The Strategic Development of Quality Improvement Land Data Incrementally Using Integrated PESTEL and SWOT Analysis in Indonesia

Nurul Huda (), Andri Hernandi, Irwan Gumilar, Irwan Meilano and Lisa A. Cahyaningtyas
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Nurul Huda: Department of Geodesy and Geomatics, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung 40132, West Java, Indonesia
Andri Hernandi: Spatial System and Cadastre Research Group, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung 40132, West Java, Indonesia
Irwan Gumilar: Geodetic Science, Engineering, and Innovation Research Group, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung 40132, West Java, Indonesia
Irwan Meilano: Spatial System and Cadastre Research Group, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung 40132, West Java, Indonesia
Lisa A. Cahyaningtyas: Geodetic Science, Engineering, and Innovation Research Group, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung 40132, West Java, Indonesia

Land, 2024, vol. 13, issue 10, 1-21

Abstract: Land registration is an important program in asset legalization with the vast land resources owned by Indonesia. The reality is that there are 48 million certificated lands out of an estimated 126 million certificates throughout Indonesia, so the Ministry of Agrarian Affairs and Spatial Planning/National Land Agency (ATR/BPN) made a breakthrough through the Complete Systematic Land Registration (PTSL) program. The grouping mechanism of the PTSL program is divided into four clusters, namely K-1, K-2, K-3, and K-4. Land parcels included in K-4 have problems, namely that they have been registered but not mapped/mapped incorrectly, so the idea of modeling the K-4 typology is needed for accelerating the improvement in land data quality (KW). The research location is in Bandung Regency, which is included in the top five land offices with the highest number of K-4 in West Java Province. This research method uses a mixed method, namely quantitative with a Slovin approach for the identification and clustering of K-4 typology and descriptive qualitative for justification of typology modeling in multiple aspects. The results of K-4 typology modeling were 128 clusters based on seven types of data criteria and obtained 4 clusters that matched the data sample, namely T-1, T-43, T-63, and T-128. The four clusters were justified against the K-4 concept in the Ministry of ATR/BPN, the FFP-LA concept, and the PESTLE framework. Dissemination of K-4 typology modeling is a breakthrough that can be implemented by the Ministry of ATR/BPN and its staff in various regions and the role of multi-concepts in this research can be an input for improving the K-4 concept that has been in effect so far.

Keywords: land data quality; complete systematic land registration; model modification (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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