Warts is a skin health problem that is generally characterized by the appearance of small, rough-textured lumps on the skin surface caused by a virus that is human papilloma virus (HPV). One technique of treatment of wart disease is immunotherapy, this method is a treatment by boosting the immune system to overcome the disease of warts. Naive bayes and Support Vector Machine (SVM) is a method of data mining algorithm used to classify. The aim of this study was to compare the Naive bayes algorithm with Support Vector Machine (SVM) in predicting the success of immunotherapy treatment method in the treatment of wart disease. Tests conducted using the method of Naive bayes and Support Vector Machine (SVM) using the R programming language, then the results are used to do the comparison. The results of this study revealed that the Naive bayes method has superior prediction capability compared to Support Vector Machine (SVM) because Naive bayes can predict all class instances correctly with the accuracy level of 1.
Cooperatives are a forum that can help people, especially small and medium-sized communities. Cooperatives play an important role in the economic growth of the community such as the price of basic commodities which are relatively cheap and there are also cooperatives that offer borrowing and storing money for the community. Constraints that have been felt by this cooperative are that borrowers find it difficult to repay loan installments, causing bad credit. Because the cooperative in conducting credit analysis is carried out in a personal manner, namely by filling out the loan application form along with the requirements and conducting a field survey. Therefore there is a need for an evaluation to be carried out in lending to borrowers. To minimize these problems, it is necessary to detect customer criteria that are used to predict bad loans and to determine whether or not the elites are eligible to take credit using data mining. The data mining technique used is classification with the Naive Bayes method. Based on testing the accuracy of the resulting model obtained accuracy level of 59%, sensitivity (True Positive Rate (TP Rate) or Recall) of 46.80%, specificity (False Negative Rate (FN Rate or Precision) of 69.81%, Positive Predictive Value (PPV) of 57.89%, and Negative Predictive Value (NPV) of 59.67%.Abstrak-Koperasi merupakan suatu wadah yang dapat membantu masyarakat terutama masyarakat kecil dan menengah. Koperasi memegang peranan penting dalam pertumbuhan ekonomi masyarakat seperti harga bahan pokok yang tergolong murah dan juga ada koperasi yang menawarkan peminjaman dan penyimpanan uang untuk masyarakat. Kendala yang pernah di rasakan oleh koperasi ini adalah peminjam susah untuk membayar angsuran pinjaman sehingga menyebabkan terjadinya kredit macet. Karena pada koperasi dalam melakukan analisa pemberian kredit dilakukan secara personal, yaitu dengan cara mengisi lembar formulir permohonan peminjaman kredit disertai dengan persyaratan dan melakukan survey lapangan. Oleh karena itu perlu adanya evaluasi yang dilakukan dalam pemberian kredit kepada para peminjam. Untuk meminimalisir permasalahan tersebut perlu dilakukan pendeteksian kriteria-kriteria nasabah yang digunakan untuk memprediksi kredit macet serta untuk menentukan layak atau tidaknya peminja m dalam pengambilan kredit dengan menggunakan data mining. Teknik data mining yang digunakan adalah klasifikasi dengan metode naive bayes. Berdasarkan pengujian akurasi dari model yang dihasilkan diperoleh tingkat accuracy sebesar 59%, sensitivity (True Positive Rate (TP Rate) or Recall) sebesar 46,80%, specificity (False Negative Rate (FN Rate or Precision) sebesar 69,81%, Positive Predictive Value (PPV) sebesar 57,89%, dan Negative Predictive Value (NPV) sebesar 59,67%. Kata Kunci-Data Mining, Kredit Macet, Naive Bayes, Prediksi. I. PENDAHULUANKoperasi merupakan suatu wadah yang dapat membantu masyarakat terutama masyarakat kecil dan menengah. Koperasi memegang peranan penting dalam pertumbuhan ekonomi masyarakat seperti harga bahan pokok yang tergolo...
<p><em>The Livestock Sector is one of the most promising agribusiness sectors. Selection of the right type of cow is the duty of cattle farmers to get cows with quality. The aim of the study was to recommend the best type of cattle using the SMART method. Data sources were obtained by interviewing and giving questionnaires to 25 random beef cattle farmers in the parbalogan village, Tanah Jawa Subdistrict, Simalungun Regency. The six types of cattle (alternative) are used such as Lemosin (A1), Simental (A2), Bali (A3), Dairy (A4), Brahma (A5) and Madras (A6). While the assessment criteria are used, namely: Origin (C1), Price (C2), Age (C3), Weight (C4), and Size (C5). The results of the study state that the type of Lemosin (A1) Beef is the first recommendation with the final value of 1 and the type of Bali cow (A3) as the second recommendation with the final value of 0.702543..</em></p><p> </p><p><em>Keywords: DSS, Beef, Breeders, SMART Method, Pematangsiantar</em></p>
Data mining techniques are used to design effective sales or marketing strategies by utilizing sales transaction data that is already available in the company. The problem in the company is that there are many data transactions that occur unknown, causing an accumulation of data unknown sales most in each month & year, unknown brands of car oil are often sold or demanded by customers. So this association search uses a priori algorithm as a place to store data using pattern recognition techniques such as static and mathematical techniques from a set of relationships (associations) between items obtained, it is expected that can help developers in designing marketing strategies for goods in the company. Software testing results that have been made have found the most sold oil brand products if you buy Shell Hx7, it will buy Toyota Motor Oil with 50% support and 66.7% confidence. If you buy Toyota Motor Oil, you will buy Shell Hx 7 with 50% support and 85.7% confidence.
Education in Indonesia still faces various problems and challenges in teaching and learning process both internal and external factors such as props, media and also implementation of information technology. The use of multimedia-based learning media in the learning process will helps students to understand the material to be delivered. Random and match is a game consisting of 4 different games that are addressed to kindergarten children to know the use of technology positively in learning process, and by applying Model Learning Technology System Architecture learning an utilization using computer will be more useful for teacher and kindergarten students.
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