Spatial Typology of Regional Development in Metropolitan PEKANSIKAWAN, Riau Province

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Stages of Scalogram Analysis:

1. Initial Data Processing

The data processing begins with organizing a table by selecting and filtering data based on the villages studied. Next, the data is categorized into facility data and accessibility data to facilitate further analysis. The final stage involves calculating the number of facilities distributed across all villages to evaluate spatial distribution and service coverage.

2. Compilation of Data Matrix

In this analysis, the facility index is calculated using the equation: $I=F / P$ where $I$ represents the facility/factor index, F is the number of facilities, and P is the population per 1,000 people. Next, to obtain the inverse value of the data index, the equation is used: $I^{\prime}=1 / I$ aiming to manipulate several variables in the opposite direction to the level of development. After that, the characteristic index weight is calculated using the formula: $W=I^{\prime} / \sum I^{\prime}$  which allows for comparisons between regions based on the proportion of the normalized facility index. Finally, all variables are normalized using: $I_{\text {norm }}=\left(I-I_{\min }\right) /\left(I_{\max }-I_{\min }\right)$, so that the final result is a standardized index, enabling a more objective and consistent comparative analysis across all studied regions.

3. Regional Level

The studied regions are ranked based on the facility index to obtain a comparative overview of service availability levels. Subsequently, the infrastructure hierarchy is determined by ordering the index values from highest to lowest. This analysis produces the Regional Development Index (RDI) at the village level, which is then categorized into three hierarchical levels and presented in Table 2.

Table 2. Determining the value of the hierarchical interval [47]

The second objective of this study is to identify the spatial utilization of the PEKANSIKAWAN metropolitan area to optimize the economic potential of each region using Rustiadi’s Quantitative Zoning method, based on spatial proximity and spatial compactness [48, 49]. There are three spatial classification methods that can be used in spatial analysis. The first is the Non-Contiguous (NC) method, which does not consider spatial connectivity between territorial units, allowing each region to be analyzed independently. Second, the Contiguous I (C1) method considers the direct spatial connectivity between adjacent regions, making the interaction patterns between areas more visible. Third, the Contiguous II (C2) method not only takes spatial connectivity into account but also applies continuity weights, allowing for a more detailed analysis of the spatial proximity influence between regions. By implementing these methods, the spatial distribution patterns can be analyzed more comprehensively in accordance with the characteristics of interregional connectivity.

The basis for using the contiguous spatial method (C') in this study is used the Euclidean Distance principle for grouping variables that form a typology, considering both proximity and regional characteristic similarities. Compared to the Non-contiguous and Contiguous (C") methods, this approach is simpler, with clear quantitative parameters and no need for data manipulation. This method (C') use Spatial proximity based on geographic coordinates easting X and Northing Y (x, y) and spatial proximity weights (B<1 strong, B>1 weak).

The calculation is performed using the Euclidean distance with the following equation:

1. Univariate:

$\left.D_{i j}=\sqrt{\left(z_i^{\prime}-z_j^{\prime}\right)^2+\beta\left\{\left(X_i^{\prime}-X_j^{\prime}\right)^2+\left(Y_i^{\prime}-Y_j^{\prime}\right)^2\right.}\right\}$                   (1)

2. Multivariate:

$D_{i j}=\sqrt{\begin{array}{c}\left(z_{1 i}^{\prime}-z_{1 j}^{\prime}\right)^2+\left(z_{2 i}^{\prime}-z_{2 j}^{\prime}\right)^2+\cdots \\ +\left(z_{m i}^{\prime}-z_{m j}^{\prime}\right)^2+\beta\left\{\left(X_i^{\prime}-X_j^{\prime}\right)^2+\left(Y_i^{\prime}-Y_j^{\prime}\right)^2\right\}\end{array}}$                         (2)

where, $D_{i j}$  represents the Euclidean distance between locations i and j; $Z_i, Z_j$ are the variable values at locations i and j; X, Y denote the spatial coordinates of each regional unit; β is the spatial continuity weight.

Standardization of Variables:

1. Non-Coordinate Variables,

$Z_{\mathrm{i}}^{\prime}=\frac{Z_i-Z_{\min }}{S D}$                 (3)

$S D=\sqrt{\frac{\sum\left(Z_i-\bar{Z}\right)^2}{n}}$                         (4)

where,, Z_min is the minimum value, $\bar{Z}$ is the average value, and n is the total number of data.

2. Coordinate Variables X and Y,

$X_i^{\prime}=\frac{\left(x_i-x_{\min }\right)^2}{\sum\left(S D_X x S D_Y\right) * 0.5}$                       (5)

$Y_i^{\prime}=\frac{\left(y_i-y_{\min }\right)^2}{\sum\left(S D_X x S D_Y\right) * 0.5}$                    （6） 

By using this approach, spatial analysis can produce a more representative regional classification. Subsequently, the spatial clustering process is carried out using several data processing applications. The best spatial clustering model is determined through the Coefficient of Variation (CV) and K-Means. According to Rustiadi dan Kobayashi (2000), the formula for calculating the CV value is as follows:

$C V=\frac{\sigma^2}{\bar{X}}$                  (7)

where, $\sigma^2$ is the standard deviation of the Euclidean distance between locations and $\bar{X}$  is the average distance. A smaller CV value indicates lower data variability within the cluster. Additionally, a smaller K-Means value signifies consistency within a cluster, indicating that the characteristics within the cluster are more homogeneous.

4.1 The regional development level in the PEKANSIKAWAN metropolitan area

The distribution pattern of regional development indicates a significant disparity within the PEKANSIKAWAN metropolitan area. Sustainable and inclusive regional development is one of the primary objectives in spatial planning and regional economic development. The spatial distribution of regional development levels in the PEKANSIKAWAN metropolitan area highlights interregional imbalances, as illustrated in the map (Figure 2). The red color, representing the highest development hierarchy, is concentrated in Pekanbaru City, while Kampar Regency, Siak Regency, and Pelalawan Regency exhibit a more diverse distribution of development hierarchies. This aligns with the growth center theory, which states that urban areas with more advanced infrastructure tend to become magnets for economic activities [50].

The distribution of development in the PEKANSIKAWAN metropolitan area forms a Hierarchy 1 corridor, which serves as a growth region connecting major activity centers (with Pekanbaru City dominating in Hierarchy 1). This reflects a high level of urbanization and intensive economic activity. The Hierarchy 1 corridor extends across the western part of the PEKANSIKAWAN metropolitan area. The distribution of villages with Hierarchy 1 development levels indicates that the most advanced areas are concentrated along major transportation routes. This finding reinforces the role of infrastructure and primary transport corridors as key drivers of regional growth. The presence of road networks connecting these areas is crucial in supporting accessibility and economic connectivity. Pekanbaru City serves as the primary hub, while Kampar, Siak, and Pelalawan Regencies have the potential to develop as secondary growth centers, supporting agricultural, industrial, trade, and distribution activities.

The distribution pattern of Hierarchy 1 development in villages within the PEKANSIKAWAN metropolitan area also indicates the role of growth corridors in enhancing regional prosperity. Areas along major transportation routes have significant potential to be developed as industrial and agro-industrial centers. These regions can be directed toward becoming industrial clusters based on local resources, particularly in Kampar Regency, through the optimization of supporting infrastructure such as logistics and transportation networks [51]. In the context of more equitable development, a development approach based on local advantages is an effective strategy. Regions with lower development hierarchies can be enhanced through agricultural modernization, the application of innovative technologies, and commodity-based ecotourism. In this way, Pekanbaru City can serve as a catalyst for driving growth in its surrounding areas, fostering a more integrated and sustainable economic ecosystem.

Table 3 shows that Pekanbaru City dominates the category of regions with Hierarchy 1, with 49 villages, reflecting its status as an economic and administrative center. In contrast, other regencies such as Kampar, Siak, and Pelalawan have significantly fewer villages in Hierarchy 1 (a total of only 44), indicating that economic growth centers are still concentrated in Pekanbaru City. The total number of villages in Hierarchy 1 is 93 (16%) out of the total 582 villages in the PEKANSIKAWAN metropolitan area. This has implications for disparities in access to infrastructure, public services, and economic opportunities across the region.

Meanwhile, Hierarchy 2, which represents areas in transition toward more advanced development, is dominated by Kampar Regency with 63 villages, followed by Siak Regency with 33, Pekanbaru City with 23, and Pelalawan Regency with 22. The relatively large number of villages in this hierarchy category, 141 in total (24%) of all villages in the PEKANSIKAWAN metropolitan area, indicates significant potential for these regions to develop more rapidly if supported by appropriate strategic policies, such as improved infrastructure connectivity, strengthened local industrial sectors, and innovation based on key commodities.

In the Hierarchy 3 category, Kampar Regency has the highest number of villages, totaling 166, followed by Pelalawan Regency with 88, Siak Regency with 83, and Pekanbaru City with 11. The total number of villages in Hierarchy 3 is 348, accounting for 60% of the total villages in the PEKANSIKAWAN metropolitan area. This condition indicates that most rural areas within the PEKANSIKAWAN metropolitan region still face significant challenges in development, particularly in terms of accessibility, infrastructure quality, and economic opportunities.

The concentration of Hierarchy I villages in the western corridor of the PEKANSIKAWAN metropolitan area particularly in Pekanbaru City and parts of Kampar and Siak Regencies reflects a pattern of uneven growth. This phenomenon aligns with spatial inequality patterns observed in other metropolitan regions, such as Jabodetabek [52]. In the case of Jabodetabek, Jakarta, as the center of economic and administrative growth, demonstrates strong dominance over its satellite cities, which often face delays in the development of basic infrastructure similar to the conditions observed in Hierarchy II and III villages within the PEKANSIKAWAN metropolitan area. However, there are significant structural differences. Jabodetabek is dominated by the tertiary sector, such as services and finance, whereas the PEKANSIKAWAN metropolitan area—particularly Kampar, Siak, and Pelalawan Regencies—remains heavily reliant on primary sectors such as agriculture, oil palm plantations, and forestry. This indicates that the development challenges in PEKANSIKAWAN are not solely spatial in nature, but also involve sectoral economic transformation that remains uneven.

A comparison can also be made with the MEBIDANGRO area (Medan, Binjai, Deli Serdang, and Karo), where development is more horizontally distributed, largely due to infrastructure connectivity such as the Medan-Binjai toll road, which has facilitated growth in peripheral areas [22]. In the context of PEKANSIKAWAN, interregional connectivity still faces significant challenges, both in terms of infrastructure quality and accessibility between growth centers. The importance of adopting a polycentric development approach in metropolitan planning to reduce inequality [44].

Disparities in access to infrastructure, public services, and economic opportunities in peripheral areas pose major challenges to equitable development. Kampar Regency has the highest number of villages in Hierarchy 3, followed by Pelalawan Regency, Siak Regency, and Pekanbaru City. Most rural areas in the PEKANSIKAWAN metropolitan region still face developmental challenges, such as limited accessibility, inadequate infrastructure quality, and restricted economic opportunities. Therefore, development strategies should focus on increasing investments in sectors that directly contribute to community welfare. Referring to the concept of sustainable development, the integration of the industrial, agricultural, and service sectors must be strengthened to create a more balanced economic ecosystem. As a strategic area in Riau Province, the PEKANSIKAWAN metropolitan region has significant potential for accelerated growth by implementing development policies based on local advantages and regional connectivity. A data-driven approach and well-planned strategies will be key to optimizing the region's economic potential to achieve inclusive and sustainable growth.

4.2 The typology of the PEKANSIKAWAN metropolitan area

Based on the results of the PEKANSIKAWAN typology analysis (Figure 3, weight β=2, best/appropriate model), the PEKANSIKAWAN metropolitan area can be categorized as an area with a combination of complementary urban and rural areas. The classification of the PEKANSIKAWAN metropolitan area consists of three clusters. Cluster 1 is a rural settlement area or traditional village, most of which are located in Kampar Regency (the number of cluster 1 members is 262 villages), which is characterized by dry land forests and non-industrial plantation forests, including natural forests and traditional agricultural lands, which reflect an agrarian and ecologically balanced rural landscape. Cluster 2, which is located in Pekanbaru City (the number of cluster 2 members is 98 villages), includes villages with urban characteristics, characterized by higher population density, advanced infrastructure, and a variety of non-agricultural economic activities, which highlight the urban transformation of rural settlements. In contrast, Cluster 3 includes villages in Siak and Pelalawan Districts (the total number of members of cluster 3 is 222 villages), which are still rural but are heavily influenced by industrial-scale land use, especially large-scale industrial tree plantation concessions and oil palm plantations, which show a strong integration of village life with commercial forestry-based and monoculture agricultural practices Table 5.

Cluster 1 represents a rural area with dominant characteristics of dryland forests and dryland agriculture. The areas within this cluster have moderate population density and human development index (HDI), indicating that development and the level of community welfare are in the medium category. The percentage of built-up land in this area is relatively low, suggesting a limited level of urbanization. However, this region has a high percentage of dryland forests and extensive dryland agriculture, reflecting that the region's economy is still heavily dependent on the forestry and dryland-based agricultural sectors.

Cluster 2 represents an urban area with high population density and HDI, indicating that this region is more advanced in terms of socio-economic aspects and development. The high percentage of built-up land suggests that this area has experienced rapid urbanization, likely dominated by residential areas, infrastructure, as well as business and trade centers. In contrast, dryland forests, industrial tree plantations, and dryland agriculture have very low percentages, indicating that the agricultural and forestry sectors are not the primary factors in the economic structure of this region.

Cluster 3 depicts a rural area that differs from Cluster 1 as it is more dominated by industrial tree plantations and rice fields. The population density and HDI in this area are relatively low, indicating that development and the well-being of its population are still limited. This region has a high percentage of industrial tree plantations and extensive rice fields, suggesting that the commercial forestry and rice farming sectors are the main contributors to the economy of this area. In contrast, dryland forests and built-up land are relatively low, indicating that this region is more focused on the production of industrial forest products and agriculture rather than urban infrastructure development.

The PEKANSIKAWAN metropolitan is a strategic area. The city of Pekanbaru serves as the center of economy and administration, with more advanced infrastructure compared to the surrounding areas. Meanwhile, Siak Regency has strong potential in the plantation and cultural tourism sectors, especially with the presence of the Siak Palace, which is a historical tourist attraction. Kampar Regency is known for its agricultural sector and small-medium industries (SMEs), particularly in agro-industry, including the processing of agricultural products [51]. Meanwhile, Pelalawan Regency has strengths in the forestry and plantation industries, particularly in palm oil, which is the main sector of the region's economy.

Pekanbaru City, as the center of economic and service activities, plays a role in providing markets, infrastructure, and innovation hubs for the surrounding areas. Siak Regency and Kampar Regency function as buffer zones that provide natural resources and labor for the urban area, while Pelalawan Regency serves as a center for resource-based industries that make significant contributions to the regional economy. The integration of these four areas creates a strong economic linkage and requires a holistic development strategy to ensure that each region can develop optimally.

In the context of development, strengthening connectivity between regions is a key factor in supporting the integration of the PEKANSIKAWAN metropolitan area. Improving transportation infrastructure, such as toll roads and logistics routes, is essential to accelerate the distribution of goods and services between regions. Furthermore, policies that encourage investment in the creative industries and technology sectors can also enhance the competitiveness of this area. One of the main challenges in the development of the PEKANSIKAWAN metropolitan area is the infrastructure and accessibility gap between regions. Some areas in Siak Regency, Kampar Regency, and Pelalawan Regency still face limitations in terms of road access and basic facilities, which can hinder investment flows and local economic growth. Therefore, integrated planning between local and central governments is needed to ensure equitable and inclusive development.

Metropolitan PEKANSIKAWAN has great potential to drive economic growth based on regional strengths with proper planning. Collaboration between the government, academia, business actors, and the community is crucial in creating an ecosystem that supports innovation and inclusive sustainable development. Through a targeted and synergistic approach, the PEKANSIKAWAN metropolitan area can develop into a new high-competitiveness economic growth center at both national and international levels. An adaptive, inclusive and integrated planning and development strategy needs to be carried out to achieve the vision of sustainable development [52]. Studies on metropolitan areas indicate that successful development depends on infrastructure integration and inclusive economic development strategies [53, 54].