Agriculture is crucial for the existence of humankind. Agriculture provides a significant portion of the income for many people all around the world. Additionally, it provides a large number of work possibilities for the general public. Numerous farmers desire for a return to the old-fashioned techniques of farming, which provides little profit in today’s market. Long-term economic growth and prosperity are dependent on the success of agriculture and associated companies in the United States. Agribusiness crop yields may be increased by carefully selecting the right crops and putting in place supportive infrastructure. Weather, soil fertility, water availability, water quality, crop pricing, and other factors are taken into consideration while making agricultural predictions. Machine learning is critical in crop production prediction because it can anticipate crop output based on factors such as location, meteorological conditions, and season. It is advantageous for policymakers and farmers alike to be able to precisely estimate crop yields throughout the growing season since it allows them to anticipate market prices, plan import and export operations, and limit the social cost of crop losses. The use of this tool assists farmers in making informed decisions about which crops to grow on their land. In this study, a machine learning framework for agricultural yield prediction is presented. Crop information is collected in an experiment’s data set. Then, feature selection is performed using the Relief algorithm. Features are extracted using the linear discriminant analysis algorithm. Machine learning predictors, namely, particle swarm optimization-support vector machine (PSO-SVM), K-nearest neighbor, and random forest, are used for classification.

Alzheimer’s disease is characterized by the presence of abnormal protein bundles in the brain tissue, but experts are not yet sure what is causing the condition. To find a cure or aversion, researchers need to know more than just that there are protein differences from the usual; they also need to know how these brain nerves form so that a remedy may be discovered. Machine learning is the study of computational approaches for enhancing performance on a specific task through the process of learning. This article presents an Alzheimer’s disease detection framework consisting of image denoising of an MRI input data set using an adaptive mean filter, preprocessing using histogram equalization, and feature extraction by Haar wavelet transform. Classification is performed using LS-SVM-RBF, SVM, KNN, and random forest classifier. An adaptive mean filter removes noise from the existing MRI images. Image quality is enhanced by histogram equalization. Experimental results are compared using parameters such as accuracy, sensitivity, specificity, precision, and recall.

Arabic communication skills for non-Arabs are faced with serious problems; therefore, the use of technology-based platforms is considered following students’ wishes in the era of digital technology. Various technological devices have been widely used by educators for multiple levels of education but have not obtained maximum results. The novelty of this research is the use of Duolingo as a platform for teaching Arabic language skills. This study describes that Duolingo is very relevant to be used as a medium for learning Arabic for beginners because the teaching material begins with the new alphabet and vocabulary equipped with pictures. However, Duolingo still needs to make an essential revolution for learning Arabic speaking skills, especially for andragogy learners who have expert Arabic skills. Based on the findings, some implications are put forward.

The learning process has changed totally since the implementation of the distance learning policy (Pembelajaran Jarak Jauh-PJJ). Lecturers and students are required to be able to optimize the internet. This article discusses the process of Maharah Qira’ah using e-learning in UIN Imam Bonjol Padang. This research is a qualitative study by describing data found in the field in depth. The data were collected through Google Forms, observation, distribution of questionnaires through Google Forms, and online interviews through social media and documentation. The results showed that the e-learning media used in Maharah Qira’ah classes are WhatsApp, Zoom, Youtube, Instagram, and Facebook applications, where Whatsapp is more significant than other media. In an effort to realize reading skills, the lecturers designed the lesson by demanding students to understand Qira'ah texts sent through WhatsApp Group, by writing new vocabulary found in the text, recording their readings, and sending them to WhatsApp Group, followed by solving 10 problems, and then discuss them with the lecturers and the other students. This study found that there is a shift in learning maharah qira’ah using e-learning from student center to media center. It means that the process depends on technology is more significant than dependence on teachers. This study also found that learning mahara qira'ah with conventional methods is more preferred by students than using e-learning. Although the teacher explains the material in depth and provides assignments that support student learning.

Knowledge of the Islam at every student is supported by many factors, one of which is the Arabic language compentence. This research aimed to evaluate and find Arabic language learning construction in strengthening al-Islam at higher education. The desire to find the construction is because there is no visible connection between Arabic language learning and al-Islam learning so that clarity of learning objectives, learning materials, learning implementation, and evaluation systems of Arabic language learning at higher education is needed. In line with this purpose, this study used a qualitative method with a phenomenological approach. The sources of data were facts, Arabic language lecturers, al-Islam lecturers, and students purposively. Data were analyzed by using critical realism. The results of the study proved that the reconstruction of learning objectives, materials, implementation, and evaluation systems is needed to realize Arabic language learning that can strengthen al-Islam at higer education.

This research aims to determine the influence of power point media towards students' interest in learning Arabic, this goal is based on the problem of low interest students in learning Arabic, the low motivation is according to the hypothesis of the researcher is caused by the inability of teachers to use media that is already familiar with students such as power points. The study used quantitative methods with a test design of the use of PowerPoint on learning in the classroom and seeing its high influence on the students ' Arab learning interests. Data sources of all X-grade students and data analysis techniques using simple recretion assisted with SPSS version 24. Analysis of research data showed: 1) the PowerPoint Medium on Arabic language learning in the high category, evidenced by the median 82.5 2) interest in learning Arabic students was in categories with median 61.7. 3) There is a significant influence of 25.7% by variable X to variable Y, with a value of sig 0.008 and R Square 0.257.