OPTIMASI PENJADWALAN SISTEM PENGAIRAN AIR IRIGASI MENGGUNAKAN METODE ALGORITMA GENETIKA DENGAN PENDEKATAN GEOGRAFIS SPASIAL (STUDI KASUS WADUK KEULILING KABUPATEN ACEH BESAR) | ELECTRONIC THESES AND DISSERTATION

Electronic Theses and Dissertation

Universitas Syiah Kuala

    THESES

OPTIMASI PENJADWALAN SISTEM PENGAIRAN AIR IRIGASI MENGGUNAKAN METODE ALGORITMA GENETIKA DENGAN PENDEKATAN GEOGRAFIS SPASIAL (STUDI KASUS WADUK KEULILING KABUPATEN ACEH BESAR)


Pengarang

NURATUZZAKIAH, S.SI - Personal Name;

Dosen Pembimbing



Nomor Pokok Mahasiswa

1609200220002

Fakultas & Prodi

Fakultas / / PDDIKTI :

Penerbit

Banda Aceh : Program Studi Magister Matematika Universitas Syiah Kuala., 2019

Bahasa

Indonesia

No Classification

519.62

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Keuliling Reservoir which is located in Kuta Cot Glie, Aceh Besar is one of the reservoirs that has a function as a provider of water for irrigation needs, supports food self-sufficiency programs and others. The reservoir area has limited volume of water so, the most important water-saving irrigation water should be done to determine the scheduling of the distribution of irrigation water to the area of rice fields. The purpose of this research is to develop a method that can be used to the calculation of scheduling and can be applied to the irrigation of the Keuliling Reservoir watershed in Aceh Besar. In this study, the Genetic Algorithm method was used to determine the optimization of the Keuliling Reservoir in the Greater Aceh District. From the analysis that has been done, the scheduling process carried out so far is 72 hours where the amount of water entering the rice fields is 1,038,211,600 liters and is wasted into the river by 257,788,400 liters. The best irrigation time obtained is based on the results of calculations using the 48 Genetic Algorithm method in which the amount of water entering the rice field area is 794,149,300 liters and is wasted into the river by 69,850,700 liters. While the visualization of these results can be displayed using the Matlab GUI software.
Keywords: Irrigation, Scheduling, Genetic Algorithms


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