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All Journal Journal of Education and Learning (EduLearn) Semeton Mathematics Journal
Ivan Luthfi Ihwani, Ivan Luthfi
brawijaya university
Humanities Education Library & Information Science Mathematics Social Sciences Other

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Computational thinking skills profile in solving mathematical problems based on computational thinking attitude Richardo, Rino; Dwiningrum, Siti Irene Astuti; Murti, Rahayu Condro; Wijaya, Ariyadi; Adawiya, Robiatul; Ihwani, Ivan Luthfi; Ardiyaningrum, Martalia; Aryani, Anggi Erna
Journal of Education and Learning (EduLearn) Vol 19, No 2: May 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v19i2.21643

Abstract

The aim of this qualitative research is to describe the thinking process as a profile of students' mathematical computational thinking (CT) skills in terms of CT attitudes. The subjects in this study were 66 junior high school students in grade IX. There were three students taken by purposive sampling based on high, medium, and low CT attitude. The main research instrument was the researcher, while the auxiliary instruments were mathematical CT ability test and CT attitude scale questionnaire. Data analysis included 3 stages, namely data reduction, data presentation, and conclusion drawing. The data credibility test used triangulation techniques, namely tests and interviews. The results showed that subjects with high CT attitude were able to show all indicators of CT ability, namely abstraction, problem decomposition, algorithmic thinking and generalisation and pattern recognition. However, subjects with moderate and low CT attitudes were only able to show one of these indicators, namely abstraction. Based on the results of this study, researchers will create a mathematics learning model to develop CT skills, especially for number pattern material.
Design of Facial Expressions Recognition for Academic Presence By Using Backpropagation Artificial Neural Networks Based on Principal Components Analysis Setiawati, Setiawati; Zahro, Uswatun Az; Robbaniyyah, Nuzla Af'idatur; Ihwani, Ivan Luthfi
Semeton Mathematics Journal Vol 1 No 2 (2024): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i2.240

Abstract

There are 4,004 universities in Indonesia where each university needs data to find out student activities, one of which is through attendance. Some universities in Indonesia still use manual attendance systems and attendance systems through the website. This system has several obstacles that require solutions. Therefore, a more concise system is needed to assist students in filling in the attendance. This research aims to make a design to make academic presence for students by using neural network. There are many methods that can be used to create this system including using Principal Component Analysis (PCA) based on Backlpropagation Neural Network (BNN) because it can help the system perform faster and more accurately without losing important information. After carrying out a series of steps of algorithm designed for student attendance, we get the recognition of facial image expressions by using ANN Backpropagation and recognition of facial image expression with PCA.
Co-Authors Adawiya, Robiatul Ardiyaningrum, Martalia Ariyadi Wijaya Aryani, Anggi Erna Rahayu Condro Murti Rino Richardo Robbaniyyah, Nuzla Af'idatur Setiawati Setiawati Siti Irene Astuti D Zahro, Uswatun Az