The Integration of Region Development Planning in Donggala Regency, Central Sulawesi Province, an Underdeveloped Region in Indonesia

Case of Pontianak City, Indonesia

Abstract

This study aims to identify key sectors suitable for development to promote economic growth and to assess economic growth pattern of Donggala Regency. This study aims also to determine the primary sectors that should be accorded development priority in Donggala Regency. Data was collected through documentation and questionnaire methods, which were subsequently analyzed using Location Quotient (LQ), Klassen Typology, and Analytical Hierarchy Process (AHP). The LQ analysis showed the presence of six basic sectors in Donggala Regency. Furthermore, the Klassen Typology identified quadrant I which included mining and quarrying, as well as government administration, defense, and social security sectors as mandatory. Results further showed that quadrant II comprised the agricultural, forestry, fisheries, construction, wholesale and retail trade, along with car and motorcycle repair sectors. Additionally, the AHP results showed mining and quarrying as priority sectors within Donggala Regency.

Introduction

Donggala Regency is an extensive area of 5,275.69 km² and comprises 16 districts. Among these districts, the Rio Pakava sub-district has the largest expanse, spanning 872.16 km² or 16.53% of the total land area. The Banawa Tengah District, on the other hand, holds the smallest area, covering 74.64 km² or 1.41% of the total area of regency. Donggala Regency, situated in the heart of Central Sulawesi Province, holds a unique position. It is one of the three underdeveloped area and is located on the Sulawesi mainland. Furthermore, regency has the highest poverty rate within Central Sulawesi Province.

The geographical location of Donggala Regency spans from 0^o30' North Latitude to 2^o20' South Latitude, and 119^o45' to 121^o45' East Longitude (Figure 1). The geographic attributes of the regency allow it to be classified into two regions. First, the West Coast includes the western coast of Sulawesi Island, extending from the northern border of Palu City to the southern border of Tolitoli Regency. In the region, sub-districts, such as Labuan, Tanantovea, Sindue, Sindue Tombusabora, Sindue Tobata, Sirenja, Balaesang, Balaesang Tanjung, Dampelas, Sojol, and North Sojol, offer substantial marine resources, particularly in terms of fisheries, mining, and fertile land suitable for agriculture. Second, the Banawa region is situated along the Palu Bay coast and a portion of the Makassar Strait. The region is separated from the west coast and shares its southern border with Pasangkayu Regency in West Sulawesi Province. Within the Banawa region, districts such as Banawa, South Banawa, Central Banawa, Pinembani, and Rio Pakava sub-districts have fertile conditions for the plantation sub-sectors. The districts also hold potential for providing environmental services and are rich in marine fisheries and aquaculture, particularly pond fisheries (Central Statistical Agency of Central Sulawesi, 2019). The initial step of the Donggala Regency toward industrialization is firmly grounded in development of the agricultural sectors, specifically in food and horticulture, plantations, fisheries, and marine sub-sectors.

Figure 1. Map of Donggala Regency in the Central of Indonesia Based on District Locations (arrow)

The Gross Domestic Region Product (GDRP) growth rate, experienced fluctuations between 2014 and 2018 based on data from the Central Statistics Agency (CSA) of Donggala Regency. In 2014, GDRP saw growth of 5.86%, with the electricity and gas procurement sectors making the largest contribution at 14.34%. The GDRP growth further increased to 5.99% in 2015, with mining and quarrying contributing the most at 15.55%. However, 2016 saw a 4.32% decrease due to a reduction in the number of sectors, along with electricity and gas procurement declining to 6.19% from 14.15% in 2015. The GDRP growth of Donggala Regency rebounded to 5.27% in 2017, with mining and quarrying as the largest contributor at 12.83%. In 2018, growth declined once again by 2.89%, with the mining and quarrying sectors experiencing a 1.38% decrease from its 12.83% performance in the previous year.

The contribution given by each sector to region GDRP plays a crucial role in increasing economic growth and fostering development. The increase in economic growth positively impacts the well-being and prosperity of the people. To achieve such region growth, the role of the government is crucial in formulating strategies and plans that adapt to the annual shifts in economic sectors. Donggala Regency had a population of 301,592 people in 2019, ranking as the third most populous region in Central Sulawesi Province. Therefore, the local government is expected to absorb the abundant labor force to enhance the welfare and prosperity of its residents.

Based on the aforementioned contextual background, the following questions are formulated. Firstly, what are the fundamental sectors to be cultivated in Donggala Regency to support economic growth? The sectors serve as the foundation for the government formulation of the Local Long-Term Development Plan (LLTDP) for the 2025-2045 period and the Local Medium-Term Development Plan (LMTDP) for the 2025-2029 period, with a focus on spatial and sustainable development in accordance with Presidential Regulation Number 59 of 2017. Secondly, how does economic growth pattern in Donggala Regency compare with that of the 12 regions in Central Sulawesi Province? The comparison aims to stimulate spatial interaction among region, contributing to the realization of Central Sulawesi Incorporated. Thirdly, which sectors should be designated as the top priority in Donggala Regency? The sectors constitute the basis for the government preparation of the LLTDP for the 2025-2045 period and the LMTDP for the 2025-2029 period. The preparation emphasizes spatial considerations and sustainable development in line with Presidential Regulation Number 59 of 2017.

This study aims to, first, identify key sectors suitable for development to promote economic growth in Donggala Regency. The identification serves as the cornerstone for the government formulation of the LLTDP for the 2025-2045 period and the LMTDP for the 2025-2029 period, taking into account spatial and sustainable development principles as stipulated by Presidential Regulation Number 59 of 2017. Second, to assess economic growth pattern of Donggala Regency in comparison to other region in Central Sulawesi. The comparative analysis is essential for fostering spatial interaction among the 13 regions, contributing to the overarching vision of Central Sulawesi Incorporated. Third, to determine the primary sectors that should be accorded development priority in Donggala Regency. The sectors form the basis for the government preparation of the LLTDP for the 2025-2045 period and the LMTDP for the 2025-2029 period, with a focus on spatial and sustainable development, as mandated by Presidential Regulation Number 59 of 2017.

Literature Review

Economic development signified an increase in a community’s per capita income, where the Gross Domestic Product (GDP) growth rate in a given year surpassed the population growth rate. The success of economic development was measured by three main values, including enhancing the community capacity to meet basic needs, bolstering self-esteem, and nurturing the choice of the people for freedom from servitude as a fundamental human right.

The long-term increase in per capita income alone is an insufficient indicator of economic development. Economic development includes not only economic growth and poverty alleviation but also the enhancement of social structures, institutional systems, and changes in attitudes and social behavior (Todaro, 2015). This perspective showed the necessity of development objectives being rooted in the improvement of people or community well-being, often referred to as depoperization (Adelman, 1975). Meanwhile, some studies describe economic growth to be a rise in GDP or GNP without considering the population growth rate, which neglects changes in economic structure and institutional improvements. The concept of depoperization by Adelman implied striving for “equity in growth,” which incorporated increasing social protection and empowering the community toward prosperity.

Jhingan (Jhingan, 2012) and Sukirno (Sukirno, 1994) predominantly emphasized economic growth paradigm as a driving force in development, without taking into account the environmental consequences of excessive natural resource exploitation. In such cases, the abundance of endowment resources could become a curse rather than a benefit due to failed market mechanisms and weak institutions. Countries that relied solely on extractive industries often pushed their populations into poverty and the breakdown of socio-economic institutions (Acemoglu & Robinson, 2012).

The prevalence of basic activities in an area enhanced revenue streams and boosted demand for goods and services, and vice versa. Economic analysis revolved around identifying the revenue base because a greater number of basic activities stimulated revenue flow and the demand for goods or services, leading to an increase in non-basic activities. Conversely, a decline in basic activities reduced the income flow and the demand for non-basic products (Adisasmita, 2005). According to economic base theory, region economic growth was driven by the increase in exports from both basic and non-basic activities, but it was fostered by basic activities.

Data analysis was used to determine whether an activity was considered basic and non-basic. The assumption was that activity was basic when 70% or more of the products were expected to be sold outside region, while it was considered non-basic when 70% or more of the products were estimated to be sold locally. For activities where the basic and non-basic proportions were not significantly distinct, a combination of the assumption and direct methods was adopted to establish a more comprehensive classification.

Donggala Regency was among the three underdeveloped region in Central Sulawesi and part of the 62 underdeveloped region in Indonesia, as determined by Presidential Regulation Number 63 of 2020, focusing on Disadvantaged Region for the years 2020-2024. The assessment of underdeveloped region was based on six key criteria, including the community economic, quality of human resources, facilities and infrastructure, region financial capacity, accessibility, and region characteristics. Out of the 16 sub-districts in Donggala Regency, 15 were classified as rural areas (Ministry of Villages, Development of Disavantaged Region and Transmigration, 2020). In the contemporary era, the world faced collective crises that transcended national borders, such as the challenges posed by COVID-19 and climate change. Process of urban development, driven by industrialization, has given rise to issues in rural region, both at the national and global levels. Nations worldwide confronted problems that necessitated both personal and international solutions international solutions (Son, Yonghoon, 2022).

Donggala Regency did not bear the burden of overcoming its challenges in isolation. Regency, on the other hand, had to cultivate a transformative mindset and instigate internal development efforts. Within Donggala District, a lack of consensus and coherence existed in development planning because the main region entities lacked a shared understanding between planning agencies, agencies responsible for generating local revenue, and agencies responsible for expenditure. Many region entities did not comprehend the significance of the Money Follow Program, initiated by President Jokowi in 2017 as a replacement for the Money Follow Function. In the context of planning, all regions adhered to the framework outlined in Law Number 25 of 2004, governing the National Development Planning System, alongside Republic of the Indonesian Government Regulation Number 8/2008, delineating the Stages, Procedures for Compilation, Control, and Evaluation of Development Plans, as well as the operational guidelines specified in Minister of Home Affairs Regulation Number 86 of 2017.

The Republic of Indonesia Law Number 23 of 2014 led to various derivative regulations, which became an essential reference for region administrators in the preparation of planning and budgeting documents. This ensured that planning and budgeting remained unsynchronized. An essential among the regulations was Government Regulation Number 18 of 2016, which was in line with Article 232 Paragraph (1) of Law Number 23 of 2014. Government Regulation Number 12 of 2017 elaborated on the mandates of Article 353 and Article 383 Law Number 23 of 2014, providing guidance and supervision for the integration of region government. Government Regulation Number 38 of 2017, focused on Region Innovation, translated the provisions within Article 390 of Law 23 of 2014. Furthermore, Government Regulation Number 45 of 2017 addressed Community Participation in the Integration of Region Government, in line with Article 354 Paragraph (5) of Law Number 23 of 2014. Government Regulation Number 2 of 2018 concerning Minimum Service Standards, elaborated on the mandate of Article 18 Paragraph (1) of Law Number 23 of 2014. The government regulations were further detailed in Minister of Home Affairs Regulations, including Minister of Home Affairs Regulation Number 55 of 2017, Minister of Home Affairs Regulation Number 86 of 2017, Minister of Home Affairs Regulation Number 90 of 2019, Minister of Home Affairs Regulation Number 40 of 2020, and Minister of Home Affairs Regulation Number 64 of 2020.

In the context of Donggala, the coordination of planning documents could be quite challenging. The role of the Local Government Budget Team (LGBT) had not been optimally used, particularly because the necessary system had not been fully established. Both the Local Planning Information System (LPIS) and the Local Financial Information System (LFIS) had not been seamlessly integrated into the working procedures of the state civil apparatus (SVA) and lacked a systematic interrelationship. The situation arose because Donggala had been more focused on the role of actors rather than digitizing development system. Therefore, synchronization remained elusive, mainly due to ego taking precedence over the primary tasks and functions. Development Planning process was not fully in line with the Local Government Work Plan (LGWP) document, which was closely connected to the Provincial Government Work Plan and the Central Government Work Plan (CGWP), but the integration of the document had not been realized. Harmonization implied that the regulations issued by the Central Government should foster a unified understanding among state administrators in various region. It ensured that discussions at the Local People's Representative Council (RPRC) primarily focused on substantive matters.

Since 2017, the Indonesian development planning transitioned from the Money Follow Function to the Money Follow Program, and subsequently, the Follows Result Program. The Money Follow Program was executed comprehensively, with standardized planning structured thematically according to the annual themes of each region in the LMTDP. The integration ensured the connection with planning at higher levels, including the LLTDP, which was referenced by the LMTDP. The LMTDP was referred to as the Local Strategic Plan (LSP), which was connected to the Annual Work Plan (AWP). The AWP served as the macro reference for the LGWP, which was further linked to the Budget Common Policy and Temporary Budget Priority Ceilings (BCP-TBPC). BCP-TBPC was connected to the List of Budget Execution (LBE), the Budget Activity Plans (BAP), and the integration of the Terms of Reference (TOR) for each sub-activity of Region Apparatuses Organizations (RAO). Locations for such activities were determined based on the evaluation results or through e-planning. The presence of Region Poverty Management Plan (RPMP), which was in line with the Money Follow Program paradigm, represented a viable solution for realizing the vision and mission of region leaders.

The coordination of planning incorporated various documents, such as the 2021-2026 district/city LMTDP documents, the 2021-2026 Central Sulawesi Provincial LMTDP documents, the LSP documents for each RAO regency/city, and the LSP for each RAO in Central Sulawesi Province for 2021-2026. These are combined with the AWP of regency/city of RAO for the 2021-2026 period, the AWP of the RAO of Central Sulawesi Province for the 2021-2026 period, regency/city LGWP for the 2021-2026 period, and the Central Sulawesi Provincial LGWP for 2021-2026. The coordination simplified the integration of Sub-Region Assistance Activities linked to Affairs/Programs and Activities based on proposals with measurable target indicators for each year. The connection also facilitated the evaluation of the Local Development Performance Indicator (LDPI), including those that has been achieved, surpassed, or remain unattained, enabling the integration of appropriate and innovative strategies.

Article 95 of Regulation of the Minister of Home Affairs Number 86 of 2017, which outlined Procedures for Planning, Controlling, and Evaluating Draft Local Regulations on LLTDP and LMTDP, as well as Procedures for Amending LLTDP, LMTDP, and the LGWP, emphasized several key objectives for regency/city areas. Firstly, it aimed to reach a consensus on local development issues. Secondly, the article agreed on local development priorities. Thirdly, it focused on agreement regarding programs, activities, sub-activities, indicative ceilings, performance indicators, targets, and their respective locations. Fourthly, the article emphasized the connection of local development programs, activities, and sub-activities with provincial development targets and priorities. Fifthly, it clarified the demarcation of programs and activities under the authority of regency/city areas in conjunction with village programs and activities proposed based on sub-district agreements. This represented the essence of the Money Follow Program and the Follow Result Program, showing the full responsibility of Region Apparatus in achieving the mission of the Donggala Regency Government. The synergy covered affairs, sub-affairs/programs, activities, sub-activities, target indicators, and budgets, all designed to achieve the desired targets. The focus of this study revolved around development planning, with a particular emphasis on economic growth indicators.

Effective region development planning required public participation to fulfill the objectives of local government. Direct participation could cover a diverse range of groups, including citizens, neighborhoods, businesses, and consumer associations. Non-governmental organizations (NGOs) and Community-Based Organizations (CBOs) acted as essential intermediaries, ensuring direct participation by bridging the gap between the people and the government. Indirect participation was safeguarded through elected representatives within the local governing body and ward committees (Sharma, Sharma, Kumar, Kumar, & Pipralia, 2022).

Stakeholder consultation was encouraged at various stages of planning process, including formulation, approval, integration, and monitoring. The representatives of the people, advisory committees, and citizens participation played a crucial role in plan formulation. At the approval stage, citizen participation in the form of public objections and suggestions was encouraged, alongside private sector engagement. The guidelines recognized multiple mechanisms for interactive public participation, such as community design charrettes, advisory committees, low-cost demonstrations and transformations, focus groups, participatory mapping, and budgeting. The proposed modifications aimed to enhance public participation, suggesting that the state planning provisions should be revised to emphasize public participation at early stages (Sharma, Sharma, Kumar, Kumar, & Pipralia, 2022).

Data and Methods

This study used a combination of secondary data from various related agencies and written sources, as well as primary data collected through interviews and questionnaire distribution. Additionally, data were gathered through a comprehensive review of reports from previous investigations. All data sources were derived from the Central Sulawesi Statistics Agency, Donggala Regency Central Bureau of Statistics, and related agencies and documents.

The study variables included Gross Region Domestic Product (GRDP), economic growth, and economic potential. To analyze the data, LQ method was used to assess economic landscape and identify the leading sectors. LQ was calculated by comparing the role of a particular sector within region (Tarigan, 2005). The analysis variables included the PDRB value of Donggala Regency and the GDRP of Central Sulawesi Province in the 2014-2018 period.

The formula for calculating LQ included the following.

LQ = (Q_ij / Q_j) / Q_in / Q_n) …………………………(1)

Description:

Q_ij= GDRP sector i in Donggala

Q_j= Total GDRP in Donggala Regency

Q_in= GDRP sector i in Central Sulawesi Province

Q_n= Total GDRP in Central Sulawesi Province

The value of LQ to be equaled to 1 for sector i signified that growth rate in Donggala Regency was in line with the one in Central Sulawesi Province. For LQ values greater than 1, it showed that regency had a higher growth rate. The value designated sector i as economic foundation for further development in Donggala Regency. Conversely, LQ values below 1 implied that regency had a low growth rate. It showed that sector i was not the primary economic base for future development in Donggala Regency. The LQ analysis used data on the GDRP of Donggala Regency and Central Sulawesi Province from 2014 to 2018, to identify both primary and secondary sectors suitable for further development by the government.

The second question was addressed using Klassen’s Typology analysis to determine the pattern and structure of region economic growth. Klassen’s Typology categorized region based on their economic growth and income per capita. It established the average economic growth and per capita income as the vertical and horizontal axes, respectively. Subsequently, Klassen’s Typology analysis classified sectors into four with distinct characteristics (Sjafrizal, 2008). First, Developed and rapidly growing sectors (Quadrant I). The quadrant comprised sectors with higher growth rates and contributions compared to others in region. The sectors were often identified by gi > g and si > s. Quadrant I typically included sectors with significant potential for achieving higher economic growth rates and shares compared to others. Second, Advanced but depressed sectors (Quadrant II). The quadrant comprised sectors with lower growth rates but higher contributions than others in region. The sectors were typically identified by gi < g and si > s. They were considered advanced but depressed due to their below-average economic growth rate and relatively larger share. Third, the Relatively developing sector (Quadrant III). The quadrant consisted of sectors with higher growth rates but lower contributions than others in region. The sectors were typically identified by gi > g and si < s. Sectors in Quadrant III were considered relatively developed, given their better-than-average economic growth rate performance and smaller share. Fourth, Relatively underdeveloped sectors (Quadrant IV). Quadrant IV comprised sectors with lower growth rates and contributions compared to others in region. The sectors were typically identified by gi < g and si < s. Sectors in Quadrant IV were perceived as relatively underdeveloped, showing their lower economic growth rates and contributions. Table 1 showed the Matrix of Klassen’s Typology.

Table 1. Klassen’s Typology Matrix

Growth Rate Contribution Average	(gi>g)	(gi<g)
(si>s)	Quadrant I Developed and rapidly growing sectors (gi>g and si>s)	Quadrant II Advanced but depressed sectors (gi<g and si>s)
(si<s)	Quadrant III The sector is relatively developed (gi>g and si<s)	Quadrant IV The sector is relatively underdeveloped (gi<g and si<s)

Source: Sjafrizal (2008).

Note: gi: Growth rate of GDRP in Donggala Regency. g: The average GDRP growth rate. si: Contribution of GDRP. s: Average contribution of GDRP.

Unstructured complex problems were addressed using the Analytical Hierarchy Process (AHP). The method organized components hierarchically and assigned subjective values to assess the relative importance of each variable. Additionally, AHP aggregated the assessment to identify the variable with the highest priority in affecting the resolution of the problem. Personal judgments were integrated, showing a logical and influenced blend of imagination, experience, and knowledge. The objective was to construct a problem hierarchy grounded in logic, intuition, and experience to provide informed judgment. Therefore, AHP aided in identifying, understanding, and estimating total system interactions (Falatehan, 2016; Pramono, Palupi, & Aditya, 2022).

AHP simplified unstructured, strategic, and dynamic complexities into the constituent parts and structured them hierarchically (Figure 2). The importance of each variable was subjectively quantified relative to others. These considerations were then synthesized to identify the variables with the highest priority in influencing the system (Marimin, 2004). The Simulation Calculation Method incorporated the following steps:

a. Identified the problem and potential solutions,

b. Developed hierarchical structure, including overarching objectives, criteria, and alternative choices.

Figure 2. AHP hierarchical structure

c. Constructed a pairwise comparison matrix to express the relative contribution of each element to the overarching objective or criteria above. The comparisons were established based on the decision maker’s assessments and judgments regarding the importance of the element (Table 2).

Table 2. Pairwise comparison rating scale

Value	Remarks
1	Two elements are equally important and have an equivalent effect.
3	One element is slightly more important, supported by experience and judgment.
5	Elements are significantly more important compared to others, underpinned by experience and judgment.
7	One element is distinctly more essential and strongly supported and dominant.
9	One element is considerably more important than any other, with the highest level of supporting evidence.
2,4,6,8	The intermediate values between adjacent considerations are used when there are compromises between the two options.

Source: Thomas L. Saaty (1994)

The study determined the priorities for all criteria using the data obtained from interviews and questionnaires (Table 3).

Table 3. Pairwise Comparison Matrix

C	$${𝐀}_1$$	$${𝐀}_2$$	…	$${𝐀}_{𝐧}$$
$$A_1$$	$$a_{11}$$	$$a_{12}$$	…	$$a_{1n}$$
$$A_2$$	$$a_{21}$$	$$a_{22}$$	…	$$a_{2n}$$
…	…	…	…
$$A_m$$	$$a_{m1}$$	$$a_{m2}$$	…	$$a_{\mathrm{\text{mm}}}$$

Source : Saaty (1994)

d. Data normalization incorporated dividing the value of each element in the paired matrix by the total value of each column.

e. Calculating the Criteria Priority value.

Priority Criteria = ∑line/∑Criteria …………………………(2)

f. Calculating the eigenvector value and testing the consistency. The data retrieval or preference was repeated when inconsistent. The eigenvector value was the maximum eigenvector value.

CI = $\frac{\mathrm{\text{λmax}}-n}{n-1}$ …………………………(3)

Information:

CI=storage ratio (deviation) consistency (consistency index);

max=The largest eigenvalue of an order matrix n;

n=Order of the matrix.

The pairwise comparison matrix was considered consistent when the CI value was 0. In this case, the inconsistency limit was determined using the CR by comparing the CI with the random index value (RI). The formula for CR was as follows:

CR = $\frac{\mathrm{\text{CI}}}{\mathrm{\text{RI}}}$ …………………………(4)

Information:

CR=Consistency Ratio

RI=Random Index

The random index value is obtained from Table 4.

Table 4. Random Index Value

N	1	2	3	4	5	6	7	8	9	10
RI	0.000	0.000	0, 80	0,900	1,120	1,240	1,320	1,410	1,450	1,490

Source: Saaty (1994)

A pairwise comparison matrix with a CR value less than 0.100 meant that the inconsistency in the decision-making opinion was acceptable. When the value was not less than 0.100, the assessment had to be repeated.

g. Steps 3, 4, and 5 were repeated for the whole hierarchy level.

h. The eigenvector value represented the weight of each element.

The AHP was a simple yet effective method used to prioritize sectors for Donggala Regency. With these priority sectors identified, the method could recommend the preparation of the LLTDP document for the 2025-2045 period and the LMTDP document for the 2025-2030 period. The priority sectors were mining and quarrying, specifically rocks and sand, which were supplied to the new nation's capital on the island of Kalimantan. It was important to observe that the sectors had a significant environmental impact. At the same time, 80% of the population of Donggala Regency was engaged in the short-term food crops and horticulture sector, plantations, livestock, and marine fisheries.

AHP offered both advantages and disadvantages in integrating region development planning. The advantages of included the following, first, the method excelled in transforming broad and unstructured problems into a flexible and easily understandable model. AHP used a systems perspective and deductive integration, allowing it to be applied to independent system elements without requiring a linear relationship. Second, AHP analysis adopted a measurement scale and methodology for determining priorities. The measurement scale used was grounded in the perspectives of policymakers, based on existing conditions, without the need for secondary data as a reference for assessment. Third, AHP consistently produced results compared to others due to its easy-to-understand and user-friendly decision-making system.

The weaknesses associated with AHP included, first, when improvements were necessary, the entire decision-making process might have needed to be restarted from the initial stage. Second, the method relied heavily on the main input, which was the perception of experts. The reliance introduced subjectivity into process, experts might have been influenced by situational factors and their preferences, perceptions, underlying concepts, and viewpoints. Moreover, the utility of the method was compromised when the expert provided inaccurate assessments.

The specific challenge faced by Donggala Regency is that there is no synchronization between development planning document and implementation documents. A part from that, development in Donggala District has not been collaborative and has not been incorporated.

Results and Discussion

Result

LQ Results

The first question was addressed through LQ analysis using GDRP data for Donggala Regency and Central Sulawesi Province during the 2014-2018 period, calculated at constant prices based on business fields. Basic and non-basic sectors data were presented in Table 5.

Table 5. The calculation for LQ Donggala Regency in the 2014-2018 Period

No.	Sector	Result of LQ Calculation					Average	Information
		2014	2015	2016	2017	2018
1	Agriculture, Forestry, and Fisheries	1.24	1.32	1.39	1.38	1.38	1.34	Basic
2	Mining and Quarrying	1.23	1.21	1.04	1.04	0.98	1.10	Basic
3	Manufacturing Industry	0.46	0.27	0.22	0.21	0.23	0.28	Non-Basic
4	Electricity and Gas Procurement	0.25	0.28	0.29	0.29	0.30	0.28	Non-Basic
5	Water Supply, Waste Management, Waste and Recycling	1.42	1.54	1.66	1.69	1.75	1.61	Basic
6	Construction	1.04	0.99	1.08	1.11	1.13	1.07	Basic
7	Wholesale and Retail Trade; Car and Motorcycle Repair	0.94	1.02	1.06	1.09	1.13	1.05	Basic
8	Transportation and warehousing	0.79	0.85	0.90	0.88	0.87	0.86	Non-Basic
9	Provision of Accommodation and Food and Drink	0.85	0.90	0.94	0.94	0.96	0.92	Non-Basic
10	Information and Communication	0.53	0.59	0.63	0.65	0.66	0.61	Non-Basic
11	Financial and Insurance Services	0.78	0.80	0.82	0.85	0.92	0.84	Non-Basic
12	Real Estate	0.56	0.60	0.63	0.62	0.63	0.61	Non-Basic
13	Corporate Services	0.35	0.38	0.39	0.39	0.40	0.38	Non-Basic
14	Mandatory Government Administration, Defense, and Social Security	1.11	1.22	1.32	1.36	1.39	1.28	Basic
15	Education Services	0.41	0.44	0.46	0.46	0.47	0.45	Non-Basic
16	Health and Social Services	0.45	0.48	0.49	0.49	0.48	0.48	Non-Basic
17	Other Services	0.72	0.75	0.78	0.80	0.82	0.77	Non-Basic

Source: Study Result

Klassen’s Typology Results

This analysis focused on six basic sectors, which included agriculture, forestry, fisheries, mining and quarrying, water supply, and waste management. Additional sectors comprised construction, wholesale and retail trade, car and motorcycle repair services, and the government administration, defense, and social security as shown in Table 6.

Table 6. Classification Results Analysis of Klassen’s Typology of Donggala Regency in the 2014-2018 Period

Quadrant I (gi>g and si>s)	Quadrant II (gi<g and si>s)	Quadrant III (gi>g and si<s)	Quadrant IV (gi<g and si<s)
1. Mining and Quarrying; 2.. Mandatory Government Administration, Defense, and Social Security.	1. Agriculture, Forestry, and Fisheries; 2. Construction; 3. Wholesale and Retail Trade, Car and Motorcycle Repair.		1. Water Supply, Waste Management, Waste, and Recycling.

Source: Study Result

AHP

The calculations were performed based on data obtained from questionnaire distribution and stakeholder interviews. The step incorporated inputting the criteria for Gross Added Value, Employment, Export, and Per Capita Income, as shown in Table 7.

Table 7. Input Criteria

Criteria	Gross Value Added	Employment	Export	Per Capita Income
Gross Added Value	1.00	0.33	3.00	0.33
Employment	3.00	1.00	3.00	1.00
Export	0.33	0.33	1.00	0.33
Income Per Capita	3.00	1.00	3.00	1.00
∑ Column	7.33	2.66	10.00	2.66

Source: Study Result

The next step consisted of normalizing the matrix, which was achieved by dividing each element in Table 7 by the corresponding column totals, as presented in Table 8.

Table 8. Normalization Criteria

Criteria for	Gross Value Added	Employment	Export	Per capita Income	∑Line
Gross Added Value	0.14	0.13	0.30	0.13	0.69
Employment	0.41	0.38	0.30	0.38	1.46
Exports	0.05	0.13	0.10	0.12	0.39
Per capita income	0.41	0.38	0.30	0.38	1.46

Source: Study Result

After the normalization, the priority values were determined by dividing the rows by the criteria, as shown in Table 9.

Table 9. Priority Criteria

Criteria for	Priority
Gross Added Value	0.17
Employment	0.36
Export	0.10
Per capita Income	0.36

Source: Study Result

The maximum eigenvalues (max) were calculated by summing the products of the column totals with their respective priorities.

max= (7.33 x 0.17) + (2.66 x 0.36) + (10.00 x 0.10) + (2.66 x 0.36) =1.246+0.957+ 1+0.957= 4.16

Given that the matrix is of order 4, the CI was determined as:

CI= $\frac{\lambda max-n}{n-1}$ = $\frac{4.16-4}{4-1}$ = 0.05

As the CI was not equal to 0, further calculations were needed to assess the consistency. The CR was calculated by dividing CI by RI. With an RI value of 0.900 for a matrix of order 4 (Saaty, 1994), the following results were obtained.

CR= $\frac{\mathrm{\text{CI}}}{\mathrm{\text{RI}}}$ = $\frac{0.05}{0.900}$ = 0.06

As CR was less than 0.100, it showed that the inconsistency in decision-making opinions was still within an acceptable range. The next step was to determine the priority of each alternative, including inputting the comparative values for each alternative concerning each criterion (Table 10, Table 11, and Table 12).

Table 10. Alternative Inputs of Gross

Gross Value Added	Mining and Quarrying	Administration of Government, Defense, and Social Security Compulsory	Agriculture, Forestry, and Fisheries	Construction	Wholesale and Retail Trade, Repair of Cars and Motorbikes
Mining and Quarrying	1.00	5.00	1.00	5.00	5.00
Government Administration, Defense, and Compulsory Social Security	0.20	1.00	0.20	0.33	0.33
Agriculture, Forestry, and Fisheries	1.00	5.00	1.00	7.00	5.00
Construction	0.20	3.00	0.14	1.00	0.20
Wholesale and retail trade, repair of cars and motorbikes	0.20	3.00	0.20	5.00	1.00
∑ Column	2.60	17.00	2.54	18.33	11.53

Source: Study Result

Table 11. Alternative Priorities Gross Added

Value Added (1)	Priority (2)
Mining and Quarrying	0.36
Mandatory Administration of Government, Defense, and Social Security	0.05
Agriculture, Forestry, and Fisheries	0.38
Construction	0.08
Wholesale and Retail Trade, Car and Motorcycle Repair	0.14

Source: Study Result

Table 12. Final Results of Calculation

Criteria Alternative (1)	Gross Added Value (2)	Employment (3)	Exports (4)	Income Per Capita (5)	Global Priority (6)
Weight	0.17	0.36	0.10	0.36
Mining and Quarrying	0.36	0.51	0.41	0.32	40%
Mandatory Administration of Government, Defense, and Social Security	0.05	0.05	0.04	0.04	5%
Agriculture, Forestry, and Fisheries	0.38	0.20	0.30	0.38	31%
Construction	0.08	0.08	0.08	0.15	11%
Wholesale and Retail Trade, Car and Motorcycle Repair	0.14	0.16	0.17	0.11	14%

Source: Study Result

Mining and Quarrying = (0.17 x 0.36) + (0.36 x 0.51) + (0.10 x 0.41) + (0.36 x 0.32) = 0.06 + 0.18 + 0.04 + 0.12 = 0.40 = 40%

Mandatory Government Administration, Defense, and Social Security = (0.17 x 0.05) + (0.36 x 0.05) + (0.10 x 0.04) + (0.36 x 0.04) = 0.01 + 0.02 + 0.00 + 0.01 = 0.05 = 5%

Agriculture, Forestry, and Fisheries = (0.17 x 0.38) + (0.36 x 0.20) + (0.10 x 0.30) + (0.36 x 0.38) = 0.06 + 0.07 + 0.03 + 0.14 = 0.31 = 31%

Construction = (0.17 x 0.08) + (0.36 x 0.08) + (0.10 x 0.08) + (0.36 x 0.15) = 0.01 + 0.03 + 0.01 + 0.05 = 0.11 = 11%

Wholesale and Retail Trade; Car and Motorcycle Repair = (0.17 x 0.14) + (0.36 x 0.16) + (0.10 x 0.11) + (0.36 x 0.17) = 0.02 + 0.06 + 0.02 + 0.04 = 0.14 = 14%

Discussion

Analytical LQ

The mining, agriculture, forestry, and fisheries collectively contributed Rp2,930,410.14 to the GDRP in 2014 and the value increased to Rp 3,208,939.1 in 2018. The analysis results showed that all the sectors had an LQ>1, signifying their status as the basis in Donggala Regency, with a more rapid growth rate compared to similar ones in Central Sulawesi Province.

The mining and quarrying contributed Rp847,738.67 to the GDRP in 2014 and the value increased to Rp1,189,886.6 in 2018. The analysis results showed that the sectors had an LQ>1, designating their status as the basis in Donggala Regency, with a faster growth rate compared to similar ones in Central Sulawesi Province.

The water supply, waste management, and waste and recycling contributed Rp14,902.86 to the GDRP in 2014, and the value increased to Rp18,595.8 in 2018. The analysis results showed that all the sectors had an LQ>1, affirming their status as the basis in Donggala Regency, with growth rate surpassing others in Central Sulawesi Province.

The construction sectors contributed Rp873,658.16 to GDRP in 2014 and subsequently experienced an increase to Rp1,010,293.3 in 2018. The results showed that the sectors had LQ>1, designating their status as the basis in Donggala Regency, with a faster growth rate surpassing others in Central Sulawesi Province.

The wholesale and retail trade and the car and motorbike repair services contributed Rp670,627.43 to GDRP in 2014 and the value increased to Rp802,100.9 in 2018. The analysis results showed that both sectors had LQ>1, classifying their status as the basis in Donggala Regency, with a faster growth rate compared to the similar ones in Central Sulawesi Province.

The government administration, defense, and compulsory social security contributed Rp479,212.63 to the GDRP in 2014 and subsequently increased to Rp668,403.0 in 2018. The results showed that all the sectors had LQ>1, designating their status as the basis in Donggala Regency, with a rapid growth rate compared to other similar ones in Central Sulawesi Province.

Klassen’s Typology Analysis

A Sector that was Progressing and Growing Rapidly (Quadrant I)

The mining and quarrying sectors had a remarkable growth rate of 9.51%, surpassing the average growth rate of the Donggala Regency of 5.82%. It also contributed significantly at 16.57%, outperforming the average contribution, which was at 5.88%. Similarly, the government administration, defense, and compulsory social security sectors showed substantial growth at 8.72%, surpassing the average growth rate of 5.82%. The sectors contributed significantly at 8.55%, exceeding the average contribution of 5.88%.

Advanced but Depressed Sector (Quadrant II)

The agriculture, forestry, and fisheries sectors had growth rate of 2.78%, falling short of the average growth rate of the Donggala Regency of 5.82%. However, they all contributed significantly at a rate of 36.95%, surpassing the average contribution of 5.88%. The construction sector showed growth rate of 4.33%, lower than the average growth rate of 5.82%. It contributed significantly at 14.87%, surpassing the average growth rate of 5.88%. The wholesale and retail trade and car and motorcycle repair services had growth rate of 4.13%, below the average growth rate of 5.82%. Despite this, the sectors contributed significantly at 8.79%, exceeding the average contribution of 5.88%.

Relatively Developing Sector (Quadrant III)

According to Klassen’s typology classification, no base sector in Donggala Regency fell into Quadrant II.

Underdeveloped Relative Sector (Quadrant IV)

The water supply, waste management, and waste and recycling sectors experienced growth rate of 5.80%, slightly below the average growth rate of the Donggala Regency of 5.82%. It contributed 0.20%, which was also less than the average contribution of 5.88%.

AHP

AHP results showed that mining and quarrying were the top-priority development sectors, representing 40% of the total priority. Following closely were agriculture, forestry, and fisheries with a 31% allocation. Subsequently, wholesale and retail trade and car and motorcycle repair received 14% priority. Construction followed with 11% allocation, and the government administration, defense, and mandatory social security with 5%.

This priority determination was grounded in data and insights from key stakeholders in Donggala Regency. Mining and quarrying served as the leading sector due to the significant growth rate contribution of 9.515, making it the second largest contributor to GDRP at 16.57%. The sector played a crucial role in supporting development of the Indonesian new capital city in Kalimantan, fulfilling essential needs imported from Donggala Regency.

Conclusions and Recommendations

In conclusion, the combination of results and discussions led to the following. First, the analysis of LQ showed that the foundational sectors in Donggala Regency, within Central Sulawesi Province, included agriculture, forestry, fisheries, mining, quarrying, construction, wholesale and retail trade, as well as government administration, defense, and compulsory social security. Second, Klassen’s Typology further categorized the sectors into distinct quadrants. The advanced and rapidly growing sectors were identified to be mining and quarrying, followed by the government administration, defense, and social security. Major but depressed sectors comprised agriculture, forestry and fisheries, construction, wholesale and retail trade, and car and motorcycle repair. The relatively underdeveloped sectors included water supply, waste management, and waste recycling. Third, the AHP results showed that the top-priority sectors in Donggala Regency were mining and quarrying.

Based on the conclusions drawn, the following recommendations were made to the local government. First, prioritize efforts to increase the foundational sectors to promote economic of regency. There was a need to foster economic growth by focusing on the foundational sectors, thereby contributing to the total economic progress. Second, optimize economic growth by leveraging influential sectors and actively attracting the expansion of others. Third, the Donggala Regency Government had to maintain developed and fast-growing sectors. The government should also enhance relatively developed services to grow faster. Fourth, the local government had to identify and minimize the causes of the lack of contribution from each existing sector.

The agricultural sector includes the sub-sectors of food crops and horticulture, plantation, forestry and fisheries, which are the main sector in Donggala District that need to be improved by downstreaming, so as to obtain increased added value. Apart from that, increasing the production of sub-district based on spatialized commodity and agro-climatology, so as to create one sub-district-one-product (OSDOP).

Author Contributions

Conceptualization, M.A.D, A.S. and E.T; Methodology; A.D.T, A.S; software, A.D.T, A.S; investigation, M.A.D, E.T, A.D.T, A.S; resources, M.A.D, A.S; data curation, A.S, A.D.T; writing-original draft preparation, M.A.D, E.T, and A.S; writing-review and editing, M.A.D, A.S, A.D.T; supervision, M.A.D, A.D.T. The published version of the manuscript was read by all authors.

Ethics Declaration

The authors declared no conflicts of interest in publishing the paper.

Acknowledgments

The authors thank the dean, vice dean, and head of Department of Economics and Development Studies at the Faculty of Economics and Business, Tadulako University, fellow academics, and anonymous referees for their invaluable comments and contributions during the discussion. Additionally, the authors thank Region Secretariat of Donggala Regency, Region Agency for Development Planning of Donggala Regency, and the Central Agency of Statistics of Donggala Regency for their collaboration and data provision.

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