Informasi Umum

Kode

19.04.4792

Klasifikasi

006.312 - Data mining

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Data Mining

Dilihat

206 kali

Informasi Lainnya

Abstraksi

Abstract—Indonesia is a country that can experience potentially adverse climate change. More than 50% of the population in Bandung Regency works in the agricultural sector. Hence, the prediction of rainfall is essential in agriculture to produce the best harvest and to minimize losses. In this study, a Classification and Regression Tree (CART) algorithm were used to forecast the rainfall in Bandung Regency. Furthermore, an Adaptive Synthetic Sampling (ADASYN) algorithm was added to optimize the model produced due to a class imbalance in the data. The weather data was collected from the Meteorology, Climatology and Geophysics Agency of Indonesia (BMKG) from 2005–2017. The results showed that using the CART algorithm yielded 93.94% rainfall prediction accuracy with a 1.38 s running time whereas using ADASYN and CART yielded an accuracy of 98.18% with a 1.48 s running time.

Keywords—ADASYN, CART, forecasting, rainfall

  • BUG1D2 - BAHASA INGGRIS I
  • BUG1E2 - BAHASA INGGRIS II
  • CS4333 - DATA MINING
  • CSH3L3 - PEMBELAJARAN MESIN
  • CCH4A3 - PENULISAN PROPOSAL
  • CCH4D4 - TUGAS AKHIR
  • CII3C3 - PEMBELAJARAN MESIN
  • CII4A2 - PENULISAN PROPOSAL
  • CII4E4 - TUGAS AKHIR
  • CPI3C3 - PEMBELAJARAN MESIN
  • III4A4 - TUGAS AKHIR
  • CII9G6 - PROPOSAL PENELITIAN

Koleksi & Sirkulasi

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Pengarang

Nama SITI NUR LATHIFAH
Jenis Perorangan
Penyunting FHIRA NHITA, ANNISA ADITSANIA
Penerjemah

Penerbit

Nama Universitas Telkom, S1 Ilmu Komputasi
Kota Bandung
Tahun 2019

Sirkulasi

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