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Pembelajaran Bahasa Arab Berbasis Contextual Teaching and Learning Melalui Kitab Ta’lim Muta’alim Di Pondok Pesantren Api Al Masykur Kab. Semarang Masud, Muhammad
MADINAH Vol 6 No 1 (2019): Madinah: Jurnal Studi Islam
Publisher : INSTITUT AGAMA ISLAM TARBIYATUT THOLABAH LAMONGAN, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58518/madinah.v6i1.1288

Abstract

Learning must refer to what students must do as recipients of the lesson, because learning does not only memorize and remember, because learning is a process that is marked by a change in a person. That is, that students are able to absorb subject matter if, they can grasp meaning in the lessons they receive, and they capture meaning in their assignments, when they can associate new information with the knowledge and experience they already have. Related to this, Islamic boarding school is a place of learning with efforts to change the behavior of students to a better direction, so that many people entrust some of the responsibilities in boarding schools, especially in efforts to establish noble character. This research is intended to obtain measurable data, about the Arabic Language Learning Model Based on Contextual Teaching And Learning Through the Book of Ta'lim Muta'alim in Islamic Boarding School of API Al Masykur Kab. Semarang. The analytical method used is qualitative data analysis carried out in conjunction with the data collection process. The analysis technique was carried out using data analysis techniques which included three concurrent activities: data reduction, data presentation and conclusion drawing (verification). The results showed that: 1) Conceptualizing the learning process of the book Ta'lim al-Muta‘allim at the research location was carried out by examining the basic things that became the foundation of learning. 2) Carry out the Concept of Learning Activity Book Ta'lim al-Muta‘allim. In the research location, the concept of learning that has been compiled is carried out using the principle of interactive communication.
Enhanced skin cancer classification via Xception model Memon, Qurban Ali; Musthafa, Namya; Masud, Muhammad; Al Ameri, Ghaya
International Journal of Advances in Applied Sciences Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i1.pp69-76

Abstract

Skin cancer is a prevalent and deadly cancer, and early detection is crucial for improving treatment success. Intelligent technologies are currently being used to classify skin lesions. The fundamental goal of this experimental research is to investigate biomedical skin cancer datasets to develop an effective approach for determining whether a cancer is malignant or benign. Well-known deep learning classification models (convolutional neural network (CNN) (sequential), ResNet50, InceptionV3, and Xception) are employed to train and categorize the dataset images. Two large and balanced datasets are collected and employed in this research. One is used to compare the performance of the employed model algorithms. Next, the selected model(s) are again trained on the second dataset for validation and generalization purposes. It turns out that the performance of the Xception model is superior and can be generalized. The performance results obtained from various simulations are tabulated and graphed. Comparative results are also presented.