CLUSTERING FRAGMEN METAGENOM MENGGUNAKAN METODE GROWING SELF ORGANIZING MAP (GSOM) ( Studi Kasus Dinas Lingkungan Hidup Kota Jayapura) - Nur Ain Banyal; Surianti Surianti (Universitas Sriwijaya, 2020)
Metagenome is a microorganism that is taken directly from nature. The sequencen process of metagenome results in the mixing of various organisms. The data collection method used was Observation, using a direct plunge technique to the Jayapura City Environmental Department. This study uses data from metagenome fragments of 300 microbes. The technique of collecting metagenome fragment data used is cluster sampling. The research location is at the Jayapura City Environmental Agency. The purpose of this study is to analyze the effectiveness and efficiency of the Growing Self Organizing Map method in large-scale microbial grouping with short fragment lengths based on oligonucleotide frequencies. For feature extraction, k-mer frequency and spaced are used. Short fragments are used because in previous studies, the length of the fragment used was a long fragment (? 8 kbp), so in this study we want to overcome the drawbacks of using short fragments in the grouping of metagenome fragments. The results of the grouping of metagenome fragments will be tested for effectiveness and efficiency.