Gradient Descent (GD) is used to find the local minimum value, its purpose is to find variables on the errorfunction so that a function can model the data with minimum error. Therefore, the purpose of this researchis to see how much iteration is needed and how big is the accuracy level in predicting the data when usingGradient Descent (GD) Standard and GD With Momentum and Adaptive Learning Rate (GDMALR)functions. In this study, the data to be processed using the gradient descent function is the data of SchoolParticipation Rate (SPR) in Indonesia aged 19-24 years, which began in 2011 to 2017. The reason forselection This age range is one of the factors that determine success education in a country, especiallyIndonesia. SPR is known as one of the indicators of successful development of education services in an areaof either Province, Regency or City in Indonesia. The higher the value of SPR, then the area is consideredsuccessful in providing access to education services. SPR data are taken from Indonesian Central Bureau ofStatistics. This study uses 3 models of network architecture, namely: 5-5-1, 5-15-1 and 5-25-1. From 3models, the best model is 5-5-1 with epoch 6202 iteration, 94% accuracy and MSE 0.0008658637. Thismodel is then used to predict SPR in Indonesia for the next 3 years (2018-2020). These results will beexpected to help the Indonesian government to further improve the scholarship and improve the quality ofeducation in the future

Acquired Immunodeficiency Syndrome or Acquired Immune Deficiency Syndrome (AIDS abbreviated) is a set of symptoms and infections that arise due to the destruction of the human immune system due to HIV viral infection. This study discusses about Rapidminer Application in Grouping Cases of AIDS Disease by Province with K-medoid Clustering Data Mining. The rise of AIDS cases in Indonesia has become a case that never escapes government attention. Attention to the ever increasing rate of death makes people worry about the spread of the AIDS virus. Sources of data and research are collected from the information document Number of Villages Who Have Health Facilities produced by the Social Security Administering Board. The data used in this study is data from 2008-2011 which consists of 34 provinces. Assessment criteria used are 2 ie 1). the average number of AIDS cases and 2). the average number of AIDS cases deaths were managed using 3 clusters ie high cluster level (C1), medium cluster level (C2) and low cluster level (C3). So that the cluster C1 obtained for Cases of AIDS Disease by Province as many as 4 provinces of Papua, DKI Jakarta, West Java and East Java, 9 provinces for cluster C2 and for cluster C3 as much as 20. This can be input to the government, the province of concern in the number of cases of AIDS.Keywords: Maining Data, AIDS Disease, Clustering, K-medoid

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Marriage dispensation is the marriage of a prospective bride or groom who is underage and has not been approved to marry according to the regulations. In fact there are still many young women who are married under the age of 20 years. This study aims to determine the marriage dispensation cluster, because there is no research on clustering marriage dispensation documents using a computer method to cluster any area that often conducts marriage dispensations with high and low clusters. The research method used is Data Mining with the K-Medoids algorithm. Based on calculations using the K-Medoids algorithm, high cluster results of 22 sub-districts and low clusters were obtained in 8 sub-districts. The results obtained from this study are expected to be input to the government through socialization activities in order to reduce the number of marriage dispensation in each region.

<p><em>Prediction is a process for estimating how many needs in the future. This study aims to predict the amount of coal exports according to the country the main goal in driving the pace of economic growth. The role of the agricultural sector in the national economy is very important and strategic. Coal is one of the fossil fuels. The general definition is a sedimentary rock that can burn, formed from organic deposits, mainly the remains of plants and formed through the process of pembatubaraan. The main elements consist of carbon, hydrogen and oxygen. Domestic production makes the government continue to implement coal export policies according to the state's main goal in driving the pace of economic growth in Indonesia. By using Artificial Neural Networks and backpropagation algorithms, architectural models will be sought to predict the amount of coal exports according to the state's main goal in driving the pace of economic growth to determine steps to assist the government in exporting coal based on the main destination country. This study uses 12 input variables with 1 target. Using 4 architectural models to test the data to be used for prediction, namely models 12-8-1, 12-16-1, 12-32-1 and 12-64-1. The best architectural model results obtained are 12-16-1 architectural models with 100% truth accuracy, the number of epoch 2602 and MSE is 0.0032. By using this model, predictions of coal exports are in accordance with the main destination countries with 100% accuracy.</em></p><p><em></em><strong><em>Keywords: </em></strong><em>Coal, Exports, predictions, backpropagation, Artificial Neural Networks</em> </p><p><em>Prediksi adalah proses untuk memperkirakan berapa banyak kebutuhan di masa depan. Studi ini bertujuan untuk memprediksi jumlah ekspor batubara menurut negara tujuan utama dalam mendorong laju pertumbuhan ekonomi. Peran sektor pertanian dalam ekonomi nasional sangat penting dan strategis. Batubara adalah salah satu bahan bakar fosil. Definisi umum adalah batuan sedimen yang dapat terbakar, terbentuk dari endapan organik, terutama sisa-sisa tanaman dan terbentuk melalui proses pembatubaraan. Unsur utama terdiri dari karbon, hidrogen, dan oksigen. Produksi dalam negeri membuat pemerintah terus menerapkan kebijakan ekspor batubara sesuai dengan tujuan utama negara dalam mendorong laju pertumbuhan ekonomi di Indonesia. Dengan menggunakan Jaringan Saraf Tiruan dan algoritma backpropagation, model arsitektur akan dicari untuk memprediksi jumlah ekspor batubara sesuai dengan tujuan utama negara dalam mendorong laju pertumbuhan ekonomi untuk menentukan langkah-langkah untuk membantu pemerintah dalam mengekspor batubara berdasarkan negara tujuan utama . Penelitian ini menggunakan 12 variabel input dengan 1 target. Menggunakan 4 model arsitektur untuk menguji data yang akan digunakan untuk prediksi, yaitu model 12-8-1, 12-16-1, 12-32-1 dan 12-64-1. Hasil model arsitektur terbaik yang diperoleh adalah model arsitektur 12-16-1 dengan akurasi 100%, jumlah zaman 2602 dan MSE adalah 0,0032. Dengan menggunakan model ini, prediksi ekspor batubara sesuai dengan negara tujuan utama dengan akurasi 100%</em>.</p><p><strong><em>Kata kunci:</em></strong><em> Batubara, Ekspor, prediksi, backpropagation, Jaringan Syaraf Tiruan</em></p>