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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Tri Dharma Mandiri: Diseminasi dan Hilirisasi Riset Kepada Masyarakat (Jurnal Pengabdian Kepada Masyarakat) Babali Emergency and Disaster Research Signal and Image Processing Letters
Agus Wahyu Widodo, Agus Wahyu
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : knowledge engineering and data science

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Optimisation of Rice Fertiliser Composition using Genetic Algorithms Anissa, Retno Dewi; Mahmudy, Wayan Firdaus; Widodo, Agus Wahyu
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate of 0.9 and the mutation rate of 0.1. The amount of generation is 10 with the best fitness value is generated is equal to 1,603.
Efficient Scheduling of Plantation Company Workers using Genetic Algorithm Mahmudy, Wayan Firdaus; Pardede, Andreas; Widodo, Agus Wahyu; Rahman, Muh Arif
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one cut point, and the selection method is elitism selection. A set of computational experiments is carried out to determine the best parameters’ value of the genetic algorithm. The final result is a better 30 days worker schedule compare to the previous schedule that was produced manually.
Co-Authors Agus Harjoko Alayasi, Mutia Albyn, Devanda Faiqh Alqorni, Faiz Anissa, Retno Dewi Ardiansyah, Fredi Arief Andy Soebroto Bakhtiyar, Rizkhy Bayu Rahayudi Daud, Nathan Dzikrullah, Muhammad Aulia Fachruz Hak, Denny Achsanul Hakim, Gibran Harianto, Dwi Cahyo Hasdar Hernando, Deo Indriati Julian Syaputra, Rangga Kurnianingtyas, Diva Lailil Muflikhah Mahendra, Andika Raka Muh Arif Rahman Muh. Arif Rahman Novanto Yudistira Nurdiansyah, Yuli Pangondian, Yosia Pardede, Andreas Pradana Rifanto, Eko Adi SURBAKTI, PRAMA Tirana Noor Fatyanosa, Tirana Noor Wayan Firdaus Mahmudy Wibowo, Tri Suryo Yuita Arum Sari