OPTIMASI WAKTU EKSEKUSI PENENTUAN RUTE MENUJU OBYEK WISATA DI MALANG RAYA DENGAN ALGORITMA GENETIKA

• Mahmud Yunus

  Teknik Informatika STMIK PPKIA Pradnya Paramita

• Ryan Markus Thobias Rumlaklak

  Teknik Informatika STMIK PPKIA Pradnya Paramita

As one of the tourist destinations in Indonesia, the area of Malang Raya offers a variety of interesting
tourist attractions. Based on BPS statistics from Kota Batu in 2015, total tourist visits were 2,089,022
people. While the total tourist visit in 2014 in Malang Regency is 2,118,008 people. Data was taken at
22 tourism object in Batu Town and 10 tourism object in Malang Regency. The location of the
destination of several distant attractions, a constraint for tourists to determine the optimal route to the
tourist attraction. One alternative solution to the problem can be done using Genetic Algorithms. The
focus of this research is to build a web based application that can provide information on the order of
route of visits to some tourism objects optimally. Implementation is done based on the completion of
Traveling Salesman Problem, using Genetic Algorithm method. Variable optimization is (1) the
shortest total distance; and (2) application execution time with Brute Force algorithm as a
comparison. The results show that if the location of the chosen destination is numerous, the Genetic
Algorithm is more efficient in the use of time and resources than the Brute Force algorithm.

Badan Perencanaan Pembangunan Daerah.

Statistik Pembangunan Daerah

(Kabupaten Malang Dalam Angka) Tahun

Malang: Pemerintah Kabupaten

Malang.

Badan Pusat Statistik Kota Batu. 2015.

Kota Batu dalam Angka 2015. Batu: Badan

Pusat Statistik Kota Batu.

Kusumadewi, S., dkk. 2005. Penyelesaian

Masalah Optimasi dengan Teknik-teknik

Heuristi. Yogyakarta: Graha Ilmu.

Lukas, dkk. 2005. Penerapan Algoritma

Genetika untuk Travelling Salesman

Problem dengan Menggunakan Metode

Order Crossover dan Insertion Mutation

(hlm. 1-5). Seminar Nasional AplikasiTeknologi Informasi

Tahyudin, Imam dan Susanti, Ika. 2015.

Pencarian Rute Terbaik pada Obyek

Wisata di Kabupaten Banyumas

Menggunakan Algoritma Genetika Metode

TSP. JUITA ISSN: 2086-9398, 3 (4): 165173

Alberto J. Urdaneta, Juan F. Gomez, Elmer

Sorrentino, Luis Flores, Ricardo Diaz. “A

Hybrid Genetic Algorithm For Optimal

Reactive Power Planning Based Upon

Successive Linear Programmingâ€. IEEE

Transactions on Power Systems, Vol. 14,

No.42, November 1999.

D.E Goldberg,â€Genetic Algorithm in

Search, Optimization & Machine Learning,†Addison-Wesley Publishing

Company, Inc., Canada, 1989, hlm. 59-86.

Anastasios G. Bakirtzis, Pandel N. Biskas,

Christoforos E. Zoumas, Vasilios Petridis.

“Optimal Power Flow by Enhanced

Genetic Algorithmâ€. IEEE Transactions on

Power Systems, Vol. 17, No.02, May 2002.

N. Sannomiya , H. Iima, “Genetic

algorithm approach to a production

ordering problem in an assembly process

with buffersâ€. Proc. of 7th IFAC &mp. On

Information Control Problems in a

Manufacturing Technology, pp. 403408,1992.

Suyanto, “Algoritma Genetika dalam

MATLABâ€. Yogyakarta: ANDI, 2005,

hlm. 1-2.

T. Sutojo, Edy Mulyanto, Vincent

Suhartono. “Kecerdasan Buatanâ€.

Yogyakarta: CV. ANDI Offset, 2011.

• PDF (Indonesian)