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Optimasi kesesuaian kompetensi pemeriksa infrastruktur jalan dengan algoritma genetika = Optimization competency compatibility of road infrastructure auditors with genetic algorithm

Ida Bagus Agung Wakya Parahita; Yusuf Latief, supervisor; Ayomi Dita Rarasati, examiner; Rully Adhika, examiner; Petroceany, Jade Sjafrecia, examiner (Fakultas Teknik Universitas Indonesia, 2014)

 Abstrak

[ABSTRAK
Infrastruktur memiliki peranan penting dalam perekonomian suatu negara. Badan Pemeriksa Keuangan (BPK) adalah lembaga negara pengawasan anggaran infrastruktur. Kompetensi pemeriksa di BPK masing-masing berbeda. Untuk mencapai hasil audit yang berkualitas diperlukan kesesuaian antara kompetensi dan tipe pekerjaan infrastruktur jalan. Metode algoritma genetika digunakan agar tercapai kesesuaian kompetensi yang optimal. Penelitian ini bertujuan mengembangkan model optimasi dengan algoritma genetika dan membandingkan hasilnya dengan model penugasan pemeriksa manual. Metode analisa yang digunakan yaitu metode algoritma genetika dan analytical hierarchy process. Hasil penelitian menunjukkan bahwa hasil metode optimasi dengan algoritma genetika lebih baik dari metode penugasan manual dari sisi kesesuaian kompetensi.

ABSTRACT
Infrastructure has important roles in economic level of the country. The Supreme Audit Board (SAB) is state institution that supervise the infrastructure budget. Auditor Competency in SAB are different each other. In order to achieve quality audit, compatibility between competency and type of road infrastructure is needed. Genetic algorithm is proposed to achieve optimum competency compatibility. This research aimed to develop optimization model using genetic algorithm method and compare the result with manual assignment method. Analytical method are genetic algorithm method and analytical hierarchy process. Results show that genetic algorithm method achieve better results than manual assignment in competency compatibility;Infrastructure has important roles in economic level of the country. The Supreme Audit Board (SAB) is state institution that supervise the infrastructure budget. Auditor Competency in SAB are different each other. In order to achieve quality audit, compatibility between competency and type of road infrastructure is needed. Genetic algorithm is proposed to achieve optimum competency compatibility. This research aimed to develop optimization model using genetic algorithm method and compare the result with manual assignment method. Analytical method are genetic algorithm method and analytical hierarchy process. Results show that genetic algorithm method achieve better results than manual assignment in competency compatibility;Infrastructure has important roles in economic level of the country. The Supreme Audit Board (SAB) is state institution that supervise the infrastructure budget. Auditor Competency in SAB are different each other. In order to achieve quality audit, compatibility between competency and type of road infrastructure is needed. Genetic algorithm is proposed to achieve optimum competency compatibility. This research aimed to develop optimization model using genetic algorithm method and compare the result with manual assignment method. Analytical method are genetic algorithm method and analytical hierarchy process. Results show that genetic algorithm method achieve better results than manual assignment in competency compatibility, Infrastructure has important roles in economic level of the country. The Supreme Audit Board (SAB) is state institution that supervise the infrastructure budget. Auditor Competency in SAB are different each other. In order to achieve quality audit, compatibility between competency and type of road infrastructure is needed. Genetic algorithm is proposed to achieve optimum competency compatibility. This research aimed to develop optimization model using genetic algorithm method and compare the result with manual assignment method. Analytical method are genetic algorithm method and analytical hierarchy process. Results show that genetic algorithm method achieve better results than manual assignment in competency compatibility]

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 Metadata

No. Panggil : T42487
Entri utama-Nama orang :
Entri tambahan-Nama orang :
Entri tambahan-Nama badan :
Subjek :
Penerbitan : Depok: Fakultas Teknik Universitas Indonesia, 2014
Program Studi :
Bahasa : ind
Sumber Pengatalogan : LibUI ind rda
Tipe Konten : text
Tipe Media : unmediated ; computer
Tipe Carrier : volume ; online resource
Deskripsi Fisik : xviii, 101 pages ; illustration ; 28 cm. + appendix
Naskah Ringkas :
Lembaga Pemilik : Universitas Indonesia
Lokasi : Perpustakaan UI, lantai 3
  • Ketersediaan
  • Ulasan
No. Panggil No. Barkod Ketersediaan
T42487 15-18-180529061 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 20390218