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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Gamatika Prosiding Seminar Matematika dan Pendidikan Matematik JURNAL SOSIAL HUMANIORA (JSH) Semesta Teknika Elkawnie Register: Jurnal Ilmiah Teknologi Sistem Informasi Science and Technology Indonesia Journal of Environment and Sustainability Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics JAIM (Jurnal Abdi Masyarakat) Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah Matematika dan Statistika (MIMS) Journal of Applied Data Sciences Journal of Research in Social Science and Humanities COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Sewagati Limits: Journal of Mathematics and Its Applications
Mohammad Isa Irawan
Departemen Matematika Institut Teknologi Sepuluh Nopember Surabaya
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Journal : International Journal of Computing Science and Applied Mathematics

 1 
A Genetic Algorithm with Best Combination Operator for the Traveling Salesman Problem Muhammad Luthfi Shahab; Titin J. Ambarwati; Soetrisno Soetrisno; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 5, No 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.627 KB) | DOI: 10.12962/j24775401.v5i2.5830

Abstract

In this research, we propose a genetic algorithm with best combination operator (BC(x,y)O) for the traveling salesman problem. The idea of best combination operator is to find the best combination of some disjoint sub-solutions (also the reverse of sub-solutions) from some known solutions. We use BC(2,1)O together with a genetic algorithm. The proposed genetic algorithm uses the swap mutation operator and elitism replacement with filtration for faster computational time. We compare the performances of GA (genetic algorithm without BC(2,1)O), IABC(2,1)O (iterative approach of BC(2,1)O), and GABC(2,1)O (genetic algorithm with BC(2,1)O). We have tested GA, IABC(2,1)O, and GABC(2,1)O three times and pick the best solution on 50 problems from TSPLIB. From those 50 problems, the average of the accuracy from GA, IABC(2,1)O, and GABC(2,1)O are 65.12%, 94.21%, and 99.82% respectively.
Sequence Alignment Using Nature-Inspired Metaheuristic Algorithms Muhammad Luthfi Shahab; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (142.567 KB) | DOI: 10.12962/j24775401.v3i1.2118

Abstract

The most basic process in sequence analysis is sequence alignment, usually solved by dynamic programming Needleman-Wunsch algorithm. However, Needleman-Wunsch algorithm has some lack when the length of the sequence which is aligned is big enough. Because of that, sequence alignment is solved by metaheuristic algorithms. In the present, there are a lot of new metaheuristic algorithms based on natural behavior of some species, we usually call them as nature-inspired metaheuristic algorithms. Some of those algorithm that are more efficient are firefly algorithm, cuckoo search, and flower pollination algorithm. In this research, we use those algorithms to solve sequence alignment. The results show that those algorithms can be used to solve sequence alignment with good result and linear time computation.
Classification of Poverty Levels Using k-Nearest Neighbor and Learning Vector Quantization Methods Santoso Santoso; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 2, No 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (288.38 KB) | DOI: 10.12962/j24775401.v2i1.1578

Abstract

Poverty is the inability of individuals to fulfill the minimum basic needs for a decent life. The problem of poverty is one of the fundamental problems that become the central attention of the local government. One of the government efforts to overcome poverty is using the alleviation programs. Government often faces some difficulties to sort out of the poverty levels in the society. Therefore it is necessary to conduct a study that helps the government to identify the poverty level so that the aid did not miss the targets. In order to tackle this problem, this paper leverages two classification methods: k-nearest neighbor (k-NN) and learning vector quantization (LVQ). The purpose of this study is to compare the accuracy of the value of both methods for classifying poverty levels. The data attributes that are used to characterize poverty among others include: aspects of housing, health, education, economics and income. From the testing results using both methods, the accuracy of k-NN is 93.52%, and the accuracy of LVQ is 75.93%. It can be concluded that the classification of poverty levels using k-NN method gives better performance than using LVQ method.
Co-Authors AA. Masroeri Abduh Riski, Abduh Adrianus Bagas Tantyo Dananjaya Akhmad Arif Junaidi Alan Catur Nugraha Alexander Setiawan Alvida Mustika Rukmi Alvida Mustikarukmi Amira, Siti Azza Andreas Handojo Antonio Galileo Tando Arie Dipareza Syafei Arifah, Enny Durratul Auliya Rahmayani Baiq Findiarin Billyan Chyntia Kumalasari Puteri Danang Wahyu Wicaksono Darmaji Darmaji Darmawan, Didiet Edi Satriyanto Ekky Hidma Octia Rahmah Elly Matul Imah Elnora Oktaviyani Gultom Elsen Ronando Erna Apriliani Fendhy Ongko Giandi, Oxsy Ginardi, Raden Venantius Hari Hadi Prasetiya Haloho, Freddi Hartanto Setiawan Hendy Hendy Hendy Hozairi Imam Mukhlash Imam Mukhlash Ira Puspitasari Kadek Eri Mahardika Ketut Buda Artana Khilmy, Akhmad Ku Khalif, Ku Muhammad Naim Mahdiyah, Umi Mardlijah - Mey Lista Tauryawati Mohamad Muhtaromi Mohammad Hamim Zajuli Al Faroby Mohammad Iqbal Mohammad Jamhuri Mohd Aziz, Mohd Khairul Bazli Muchamad Jati Nugroho Muhammad Agung Adi Maulana Muhammad Ahnaf Amrullah Muhammad Athoillah, Muhammad Muhammad Fakhrur Rozi Muhammad Hajarul Aswad Muhammad, Noryanti Mujiono, Edo Priyo Utomo Putro Ni Nyoman Tri Puspaningsih Nugraha, Arma Perwira NURUL HIDAYAT Nurul Hidayat Pratama, Qoria Yudi Putri, Endah R.M. Putri, Endah Rokhmati Merdika Rasyadan Taufiq Probojati Resi Arumin Sani Rita Ambarwati Rita Ambarwati Sukmono Robin Wijaya, Robin Ronando, Elsen Rukmini, Meme Samsul Setumin Santoso Santoso Sepriadi, Robby Setiawan, Muhammad Nanda Shahab, Muhammad Luthfi Siti Maghfiroh Soetrisno Soetrisno Sulastri Sulastri Titin J. Ambarwati Victory Tyas Pambudi Swindiarto YAN ADITYA PRADANA Yongky Ujianto Yuda Dian Harja Zulfa Afiq Fikriya