No abstract

Recently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of the forecasting. Therefore, the paper will discuss reducing error using model translation. The error that will be reduced is Mean Square Error (MSE). Here, the analysis is done mathematically and the empirical study is done by applying translation to fuzzy model for enrollment forecasting at the Alabama University. The results of this analysis show that the translation in the extent of mean error can reduce the MSE.

Brain cancer is one of the most dangerous cancers that can attack anyone, so early detection needs to be done so that brain cancer can be treated quickly. The purpose of this study is to develop a new procedure of modeling radial basis function neural network (RBFNN) using singular value decomposition (SVD) method and to apply the procedure to diagnose brain cancer. This study uses 114 brain Magnetic Resonance Images (MRI). The RBFNN model is constructed by using steps as follows; image preprocessing, image extracting using Gray Level Co-Occurrence Matrix (GLCM), determining of parameters of radial basis function and determining of weights of neural network. The input variables are 14 features of image extractions and the output variable is a classification of brain cancer. Before learning process, the input data is normalized. The modeling is done by using K-means clustering method where the activation function in the hidden layer is Gaussian function and by determining the optimum weights of the model using SVD method. The best RBFNN model is 14 input neurons, 10 hidden layer neurons, and 1 output neuron. The results show that the sensitivity, specificity, and accuracy of RBFNN diagnoses with backpropagation equal to those of RBFNN with SVD. However, the RBFNN-SVD delivers an advantage in the running speed of the program.Index Terms-Radial basis function neural network, diagnosis brain cancer, singular value decomposition.

Pemanfaatan teknologi informasi dalam pelaksanaan pembelajaran sebagai aktivitas evaluasi pembelajaran. Guru dapat memanfaatkan kemajuan teknologi untuk merancang soal berbasis aplikasi yang bisa dijadikan media untuk pelaksanaan penilaian. Penggunaan penilaian yang berbasis aplikasi merupakan salah satu alternatif untuk mengatasi kelemahan penggunaan penilaian tradisional yang sifatnya offline. Terdapat berbagai aplikasi yang dapat digunakan untuk mendukung kesuksesan proses penilaian di masa pandemic covid-19 seperti Kahoot dan Quizizz. Permasalahan mitra adalah: a) Guru belum optimal dalam memahami makna, manfaat, dan cara penggunaan teknologi informasi dalam kegiatan pembelajaran, b) Pengetahuan tentang teknologi informasi yang belum memadai menjadikan kemampuan guru dalam mengembangkan soal berbasis teknologi untuk kepentingan evaluasi pembelajaran perlu ditingkatkan, c) Pihak sekolah belum menyediakan media atau software komputer yang mendukung dalam pembuatan soal dengan aplikasi Kahoot dan Quizizz, d) Kurangnya narasumber yang bisa ditempati bertanya jika guru mengalami kesulitan untuk membuat soal dengan aplikasi Kahoot dan Quizizz. Berdasarkan analisis situasi yang terjadi pada saat pelaksanaan kegiatan pengabdian, tim pengabdi dapat menyimpulkan bahwa secara umum kegiatan pengabdian ini berjalan lancar dan baik. Namun tak dapat dipungkiri, ada beberapa kondisi yang menyebabkan hasil yang dicapai belum optimal. Hal tersebut disebabkan oleh waktu pelaksanaan pengabdian yang singkat serta kemampuan beberapa guru yang memang masih perlu bimbingan intensif. Selain itu kendala juga terdapat pada jaringan internet yang kurang stabil. Hal ini menyebabkan banyak waktu yang digunakan untuk menunggu proses selanjutnya. Kata Kunci:  Kahoot; Quizizz; Pelatihan; Teknologi; Matematika

This study aims to describe the application of the RME approach in increasing student activity and learning outcomes in the material for adding fractions for class V SD Inpres 3 Birobuli. This research uses classroom action research (PTK) which refers to Kemmis and Mc.Taggart Data collection techniques used were tests, observations, interviews, and field notes. The results showed that the application of the RME approach could increase student learning activities and results in the material for addition operations for class V SD Inpres 3 Birobuli by following the steps of the RME approach; (1) understand contextual problems, (2) explain contextual problems, (3) solve contextual problems, (4) compare and discuss student answers, and (5) conclude problems. This research was conducted in two cycles. The results showed that there was an increase in activity and learning outcomes which were seen in the observation of teacher activity in the very good category, student activity in the very good category, student activity in the very active category, and student affective learning outcomes were good. habits, and psychomotor learning outcomes of highly skilled students in cycle II. Likewise, the results of students' final tests with a percentage of learning completeness of 85% in cycle II.