Spatial patterns and inequality of Blue Economy sustainability in Indonesia: Evidence from the 2024 Indonesia Blue Economy Index
DOI:
https://doi.org/10.67964/9acm8y14Keywords:
Indonesia Blue Economy Index, Spatial inequality, Spatial autocorrelation, Blue economy clusters, Blue economy sustainabilityAbstract
The blue economy has become a strategic approach to integrating marine resource utilization with environmental sustainability and societal well-being, yet its performance remains uneven across regions. This study aims to analyze the spatial distribution and dependence of blue economy sustainability across 34 Indonesian provinces using the 2024 Indonesia Blue Economy Index (IBEI). Exploratory Spatial Data Analysis (ESDA) was conducted using Global Moran’s I and Local Indicators of Spatial Association (LISA) with a Queen contiguity spatial weight matrix. The results show that IBEI scores range from 11.61 to 66.51, with a mean of 37.24, while Moran’s I of 0.290 indicates positive spatial autocorrelation. LISA identifies South Sulawesi as High–High, South Sumatra and Lampung as Low–Low, West Sulawesi as Low–High, and the Riau Islands as High–Low. These findings demonstrate distinct spatial configurations of blue economy inequality and provide a basis for differentiated regional policies tailored to the spatial characteristics of each province.
Abstrak
Ekonomi biru menjadi pendekatan strategis untuk mengintegrasikan pemanfaatan sumber daya laut dengan keberlanjutan lingkungan dan kesejahteraan masyarakat, tetapi kinerjanya menunjukkan ketimpangan antardaerah. Penelitian ini bertujuan menganalisis distribusi dan ketergantungan spasial keberlanjutan ekonomi biru pada 34 provinsi di Indonesia berdasarkan Indonesia Blue Economy Index (IBEI) 2024. Penelitian menggunakan Exploratory Spatial Data Analysis (ESDA) melalui Global Moran’s I dan Local Indicators of Spatial Association (LISA) dengan matriks bobot spasial Queen contiguity. Hasil menunjukkan IBEI berkisar 11,61–66,51 dengan rata-rata 37,24, sedangkan Moran’s I sebesar 0,290 mengindikasikan autokorelasi spasial positif. LISA mengidentifikasi Sulawesi Selatan sebagai High–High, Sumatera Selatan dan Lampung sebagai Low–Low, Sulawesi Barat sebagai Low–High, serta Kepulauan Riau sebagai High–Low. Temuan ini menunjukkan bahwa ketimpangan ekonomi biru memiliki konfigurasi spasial yang berbeda dan memberikan dasar bagi kebijakan regional yang lebih terdiferensiasi sesuai karakteristik spasial setiap provinsi.
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Copyright (c) 2026 Abdul Azis, Etty Soesilowati, Thomas Soseco, Inayati Nuraini Dwiputri, Farida Rahmawati, Agus Romadhon, Endang Tri Wahyurini (Author)
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