Thalassaemia is the genetic disease caused by deficiency and syinthesis of globin chains. It influences our body by decreasing eroticist and hemoglobin degree. People with Thalassaemia in 2015 at Tasikmalaya, Garut, and ciamis west java were 203 people. They organized in POPTI Tasikmalaya branch that placed in Dr. Soekardjo and Preasetya Bunda hospital. On the therapy process, they have different time needs and blood volume needs in every transfusion process. On the other hand, the difference transfusion levels also influence in giving iron chelation medicine. Furthermore, the method needed to help POPTI committee and health staff in appropriating blood volume and Iron Chelating Agent trough Thalassaemia people. Datamining method used by applying clustering method used Kmeans algorithm. Furthermore, this research conducted to categorized people with Thalassaemia based on blood volume need and HB in every transfusion process. Moreover, the pattern known by minor Thalassaemia, intermediate Thalassaemia, and mayor Thalassaemia based on age pattern, HB level in transfusion process, and blood volume needs. The research method is begin by pre observation and data mining analysis method to analyze data on data mining using 3 steps of KDD such as data cleaning, data integration, data selection, data transformation, and data knowledge presentation. Further, the result of this research has 374 data that divided into 3 cluster. They are cluster 1 that has 214 data, cluster 2 has 137 data, and cluster 3 that has 23 data with the pattern that shows that the transfusion blood volume increase based on patient's age. KATA KUNCI
Traffic accidents are one of the causes of high mortality in the community. Based on information from the World Health Organization (WHO) the number of accident victims in each year amounts to 1,300,000 fatalities, this is caused by traffic accidents that exist throughout the world. The police recorded data on accidents that occurred in several regions of East Priangan namely Ciamis and Tasikmalaya Regencies for the 2016-2017 period reaching an accident rate of ± 1500. The analysis that can be done to reduce the intensity of the occurrence of these events is to use data mining processing techniques. The right method is used by looking at the condition of the data obtained, namely the Association Rules method with the calculation of the Apriori Algorithm. This method will look for patterns of data relations that are formed from combinations of an itemset, so that knowledge will appear from large datasets. The pattern of the relationship sought is the linkages of itemset variables involved in the accident by involving 4 variables that describe the identity of the perpetrators, namely gender, age, profession and level of education and 22 attributes of the dataset. The minimum limit of support, confidence and lift ratio values used in the Apriori Algorithm calculation rules is 15%, 70% and 1.1. This value is used to get many rules that have a high level of occurrence accuracy. The results of the combination pattern calculation were 3 times iterations on each number of data in each region, the pattern of associations found in the Tasikmalaya region were the relation of the professional variables and the age of the perpetrator with the attribute of the Student profession dataset and the boundary group ages 16 to 30 years, while for the pattern associations found in the area of Ciamis Regency, namely the relation between age and education level with the attribute dataset of the 16 to 30 year age group and high school education level. The accuracy of the value obtained is calculated manually and uses one of the data mining applications as a comparison of value accuracy, namely Tanagra 1.4.
Data transaksi penjualan produk kartu perdana kuota internet dapat dijadikan sebagai bahan acuan untuk mengetahui seberapa besar tingkat penjualan produk yang telah dipasarkan oleh beberapa operator telekomunikasi seluler. Data tersebut tidak hanya dijadikan sebagai data arsip penyimpanan laporan penjualan perusahaan saja, tetapi dapat dianalisa dan dimanfaatkan menjadi sebuah informasi untuk membantu dalam melakukan pengembangan strategi pemasaran produk. Tujuan dari penelitian ini yaitu untuk menemukan aturan asosiasi kombinasi antar item produk operator telekomunikasi seluler mana saja yang paling laku terjual di wilayah penjualan Priangan Timur meliputi cluster Ciamis, Garut dan Tasikmalaya. Perhitungan Algoritma Apriori pada aturan asosiasi ini dihitung melalui tiga tahap iterasi pembentukan kandidat k-itemset. Hasil analisa aturan asosiasi yang terbentuk dari perhitungan algoritma apriori dengan menentukan nilai minimum support 35% dan nilai minimum confidence 80%, menghasilkan 9 aturan asosiasi final terbaik pada cluster Ciamis, 21 aturan asosiasi final untuk cluster Tasikmalaya dan 7 aturan asosiasi final untuk cluster Garut. Ketiga wilayah penjualan tersebut produk yang paling sering laku terjual dipasaran outlet adalah produk dari operator kartu kuota internet XL dengan Telkomsel dan produk Indosat dengan Telkomsel. Dengan demikian hasil yang diperoleh dapat digunakan untuk membantu pengambil keputusan dalam meningkatkan penjualan produk yang lebih baik
The availability of clean water is a hope for the community to meet the needs of drinking sources and the availability of proper sanitation will prevent various diseases. So the government collaborates with villages in providing Community Based Drinking Water and Sanitation (PAMSIMAS). The PAMSIMAS program aims to increase the number of clean water facilities for communities in areas with low economic income levels. In the PAMSIMAS program in Tigaherang Village, Rajadesa District, Ciamis Regency, socialization steps are needed to the community to provide an understanding of clean water and sanitation, monitoring of clean water use and transparency of the PAMSIMAS program. To support its implementation, a Web-based Information System for Water Supply and Sanitation (PAMSIMAS) application design is proposed. This information system is expected to be able to optimize the performance and service of clean water for the community. Keywords: Community, PAMSIMAS Program (community based drinking water supply and sanitation), Information System.
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