Identifikasi Indikasi Tanah Terlantar Guna Mendukung Pendayagunaan Tanah Di Kabupaten Sidoarjo

Fauzi, Muhammad Rafinaldy (2026) Identifikasi Indikasi Tanah Terlantar Guna Mendukung Pendayagunaan Tanah Di Kabupaten Sidoarjo. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5016221082-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (5MB) | Request a copy

Abstract

Tanah merupakan sumber daya yang harus dimanfaatkan secara optimal sesuai dengan fungsi sosialnya, namun di Kabupaten Sidoarjo sebagai wilayah penyangga utama Kota Surabaya yang mengalami pertumbuhan urbanisasi pesat, masih dijumpai bidang-bidang tanah yang tidak dimanfaatkan secara optimal sehingga berpotensi menjadi tanah terlantar. Penelitian ini bertujuan mengidentifikasi indikasi tanah terlantar di Kabupaten Sidoarjo melalui analisis multi-temporal tutupan lahan menggunakan citra Sentinel-2A pada platform Google Earth Engine periode 2023–2025. Klasifikasi tutupan lahan dilakukan menggunakan algoritma Random Forest dengan 10 fitur spektral, terdiri atas lima band asli serta indeks NDVI, NDBI, BSI, SAVI, dan MNDWI, dengan validasi menggunakan confusion matrix. Indikasi tanah terlantar diperoleh melalui operasi tumpang susun Strict AND terhadap hasil klasifikasi lahan terbuka yang konsisten pada ketiga tahun pengamatan. Hasil penelitian menunjukkan model klasifikasi Random Forest mencapai Overall Accuracy sebesar 96,86% dan Kappa Coefficient sebesar 0,84, yang menunjukkan tingkat akurasi yang tinggi. Luas lahan terbuka tahunan berfluktuasi dari 7.829,82 Ha (2023), 9.963,79 Ha (2024), hingga 7.477,37 Ha (2025), sedangkan hasil overlay Strict AND mengidentifikasi area terindikasi tanah terlantar seluas 2.856,55 Ha yang tersebar di wilayah Kabupaten Sidoarjo. Hasil penelitian ini selanjutnya dijadikan dasar penyusunan rekomendasi pendayagunaan tanah berbasis kondisi fisik-spektral, sebagai data awal pendukung verifikasi lapangan dan proses penertiban tanah terlantar oleh instansi pertanahan guna mendukung optimalisasi pemanfaatan tanah sesuai fungsi sosialnya di Kabupaten Sidoarjo.
===================================================================================================================================
Land is a resource that must be optimally utilized in accordance with its social function. However, in Sidoarjo Regency, the main buffer area of Surabaya City experiencing rapid urbanization growth, parcels of land that remain unutilized can still be found, potentially indicating abandoned land. This research aims to identify indications of abandoned land in Sidoarjo Regency through multi-temporal land cover analysis using Sentinel-2A imagery on the Google Earth Engine platform for the 2023–2025 period. Land cover classification was carried out using the Random Forest algorithm with 10 spectral features, consisting of five raw bands and the NDVI, NDBI, BSI, SAVI, and MNDWI indices, validated using a confusion matrix. Indications of abandoned land were obtained through a Strict AND overlay operation on the open-land classification results that were consistently identified across the three years of observation. The results show that the Random Forest model achieved an Overall Accuracy of 96.86% and a Kappa Coefficient of 0.84, indicating a high level of accuracy. The annual open land area fluctuated from 7,829.82 ha (2023), 9,963.79 ha (2024), to 7,477.37 ha (2025), while the Strict AND overlay identified a total area of 2,856.55 ha indicated as abandoned land scattered across Sidoarjo Regency. These findings serve as the basis for formulating land utilization recommendations based on physical-spectral conditions, providing preliminary spatial data to support field verification and the abandoned land enforcement process by relevant land authorities, in order to support the optimization of land utilization in accordance with its social function in Sidoarjo Regency.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Google Earth Engine, Google Earth Engine, Kabupaten Sidoarjo, Sidoarjo Regency, Penginderaan Jauh, Remote Sensing, Random Forest, Random Forest, Sentinel-2A, Sentinel-2A, Tanah Terlantar, Abandoned Land.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Muhammad Rafinaldy Fauzi
Date Deposited:	22 Jul 2026 03:24
Last Modified:	22 Jul 2026 03:24
URI:	http://repository.its.ac.id/id/eprint/136176

Actions (login required)

View Item