perception that a coastal flooding early warning system would be suitable as a solution to manage coastal flooding.
The questionnaire results showed that there were various responses regarding the respondents’ perception of a coastal flooding early warning system that was already implemented in the community (i.e., local wisdom); 44.75% of respondents stated that they agreed or strongly agreed that the traditional early warning system was sufficient for the flood evacuation process. Nevertheless, the remaining 55.25% of respondents thought that it would be necessary to add another early warning system besides the traditional system of local wisdom.
The recapitulation results showed that 62.5% respondents thought that there was no local wisdom related to a flood early warning system. In contrast, 20.25% of the respondents stated that there was local wisdom in responding to early warning systems, such as traditional equipment like kentongan (a drum made from bamboo or wood that is struck to sound an alarm) or announcements from places of worship (such as a mosque). The remaining 17.25% of respondents suggested that there was already a flood warning system where they live in the form of technology conveying information via the internet. The local wisdom that exists in the community related to flood disasters and flood predictions includes paying attention to natural signs (28.75% of respondents) and information from neighbors and families and local government officials (27.25% of respondents). The remaining 44% of respondents received news from newspapers, TV, and the internet.
For the community attitude variable, the lowest average score was in Cilincing village (3.75), while the highest score was 4.81 in Koja Utara village. Overall, we concluded that the coastal communities of North Jakarta think that it is quite appropriate to use an early warning system to manage coastal flooding disasters.
shows the community’s level of knowledge, perceptions, and attitudes more clearly based on each village observed in the study. This may be closely related to the community’s social strata in Cilincing and Pluit villages, which are not directly located on the coast.
3.3. Cross Tabulation
The cross tabulation analysis was conducted to determine the relationship amongst knowledge, perception, and attitude variables. The results of this analysis are presented in Table 6
which shows that these three variables in the research correlates with each other.
If seen in more detail as in Table 7
, it can be seen how the relationship between the characteristics of the respondents to the variables of knowledge, perception, and attitude.
From Table 7
, the characteristics that have a relationship with these three variables are education and average income. Meanwhile, occupation, residence status, and RT/RW management status are related to the two variables observed. Furthermore, age is only related to one variable. In addition, it shows that gender does not have any impact in responding to answers regarding the variables observed.
The highest correlation coefficient between the community variables’ knowledge and attitude based on Table 8
was found in Kali Baru Village (0.687). This implied that the Kali Baru community tends to have a strong relationship between their knowledge and the community’s attitude regarding the development of an early warning system of coastal flooding. The highest correlation coefficient between perceptions and community attitudes variables was in Warakas village by 0.622, which showed that Warakas community tends to have a strong relationship between the community’s perceptions and the community attitudes regarding the development of a coastal flooding early warning system.
As seen in Table 8
, several relationship anomalies occur in several urban villages that result in negative correlations. Ancol village has a high negative correlation (−0.63) for the relationship between the knowledge and the attitude variables. Meanwhile, Cilincing and Ancol villages (−0.122 and −0.051) show a low negative correlation between the perception and the attitude variables. The negative correlation related to the relationship between the knowledge and the attitude variables indicates that the higher the knowledge of Ancol community, the smaller the community’s perception of the coastal flooding early warning model, and this shows a contradiction to a study conducted by Jing Huang [37
] stating that there is a positive correlation between knowledge and attitudes related to behavior of flood protection handling. This contradiction can be traced by looking at the characteristics of the respondents and the community capacities in the Ancol Village in further research.
3.4. Path Analysis
The results of path analysis calculation as seen in Table 9
, show that the knowledge variable has a direct effect on the attitude variable by 7.3%. Furthermore, Figure 7
indicates that ttest
is 6.18, as shown from the test results of knowledge influence on the community’s attitudes. The value of ttest
(6.18) is higher than the value of ttable
(1.96). This means that public knowledge of the coastal flooding early warning model has a significant effect on the attitudes of the community towards the coastal flooding early warning model.
The path coefficient between knowledge and community’s attitudes is 0.37, as shown in Figure 8
, which is positive. This means that the higher the community’s knowledge about the coastal flooding early warning model, the community’s attitude in responding to the coastal flooding early warning model that is formed will increase.
strengthens the previous correlation analysis results that Kali Baru Village has the highest knowledge relationship on community attitudes regarding the coastal flooding early warning model compared to other villages. This is indicated by many respondents, the majority of whom have a senior high-level education compared to other villages. This analysis is reinforced by a previous study [38
], which states that individuals with higher education are less likely to be affected by flooding than individuals with low education. These results are also consistent with other studies [39
], which showed that respondents who were knowledgeable about floods felt higher adaptive capacity and were more likely to take adaptive measures.
shows the remarkably diverse variations in education levels in coastal communities, it can be used as a reference for determining the method of dissemination that must be carried out so that the level of public acceptance of the coastal flooding early warning model becomes better. Methods of delivery that can be carried out to embrace all society elements without paying attention to education level include the dissemination of information through social media, printable media, or through the official website of related agencies/institutions.
also shows that the perception variable has a direct influence on the attitude variable by 16.0%. The test results on the effect of perception on the community’s attitudes obtained a ttest
as much as 9.12, as seen in Figure 7
. Accordingly, the value of ttest
(9.12) is higher than the value of ttable
(1.96). This indicates that the community’s perception on the coastal flooding early warning model has a significant effect on their attitudes towards the coastal flooding early warning model.
The path coefficient between perceptions and the community’s attitudes is 0.51 positive, as shown in Figure 8
. This means that the higher the public perception of the coastal flooding early warning model, the community’s attitude in responding to the coastal flooding early warning model that is formed will increase.
shows that respondents in Warakas and Kali Baru Villages have a high proportion of respondents with a duration of stay of more than 20 years, higher than 50% compared to other villages. This strengthens the results of the correlation analysis, which states that people’s perceptions in Warakas Village on their attitudes regarding the coastal flooding early warning model have the highest relationship compared to other villages. People who have lived in an area for a long time make the perception formed in the community better in coastal flooding disasters because they are more familiar with the condition of the area. It affects the increase of the level of public acceptance. The results of this analysis are in accordance with other researchers [40
], which shows that cultural and historical relationships with place are a significant driver of their desire to stay on riverbanks affected by flooding.
Lastly, knowledge and perception variables simultaneously influence the attitude variable by 23.3%. Therefore, such a simultaneously great influence of knowledge and perception variables on the attitude variable indicates that the community’s attitude in responding to the coastal flooding early warning model can be explained by knowledge and perception variables simultaneously by 23.3%. Besides, the remaining 76.7% is explained by other variables not investigated in the research.