Automatic segmentation methods for in vivo magnetic resonance imaging are increasing in popularity because of their high efficiency and reproducibility. However, automatic methods can be perfectly reliable and consistently wrong, and the validity of automatic segmentation methods cannot be taken for granted. Quality control (QC) by trained and reliable human raters is necessary to ensure the validity of automatic measurements. Yet QC practices for applied neuroimaging research are underdeveloped. We report a detailed QC and correction procedure to accompany our validated atlas for hippocampal subfield segmentation. We document a two‐step QC procedure for identifying segmentation errors, along with a taxonomy of errors and an error severity rating scale. This detailed procedure has high between‐rater reliability for error identification and manual correction. The latter introduces at maximum 3% error variance in volume measurement. All procedures were cross‐validated on an independent sample collected at a second site with different imaging parameters. The analysis of error frequency revealed no evidence of bias. An independent rater with a third sample replicated procedures with high within‐rater reliability for error identification and correction. We provide recommendations for implementing the described method along with hypothesis testing strategies. In sum, we present a detailed QC procedure that is optimized for efficiency while prioritizing measurement validity and suits any automatic atlas.

The development of technology today with the existence of artificial intelligence, conducted research to prove the Backpropagation method can predict students / wati in the modern boarding school Al-Kautsar. Artificial neural network is a method that is able to perform mathematical processes in predicting santri / wati. Bacpropagation algorithm is used to process data that is implemented with Matlab. Where data is collected through direct observation. Data is grouped by majors. The results obtained from the Matlab test performace and epoch values of each architecture are not the same as the results of the tests are displayed in the form of a graph comparing the target value with the research and testing process. The results of this study provide information on the modern Al-Kautsar boarding school on the number of registrants in 2020

Novel merupakan karya sastra naratif yang menyajikan gambaran kehidupan yang  dibawakan melalui tokoh. Fenomena kajian psikologi menjadi kajian yang menarik karena dapat  mengungkapkan kepribadian tokoh-tokoh dalam novel. Novel Hati Suhita memiliki tokoh yang  menarik untuk dikaji, yakni tokoh Alina Suhita. Tujuan penelitian ini tidak lain adalah untuk  mengungkapkan kepribadian tokoh Suhita dalam novel Hati Suhita. Pendekatan yang digunakan  dalam penelitian ini adalah teori psikologi humanistik Abraham Maslow. Penelitian ini  menerapkan isi dengan pendekatan kualitatif. Dengan menggunakan teori psikologi humanistik Abraham Maslow, penelitian ini akan memberikan penjelasan tentang hierarki kebutuhan tokoh  Alina Suhita sebagai individu dalam novel. Metode kualitatif yang digunakan dalam penelitian ini menghasilkan bahwasanya tokoh Alina dalam novel Hati Suhita mempunyai lima kebutuhan hierarki, yakni kebutuhan fisiologis, kebutuhan rasa aman, kebutuhan cinta dan kasih sayang, kebutuhan akan harga diri, dan kebutuhan aktualisasi diri.