The purpose of this research is to combine the classification and classification methods that are part of data mining. The case raised was the number of the spread of the Covid-19 pandemic in Indonesia as of July 7, 2020 with 34 records. Data sources were obtained from Ministry of Health Data, sampled and processed from covid19.go.id and bnpb.go.id. The variables used in the study are the number of positive cases (x1), number of cases cured (x2) and number of deaths (x3) by province. The classification and classification methods used are k-medoids and C4.5. The k-medoids method works to map clusters of regions in Indonesia by province. The mapping labels used are 3 clusters: high cluster (C1 = red zone), alert cluster (C2 = yellow zone), low cluster (C3 = green zone). The results of the mapping are continued using the C4.5 method to see the rules in the form of a decision tree. The analysis process is assisted with the RapidMiner software. Determination of the number of clusters (k) is determined by using the Davies Bouldin Index (DBI) parameter to optimize the cluster results obtained. For k = 3 has an optimal value of 0.740. The mapping results obtained 9 provinces are in the high cluster (C1 = red zone), 3 provinces are in the alert cluster (C2 = yellow zone) and 22 provinces are in the low cluster (C3 = green zone). The value obtained from the decision tree for cluster height (C1 = red zone) based on C4.5 is if the number of positive cases is smaller than 9524 and greater than 4329 (4329> x1 <9524). The nine provinces included in the high cluster (C1 = red zone) are Aceh, Bali, DKI Jakarta, West Java, Central Java, East Java, South Kalimantan, South Sumatra and South Sulawesi. The results of the combination of these methods can be applied and provide knowledge in the form of new information about mapping in the form of clusters to the distribution of the Covid-19 pandemic in Indonesia
The purpose of this research is to analyze and implement the data mining technique in the export of crude petroleum materials to the destination country. This is because Indonesia is a member of OPEC (Organization of the Petroleum Exporting Countries) which is one of the largest petroleum exporters in the world. It aims to obtain profits in the form of foreign exchange income obtained by the State. The data source was obtained from the Central Statistics Agency (BPS) with the website https://www.bps.go.id for data for 2017-2018. The calculation process The technique used is clustering with the K-Medoids algorithm. The calculation process is carried out using the help of Rapid Miner tools. The clusters used in this study are 2 namely: high cluster (C1) for export of crude oil materials and low cluster (C2) for crude oil materials. The results of the study stated that the high cluster (C1) consisted of 3 countries (Japan, Thailand and the United States) and the low cluster (C2) consisted of 6 countries (South Korea, Taiwan, China, Singapore, Malaysia and Singapore). It is hoped that the research results will be input and information for the government to rearrange policies in order to increase competitiveness, ensure business certainty and the sustainability of domestic industrial raw materials.
The Rough Set (RS) method is part of machine learning that analyzes the uncertainty of the dataset used to determine the attributes of important objects (classification). The purpose of this study was to extract information from the rough set using the Rosetta application in predicting cases of students' level of understanding of the course. The attributes used are communication (F1), learning atmosphere (F2), learning media (F3), appearance (F4), and teaching methods (F5). Sources of data obtained from the output of the Journal of Physics: Conference Series, 1255 (1). https://doi.org/10.1088/1742-6596/1255/1/012005. The results of the application of the Rough Set method in determining the prediction of the level of student understanding of the course, produce new knowledge, namely learning outcomes based on the subject. There are 15 Reductions with 90 Generate Rules. But overall, the attributes that affect the level of student understanding of the subject are communication (F1) and learning media (F3)
The selection of Calcium Dairy Products that are suitable for old age uses the PROMETHEE II Algorithm. This study aims to recommend calcium milk products that are appropriate for elderly people based on consumer selection. This research was conducted in Simalungun district using interview techniques, observation and questionnaires to 350 elderly respondents randomly. This study also uses a quantitative data approach, which is testing four calcium milk products (alternatives) that are considered appropriate for use in old age. The four dairy products are widely used for the elderly, namely: Anlene Gold (A1), Entrasol (A2), Prolansia (A3) and Appeton 60+ (A4). The assessment criteria used in the selection of calcium milk recommendations appropriate for old age are: price (C1), content (C2), side effects (C3) and taste variants (A4). The solution used is to use a decision support system with PROMETHEE II algorithm. The results of PROMETHEE II calculation show that Anlene (A1) is obtained as the first recommendation of the right calcium milk with a value (net flow 0.5) and Appeton 60+ (A4) as the second recommendation with a value (net flow 0.484).
UMKM merupakan pelaku bisnis yang bergerak pada berbagai bidang usaha untuk kepentingan masyarakat. Pada saat ini UMKM dianggap sebagai cara yang efektif dalam pengentasan kemiskinan. UMKM pada saat ini sebagian besar dihadapkan dalam suatu permasalahan yang membuat usaha tersebut menjadi tidak lancar atau tidak berkembang, hal ini disebabkan oleh faktor permodalan, pengembangan kemitraan, promosi, pengembangan usaha dan sumber daya manusia. Penerapan ilmu datamining untuk menganalisa atribut pelaku usaha UMKM diperlukan untuk membantu permasalahan tersebut dengan melihat hasil uji algoritma klasifikasi yaitu Decision Tree dan CHAID serta algoritma Asosiasi Tertius. Pemberian bantuan terhadap pelaku usaha UMKM dengan cara memberi pelatihan strategi pemasaran dan penggunaan sarana prasarana penjualan sesuai proporsi masing-masing pelaku usaha dengan melihat hasil analisa algoritma datamining.Hasil pengujian menunjukan bahwa perbandingan algoritma klasifikasi Decision Tree dengan CHAID akurasi tertinggi 90.49% untuk algoritma Decision Tree sedangkan 89.51% untuk algoritma CHAID. Sedangkan pengujian algoritma asosiasi menggunakan algoritma Tertius mendapatkan kombinasi asosiasi antara nilai atribut umur, jenis kelamin, dan pekerjaan. Kata kunci : Klasifikasi, Asosiasi, UMKM, Decision Tree, CHAID, Tertius
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.