Zuherlina, Reni (2017) Pemodelan Pendapatan Asli Daerah di Provinsi Sumatera Barat Menggunakan Feed Forward Neural Networks. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Peran pemerintah dalam pembangunan membutuhkan berbagai sarana dan fasilitas pendukung agar terlaksananya pembangunan yang berkesinambungan. Mengoptimalkan penerimaan keuangan daerah dapat mengurangi ketergantungan terhadap pemerintah pusat sehingga dapat mewujudkan kemandirian daerah. Untuk mencapai hal tersebut, diperlukan pengelolaan Pendapatan Asli Daerah (PAD) secara efektif, efisien, serta profesional, dan berkelanjutan. PAD dipengaruhi oleh pengeluaran pemerintah, Produk Domestik Regional Bruto, jumlah penduduk, jumlah perusahaan, jumlah hotel dan jumlah pelanggan listrik. Hasil penerimaan PAD yang selalu berubah sulit untuk memprediksi-nya, sehingga diperlukan pemilihan metode prediksi yang ber-guna meminimumkan kesalahan dalam memprediksi. Metode prediksi yang digunakan pada penelitian ini adalah Neural Networks bertujuan untuk memodelkan PAD. Salah satu algoritma Neural Networks adalah Feed Forward Neural Networks. Model Feed Forward Neural Networks terdiri dari lapisan input, hidden, dan output. Model yang optimum di hidden layer sebanyak 1 neuron, dengan model terbentuk adalah FFNN (12,1,1).
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The role of government in development requires various supporting infrastructures and facilities for the implementation of sustainable development. Optimizing local financial revenue can reduce dependence on the government so as to realize regional self-reliance. In order to achieve that, the effective, efficient, professional, and sustainable Local Government Revenue management is required. Local Government Revenue is affected by government expenditures, Gross Regional Domestic Product, population, number of firms, number of hotels, and number of electricity customers. The frequently changing Local Government Revenue acceptance result is difficult to predict, so it is required to choose the useful prediction methods to minimize errors in predicting. The prediction method used in this research is Neural Networks aims to model PAD. One of Neural Networks algorithms is Feed Forward Neural Networks. Feed Forward Model Neural Networks consists of input, hidden, and output layers. The optimum model in the hidden layer is 1 neuron, with the model obtained is FFNN (12,1,1).
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 511.34 Zuh p-1 |
| Uncontrolled Keywords: | Feed Forward Neural Networks, Local Government Revenue, Feed Forward Neural Networks, Pendapatan Asli Daerah. |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | - Reni Zuherlina |
| Date Deposited: | 17 Jan 2018 04:22 |
| Last Modified: | 05 Mar 2019 04:11 |
| URI: | http://repository.its.ac.id/id/eprint/48477 |
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