Higher education institutions are demanded to be quality education providers. One of the instruments used by the government to measure the quality of education providers is the number of graduates. The higher the graduation level, the better the quality of education and this good quality will positively influence the value of accreditation given by BAN-PT. Therefore, in this study the researchers provided input for research conducted at Bhayangkara Jakarta Raya University to predict student graduation rates using the Neural Network algorithm. Neural Network is one method in machine learning developed from Multi Layer Perceptron (MLP) which is designed to process two-dimensional data. Neural Network is included in the Deep Neural Network type because of its deep network level and is widely implemented in image data. Neural Network has two methods; namely classification using feedforward and learning stages using backpropagation. The way Neural Network works is similar to MLP, but in Neural Network each neuron is presented in two dimensions, unlike MLP where each neuron is only one dimensional in size. The prediction accuracy obtained is 98.27%.
This study aims to formulate public opinion about bank interest included in the category of usury or not. The method used in this study is the analysis of usury sentiments on bank interest using Twitter data with the K-NN algorithm. Sentiment analysis using the K-NN algorithm gives good results. Evidenced by testing 170 twitter dataset using the K-NN algorithm obtained an accuracy of ± 70.59%. Assisted by the preprocessing process which aims to erase unnecessary parts and also change the form of documents in the form of tweets to a standard form so that classification can be carried out, so that the results of usury sentiment analysis on bank interest can clarify assumptions in the community and serve as a reference in determining appropriate banking products to the needs of customers
Perancangan Sistem Informasi Antrian Online untuk Pasien pada Rumah Sakit Seto Hasbadi dalam bentuk aplikasi berbasis Android menggunakan SMS gateway yang bertujuan merancang sistem informasi antrian online untuk pasien, sehingga proses pendaftaran antrian dapat dilakukan secara online serta memudahkan pasien dalam mendapatkan seputar informasi jadwal praktek dokter dan memudahkan pasien dalam pengambilan nomor urut antrian. Metode pengumpulan data yang digunakan dalam penelitian ini, yaitu observasi, interview, studi pustaka,dan metode pengembangan sistem. Metode pengembangan sistem yang digunakan dalam perancangan sistem informasi antrian online ini menggunakan metode Prototyping.
Abstract−Data Mining is a process of extracting data or filtering data that utilizes large data sets through a series of processes to obtain information that stands out from the data. PT. Coca-Cola Amatil Indonesia Cibitung-Plant has one of the largest warehouse in Indonesia exactly warehouse mega distribution center (DC). With ±32000 m2 warehouse area or equivalent to ±30000 Pallets. To maintain the accuracy of the stock in the warehouse of course required a good system in order to support the operational activities in the warehouse, one way to maintain the accuracy of stock in the warehouse is to do the overall product calculation in the warehouse (Stock Opname), in order to know the accuracy data in the system with the physical stock in the warehouse. With the data transactions stored in the database, sometimes the transaction data is only on leave to accumulate without any further action, then make the information system that manages the data to dig information by data mining techniques.
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