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KAJIAN EKSISTING DAN PREDIKSI ELEVASI MUKA AIR TANAH DALAM BERDASARKAN ANALISIS ANFIS (ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM) DI KOTA SEMARANG

SUHARYANTO, Oasiska Nuhannaning and Helmi, Muhammad and Hidayat, Jafron Wasiq (2026) KAJIAN EKSISTING DAN PREDIKSI ELEVASI MUKA AIR TANAH DALAM BERDASARKAN ANALISIS ANFIS (ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM) DI KOTA SEMARANG. Masters thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Penelitian ini dilatarbelakangi oleh pengaruh kritis distribusi spasial penggunaan lahan terhadap variasi elevasi muka air tanah dalam di Kota Semarang, yang dieksploitasi secara berlebihan untuk memenuhi kebutuhan domestik, industri, dan komersial. Tujuan penelitian adalah untuk menganalisis elevasi muka air tanah dalam eksisting yang dipengaruhi oleh distribusi spasial penggunaan lahan, memprediksi elevasinya untuk periode 5 hingga 20 tahun ke depan, serta menganalisis peran masyarakat dalam mitigasi penurunannya dengan menggunakan Adaptive Neuro Fuzzy Inference System (ANFIS). Data kualitatif diperoleh dari observasi lapangan mengenai peran masyarakat, sementara data kuantitatif meliputi elevasi muka air tanah dari sumur pantau ESDM Provinsi Jawa Tengah, data meteorologis, dan data jumlah penduduk dari Pusdataru Kota Semarang, yang dianalisis dengan regresi linear untuk menentukan variabel masukan sebelum pemodelan ANFIS. Hasil penelitian memprediksi tren perubahan elevasi yang sangat bervariasi antar kluster penggunaan lahan. Berdasarkan analisis ANFIS, penelitian ini memprediksi penurunan elevasi muka air tanah dalam di empat lokasi di Kota Semarang untuk 20 tahun ke depan. Sumur Pantau Teknik Geologi mengalami penurunan paling drastis (40,96% dalam 5 tahun) dan diprediksi rusak, diikuti SMKN 1 Semarang yang mengarah kritis. Sementara itu, Sumur Pantau PT Bitratex dan PT Savana Tirta Makmur berada dalam kondisi aman. Penurunan terparah terjadi di kawasan dengan pertumbuhan penduduk pesat, sehingga diperlukan aksi kolektif masyarakat untuk konservasi air tanah, khususnya di wilayah berstatus kritis dan rusak. Pada penelitian selanjutnya, penyempurnaan dapat difokuskan pada tiga aspek utama. Pertama, meningkatkan kualitas data melalui preprocessing seperti denoising dan penanganan outlier. Kedua, mengoptimalkan konfigurasi model dengan analisis time lag yang lebih komprehensif dan rekayasa fitur. Ketiga, mengatasi keterbatasan data melalui augmentasi, validasi yang ketat, dan perbandingan dengan model alternatif. Serta pendalaman aspek budaya dan biologi yang mempengaruhi perubahan air tanah. Pendekatan ini diharapkan dapat meningkatkan akurasi prediksi secara signifikan.
Kata kunci: Elevasi Muka Air Tanah, ANFIS, Prediksi

This research is motivated by the critical influence of the spatial distribution of land use on variations in deep groundwater table elevation in Semarang City, which is being excessively exploited to meet domestic, industrial, and commercial needs. The research aims to analyze the existing deep groundwater table elevation influenced by the spatial distribution of land use, predict its elevation for the next 5 to 20 years, and analyze the community's role in mitigating its decline using the Adaptive Neuro-Fuzzy Inference System (ANFIS). Qualitative data were obtained from field observations regarding the community's role, while quantitative data included groundwater table elevation from monitoring wells of the Central Java Provincial ESDM Office, meteorological data, and population data from the Semarang City Pusdataru, which were analyzed using linear regression to determine input variables before ANFIS modelling. The results predict highly varied trends in elevation changes across different land-use clusters. Based on the ANFIS analysis, this research predicts a decline in deep groundwater table elevation at four locations in Semarang City over the next 20 years. The Geological Engineering Monitoring Well experienced the most drastic decline (40.96% in 5 years) and is predicted to be damaged, followed by SMKN 1 Semarang which is heading toward a critical state. Meanwhile, the PT Bitratex and PT Savana Tirta Makmur Monitoring Wells are in safe condition. The most severe decline occurs in areas with rapid population growth, necessitating collective community action for groundwater conservation, especially in critical and damaged status areas. For future research, refinement can be focused on three main aspects. First, improving data quality through preprocessing such as denoising and outlier handling. Second, optimizing model configuration with more comprehensive time lag analysis and feature engineering. Third, addressing data limitations through augmentation, rigorous validation, and comparison with alternative models, as well as deepening the aspects of culture and biology that influence groundwater changes. This approach is expected to significantly improve prediction accuracy.
Keywords: Ground Water Level (GWL), ANFIS, Prediction

Item Type: Thesis (Masters)
Uncontrolled Keywords: Elevasi Muka Air Tanah, ANFIS, Prediksi
Subjects: Sciences and Mathemathic
Engineering
Divisions: Postgraduate Program > Master Program in Environmental Science
Depositing User: ekana listianawati
Date Deposited: 26 Feb 2026 04:53
Last Modified: 26 Feb 2026 04:53
URI: https://eprints2.undip.ac.id/id/eprint/46079

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