Smart Village Development Strategy: Central Sulawesi's Pakuli Village Hindered by Low Digital Literacy

Ilustration by AI 

FORMOSA NEWS

The implementation of the smart village initiative in Pakuli Village, Gumbasa District, Sigi Regency, Central Sulawesi, faces major hurdles due to low digital literacy and sub-optimal management of local assets. These findings were revealed in a study conducted by researchers from Pakuan University—Rio Romanda, Lilis Sri Mulyawati, and Mujio—published in Jurnal Multidisiplin Madani (MUDIMA), Volume 6, No. 7 (July 2026 issue). The study highlights that the primary bottleneck in rural digital transformation outside Java Island is no longer mere physical infrastructure, but rather human resource readiness to utilize technology productively.

Addressing the Digital Divide in Rural Areas Outside Java

Smart village frameworks have become a key policy instrument across Indonesia to foster economic self-reliance, improve public service efficiency, and enhance rural living standards. The Regional Government of Central Sulawesi enacted Governor Regulation Number 44 of 2022 concerning the Implementation of the Smart Village Program for 2022–2026, designating twelve pilot villages, including Pakuli Village.

However, empirical evaluations of smart village policies outside Java remain scarce. Previous research overwhelmingly focused on Java, where basic infrastructure and human capital are relatively well-established. Pakuli Village represents a classic rural agrarian profile with 470 hectares of agricultural land, 513 hectares of forest area, and a unique local asset in the form of a Traditional Medicinal Garden. Conversely, 57.09% of its residents have completed only elementary education, creating a pronounced digital divide.

An Integrated Multi-Tiered Evaluation Methodology

To evaluate actual conditions objectively, the research team employed a Mixed Methods Explanatory Sequential Design. The study combined four analytical tools: scoring analysis, spider web visualization via the Cobweb Model, Gap Analysis, and a qualitative SWOT Analysis.

Data collection involved structured questionnaires distributed to 25 purposively selected respondents across five stakeholder groups—village administration, sub-district/district government, community leaders, business actors, and local residents—complemented by in-depth interviews, field observations, and document analysis. The researchers assessed seven smart village dimensions covering 17 operational indicators:

• Smart Governance: Digital public services, information transparency, and citizen participation.
• Smart Economy: Digital entrepreneurship, innovation, and digital training.
• Smart Mobility: Road accessibility, public transportation, and ICT/GIS infrastructure.
• Smart Environment: Waste management, energy efficiency, greening, and conservation.
• Smart People: Digital literacy, education, and citizen creativity.
• Smart Living: Health and education facilities, internet access, and public amenities.
• Smart Tourism: Tourism management and promotion.

All measurement instruments demonstrated solid statistical validity ($r = 0.421 - 0.821$) and high reliability (Cronbach's Alpha 0.92).

Key Findings: Overall Condition Remains Poor

The composite evaluation across the seven dimensions revealed that smart village implementation in Pakuli Village falls into the Poor category, with an overall mean score of 2.23 out of a maximum of 5.00.

The performance across individual dimensions breaks down as follows:

1. Smart Living: Score 3.84 (Good) – Supported by functional educational facilities (2 primary, 1 junior high, and 1 senior high school) and healthcare centers (Puskesmas, Poskesdes, Posyandu).
2. Smart Governance: Score 3.51 (Good) – Backed by an active village website and transparent publication of village fund allocations.
3. Smart Mobility: Score 2.09 (Poor) – Hindered by limited inter-hamlet road connectivity and a lack of public transit.
4. Smart Environment: Score 1.65 (Very Poor) – Lacks structured waste management systems and renewable energy initiatives.
5. Smart People: Score 1.54 (Very Poor) – Plagued by low digital literacy and limited formal educational attainment.
6. Smart Economy: Score 1.52 (Very Poor) – Marked by inactive Village-Owned Enterprises (BUMDes) and an absence of e-commerce channels for local produce.
7. Smart Tourism: Score 1.48 (Very Poor) – The Traditional Medicinal Garden remains unmanaged professionally and lacks digital promotion.

Qualitative findings revealed that previously launched digital public administration tools had to be halted because residents could not navigate them. Similarly, installed public Wi-Fi networks remained largely underutilized. This demonstrates that physical ICT availability does not automatically drive adoption without corresponding human resource capacity building.

Through Gap Analysis, four dimensions were identified as a cohesive "Very High Priority" cluster requiring immediate intervention: Smart Tourism (gap 3.52), Smart Economy (gap 3.48), Smart People (gap 3.46), and Smart Environment (gap 3.35).

Although Smart People ranks third quantitatively, substantively it acts as the underlying root cause. Low digital literacy directly sabotages initiatives across all other dimensions.

Policy Implications and Strategic Roadmap

The SWOT analysis synthesized these findings to recommend a WO (Weakness-Opportunity) or conservative strategy group as the most realistic starting point. This approach leverages external opportunities—such as provincial regulatory backings and academic partnerships—to fix internal structural weaknesses.

Key strategic actions include:

• Digital Literacy Programs: Establishing a Village Digital House to conduct practical digital skills training.
• BUMDes Revitalization: Reactivating Village-Owned Enterprises to operate as digital marketplace hubs for local agricultural commodities (such as cocoa and herbs), reducing reliance on middlemen.
• Edutourism Development: Forming Tourism Awareness Groups (Pokdarwis) to digitize and manage the Traditional Medicinal Garden.
• Community-Based Environmental Action: Instituting local waste management and forest conservation frameworks.

The study offers critical implications for regional policymakers. Designating pilot smart villages must be paired with accurate baseline evaluations rather than applying a uniform approach across villages with distinct needs. Furthermore, program success should be measured by actual digital service utilization by citizens rather than physical infrastructure deployments.

"In rural areas with limited capacity, smart village execution cannot jump straight into technical digitization; it must be preceded by strengthening digital literacy and local institutions as foundational prerequisites," the researchers concluded in their study.

Author Profiles

• Rio Romanda, S.P., M.Si. – Lead author and researcher from Pakuan University specializing in rural area development and local development planning.
• Dr. Ir. Lilis Sri Mulyawati, M.Si. – Lecturer and researcher at Pakuan University focusing on development management, community institutions, and rural public policy.
• Dr. Ir. Mujio, M.Si. – Lecturer and researcher at Pakuan University with expertise in spatial analysis, regional planning, and environmental resource management.

Source Article:

Article Title: Smart Village Development Strategy In Pakuli Village, Sigi Regency, Central Sulawesi Province
Journal: Jurnal Multidisiplin Madani (MUDIMA)
Publication Year: 2026 (Vol. 6, No. 7, July 2026)
DOI: https://doi.org/10.55927/mudima.v6i7.108
URL : https://journalmudima.my.id/index.php/mudima