The dataset for Santander banks is released on kaggle.com to decide whether the customer makes a transaction or not. The classes in this dataset are 2 with 200,000 entries in records. Earlier experiments using the regression algorithm led to a precision rate of 89%. In this analysis, the best accuracy value from the algorithm was obtained by using 6 different algorithms, namely Support for the Vector Machine (SVM), Neural Network (NN), Naive Bayes (NB), Decision Tree (DT). Before performing the data mining with the algorithm, preprocessing is carried out using a normalizing technique using the range transformation method with values 0 and 1. From the study, the best results were obtained in a Decision Tree 96.03% accurate algorithm, 95.82%, and 95.71%, 95.38%, 90.42%, 90.42%, and Naive Bayes 14.69%. The algorithms of the Decision Tree are 95.03%, 95.71% and 92%. Except for the Naïve Bayes algorithm, the precise value is better than previous study.
The production of fish-based food processing has become a commodity for restaurants, restaurants, catering and home consumption, but there are still many people who don’t know how fish can be processed in various dishes for their daily needs. To find out how to make fish-based dishes, the researchers provide a solution to cooking any kind of food, starting from the grouping of types of dishes, the basic ingredients that must be prepared, how to cook them, to the address of the cooking link with ingredients from fish. This study aims so that people can cook various menus whose basic ingredients come from fish. This research uses clustering algorithm, k-means and k-medoids. The stages of this research consisted of data collection, data selection, modeling, data training, data testing and evaluation. The object in the study of menu data for various processed fish dishes consisted of 978 datasets of processed fish dishes. The data used for data relating to fish food ingredients with fish food attributes and the number of likes via the website, the fish dataset is sourced from https://ipm.bps.go.id/data/dataset/ikan. From the two algorithms, the best accuracy results are -1.777 for the k-means algorithm, while -1.535 results are obtained for the accuracy of the k-medoids algorithm.
Data mining is a way of searching for information from large amounts of data for the purposes of various applications. Several techniques in data mining can be used for association, classification, clustering, prediction, and sequential modeling. Machine learning is used in medical science to help medical teams find out the condition of patients with heart disease. A lot of machine learning still has limited predictive capabilities, and is incompatible. This study uses different machine learning techniques, namely PSO-based SVM, Neural Network, Decision Tree, Naïve Bayes and SVM to assist in building, understanding and interpreting different models of heart disease diagnosis. The use of the pso-based svm algorithm in the prediction of heart disease shows a 100% greatest accuracy than the Decision Tree, only 88.68% and Naïve Bayes of 82.15%, Neural Network with an accuracy of. 95.71%, SVM with an accuracy of 99.71%. The results of this study are expected to be beneficial for the world of health and for researchers who use machine learning techniques.
Tanaman Palawija merupakan tanaman pertanian yang ditanam pada lahan kering. Biasanya palawija berupa tanaman kacang – kacangan, serealia selain padi (jagung) dan umbi – umbian semusim (ketela pohon dan ubi jalar). Jenis tanah untuk menanam Palawija adalah tanah kering atau yang biasa disebut Latosol. Di dalam tanah Latosol terkandung pH 4,5 – 6,5. Dewasa ini telah berkembang media informasi berbasis Web dengan internet sebagai media. Tapi dalam studi kasus ini sistem pakar sangatlah tepat untuk media konsultasi, karena mampu merekomendasikan suatu rangkaian tindakan. Pada makalah ini diusulkan sebuah Sistem pakar menggunakan metode k-means clustering sebagai pendukung keputusan yang lebih baik dan lebih cepat. Dari keputusan hasil konsultasi yang didapat, akan muncul solusi pemilihan jenis tanah yang dapat digunakan untuk membudidaya-kan tanaman Palawija.
Pada era industri sekarang ini perkembangan ekspedisi jasa kirim mengalami peningkatan yang relatif pesat, membuat jalur perdagangan barang maupun bidang jasa menjadi meningkat untuk memenuhi kebutuhan konsumen. Salah satu ekspedisi jasa kirim yaitu PT Pos Indonesia yang merupakan Badan Usaha Milik Negara (BUMN). Kantor Pos Cirebon saat ini mempunyai banyak pesaing diantaranya yaitu JNE,TIKI, Sicepat, dan J&T. Salah satu faktor utama dalam proses pengiriman yaitu dibutuhkan keakuratan dalam mengelompokkan data pengiriman, maka diperlukan proses perhitungan yang tepat, agar dapat mencapai hasil yang akurat. Pada penelitian ini dilakukan proses clustering dengan algoritma K-Means dengan tujuan untuk mendapatkan informasi dari data pengiriman paket yang ada di Kantor Pos Cirebon pada bulan juli 2020 serta memperoleh kelompok terbaik berdasarkan hasil evaluasi DBI. Hasil cluster data pengiriman paket menggunakan algoritma K-means serta dengan perhitungan Davies Bouldin Index nilai yang paling mendekati angka 0 dengan percobaan cluster 2 sampai cluster 10 menghasilkan nilai k terbaik pada cluster 3 yaitu 0.104 dengan jumlah anggota Cluster 0: 414 items, Cluster 1: 280 items, Cluster 2: 6 items.
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