West Science Information System and Technology Vol.
No.
April 2025, pp.
Smart Village Initiative for Drug-Free Communities: A TechnologyBased Approach in West Java Ismail1.
Felecia2.
Anisa Kurniatul Azizah3.
Diana Rahmawati4
1,3,4
Universitas Bhayangkara Surabaya
2Universitas Kristen Petra Article Info
ABSTRACT
Article history:
The Smart Village Initiative in West Java leverages technology to combat drug-related issues and foster drug-free communities.
This study employs a quantitative analysis with 150 respondents using a Likert scale .
Ae.
, analyzed via Structural Equation Modeling-Partial Least Squares (SEM-PLS).
The findings reveal that technological interventions significantly enhance drug prevention outcomes and community engagement, with community engagement mediating the relationship between technology and outcomes.
The results demonstrate the initiative's effectiveness in promoting awareness, participation, and safety within communities.
These findings underscore the potential of integrating technology and communitydriven approaches to address complex social issues, offering a scalable model for other regions.
Future research should explore long-term impacts and adaptations for diverse contexts.
Received April, 2025 Revised April, 2025 Accepted April, 2025 Keywords:
Smart Village Initiative.
Drug-Free Communities.
Technological Interventions.
Community Engagement This is an open access article under the CC BY-SA license.
Corresponding Author:
Name: Ismail Institution: Universitas Bhayangkara Surabaya Email: ismail@ubhara.
INTRODUCTION
1 Background Drug abuse remains a critical challenge to public health, safety, and socioeconomic stability worldwide, with rural areas in Indonesia, such as West Java, facing pronounced issues due to limited resources for prevention and rehabilitation.
This problem is exacerbated by societal stigma, inadequate rehabilitation infrastructure, particularly affecting youth and vulnerable IndonesiaAos Law No.
35 of 2009 on Narcotics provides for rehabilitation, but its implementation is hindered by gaps and societal stigma, necessitating reforms that prioritize rehabilitation over punitive measures and include judicial education and improved facilities .
, .
Comparative studies with countries like Portugal and Switzerland underscore the importance of clearer legal guidelines and robust rehabilitation frameworks .
Family resilience and community-driven programs play a vital role in reducing relapse rates among adolescents, with theories like BanduraAos social learning and SutherlandAos differential association emphasizing family support in recovery .
, .
Furthermore, socioeconomic factors such as poverty and economic crises exacerbate drug abuse, contributing to crime and health issues like HIV/AIDS, highlighting the need for Journal homepage: https://wsj.
westscience-press.
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php/wsist West Science Information System and Technology A 10 integrated community support and economic opportunities to address these challenges .
The Smart Village Initiative in Indonesia offers a strategic and technologydriven approach to combating drug abuse, integrating digital tools to enhance real-time monitoring, and resource allocation while aligning with the nation's goals of digital By fostering leadership, culture, and governance through digital transformation, this initiative empowers rural communities to take proactive and collective action against drug abuse .
, .
Emerging technologies such as IoT.
AI, and big data enable real-time monitoring and timely interventions, as demonstrated in pilot projects like Desa Saradan, which utilize digital tools for resource mapping and administrative services adaptable to drug abuse prevention .
, .
Moreover, the Sustainable Development Goals (SDG.
by promoting inclusive development and ensuring no village is left behind, as seen in Desa Jatibarang, where digital platforms are used for education and small businesses, fostering readiness for broader social welfare initiatives, including drug abuse prevention .
, .
Drug abuse remains a critical issue in Indonesia, particularly in rural areas like West Java, where limited access to prevention and rehabilitation services exacerbates its impact on community safety, productivity, and economic stability.
This alarming rise in drugrelated cases, especially among youth and low-income inadequacy of traditional approaches, such as law enforcement and public awareness campaigns, which have demonstrated limited long-term success .
, .
Challenges like high relapse rates, reaching up to 80% among adolescents, further emphasize the need for innovative strategies .
Strengthening family resilience, as supported by social learning theories, is critical for preventing relapses .
Additionally, empowering communities through education and fostering cross-sector collaboration can address .
Public-private partnerships, integrating government and private sector efforts, provide a pathway for enhancing rehabilitation services and aligning with public health mandates .
These multifaceted strategies are essential for tackling the root causes of drug abuse and fostering sustainable solutions.
Despite various initiatives to reduce drug abuse in West Java, challenges persist in effectively reaching rural communities.
These challenges include limited infrastructure, campaigns, and a lack of integrated systems for monitoring and reporting drug-related Additionally, rural communities often lack the tools and platforms needed to actively participate in drug prevention efforts.
This disconnect hampers the effectiveness of existing programs and allows drug abuse to remain a persistent threat.
Current strategies also fail to fully harness the potential of digital technology, which could bridge gaps in communication, resource allocation, and community engagement in these underserved 2 Research Objective The primary objective of this study is to evaluate the impact of the Smart Village Initiative in fostering drug-free communities in West Java through a technology-based This research aims to:
Analyze enhancing community awareness and participation in anti-drug efforts.
Investigate the role of digital platforms in improving real-time reporting and resource management for drug prevention.
Provide actionable insights and recommendations for policymakers and stakeholders to optimize and replicate the Smart Village model in other regions.
Vol.
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West Science Information System and Technology LITERATURE REVIEW 1 Drug Abuse and Its Impact on Communities Drug abuse in rural areas of Indonesia, such as West Java, poses unique individuals, families, and communities.
Limited access to healthcare, rehabilitation, and awareness programs exacerbates the issue, disproportionately affecting youth and low-income groups, as highlighted by the National Narcotics Board (BNN).
This crisis leads to emotional distress, financial strain, and the breakdown of trust within families, often resulting in child neglect or abuse .
, .
Additionally, it burdens public health systems and law enforcement due to productivity, and higher crime rates, especially in resource-scarce rural areas .
, .
Challenges like high relapse rates among adolescents, reaching up to 80%, underscore the need for robust family support systems community-based (Christiana et al.
, 2.
Comprehensive strategies combining prevention, education, treatment, and rehabilitation are essential, with family resilience playing a crucial role in relapse prevention .
, .
Communitybased initiatives, such as those by UF/IFAS, focus on adolescent prevention efforts, addressing the specific needs of rural communities .
2 Community-Based Interventions in Drug Prevention Community-based approaches to combating drug abuse are effective due to their reliance on local resources, cultural understanding, and community engagement, with initiatives focusing on collective action and empowerment through awareness campaigns and local leadership.
The success of these programs is amplified when tailored to the cultural and social dynamics of the target population, as highlighted by .
For example, urban programs benefit from diverse intervention tools and resources, while rural efforts excel in personalized, community-centric A 11 embedded in local culture .
In Africa, leveraging cultural practices and community structures, such as peer education and local partnerships, has proven effective .
However, challenges like inconsistent participation, resource limitations, and lack of stakeholder cooperation, as seen in South African townships, can hinder success .
Integrating technology into these initiatives offers promising solutions by expanding reach and enhancing engagement.
Mobile apps, social media campaigns, and mobile health solutions have demonstrated potential in delivering prevention and intervention services, especially in regions with high mobile phone use .
3 The Role of Technology in Social Interventions Digital technologies have emerged as powerful tools in addressing social challenges, including drug abuse, by dissemination, and community engagement.
In rural Indonesia, where internet penetration is growing, initiatives like the Smart Village model leverage these technologies to combat drug abuse effectively.
Digital platforms facilitate real-time communication and resource sharing, making them highly effective in addressing complex issues, particularly in underserved areas where traditional methods may fall short.
Digital health tools, such as telemedicine and mobile health applications, overcome geographical and economic barriers, improving healthcare access and fostering health equity .
Information Communication Technologies (ICT.
information and treatment, appealing to interventions showing potential in reducing alcohol and drug-related harms .
Social media platforms play a critical role in awareness and educational content while enhancing community engagement, though they should complement traditional outreach efforts .
, .
Additionally, computerbased interventions offer new possibilities for drug abuse prevention, particularly for youth.
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West Science Information System and Technology though further evaluations are needed to establish their efficacy .
4 The Smart Village Concept The Smart Village concept leverages digital technologies to enhance rural life, offering a promising platform for drug prevention through education, real-time By integrating technologies such as the Internet of Things (IoT) and electronic sensor devices.
Smart Villages create interconnected communities that facilitate real-time communication, efficient resource management, and data sharing, which are crucial for implementing drug prevention programs .
, .
These technologies empower communities through education, and economic opportunities, fostering an environment supportive of drug prevention initiatives.
Smart Villages also promote innovative education systems, disseminating drug prevention content and raising awareness among residents through digital platforms .
, .
Enhanced healthcare infrastructure allows for better monitoring and reporting of drug-related incidents, while real-time data collection aids in timely interventions .
, .
empowering residents and supporting Smart Villages effectively coordinate and implement community-driven drug prevention strategies .
5 Research Gaps While existing literature highlights community-based potential of technology, there is a lack of research on the integration of these elements in addressing drug abuse in rural Indonesia.
Most studies focus on urban settings or examining the specific challenges and This study bridges these gaps by evaluating the Smart Village InitiativeAos role
in creating drug-free communities in West
Java, contributing to the growing body of technology-driven
METHODS
1 Research Approach This study employs a quantitative research design to evaluate the impact of the Smart Village Initiative on fostering drug-free communities in West Java.
The focus lies on engagement, and drug prevention outcomes, with Structural Equation Modeling - Partial Least Squares (SEM-PLS) serving as the primary analytical tool to examine these relationships and test the proposed The target population comprises community members residing in rural areas of West Java where the Smart Village Initiative has been implemented.
A purposive sampling technique was used to select 150 respondents who have directly participated in or benefited from the initiative, ensuring representation across various demographic groups, including age, gender, and socioeconomic status, to capture diverse 2 Data Collection and Analysis Data were collected using a structured questionnaire divided into three main sections: Technological Interventions.
Community Engagement.
Drug Prevention Outcomes, with responses recorded on a Likert scale ranging from 1 (Strongly Disagre.
to 5 (Strongly Agre.
The questionnaire underwent pretesting for clarity, reliability, and validity before fullscale data collection, which involved face-toface interviews and online surveys, facilitated by trained enumerators adhering to ethical Analysis was conducted using SEM-PLS with SmartPLS 3 software in three stages: .
Measurement Model Assessment for reliability and validity, including CronbachAos alpha and AVE.
Structural Model Assessment to test hypotheses by analyzing path coefficients, t-statistics, and Rsquared values.
Mediation Analysis to explore the role of community engagement in Vol.
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West Science Information System and Technology A 13 prevention outcomes.
1 Demographic The demographic profile of the 150 respondents surveyed is summarized below, representing diverse backgrounds to provide a comprehensive view of the community involved in the Smart Village Initiative.
RESULTS AND DISCUSSION
Figure 1.
Distribution Sample The study's respondents comprised 1 Internal Consistency Reliability 150 individuals, with a gender distribution of Internal consistency reliability was 84 males .
%) and 66 females .
%).
Age evaluated using Cronbach's Alpha and groups included 53 respondents .
%) aged Composite Reliability (CR), with both metrics 18Ae30 years, 68 respondents .
%) aged 31Ae45 surpassing the threshold of 0.
70 for all years, and 29 respondents .
%) above 45 In terms of education, 45 respondents measurement of the intended concepts.
The .
%) had primary education, 75 respondents Cronbach's Alpha and CR values were 0.
%) had secondary education, and 30 911 for Technological Interventions, respondents .
%) had tertiary education.
842 and 0.
897 for Community Engagement.
Regarding 896 and 0.
933 for Drug Prevention respondents .
%) were employed, 45 Outcomes, respectively.
%) were self-employed, and 2 Convergent Validity 15 respondents .
%) were unemployed.
Convergent validity was assessed 2 Measurement Model Assessment using Average Variance Extracted (AVE).
The measurement model assessment with all constructs achieving AVE values evaluates the reliability and validity of the above the acceptable threshold of 0.
This constructs used in this study.
It ensures that indicates that the items accounted for a the instruments accurately measure the substantial portion of the variance within intended variables and are suitable for their respective constructs.
The AVE values subsequent structural model analysis.
The 681 for Technological Interventions, assessment focused on three key criteria:
632 for Community Engagement, and 0.
internal consistency reliability, convergent for Drug Prevention Outcomes.
validity, and discriminant validity.
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West Science Information System and Technology A 14 3 Loading Factor Analysis between the indicator and its construct.
In this The loading factor analysis assesses study, all indicators demonstrated acceptable the extent to which each indicator contributes loading values, confirming their reliability in to its respective construct.
A loading factor measuring the constructs.
value above 0.
7 indicates a strong relationship Table 1.
Loading Factors Indicator Loading Factor TI1 (Mobile App Usag.
TI2 (Online Reporting Syste.
TI3 (Community Training via Technolog.
TI4 (Access to Real-Time Informatio.
CE1 (Participation in Awareness Campaign.
CE2 (Attendance at Community Meeting.
CE3 (Feedback Contribution via Platform.
CE4 (Volunteer Involvement in Initiative.
DPO1 (Reduction in Drug Usage Case.
DPO2 (Increased Awareness About Drug.
DPO3 (Community Reports on Drug Incident.
DPO4 (Community Perception of Safet.
All indicators displayed loading Discriminant validity was assessed factor values above the acceptable threshold using the Fornell-Larcker criterion, which requires that the square root of the AVE for contribution to their respective constructs.
each construct be greater than the correlations The high loading factors confirm the between the construct and other constructs.
suitability of the selected indicators in The results met this criterion, indicating good capturing the essence of each construct.
discriminant validity.
Table 2.
Discriminant Validity Construct
DPO
Technological Interventions 0.
Community Engagement Drug Prevention Outcomes 0.
3 Structural Model Assessment effects evaluated the immediate relationships The structural model assessment between independent and dependent variables, while indirect effects explored the constructs to test the study's hypotheses, mediating role of Community Engagement in analyzing both direct and indirect effects the relationship between Technological through path coefficients, t-statistics, and the Interventions Drug Prevention significance of relationships using SEM-PLS Outcomes.
with bootstrapping .
Direct Table 3.
Direct and Indirect Original tpPath Sample Statistic Value H1: Technological Interventions Ie Drug Prevention <0.
Outcomes H2: Community Engagement Ie Drug Prevention Outcomes 0.
<0.
H3: Technological Interventions Ie Community Engagement 0.
<0.
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West Science Information System and Technology H4: Technological Interventions Ie Community Engagement Ie Drug Prevention Outcomes <0.
The SEM-PLS ( = 0.
551, t = 7.
453, p < 0.
, while the significant relationships among technological mediated pathway through community interventions, community engagement, and involvement ( = 0.
221, t = 4.
526, p < 0.
drug prevention outcomes.
Technological highlights the synergistic effect of integrating interventions directly enhance prevention technology with active participation.
These efforts ( = 0.
452, t = 6.
782, p < 0.
by findings stress the need for combining improving resource access, communication, community-driven and monitoring.
Community engagement strategies to combat drug abuse effectively.
also positively impacts outcomes ( = 0.
409, t The total effects combine direct and = 5.
897, p < 0.
, emphasizing the indirect effects to assess the overall impact of importance of participation and collaboration.
Technological Interventions and Community Furthermore, technology fosters engagement Engagement on Drug Prevention Outcomes.
Table 4.
Total Effect Total Effect tpPath Result Statistic Value Technological Interventions Ie Drug <0.
Significant Prevention Outcomes Community Engagement Ie Drug Prevention <0.
Significant Outcomes The total effects analysis reveals the combined direct and indirect influences of technological interventions and community engagement on drug prevention outcomes.
Technological substantial impact ( = 0.
671, t = 8.
212, p < .
, emphasizing the importance of integrating tools like IoT devices, mobile applications, and digital platforms to enhance prevention efforts directly and through community engagement.
This highlights technology's role in improving accessibility, coordination, and monitoring to address drug abuse effectively.
Similarly, community engagement significantly contributes to sustainable drug prevention outcomes ( = 402, t = 5.
897, p < 0.
by fostering participation, collaboration, and awareness among community members.
Together, these findings underscore the critical interplay between technological solutions and active community participation in combating drug The Coefficient of Determination (RA) and Predictive Relevance (QA) values highlight the model's explanatory and Community Engagement has an RA of 0.
30, indicating that 30% of its variance is explained by Technological Interventions, while Drug Prevention Outcomes have an RA of 0.
showing that 58% of their variance is Technological Interventions and Community Engagement.
The QA values, derived through blindfolding, further validate the model's predictive relevance, with Community Engagement achieving a QA of 0.
24 and Drug Prevention Outcomes a QA of 0.
Both QA values exceed zero, confirming the model's strong predictive relevance for its endogenous constructs.
DISCUSSION
The underscores the strong relationships between economic factors, social support, and health service accessibility in drug abuse prevention, affirming the initiative's scalability and relevance for policy implementation in diverse regions.
This is particularly evident in urban communities in East Java, where these factors are closely intertwined with successful drug misuse interventions.
The findings suggest the model's adaptability to various socio-economic and cultural contexts, making Vol.
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West Science Information System and Technology A 16 it highly relevant for broader policy applications aimed at achieving drug-free Addressing these dimensions holistically can significantly enhance the effectiveness of interventions .
Key components of the structural model include economic factors, social support, and health service accessibility.
Economic factors play a pivotal role, as economic inequality impacts access to resources and support systems critical for intervention success .
Social support emerges as another essential element, with community-based initiatives fostering robust social networks and engagement proving effective in drug abuse prevention .
, .
Additionally, health service accessibility prevention and treatment efforts, highlighting the necessity of strengthening healthcare infrastructure .
The scalability of the model is exemplified by programs like the Drug-Free Communities Support Program in the US, which employs multi-sectoral collaboration and youth engagement strategies adaptable to other regions .
, .
, .
Similarly, culturally rooted strategies in Africa, such as peer education and partnerships with local organizations, demonstrate the model's flexibility in addressing region-specific needs .
These insights emphasize the importance of incorporating cultural relevance and community collaboration into intervention Technological interventions also significantly enhance drug prevention Tools such as mobile applications, online reporting systems, and real-time information access enable communities to identify and address drug-related activities effectively, fostering transparency and Policymakers prioritize investing in technology-driven solutions while implementing training programs to maximize the community's ability to utilize these tools effectively.
The findings align with prior research on addressing complex social challenges.
Community engagement, another critical factor, significantly improves drug prevention outcomes.
Active participation in campaigns, meetings, and volunteer efforts fosters a collective commitment to combating Moreover, engagement mediates the relationship between technological interventions and outcomes, amplifying the impact of technology when paired with participatory These findings highlight the importance of hybrid strategies combining technological tools with active community Continuous evaluation and refinement of these initiatives are essential for sustaining their effectiveness and scalability in different regions.
The findings align with West Java's policy objectives of creating drug-free communities through innovative and inclusive strategies.
By leveraging technology and fostering community participation, the initiative contributes to broader social and developmental goals.
CONCLUSION
The Smart Village Initiative in West Java highlights the transformative impact of combining technology and community collaboration in addressing drug-related Technological interventions, such as mobile applications and online reporting systems, enhance drug prevention outcomes by fostering community awareness and Community engagement plays a vital role, both directly contributing to drug prevention efforts and technological tools and their outcomes.
This importance of aligning technology-driven The relationships, showcasing high explanatory and predictive power.
These findings affirm the initiative's scalability and relevance for policy implementation in other regions Vol.
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West Science Information System and Technology A 17 drug-free Policymakers encouraged to integrate technology with participatory approaches, tailoring programs to fit local cultural and contextual dynamics.
Future research should explore the sustainability of such initiatives through longitudinal studies, examine the potential of emerging technologies, and refine strategies to adapt to diverse community settings.
This research underscores the transformative potential of technology-enabled community initiatives in overcoming critical social
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