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All Journal Journal on Education MES: Journal of Mathematics Education and Science Journal of Information Systems and Technology Research
Muhammad Huda Firdaus
AMIK Medicom
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Mathematics

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Peran Ayah dalam Pengasuhan dan Kecerdasan Matematis Siswa di SD Negeri Padang Bujur Sipirok Yulia Anita Siregar; Winmery Lasma Habeahan; Muhammad Huda Firdaus
Journal on Education Vol 5 No 3 (2023): Journal on Education: Volume 5 Nomor 3 Tahun 2023
Publisher : Departement of Mathematics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The research was conducted at SD N Padang Bujur in Sipirok District. The study used Spearman's rank correlation research. The aims of the study were to: Know the relationship between the father's role in parenting and Mathematical Intelligence in Students of SD N Padang Bujur Sipirok. This study resulted in an average father's role in parenting of 99.28 while the average mathematical intelligence was 97.28. From the results of the analysis calculations in answering the research hypothesis, it is obtained ρ count = 0.995 with a very strong category and ρ table = 0.339. So it can be concluded that there is a significant relationship between the father's role in parenting and Mathematical Intelligence in SD N Padangbujur Sipirok students with a contribution of 99%. This means that the role of fathers in parenting is needed in shaping students' mathematical intelligence.
PENGARUH SELF EFFICACY TERHADAP KEMAMPUAN BERPIKIR KREATIF MATEMATIS SISWA DI SMA HARVARD Winmery Lasma Habeahan; Meilisa Malik; Muhammad Huda Firdaus
MES: Journal of Mathematics Education and Science Vol 8, No 2 (2023): Edisi April
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v8i2.6995

Abstract

The aim of this study was to determine the effect of students' self-efficacy on the mathematical creative thinking abilities of students at Harvard High School. The subjects in this study were students of class X-IPA 1 which consisted of 20 students. This research is a true experiment research, with a one group pretest-posttest research design. Data collection was carried out through an instrument test for mathematical creative thinking ability and a non-test instrument test in the form of a self-efficacy questionnaire. Data analysis techniques were carried out through the Independent Sample t test using the SPSS application. The results of the study show that: There is an effect of self-efficacy on the ability to think creatively at Harvard High School
The Integration of HSV and GLCM Features with LDA for Classification of Breadfruit Maturity Levels Hamdan Pratama; Nurul Khairina; Nanda Novita; Muhammad Huda Firdaus; Yolanda Y.P. Rumapea
Journal of Information Systems and Technology Research Vol. 5 No. 1 (2026): January 2026
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v5i1.1377

Abstract

Breadfruit is a perennial plant that has historically been distributed throughout Southeast Asia as a food source. Breadfruit that has entered the harvest period or has fallen on its own has several levels of maturity, namely raw, unripe, ripe, and rotten. Breadfruit that has been separated from the tree will have the same characteristics, namely green and slightly yellowish or brownish in colour. The research problem centres on the trouble buyers and sellers have when determining the maturity level of breadfruit. Based on this problem, the purpose of this study is to classify the maturity level of breadfruit using the LDA method. With image classification, it is hoped that the maturity level of breadfruit can be identified more accurately. The research gap in this study lies in the limited number of feature extraction methods used simultaneously, as well as the infrequent use of LDA methods for classification. In this study, Linear Discriminant Analysis is applied together with GLCM and HSV-based feature extraction. The LDA is a statistical method used for classification. LDA focuses on finding lines that separate two or more classes in a dataset by maximizing the distance between class averages and minimizing variance within classes. GLCM feature extraction is an image-processing technique used to evaluate texture. The contribution of this research lies in its improved classification performance and greater accuracy compared to previous studies. It offers a statistical description of how pairs of gray levels are distributed within an image, helping to reveal texture patterns and characteristics. The results of this study show that the classification of maturity levels in breadfruit images is good. This is measured by an accuracy of 89.9333%, precision of 90.1732%, recall of 89.3333%, and an F1-score of 89.7513%.
Co-Authors Hamdan Pratama Malik, Meilisa Nanda Novita Nurul Khairina Winmery Lasma Habeahan Winmery Lasma Habeahan Yolanda Y.P. Rumapea Yulia Anita Siregar