Emmi Desniati Desniati
Road and Bridge Construction Engineering Technology, Lampung State of Polytechnic, Lampung

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Analisis Distribusi Spasial dan Jarak Fasilitas Umum Berbasis SIG di Politeknik Negeri Lampung Emmi Desniati Desniati; Tanya Audia Balqis; Rahayu Putri Amalia
JURNAL TEKNIK SIPIL CENDEKIA (JTSC) Vol 7 No 2 (2026): May
Publisher : Departement of Civil Engineering, Universitas Winaya Mukti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51988/jtsc.v7i2.535

Abstract

The spatial distribution of campus facilities is a critical determinant of the efficiency of spatial planning in higher education institutions. This study examines the spatial distribution pattern of campus public facilities using the Average Nearest Neighbor (ANN) method within a Geographic Information System (GIS) framework. The study was conducted at Lampung State Polytechnic using centroid point data of buildings with a total study area of 202,943.98 m². The analysis yielded a Nearest Neighbor Ratio (NNR) of 0.884, indicating a tendency toward spatial clustering. However, this tendency was not statistically significant at the 95% confidence level (Z-score = ?1.567; p = 0.117 > 0.05), and the building distribution is therefore classified as random. Inter-building distance analysis revealed that the observed mean distance (28.16 m) is approximately 11.6% shorter than the expected distance under a random distribution (31.85 m), suggesting that contextual factors—including land constraints, functional connectivity requirements, incremental development patterns, and utility network efficiency—have collectively influenced building placement. The predominantly random distribution pattern reflects a process of adaptive spatial development conducted without reference to a comprehensive spatial master plan, which may give rise to circulation inefficiencies, utility integration challenges, and suboptimal open space utilization. This study demonstrates that GIS-based spatial statistical analysis affords an objective, quantitative evaluation of campus spatial planning and can serve as a scientific basis for the formulation of more structured, data-driven facility development policies.