JAMBA Jàmbá - Journal of Disaster Risk Studies 2072-845X 1996-1421 AOSIS JAMBA-17-1972 10.4102/jamba.v17i1.1972 Original Research Community leaders’ knowledge and practices in landslide management: A case study from Indonesia https://orcid.org/0000-0002-2763-0219 Fatmah Fatmah 1 https://orcid.org/0009-0004-9744-6830 Purwana Rachmadhi 1 https://orcid.org/0000-0003-3686-7549 Razak Khamarrul A. Bin 2 Department of Environmental Science, Graduate School of Sustainable Development, University of Indonesia, Jakarta, Indonesia Disaster Preparedness and Prevention Center, University of Technology Malaysia, Kuala Lumpur, Malaysia Corresponding author: Fatmah Fatmah, ffatmah@ui.ac.id 04122025 2025 17 1 1973 02082025 17102025 © 2025. The Authors 2025 Licensee: AOSIS. This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Community leaders play a crucial role in reducing disaster risk and enhancing preparedness at the community level. However, despite their importance, research on the role of community leaders in the context of landslide risk management, particularly in relation to the implementation of emergency response plans (ERP), remains limited. The study aimed to assess the associations between socio-demographic, natural hazards and landslides knowledge, early warning systems (EWS), and ERP with community leaders’ practice in landslide management (pre, during and post). A cross-sectional design was utilised among 137 respondents residing in landslide-prone areas. Results showed that gender and educational attainment were both significantly associated with community leaders’ landslide management practices. Knowledge of natural hazards and landslides also had a positive influence on their practices. In contrast, EWS showed no significant effect on landslide management practice (p > 0.05). Community leaders with an ERP were found to be 11.6 times more likely to implement the practices compared with those without one. It is recommended that community leaders develop an ERP specifically to strengthen landslide preparedness.

Contribution

The research assessed the knowledge and practice of community leaders in landslide management. It is necessary to provide an emergency response plan for community leaders to enhance landslide preparedness, particularly for vulnerable groups.

 landslide knowledge practice community leaders emergency response plan Funding information The study was funded by the Universitas Indonesia through the PUTI Q2 Scopus Grant Year 202 (NKB-737/UN2.RST/HKP.05.00/2024). Introduction

Landslides pose a major geohazard worldwide, causing widespread destruction, thousands of fatalities and substantial property damage each year (Schuster & Highland 2021). Globally, landslides account for approximately 17% of annual deaths from natural hazards (Aristizábal & Sánchez 2020). The earliest recorded landslide disaster dates to 1767 BC in Honan Province, China, where an earthquake-triggered slide formed a landslide dam (Schuster 1996). Indonesia, frequently affected by a wide range of natural hazards, is recognised as one of the most disaster-prone countries in the world. The risk indices for tsunamis, floods, landslides, droughts and forest fires are significantly higher than the global average. Between January 2024 and October 2024, 1512 natural hazards were reported nationwide, with floods (766 cases), extreme weather (262 cases), and landslides (91 cases) being the most prevalent (Geoportal of Indonesian Disaster 2024).

Several regions are particularly vulnerable to landslides, including Bogor Regency, Depok City and parts of Jakarta. Landslide research in Jakarta, Depok and Bogor is crucial for reducing the risk and mitigating the impact of landslides in these vulnerable areas. Although Jakarta is not a mountainous region, it still has significant landslide potential, particularly in specific vulnerable areas. Depok has a varied topography with several hilly areas and river basins prone to landslides. Bogor is known to have a high risk of landslides, mainly because of high rainfall, steep slopes and unstable soil conditions. These regions, characterised by rapid urban development, varied topography and seasonal heavy rainfall, are particularly susceptible to landslide hazards National Disaster Management Authority (BNPB 2024). In Bogor Regency, 10 of 20 disaster events between December 2022 and January 2023 were landslides, and another landslide in November 2023 damaged 497 buildings (Rostanti 2023). Bogor is thus categorised as having a high landslide risk index (BNPB 2024). Depok City has 10 landslide-prone villages situated near riverbanks and road cliffs (Rajaguguk 2024), while Jakarta still contains 16 landslide-prone sub-districts based on hazard overlays from the Meterology, Climatology, and Geophysics Agency (BMKG) (Bustomi & Sari 2024).

To achieve sustainable and environmentally sound development, the paradigm of disaster risk reduction needs to be strengthened at the community level through community leaders. Local communities stand at the forefront, becoming increasingly aware of both the immediate impacts and root causes of emerging challenges. They play a pivotal role as advocates for risk reduction, translating this awareness into tangible, small-scale interventions. They serve as key mobilisers and decision-makers at the local level who can greatly influence disaster risk reduction efforts. Empowering community leaders in disaster risk reduction is an integral part of the Community-Based Disaster Risk Reduction (CBDRR) Programme, which is designed to empower communities to actively participate in all phases of disaster risk management. By doing so, the programme aims to enhance community preparedness, reduce vulnerabilities and minimise losses arising from disasters. This approach aligns with international standards in disaster risk reduction, particularly the Sendai Framework for Disaster Risk Reduction (2015–2030), which emphasises strengthening resilience at the community level. Improving community preparedness through the active involvement of community members and leaders is closely tied to the strengthening of social capital (Ruslanjari, Wahyunita & Permana 2018), including a culture of cooperation, togetherness and leadership. The programme also draws on the principles of participatory risk management (Pramono & Suranto 2021) and collaborative governance (Amil 2025), ensuring that disaster risk management is inclusive, locally driven and sustainable.

Key indicators for measuring disaster preparedness include community leaders’ knowledge about natural hazards, the existence and quality of emergency response plans (ERP), and the availability and effectiveness of early warning systems (EWS). These elements are critical in assessing a community’s ability to anticipate, respond to and recover from disaster events like landslides (Granberg 2013). Factors influencing landslide management practices are knowledge, EWS, ERP and socio-demographic characteristics (educational attainment, gender and income). Knowledge and attitude are associated with landslide preparedness practices (Indriani et al. 2023). Early Warning Systems enable community leaders to help initiate early evacuations, mobilise emergency resources and implement risk mitigation strategies. Early warning system is a key tool in enhancing preparedness, strengthening community resilience and supporting informed decision-making in all phases of landslide disaster management (Trogrlic et al. 2022). Emergency Response Plans offer a structured framework for managing disaster events across all phases– before, during, and after a landslide. A well-designed ERP not only improves the efficiency of emergency operations but also strengthens community resilience by promoting preparedness, minimising confusion and accelerating recovery (Ardiansyah et al. 2024). Educational attainment affects disaster management practice. Several studies have shown that final education is related to the level of community preparedness in natural hazards preparedness (Hoffmann & Blecha 2020). Gender plays a significant role in disaster management, and gender-inclusive practices are essential for effective disaster risk reduction (Hedriyanti & Syamsudin 2021). Socio-economics, represented by monthly income, is essential in explaining behaviour after natural hazards. High income is associated with relatively high-risk perception (Fussell, Sastry & VanLandingham 2009).

Cadres are community members or community leaders who are trained to enhance preparedness, lead prevention and mitigation measures and facilitate rapid response, particularly in the health sector (Zuliani & Hariyanto 2021), and vulnerable groups such as pregnant women during landslide emergencies (Maharani 2021). Several studies have examined the role of community leaders in disaster management, including research on landslide mitigation in Sukoharjo Regency (Dahroni & Subadi 2017), the influence of local opinion leaders on shaping community attitudes towards disaster mitigation in North Lombok Regency (Ain, Hadi & Teluma n.d.), the effectiveness of landslide mitigation in Bogor Regency (Ulvia n.d.), and the role of community leaders in coronavirus disease 2019 (COVID-19) mitigation in Padang City (Fahzima 2021). In addition, four other studies have quantitatively explored the roles of community leaders in disaster mitigation outside the selected areas of Jakarta, Bogor and Depok. However, despite these contributions, there remains little evidence on the knowledge and practice of community leaders in landslide management, specifically within Jakarta and Bogor areas that are increasingly vulnerable to landslides because of urban expansion, environmental degradation and climate variability. This knowledge gap limits the ability of disaster management agencies and local governments to design interventions that fully harness local leadership capacities. This study aims to assess the associations in community leaders’ socio-demographic, natural hazards and landslides knowledge, EWS and ERP in landslide management practice (pre, during and post). The hypothesis in the study was developed from the formulation of the first problem, namely that there are significant differences in community leaders’ practices in landslide management according to the socio-demographic characteristics, knowledge about natural hazards and landslides, EWS and ERP.

 Research methods and design Study design

This study employed a cross-sectional study design, with a sample size of 137 participants distributed across 17 selected villages in Jakarta, Bogor and Depok (Figure 1, Figure 2, Figure 3).

Map of Jakarta’s landslide-prone area.

Map of Bogor’s landslide-prone area.

Map of Depok’s landslide-prone area.

 Population and sample

The research included all communities impacted by landslides over the past decade in 17 chosen villages in Jakarta City (Ancol, Kembangan and Pejaten Timur Villages), Bogor Regency (Sentul, Sukamulih, Cimandala and Limusnunggal Villages) and Depok City (Cilangkap, Jatijajar, Tugu, Pasir Gunung Selatan, Sukmajaya, Abadi Jaya, Cisalak, Mekarjaya, Ratu Jaya and Pasir Putih Villages). Seventeen villages and sub-districts were selected for inclusion in the study based on records of landslide-prone areas covering the period 2010–2025 (BNPB 2019). A total of 137 participants who met the inclusion criteria, that is, both male and female individuals, community leaders or the integrated community post cadres, and those who had experienced a landslide disaster in the last 10 years, were involved in the study. The participants were chosen using purposive sampling because only those with specific characteristics aligned with the research objectives were selected, so the findings are highly relevant to that group. However, as a result, the study’s conclusions cannot be generalised to the broader population or to the entire city level. The sample size was calculated using Slovin’s formula to ensure a representative sample of respondents (Tejada & Punjalan 2012). By entering the relevant values into Slovin’s formula and adding 10%, the estimated sample size was determined to be 137 people, where n represents the sample size, N represents the total people affected by natural hazards in 2024 (4 649 403 people) (Nua 2024), and e represents the 9% error margin (Equation 1): n=N(1+N.e2)

 Study variables and instruments

Independent variables (Figure 4) included participants’ socio-demographic attributes (marital status, age, latest education, main occupation, residence, number of biological children, monthly income, length of time as a community leader); knowledge of natural hazards (meaning, types, impacts, disaster-prone groups and mitigation efforts) and landslide (definition, causes, signs, impacts); and ERPs influencing the landslide management practice of community leader and cadres as the dependent variable. Landslide management practices were categorised into three phases: pre-landslide, during the landslide and post-landslide. The total knowledge score was 16, with a minimum score of zero. Subsequently, the knowledge level was categorised as either low (i.e. below the mean score) or medium (i.e. equal to or above the mean score).

Conceptual framework of factors affecting community leaders’ practice on landslide management.

The level of the ERP was established based on the mean score, which was categorised into two groups: low (less than the mean score) and medium (greater than or equal to the mean score). A total of 14 questions were answered with a score of 1 for a positive response and 0 for a negative response. The respondents’ practices were evaluated in three phases: before, during and after the landslide. Each phase was assessed using a different set of questions. The knowledge level of landslide management practices was determined by categorising responses into two groups: those deemed to demonstrate a good understanding of the subject matter if the score was equal to or greater than the mean score, and those indicating a poor understanding if the score was less than the mean score.

 Data analysis

The analysis involved examining the frequency distribution of different variables, such as socio-demographic characteristics, knowledge of natural hazards and landslides, EWS practices, ERPs and landslide management practices (before, during and after). IBM® SPSS® Statistics software for Windows 24 was used to conduct the analysis. Univariate analysis included reviewing the mean, minimum and maximum values distribution. Bivariate data analysis was performed to determine if there was a correlation between independent variables such as socio-demographic characteristics, knowledge about natural hazards and landslide, EWS, ERP and the practice of landslide management. The Chi-Square test was used for bivariate analysis, with the relationship criteria based on the value (probability) generated with a 95% confidence interval. The study utilised logistic regression as a multivariate analysis method to evaluate the determining factors affecting landslide management practices. The equation model (Equation 2) is described below: X1:Socio-demographic characteristicsY=α+β1X1+β2X2+β3X3+β3X4+εX2:Knowledge about natural hazards and landslidesX3:The Early Warning System (EWS)X4:The Emergency Response Plan (ERP)

 Ethical considerations

Ethical clearance to conduct this study was obtained from the Ethics Commission for Health Research and Development of STIKES Sint Carolus Jakarta on 22 July 2024 (No. 107/KEPPKSSTIKSC/VII/2024).

 Results Factors influencing the landslide management practice Socio-demographic characteristics

The socio-demographic characteristics of the respondents, including age group, gender, marital status, highest level of education attained, current employment status, family income, family structure, number of biological children, status as a community leader and willingness to become a disaster preparedness cadre are described in Table 1. Most respondents were 50 years or above, with a mean age of 45.6 years. Many respondents were male and married. Most respondents had received an education at the secondary level, holding either a high school diploma or a bachelor’s degree. The proportion of employed respondents was approximately double that of those who were not employed. One-third of the total respondents reported a monthly income of approximately $193.5, with most of these individuals belonging to nuclear families comprising a father, mother and children. A more significant proportion of the total respondents (more than one-third) identified as community leaders in their respective neighbourhoods. During the interview, it was established that approximately 50% of the respondents had fewer than two biological children.

Socio-demographic characteristics.

Variable People (n) Proportion (%)
Age group (years old)
20–39 42 30.7
40–59 80 58.4
60–75 15 10.9
Gender
Male 77 56.2
Female 60 43.8
Marital status
Married 116 84.7
Single (widow/widower) 21 15.3
Last education
Less than 12 years of schooling 59 43.1
More than or equal to 12 years of schooling 78 56.9
Working status
Yes 86 68.6
No 51 37.2
Monthly income ($)
< 193.5 44 32.1
193.5–322.6 60 43.8
> 322.6 33 24.1
Family type
Nuclear 108 78.8
Extended 29 21.2

Note: Age group Mean ± standard deviation = 45.6 ± 11.8.

s.d., standard deviation.

Knowledge of natural hazards and landslides began with questions on the definition, types, examples and impacts of natural hazards. More than half of the respondents knew the meaning of natural hazards, and all respondents could mention the types, examples and effects. Older people were part of the most disaster-prone groups, as respondents expressed, followed by children and toddlers. This group needs to prepare for a landslide, according to most respondents. Although nearly all respondents could accurately describe a landslide, its definition, causes, impacts and hallmarks, their overall understanding of natural hazards and landslide-specific knowledge remained low (mean score = 37.4). This shortfall is primarily driven by limited awareness of which population groups are most vulnerable during disasters and by gaps in knowledge about landslide management (Table 2).

Frequency distribution of knowledge about natural hazards and landslides, landslide management knowledge and landslide management practices.

Variable People (n) Proportion (%)
Knowledge about natural hazards
Definition 94 68.6
Types 127 92.7
Examples 137 100
Impact 137 100
Landslide-prone group
Older people 94 68.6
Children 77 6.2
Under-five children 64 46.7
Pregnant women 31 22.8
People with disabilities 12 8.8
The need for vulnerable groups to prepare for landslide 67 48.9
Knowledge of landslides
Definition 115 83.9
Causal factors 130 94.9
Impact 134 97.8
Signs of landslide 120 87.6
Knowledge about landslide management
Preparedness mitigation definition 50 36.5
Types of landslide mitigation 40 29.2
Level of knowledge about natural hazards and landslides
Poor 76 55.5
Good 61 29.2
Practice of landslide management
Pre-landslide:
 Learning and practising evacuation routes 32 23.4
 Discussing countermeasures with family members 34 24.8
Self-preparation habits before a landslide
Preparing a preparedness bag 20 14.6
Planning or placing items in a relatively safe place 19 13.9
Disrupting daily life 68 49.6
Early signs of a landslide 130 94.9
At – landslide
Evacuate landslide-prone family members to a safe place 68 49.6
Source of landslide information from:
social media 53 38.7
mosque bell 19 81
Inform the public of the landslide and update the information 81 59.1
Feeling anxious when a landslide occurs 105 76.6
Evacuation site during landslide:
Mosque/church 25 18.2
Safer relative/neighbour’s home 38 27.7
Field 7 5.1
EWS of landslide
Availability of EWS landslide 49 35.8
The information sources:
WhatsApp Group 46 33.6
Mosque/musholla speakers 22 16.1
Neighbours 27 19.7
Kentongan/electricity pylons 85 62
First action when community leaders heard the landslide EWS:
Pick up the disaster preparedness bag 12 8.8
Rush to the evacuation centre 90 65.7
Assist vulnerable groups to safer places 43 31.4
Calm down and do not panic 33 24.1
EWS of landslide level
Poor 84 61.3
Good 53 38.7
ERP of the landslide
Tasks division in flood emergency rescue 14 10.2
Something is being undertaken for landslide evacuation 72 52.6
Maps, places, evacuation routes, assembly points are available 5 3.6
There were relatives/families providing shelter 70 51.1
There was first aid medicine when there was a landslide 56 49.9
There were family members who had taken part in training 2 1.5
There are evacuation routes in case of a landslide 9 6.6
Family lighting equipment available in emergency 119 86.9
Family communication tools are available during a landslide 126 92
Have prepared a disaster preparedness 11 8
Have an important phone number (hospital, police office firefighter) in the emergency 34 24.8
Have ever received landslide preparedness training 2 1.5
Level of emergency response plan parameter
Poor 79 57.7
Good 58 42.3

Note: Level of knowledge about natural hazards and landslides - Mean ± s.d. = 37.4 ± 12.1; EWS of landslide level - Mean ± s.d. = 28.5 ± 22.5; Level of emergency response plan parameter - Mean ± s.d. = 35.9 ± 13.6.

s.d., standard deviation; EWS, early warning systems; ERP, emergency response plans.

Practices for managing landslides commence during the pre-landslide phase, identified by a few participants through early detection of landslide signs, family conversations about landslide management and assembling disaster preparedness kits. Nearly half of the respondents relocated family members at risk of landslide to a secure location. The primary sources of landslide information are mainly social media. Most respondents shared the latest landslide developments with other community members. Feeling anxious during a landslide, they typically evacuate to the safer homes of relatives or neighbours. Following a landslide, the most common actions include ensuring no further landslides and cleaning the house and surroundings if the house remains intact (undamaged). Landslide management practices still need to be increased based on the above practices. One-third of the total survey participants already possess a landslide EWS in the form of bells, electric poles and a WhatsApp group. The most common response to the landslide EWS sounding was rushing to the evacuation site, while the least common action was taking a disaster preparedness bag. It is evident that the landslide EWS still needs improvement. The level of preparedness in the ERP could be higher, particularly in the pre-landslide actions, which are seldom carried out except during an actual landslide (Table 2).

Significant variations in landslide management practices are based on age, educational attainment, working status, monthly income, EWS, ERP of landslide and knowledge about natural hazards and landslides. These are presented in Table 3. The variables of age, educational attainment, monthly income, EWS level, ERP level, level of knowledge about natural hazards and landslides, and level of landslide management practices were significantly different from genders. Males rather than females dominate the age group above 50 years. The proportion of male respondents with senior high school education is twice that of females. Similarly, a monthly income above $322.6, the position of community leader, a good level of EWS, a good level of the ERP, a level of knowledge about natural hazards and landslides, and a good level of landslide management practices are owned mainly by male respondents. Landslide management practices (pre, during, post) of a community leader with a good level of ERP are 11.6 times higher than that of a community leader with a low level (Table 4). Table 4 explained that the Hosmer–Lemeshow test yielded a Chi-Square value of 1.737 with a p-value of 0.973 (> 0.05). This indicates that the logistic regression model fits the data well, as there is no significant difference between the observed and predicted values. The −2 Log Likelihood value of the logistic regression model is 102.758, which is smaller than the Chi-Square table value (degrees of freedom [df] = 132) of 159.814. This indicates that the logistic regression equation meets the test requirements and shows good overall model fit. The Omnibus Test shows a Chi-Square value of 85.929 with a p-value < 0.05. This means that the independent variables: gender, number of biological children, ERP, and knowledge about natural hazards and landslide have a simultaneous, statistically significant effect on the community leaders’ practice in landslide management. The Nagelkerke R Square value is 0.623, indicating that the four independent variables listed above together explain 62.3% of the variation in the community leaders’ practice in landslide management, while the remaining 37.7% of the variation is because of other factors not included in the model.

Analysis of the differences in the proportion of sociodemographic characteristics, knowledge of natural hazards and landslide, emergency response plans with landslide management practices.

Variable n Practice before the landslide
 Practice at the landslide
 Practice post-landslide
 Practice of landslide management
Poor
 Good
 OR (95% CL) p-value Poor
 Good
 OR (95% Cl OR) p-value Poor
 Good
 OR (95% Cl OR) p-value Poor
 Good
 OR (95% Cl OR p-value
n % n % n % n % n % n % n % n %
Gender
Women 60 39 65.0 21 35.0 1 - 43 71.7 17 28.3 1 - 38 63.3 22 36.7 1 - 40 66.7 20 33.3 1 -
Men 77 40 51.9 37 48.1 1.7 0.125 43 55.8 34 44.2 2.0 0.047 41 53.2 36 46.8 1.5 0.236 35 45.5 42 54.5 2.4 *0.000
- - - - - (0.9–3.4) - - - - - (19–4.1) - - - - - (0.8–3.0) - - - - - (1.2–4.8) -
Marital status
Single/widow/widower 21 12 57.1 9 42.9 1 0.958 15 71.4 6 28.6 1 0.373 12 57.1 9 42.9 1 0.958 13 61.9 8 38.1 1 0.400
Married 116 67 57.8 49 42.2 0.9 - 71 61.2 45 38.8 1.6 - 67 57.8 49 42.2 0.9 - 62 53.4 54 46.6 1.4 -
- - - - - (1.4–2.5) - - - - - (0.6–4.4) - - - - - (0.4–2.5) - - - - - (0.5–3.7) -
Age group (years old)
< 40 42 22 52.4 20 47.6 1 - 27 64.3 15 35.7 1 - 22 52.4 20 47.6 1 - 21 50.0 21 50.0 1 -
40–50 47 31 66.0 16 34.0 0.6 0.194 33 70.2 14 2.9.8 0.8 0.552 30 63.8 17 36.2 0.6 0.623 31 66.0 16 34.0 0.5 0.100
- - - - - (0.2–1.3) - - - - - (0.3–1.9) - - - - - (0.3–1.5) - - - - - (0.2–1.2) -
> 50 48 26 54.2 22 45.8 0.9 0.865 26 54.2 22 45.8 1.5 0.331 27 56.3 21 43.8 0.9 0.713 23 47.9 25 52.1 1.1 -
- - - - - (0.4–2.1) - - - - - (0.7–3.6) - - - - - (0.4–1.9) - - - - - (0.5–2.5) -
Final education
Completed secondary education or less 71 55 77.5 16 22.5 1 - 62 87.3 9 12.7 1 - 53 74.6 18 25.4 1 - 55 77.5 16 22.5 1 0.800
High school graduates and above 66 24 36.4 42 63.6 6.0 *0.001 24 36.4 42 63.6 12.1 *0.001 26 39.4 40 60.6 4.5 *0.001 20 30.3 46 69.7 7.9 *0.000
- - - - - (2.8–12.7) - - - - - (5.1–28.5) - - - - - (2.2–9.4) - - - - - (3.7–1.70) -
Working status
No 51 32 62.7 19 37.3 1 - 37 72.5 14 27.5 1 - 32 62.7 19 37.3 1 - 32 62.7 19 37.3 1 -
Yes 86 47 54.7 39 45.3 1.4 0.354 49 57.0 37 43.0 2.0 0.068 47 54.7 39 45.3 1.4 0.354 43 50.0 43 50.0 1.7 0.100
- - - - - (0.7–1.8) - - - - - (0.9–4.2) - - - - - (0.7–2.8) - - - - - (0.8–3.4) -
108 58 63.0 40 37.0 1 0.500 68 63.0 40 37.0 1 0.930 64 59.3 44 40.7 1 0.466 63 58.3 45 41.7 1 0.1 -
Extended family 29 11 37.9 18 62.1 2.8 - 18 62.1 11 37.9 1.0 - 15 51.7 14 48.3 1.4 - 12 41.4 17 58.6 1.9 -
- - - - - (1.2–6.5) - - - - - (0.4–2.4) - - - - - (1.6–3.1) - - - - - (0.9–4.6) -
Number of biological children
> 2 76 48 63.2 28 36.8 1 - 50 65.8 26 34.2 1 - 47 61.8 29 38.2 1 - 47 61.8 29 38.2 1 0.100
1–2 61 31 50.8 30 49.2 1.7 0.146 36 59.0 25 41.0 1.3 0.415 32 52.5 29 47.5 1.5 0.269 28 45.9 33 54.1 1.9 -
- - - - - (0.8–3.2) - - - -- (0.7–2.3) - - - - - (0.7–2.9) - - - - - (0.9–3.8) -
Monthly family income (USD)
< 193.5 47 37 78.7 10 21.3 1 - 41 87.2 6 12.8 1 - 33 70.2 14 29.8 1 *0.046 37 78.7 10 21.3 1 -
193.5–322.6 58 32 55.2 26 44.8 3.0 *0.013 32 55.2 26 44.8 5.6 *0.001 30 5.17 28 48.3 2.2. - 27 46.6 31 53.4 4.2 *0.013
- - - - - (1.3–7.2) - - - - - (2.0–15.1) - - - -- (0.9–4.9) - - - - (1.8–10.1) -
> 322.6 32 10 31.3 22 68.8 8.1 *0.011 13 40.6 19 59.4 9.9 *0.001 16 50.0 16 50.0 2.4 *0.032 11 34.4 21 65.6 7.1 -
- - - - - (2.9–22.6) - - - - - (2.9–22.6) - - - - - (0.9–4.9) - - - - - (2.6–19.4) -
EWS of landslide
Poor 84 50 59.5 34 40.5 1 - 55 65.5 29 34.5 1 - 53 63.1 31 36.9 1 - 53 63.1 31 36.9 1 -
Good 53 29 54.7 24 45.3 1.2 0.579 31 58.5 22 41.5 1.3 0.410 26 49.1 27 50.9 1.8 0.105 22 41.5 31 58.5 2.4 *0.013
- - - - - (0.6–2.4) - - - - - (0.7–2.3) - - - - - (0.9–3.6) - - - - - (1.2–4.9) -
Emergency response plan
Poor 79 61 77.2 18 22.8 1 - 65 82.3 14 17.7 1 - 59 74.7 20 25.3 1 - 63 79.7 16 20.3 1 -
Good 58 18 31.0 40 69.0 7.5 *0.001 21 36.2 37 63.8 8.2 *0.001 20 34.5 38 65.3 5.6 *0.001 12 20.7 46 79.3 15.1 *0.000
- - - - - (3.5–16.2) - - - - - (3.7–17.9) - - - - - (2.7–11.8) - - - - - (6.5–34.9) -
Knowledge about natural hazards and landslide
Poor 76 59 77.6 17 22.4 1 - 60 86.8 10 13.2 1 - 57 75.0 19 25.0 1 - 62 81.6 14 18.4 1 -
Good 61 20 32.8 41 67.2 7.2 *0.001 20 32.8 41 67.2 13.5 *0.001 22 36.1 39 63.9 5.3 *0.001 13 21.3 48 78.4 16.4 *0.000
- - - - - (3.3–15.2) - - - - - (5.8–31.8) - - - - - (2.5–11.1) - - - - - (7.0–38.0) -

OR, odds ratio; CI, confidence interval; USD, United States Dollar; EWS, emergency warning system.

, p < 0.005.

Logistic regression analysis of gender, number of biological children, emergency response plans, knowledge about natural hazards and landslides with practice of landslide management.

Variable B SE Wald df p-value OR Lower Upper
Gender (men vs women) 1.273 0.534 5.669 1 0.017 3.6 1.3 10.2
Number of biological children (1–2 vs > 2) 1.160 0.537 4.664 1 0.031 3.2 1.1 9.1
ERP (good vs poor) 2.454 0.537 20.836 1 0.000 11.6 4.1 33.3
Knowledge about natural hazards and landslide (good vs poor) 2.443 0.523 21.798 1 0.000 11.1 4.1 32.1
Constant 3.623 0.682 28.223 1 0.000 0.0 - -

Note: Chi-Square Hosmes andLemeshow 1 737; –2 Lokehood = 102 758; Chi-quare Omnibus Test = 85 929 dan Nagelkerke R Square –0.623.

SE, standard error; OR, odds ratio; CI, confidence interval; df, degrees of freedom; ERP, emergency response plan.

 Discussion

In Indonesia, Community-Based Disaster Management (CBDM) is a critical strategy for preparedness and response, utilising local knowledge and resources to strengthen resilience. Given the country’s high vulnerability to natural hazards such as earthquakes, volcanic eruptions and floods, CBDM is essential for risk mitigation and fostering community self-reliance through community participation, local knowledge, resource mobilisation and capacity building. A key objective of CBDM is to enhance community leaders’ knowledge of disasters, EWS and ERP in the context of landslide management (Ali et al. 2019). Landslide management practice of community leaders influenced by socio-demographic characteristics (gender, education attainment, and monthly income); knowledge about natural hazards and landslides; EWS and ERP. This section highlights the role of four factors affecting landslide management practice and the current research’s role in enriching the landslide disaster management research repertoire in Indonesia.

Socio-demographic characteristics such as gender, educational attainment, and monthly income exhibit notable variances in community leaders’ practices in landslide management. The study showed that the proportion of men is slightly higher than that of women. Many respondents in the study were male community leaders. The Indonesian culture of appointing a community leader in Indonesia is male, and the patriarchal culture encourages many men to become community leaders today. Community leaders are agents of change in changing the disaster preparedness behaviour of the community.

Landslide management practices show significant gender disparities. Compared to adult men, women are at a 14 times higher risk of being victims of disasters. The level of good landslide management practices was found to be higher among men than among women. This difference appears to be influenced by the fact that most men had at least a high school education, were employed, had a monthly income above $322.6, possessed good knowledge about natural hazards and landslides, and had prepared a good contingency plan. This reinforces that women play essential roles across all phases of disaster management. In emergency response, women frequently assist the injured before official responders arrive and contribute significantly to search and rescue operations. During reconstruction and recovery, they organise community celebrations of survival, fostering solidarity and social cohesion (Enarson, Fothergill & Peek 2017).

The management of landslides varies significantly depending on the level of education achieved. This means that educational attainment influences community leaders’ practice of landslide management. Respondents who had completed high school or a higher level of education demonstrated significantly better landslide management practices compared with those who had only completed secondary education or less. This finding is supported by Cahyani and Suharini (2021), and Haristiani et al. (2023), who found that education level influenced preparedness for landslide disasters. High-level education graduates were expected to be more prepared because of their exposure to emergency systems, and education may influence the degree to which individuals process risk mitigation information (Menard, Slater & Flaitz 2011).

Family income influences landslide management practices. Community leaders with monthly incomes between $193.5 and $322.6 exhibited better landslide management practices compared with those whose monthly incomes were below $193.5. This study is consistent with the Zamboni and Martin (2020), which showed that higher income increases the likelihood that households will be prepared and evacuate when necessary. This strengthens the amount of family income supports families in providing items needed to prepare for disasters, such as food reserves, savings, insurance and others that cause families to be better prepared for the impacts that will occur because of disasters (Rohman & Suroso 2013).

The understanding of natural hazards and landslides differs significantly from implementing landslide management based on gender. The proportion of respondents with good knowledge about natural hazards and landslides was higher among men compared to women. The level of good landslide management practices is higher among men than women. This condition is influenced by most men having at least a high school education, working status, a monthly income above $322.6, good knowledge about natural hazards and landslides and a good contingency plan. This conclusion aligns with the findings of Fatmah, Fitrinitia and Ambran (2025), who reported that earthquake preparedness is associated with knowledge. Similarly, Fatmah (2024) found that knowledge about floods correlates with effective flood management. This strengthens that the local community possesses indigenous knowledge to reduce the impacts of landslide disasters (Cahyono, Wuryanta & Lastiantoro 2021). Men’s contingency plans are also better than women’s because men are more responsive to natural hazards, including a quicker response attitude in disaster mitigation efforts than women (Sari & Ridwan 2019). Knowledge plays a crucial role in the preparedness of a community, which shapes an individual’s readiness. Knowledge is the outcome of perception, an individual’s comprehension of objects through their senses, which include sight, hearing, smell, taste and touch (Notoatmodjo 2010).

The EWS does not have any influence on the practices of community leaders in managing landslides. The EWS for landslide primarily relies on a WhatsApp group-based disaster information system. Effective communication and information distribution are essential in reducing the impact of landslide disasters. Initially, the communities used kentongan for communication, but it could have been more effective and efficient, so they switched to WhatsApp. This finding is different from Wardyaningrum (2014), who found that the relationships in a centralised communication network among stakeholders in this area significantly reduce disaster risk by utilising local capabilities. This reinforces that EWS affect community preparedness in landslide disasters. Disaster early warnings that are built or available and affordable to the community can increase community preparedness in dealing with landslide disasters (Suparji, Nugrogo & Surtinah 2022).

Emergency response plans impact the community leaders’ approach to landslide management. The management of landslides differs significantly from efforts to build a disaster-resilient community, as the integration of emergency response planning within landslide management remains relatively low. Respondents with low levels of ERP tended to exhibit poorer landslide management practices. This gap indicates a need to strengthen the role of preparedness and coordinated response in overall landslide risk reduction strategies. This finding aligns with research on the factors influencing volunteer willingness in China, which is at 14.65% (Ma et al. 2021). This is reinforced by emergency response is critical to disaster management practices (before, during and after). Managing disasters and responding to emergencies require efficient coordination and preparedness to mitigate the impacts of disasters and protect human lives (Ardiansyah et al. 2024). Emergency response plans involve aspects of emergency relief skills that significantly affect community preparedness for disasters.

The current research has enriched previous research results on factors related to landslide management practices of community leaders, such as socio-demographic characteristics, knowledge about natural hazards and landslides, EWS, and ERP, but a study on the development of a landslide risk reduction model in landslide-prone areas does not exist yet. Therefore, the research results can be the basis for forming a Community-Based Risk Reduction (CBRR) model of community leaders to improve landslide management practices through ERP, for example, Disaster Prepared Village (KSBs) and Destana Programme.

At the policy level, the CBRR empowerment programme in emergency response parameters in landslide-prone areas can be developed by the provincial, district and city of the Local Disaster Management Authority (BPBDs) in collaboration with the Ministry of Social Affairs, and provincial, city and district social services. In addition, disaster training, including landslide emergency response, landslide mitigation and evacuation simulation, must be provided to KSB members to improve their knowledge, attitudes and skills in dealing with landslides.

 Conclusion

Firstly, the limitations of the study are the small sample size, which resulted in an insufficient representation of landslide management approaches among community leaders in the study’s geographic locations. Secondly. The use of purposive sampling limits the external validity of the findings; therefore, the results cannot be generalised to the broader population or to district- and provincial-level contexts.

The study results indicate that gender and educational attainment were both significantly associated with community leaders’ landslide management practices. Knowledge of natural hazards and landslides had a positive influence on the implementation of good landslide management practice. In this study, it was also found that the presence of an EWS showed no significant effect on landslide management practices. Community leaders who had an ERP were 11.6 times more likely to implement good landslide management practices compared with those without such a plan.

Additional research is needed to investigate the knowledge and landslide management practices of various vulnerable populations – including children, pregnant and breastfeeding women, older adults and individuals with disabilities – regarding landslide disasters. Extending this line of inquiry to other types of disasters is also essential. Intervention studies focusing on landslide management training for both the broader community and vulnerable groups should be conducted, with assessments of changes in management practices following the interventions. In addition, proper implementation of landslide management strategies underscores the need for wider adoption of preparedness and mitigation measures. Such strategies include assembling disaster preparedness kits and participating in training sessions, simulations, seminars and webinars to enhance readiness and mitigation efforts among vulnerable groups and their families.

 Acknowledgements

The authors greatly appreciate the support provided by the University of Indonesia through the Q2 Scopus Publication of the Internal Grant Programme Year 2024. Additionally, the authors express their gratitude to all parties involved in facilitating this study, including the respondents from selected villages of Jakarta, Bogor and Depok Cities, especially to community leaders who actively participated in the research.

Competing interests

The authors reported that they received funding from Universitas Indonesia through the PUTI Q2 Scopus Grant Year 2024, which may be affected by the research reported in the enclosed publication. The authors have disclosed those interests fully and have implemented an approved plan for managing any potential conflicts arising from their involvement. The terms of these funding arrangements have been reviewed and approved by the affiliated university in accordance with its policy on objectivity in research.

 CRediT authorship contribution

Fatmah Fatmah; Visualisation; Data curation, Writing – original draft, Writing – review & editing. Rachmadhi Purwana; Writing – original draft. Khamarrul A. Bin Razak; Writing - review & editing.

 Data availability

The data that support the findings of this study are available from the corresponding author, F.F., upon reasonable request.

 Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

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How to cite this article: Fatmah, F., Purwana, R. & Razak, K.A.B., 2025, ‘Community leaders’ knowledge and practices in landslide management: A case study from Indonesia’, Jàmbá: Journal of Disaster Risk Studies 17(1), a1972. https://doi.org/10.4102/jamba.v17i1.1972