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This study aims to analyze the factors that influence students' interest in continuing their education to college using a machine learning approach. Data was collected through an online questionnaire completed by 727 students between July 27 and August 22, 2025, covering 23 variables consisting of respondent identity (gender, grade level, major) as well as internal and external factors such as parental support, learning motivation, and preferred type of college. The data preparation stage was carried out through column cleaning, deletion of empty data, encoding of categorical variables, and division of the dataset into 80% training data and 20% test data. The Naive Bayes algorithm of the CategoricalNB type was used because it was suitable for the categorical nature of the data. The evaluation results showed that the model was able to predict student interest with 96% accuracy. For the class of students interested in continuing their studies, the precision, recall, and F1-score values were above 0.95, while the performance in the class of students who were not interested was slightly lower due to the smaller amount of data. These findings show that Naive Bayes is proven to be effective and reliable in classifying students' interest in continuing their studies and can be the basis for decision-making in designing more targeted educational strategies.

Tanaman obat (TO) adalah tanaman yang memiliki khasiat obat dan digunakan sebagai obat dalam penyembuhan maupun pencegahan penyakit. TO sebagai Obat Tradisional (OT) ini masih banyak digunakan oleh masyarakat, terutama dari kalangan menengah ke bawah. Bahkan dari masa ke masa,  OT ini mengalami perkembangan yang semakin meningkat, terlebih dengan munculnya isu kembali ke alam (back to nature) serta krisis yang berkepanjangan dan telah diakui juga bahwa OT dari TO tersebut  memiliki efek samping relatif kecil dibandingkan obat modern, meski tetap perlu diperhatikan bila ditinjau dari kepastian bahan aktif dan konsistensinya yang belum terjamin terutama untuk penggunaannya secara rutin. Bentuk dari kearifan budaya khususnya bagi masyarakat yang melestarikan pengobatan alami, TO perlulah didata dan didokumentasikan dengan tujuan agar berbagai manfaat TO dapat semakin banyak teridentifikasi dan secepatnya diimplementasikan kepada masyarakat. Dalam penelitian ini dihasilkan sebuah Elektronik Ensiklopedia Tanaman Herba (EETH) berbasis WEB yang merupakan salah satu upaya mendokumentasikan dan menginformasikan kepada masyarakat tentang berbagai tanaman yang berkhasiat obat. EETH ini dapat menyajikan informasi secara online mengenai berbagai macam tanaman yang berkhasiat obat/tanaman herba yang dapat membantu user dalam menambah pengetahuan mereka mengenaiTO, terutama TO yang tumbuh di sekitar lingkungan rumah dan cara pengolahan TO agar menjadi obat yang berkhasiat   Kata Kunci : Tanaman, Obat, Penyembuhan, Penyakit, Ensiklopedia

Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigations Remote sensing data is of such nature and volume as to require it to be compatible with processing and outputing by computers. They are the easiest, fastest, and most efficient way to produce images, extract data sets, and assist in decision making. One special function is to assist in manipulating other kinds of data about the spatial or locational aspects of areas in the world that are the subjects of interpretation and decision making. The bulk of the data in such systems have in common a geographical significance, that is, they are tied to definite locations on the Earth. In this sense, they are similar to or actually make up what has become a powerful tool in decision making and management. The Image-Based Information System (IBIS) was developed in 1975 at the Jet Propulsion Laboratory, and is designed to be a comprehensive geographic information system that performs operations on raster image, tabular, and graphics format data, using the Video Image Communication And Retrieval (VICAR) image processing system. This was accomplished by the creation of a new VICAR-based file format for tabulating raster format geographic information over multiple data planes.

This article discuss research progress and future opportunities for modeling consumer choice on the Internet using clickstream data and also to compare the nature of Internet choice (as captured by clickstream data) with supermarket choice (as captured by UPC scanner panel data). Though the application of choice models to clickstream data is relatively new, and review existing early work and provide a two-by-two categorization of the applications studied to date (delineating search versus purchase on the one hand and within-site versus across-site choices on the other). The article discusses additional opportunities afforded by clickstream information, including personalization, data mining, automation, and customer valuation and also offers directions for further research in these areas. Notwithstanding the numerous challenges associated with clickstream data research.