Kriminalitas merupakan salah satu masalah penting di wilayah perkotaan termasuk di Kota Semarang. namun di Polrestabes Kota Semarang selama ini hanya mencatat laporan terjadinya kriminalitas tanpa memvisualisasikan ke dalam bentuk informasi spasial. Hal ini perlu dilakukan untuk memudahkan pihak berwenang dalam memetakan dan monitoring sebaran daerah rawan kriminalitas. Pada penelitian ini, dilakukan perbandingan metode clustering untuk menentukan metode yang paling baik untuk memetakan daerah rawan kriminalitas di Kota Semarang. Metode clustering yang digunakan yaitu Fuzzy C-Means dan K-Means. Metode Fuzzy C-Means adalah pengelompokan data ditentukan oleh derajat keanggotaan, sedangkan metode K-Means adalah pengelompokan data ditentukan dari centroid kejadian kriminalitas. Hasil penelitian ini menunjukan terdapat 1.965 kasus kriminalitas selama kurun waktu tahun 2016-2018. Daerah tingkat kerawanan dari kedua metode tersebut mempunyai hasil yang berbeda-beda. Nilai uji pengolahan metode Fuzzy C-Means sebesar 0,818 dikategorikan baik karena mendekati angka 1. Hasil verifikasi dari kedua metode terhadap data kriminalitas tahun 2019, menunjukan nilai metode Fuzzy C-Means lebih baik dengan persentase sebesar 71,23 %.
Land Subsidence is phenomena likey common and occurred due to natural cause, loading, and geological setting. In the coastal area land subsidence became worse, cause influence by sea-level rise, The impact land subsidence can lead to wider expansion (flooding area called rob), damage or cracking construction/building and large of maintenance cost. Semarang is the capital city in Central Jawa have experienced in land subsidence in several decades. The north of Semarang was reported a higher rate of land subsidence compared with the south. It was believed that the land subsidence areas were affected by young alluvium, ground extraction and a load of the building. To anticipate, land subsidence should be monitored and detected in an early stage. The most effective way of monitoring land subsidence using GPS, DInSAR to evaluate the characteristic of land subsidence. The GPS observation was conducted in 2016 – 2018 using CORS UDIP as a base station and Sentinel Data was conducted to analyzed the subsidence rate in Semarang. The result showed land subsidence rate in several areas was distributed both spatially and temporally.
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