EMODELAN TINGKAT PENYERAPAN DAK FISIK REGULER OLEH PEMERINTAH DAERAH DENGAN MENGGUNAKAN DATA MINING (STUDI KASUS BIDANG PENDIDIKAN)

KHAIRUNNISA, DINA (2023) EMODELAN TINGKAT PENYERAPAN DAK FISIK REGULER OLEH PEMERINTAH DAERAH DENGAN MENGGUNAKAN DATA MINING (STUDI KASUS BIDANG PENDIDIKAN). Skripsi thesis, Politeknik Keuangan Negara STAN.

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Abstract

Tujuan dari penelitian ini ialah untuk menentukan model terbaik dalam mengklasifikasikan tingkat penyerapan DAK fisik reguler agar dapat menjadi data pembanding dalam menilai kinerja pengelolaan DAK fisik dan menjadi bahan masukan dalam pertimbangan pengalokasian DAK fisik tahun berikutnya. Pembangunan model klasifikasi ini menggunakan data yang bersumber dari DJPB, BPS, KPU, dan BPKP dalam tahun 2020 s.d. 2022. Algoritma klasifikasi yang digunakan ialah random forest, gradient boosting, naïve bayes, logistic regression, dan neural network. Hasil evaluasi model menunjukkan bahwa model neural network merupakan model terbaik dengan recall score sebesar 93,18%. Kata kunci: DAK Bidang Pendidikan, Penyerapan DAK, Data Mining, Algoritma Klasifikasi he aim of this research is to determine the best model for classifying the level of absorption of regular physical Special Allocation Fund (SAF) so that it could be used as a data comparison in assessing the performance of physical SAF management and as input in considering the allocation of physical SAF for the following year. The development of this classification model uses data sourced from DJPB, BPS, KPU, and BPKP from 2020 to 2022. The classification algorithms used are random forest, gradient boosting, naïve bayes, logistic regression, and neural network. The model evaluation results show that the neural network model is the best model with a recall score of 93.18%. Keywords: SAF For Education Sector, SAF Absorption, Data Mining, Classification Algorithm

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