Electronic Theses and Dissertation

Penentuan Zona Nilai Tanah (ZNT) di Kota Banda Aceh saat ini masih menggunakan pendekatan administratif dan zonasi manual yang belum memiliki ukuran kuantitatif yang jelas, sehingga menyebabkan ketidaksesuaian antara Nilai Jual Objek Pajak (NJOP) dengan nilai pasar aktual dan berdampak pada ketidakadilan beban pajak serta penurunan potensi penerimaan Pendapatan Asli Daerah (PAD). Penelitian ini bertujuan untuk: (1) membentuk ZNT berbasis Sistem Informasi Geografis (SIG) menggunakan metode K-Means Clustering dengan variabel jarak spasial (Nearest Distance) terhadap 13 fasilitas strategis, dan (2) membandingkan hasil ZNT clustering dengan ZNT eksisting BPKK Kota Banda Aceh. Objek penelitian adalah 12.493 persil tanah di Kecamatan Syiah Kuala. Proses analisis dilakukan melalui tiga tahap utama: analisis proximity menggunakan tool Near pada ArcGIS untuk menghitung jarak minimum setiap persil ke fasilitas umum (jalan nasional, jalan provinsi, jalan desa, SD, SMP, SMA, universitas, rumah sakit, pusat kota, pusat ekonomi, RTH, tambak, dan zona risiko tsunami); normalisasi data dengan metode Min-Max Scaling; serta penentuan jumlah cluster optimal menggunakan Elbow Method, Silhouette Score, dan Davies-Bouldin Index (DBI) yang secara konsisten menunjuk k=15 sebagai nilai optimal. Hasil penelitian menghasilkan 15 zona nilai tanah dengan gradasi yang jelas, dari Zona 1 (paling strategis: rata-rata jarak 994,2 m, NJOP rata-rata Rp 920.039/m²) hingga Zona 15 (paling tidak strategis: rata-rata jarak 2.812,4 m, NJOP rata-rata Rp 122.862/m²). Tiga faktor dominan pembentuk pola zonasi adalah: kedekatan ke universitas (university premium effect), risiko tsunami yang menekan nilai lahan, dan fungsi lahan tambak yang membentuk zona tersendiri. Perbandingan dengan ZNT eksisting BPKK mengungkap bahwa kode AL (Rp 537.000/m²) tersebar di 11 zona clustering berbeda, mengindikasikan kelemahan mendasar zonasi manual dalam menangkap variasi spasial mikro. Pendekatan berbasis data spasial ini terbukti menghasilkan pengelompokan yang lebih konsisten dan objektif, serta dapat menjadi dasar kuantitatif yang transparan untuk mendukung pemutakhiran ZNT dan NJOP PBB-P2 sesuai Peraturan Menteri Keuangan Nomor 85 Tahun 2024.

Kata Kunci : Zona Nilai Tanah, K-Means Clustering, Sistem Informasi Geografis, Analisis Proximity, NJOP, PBB-P2, Kecamatan Syiah Kuala.

The current determination of Land Value Zones (ZNT) in Banda Aceh City still relies on administrative and manual zoning approaches that lack clear quantitative measures, resulting in discrepancies between the Government-Assessed Property Value (NJOP) and actual market values. This leads to inequitable tax burdens and reduced potential for Regional Own Revenue (PAD). This study aims to: (1) establish ZNT using a Geographic Information System (GIS) framework with K-Means Clustering incorporating spatial distance variables (Nearest Distance) against 13 strategic facilities, and (2) compare the clustering-based ZNT results with the existing ZNT used by the Regional Tax Office (BPKK) of Banda Aceh. The research object comprises 12,493 land parcels in Syiah Kuala District. The analytical process involved three main stages: proximity analysis using the Near tool in ArcGIS to calculate the minimum distance from each parcel to public facilities (national roads, provincial roads, village roads, elementary schools, junior high schools, senior high schools, universities, hospitals, city centers, economic centers, green open spaces, fish ponds, and tsunami risk zones); data normalization using Min-Max Scaling; and determination of the optimal number of clusters using the Elbow Method, Silhouette Score, and Davies-Bouldin Index (DBI), all of which consistently indicated k=15 as the optimal value. The results produced 15 land value zones with a clear gradient, ranging from Zone 1 (most strategic: average distance 994.2 m, average NJOP Rp 920,039/m²) to Zone 15 (least strategic: average distance 2,812.4 m, average NJOP Rp 122,862/m²). Three dominant factors shaping the zoning pattern were identified: proximity to universities (university premium effect), tsunami risk that suppressed land values, and fish pond land use that formed distinct zones. Comparison with the existing BPKK ZNT revealed that the AL code (Rp 537,000/m²) was scattered across 11 different clustering zones, indicating a fundamental weakness of manual zoning in capturing micro-spatial variation. This spatial data-based approach demonstrably produces more consistent and objective groupings, and can serve as a transparent quantitative basis for updating ZNT and NJOP for Rural and Urban Land and Building Tax (PBB-P2) in accordance with Minister of Finance Regulation Number 85 of 2024. Keywords : Land Value Zone, K-Means Clustering, Geographic Information System, Proximity Analysis, NJOP, PBB-P2, Syiah Kuala District