Pratiwi, Erlyan Eka (2017) Penerapan Algoritme Genetika pada Kasus Optimasi Penentuan Bibit dan Pemerataan Subsidi Pupuk. Sarjana thesis, Universitas Brawijaya.
Abstract
Pemerataan dalam pembagian pupuk bersubsidi memiliki beberapa kendala. Berdasarkan survei pemerataan subsidi benih dan pupuk pada kelompok tani Desa Pandansari Kabupaten Kediri, beberapa kendala pemerataan tersebut yaitu kebanyakan petani tidak mempunyai dasar dan perhitungan yang tepat dalam membeli subsidi pupuk berdasarkan kebutuhan nutrisi jenis benih yang di tanam. Sehingga berakibat petani hanya membeli jenis pupuk dengan komposisi yang sama padahal varietas tanaman yang ditanam berbeda menyebabkan hasil panen yang kurang maksimal. selain itu jugs jika komposisi pupuk tidak sesuai dengan varietas maka jumlah pupuk di gudang akan kekurangan dan kelebihan. Untuk memecahkan masalah tersebut digunakan metode Algoritme Genetika. Parameter algoritme yang digunakan pada tanaman padi adalah populasi sebanyak 220, generasi sebanyak 1100, nilai crossover rate 0,8 dan mutation rate 0,2 sedangkan pada tanaman jagung populasi sebanyak 320, generasi sebanyak 1250, nilai crossover rate 0,8 dan crossover rate 0,2. Nilai selisih persentase rata-rata yang dihasilkan algoritme genetika dan pupuk di gudang pada tanaman padi sebesar 9,873% sedangkan pada tanaman jagung menghasilkan selisih persentase rata-rata antara pupuk di gudang dan algoritme genetika sebesar 24,882%. Solusi Komposisi pupuk yang dihasilkan oleh algoritme genetika dapat dipastikan bahwa nutrisi yang dibutuhkan tanaman terpenuhi sehingga hasil panen dapat meningkat.
English Abstract
Equity in the distribution of subsidized fertilizer has several constraints. Based on a survey of equal distribution of seed and fertilizer subsidy at farmer group of Pandansari Village of Kediri Regency, several equality obstacles are that most farmers have no basis and proper calculation in buying fertilizer subsidy based on nutrition requirement of planted seeds. So that resulted in farmers only buy the type of fertilizer with the same composition when different plant varieties that cause less than maximum yield. Besides also if the composition of fertilizer not in accordance with the varieties then the amount of fertilizer in the warehouse will be shortages and excess. To solve the problem used Genetic Algorithm method. The algorithm parameters used in rice plants are population as much as 220, generation as much as 1100, crossover rate 0,8 and mutation rate 0,2 whereas in corn plant population as much as 320, generation 1250, crossover rate 0,8 and crossover rate 0 , 2. The average percentage difference in value generated by genetic algorithm and fertilizer in warehouses on rice plant is 9,873% while in corn plants yield difference of mean percentage between fertilizer in warehouse and genetic algorithm equal to 24,882%. Solution The composition of fertilizers produced by genetic algorithms can be ascertained that the nutrients needed by plants are met so that the yield can increase.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2017/687/051708199 |
| Uncontrolled Keywords: | Pupuk, Subsidi, Pemerataan, Algoritme Genetika |
| Subjects: | 000 Computer science, information and general works > 006 Special computer methods > 006.3 Artificial intelligence > 006.31 Machine learning |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Yusuf Dwi N. |
| Date Deposited: | 25 Sep 2017 04:18 |
| Last Modified: | 11 Jan 2021 04:28 |
| URI: | http://repository.ub.ac.id/id/eprint/2895 |
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