Average Weight Information Gain Untuk Menangani Data Berdimensi Tinggi Menggunakan Algoritma C4.5

Abstract. In the recent decades, a large data are stored by companies and organizations. In terms of use, big data will be useless if not processed into information according to the usability. The method used to process data into information is called data mining. The problem in data mining especially classification is data with a number of attributes that many and each attribute are irrelevant. This study proposes attribute weighting method using weight information gain method, then the attribute weights calculates the average value. Having calculated the average value of the attribute selection, the selected attributes are those with a value weights above average value. Attributes are selected then performed using an algorithm C4.5 classification, this method is named Average Weight Information Gain  C4.5 (AWEIG-C4.5). The results show that AWEIG-C4.5 method is better than C4.5 method with the accuracy of the average value of each is 0.906 and 0.898. Keywords: data mining, high dimensional data, weight information gain, C4.5 algorithmAbstrak. Dalam beberapa dekade terakhir, data yang besar disimpan oleh perusahaan dan organisasi. Dari segi penggunaan, data besar tersebut akan menjadi tidak berguna jika tidak diolah menjadi informasi yang sesuai dengan kegunaan. Metode yang digunakan untuk mengolah data menjadi informasi adalah data mining. Masalah dalam data mining khususnya klasifikasi adalah data dengan jumlah atribut yang banyak atau dalam bahasa komputer disebut data berdimensi tinggi. Pada penelitian ini diusulkan metode pembobotan atribut menggunakan metode weight information gain, kemudian bobot atribut tersebut dihitung nilai rata-rata. Setelah dihitung nilai rata-rata dilakukan pemilihan atribut, atribut yang dipilih adalah atribut dengan nilai bobot di atas nilai rata-rata. Atribut yang terpilih kemudian dilakukan klasifikasi menggunakan algoritma C4.5, metode ini diberi nama Average Weight Information Gain C4.5 (AWEIG-C4.5). Hasil penelitian menunjukkan metode AWEIG-C4.5 lebih baik daripada metode C4.5 dengan nilai rata-rata akurasi masing-masing adalah 0,906 dan 0,898. Dari uji paired t-Test terdapat perbedaan signifikan antara metode AWEIG C4.5 dengan metode C4.5.Kata Kunci: data mining, data berdimensi tinggi, weight information gain, algoritma C4.

Preparation of Silver Decorated Reduced Graphene Oxide Nanohybrid for Effective Photocatalytic Degradation of Indigo Carmine Dye

Background: Even though silver decorated reduced graphene oxide (Ag-rGO) shows max- imum absorptivity in the UV region, most of the research on the degradation of dyes using Ag-rGO is in the visible region. Therefore the present work focused on the photocatalytic degradation of indigo carmine (IC) dye in the presence of Ag-rGO as a catalyst by UV light irradiation. Methods: In this context, silver-decorated reduced graphene oxide hybrid material was fabricated and explored its potential for the photocatalytic degradation of aqueous IC solution in the UV region. The decoration of Ag nanoparticles on the surface of the rGO nanosheets is evidenced by TEM analysis. The extent of mineralization of the dye was measured by estimating chemical oxygen demand (COD) values before and after irradiation. Results: The synthesized Ag-rGO binary composites displayed excellent photocatalytic activity in 2 Χ 10-5 M IC concentration and 5mg catalyst loading. The optical absorption spectrum of Ag-rGO showed that the energy band-gap was found to be 2.27 eV, which is significantly smaller compared to the band-gap of GO. 5 mg of Ag-rGO was found to be an optimum quantity for the effective degrada- tion of IC dye. The degradation rate increases with the decrease in the concentration of the dye at al- kaline pH conditions. The photocatalytic efficiency was 92% for the second time. Conclusion: The impact of the enhanced reactive species generation was consistent with higher pho- tocatalytic dye degradation. The photocatalytic mechanism has been proposed and the hydroxyl radi- cal was found to be the reactive species responsible for the degradation of dye. The feasibility of reus- ing the photocatalyst showed that the photocatalytic efficiency was very effective for the second tim

Non-communicable Diseases, Big Data and Artificial Intelligence

This reprint includes 15 articles in the field of non-communicable Diseases, big data, and artificial intelligence, overviewing the most recent advances in the field of AI and their application potential in 3P medicine

Molecular genetic investigations of renal cell carcinoma predisposition

Renal Cell Carcinomas (RCC) are a diverse group of histologically and genetically distinct renal neoplasms accounting for 2.4% of all cancers worldwide. While a majority of RCC cases are sporadic in nature, a proportion are due to genetic predisposition caused by syndromic and non-syndromic conditions. Inherited renal cell carcinoma is associated with alterations in genes such as VHL, MET, FH, and FLCN and identification of these genes has been critical to understanding the molecular biology of both inherited and sporadic RCC, informing both clinical management and treatment. Despite the large number of known genes which are linked to RCC predisposition, most individuals with features of RCC predisposition do not harbour variants in known inherited RCC genes, suggesting additional unknown causes of heritability have yet to be uncovered. This study has utilised a range of genomic sequencing methodologies, scaling from single gene to whole genome sequencing, on individuals with features of renal cell carcinoma predisposition in order to identify novel causes of heritability associated with RCC. Multiple genomic sequencing approaches in these individuals has uncovered a range of potential genetic features that could be associated with predisposition to RCC, including genes not previously known to be associated with RCC, discovery of new molecular mechanisms of genetic inheritance for known RCC predisposition syndromes, and provided innovative methods for the identification and characterisation of molecular alterations in specific inherited RCC subtypes

Radiation and the Stent: Results From Catheter - Based Radiation. And Radioactive Stenting

Angiographic restenosis occurs in up to 60% of cases after balloon angioplasty (BA). Restenosis after BA occurs due to elastic recoil of the artery, vascular remodeling with vessel shrinkage and neointimal hyperplasia. Neointimal hyperplasia develops by migration and proliferation of smooth muscle cells (SMCs) and myofibroblasts after balloon-induced trauma of the arterial wall and by deposition of an extracellular matrix by the SMCs. By preventing elastic recoil and negative remodeling stent implantation has resolved many of the problems created by balloon angioplasty. However, a new problem has been created - that of in-stent restenosis, wh