MENDETEKSI ANOMALI PADA DATA TRANSAKSI JUAL BELI AKTA TANAH DENGAN MENGGUNAKAN ALGORITMA DECISION TREE, ISOLATION FOREST, DAN RANDOM FOREST

DWIARIPUTRA, YONATHAN HARTOKO (2022) MENDETEKSI ANOMALI PADA DATA TRANSAKSI JUAL BELI AKTA TANAH DENGAN MENGGUNAKAN ALGORITMA DECISION TREE, ISOLATION FOREST, DAN RANDOM FOREST. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Currently, Land Agency had been utilize information technology and communication to keep, manage, and provide land services for the public so that resulting in land databases as decisions making tool. However there has been several issue found along the way such as land certificate value abnormality in several region. Those land certificate value had been recognize as contrasted as the average land certificate value in each region. Along with the issue, come into view the initiative for finding outliers in transactin data using a machine learning model that kan be utilized for classifying the contrasted value. This paper that has the title Identifying Anomalies in Land Certificate Transaction Data using Decision Tree, Isolation Forest, and Random Forest Algorithm that contains all materials regarding Thesis's research that didn't published in the article. In this paperwork, will be explained about literature review, used dataset, along with planing steps, implementation phase, and research report results. Keywords: Classification, Outlier Detection, Decision-Tree, Isolation Forest, Random Forest, Tree-Based Classifier Instansi pertanahan saat ini telah memanfaatkan Teknologi Informasi Komunikasi dalam menyimpan, mengolah dan memberikan pelayanan pertanahan kepada masyarakat sehingga menghasilkan database pertanahan sebagai alat pendukung pengambilan keputusan. Namun demikian terdapat beberapa permasalahan antara lain masih terdapat nilai akta abnormal pada berbagai daerah. Nilai akta ini dianggap tidak sesuai dengan nilai akta rata-rata pada daerah tersebut. Dari permasalahan tersebut muncul inisiatif untuk menemukan anomali pada data transaksi jual beli dengan menggunankan sebuah model machine learning yang dapat digunakan untuk mengklasifikasikan nilai yang tidak sesuai. Kertas kerja berjudul Mendeteksi Anomali Pada Data Transaksi Jual Beli Akta Tanah Dengan Menggunakan Algoritma Decision Tree, Isolation Forest, dan Random Forest yang berisi semua material hasil penelitian Tugas Akhir yang tidak dimuat atau disertakan di artikel jurnal. Dalam kertas kerja ini akan dijelaskan mengenai literature review, dataset yang digunakan, serta langkah-langkah perancangan, tahapan implementasi dan hasil pengujian penelitian. Kata Kunci: Classification, Outlier Detection, Decision-Tree, Isolation Forest, Random Forest, TreeBased Classifier

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