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Pythagoras: Jurnal Matematika dan Pendidikan Matematika
Published by Universitas Negeri Yogyakarta
ISSN : 19784538     EISSN : 2527421X     DOI : 10.21831
Core Subject : Education,
Education Mathematics
Arjuna Subject : -
Articles 294 Documents
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Mathematical Communication Ability of Madrasah Aliyah Students Given Self-Confidence and Learning Independence Handayani, Rizki; Siregar, Nurhasanah; Simanjuntak, Erlinawaty; Molliq, Yulita
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 19 No. 1: June 2024
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v19i1.72580

Abstract

The research aims to ascertain how mathematical communication ability is impacted by self-confidence, how learning independence affects mathematical communication ability, and how self-confidence and learning independence affect mathematical communication ability in 11th-grade students at MA Muhammadiyah 1 Medan in the 2023–2024 academic year. This is a correlational study with a quantitative methodology. This research used cluster sampling, and the total sample size was 31 students. This study collected data using questionnaires and tests. The research instruments used were self-confidence and learning independence questionnaires, as well as mathematical communication ability tests. Multiple regression analysis was used in this study's data analysis procedures. The analysis's findings indicate that self-confidence impacts on mathematics communication with a value of sig. 0.025 and a value of tcount 2.317; learning independence impacts on mathematics communication ability, with a value of sig. 0.12 and the value of tcount 2.512; self-confidence and learning independence positively and significantly impact on mathematics communication ability, with a value of . 0.000; and a coefficient of determination of 0.612, implying that self-confidence and learning independence affect mathematical communication by 61.2%.
The Complexity of Pencil Graph and Line Pencil Graph Hanssen, Calvin; Fran, Fransiskus; Yundari, Yundari
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 19 No. 2: December 2024
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v19i2.77747

Abstract

Let ð’¢ be a linked and undirected graph. Every linked graph ð’¢ must contain a spanning tree ð’¯, which is a subgraph of ð’¢that is a tree and contain all the nodes of ð’¢. The number of spanning trees in graph ð’¢, also called the complexity of the graph ð’¢, represented by Ï„(𝒢), is the total number of distinct spanning trees of graph ð’¢. This research aims to formulate the complexity of pencil graph and line pencil graph. In this research, the complexity of pencil graph and line pencil graph are determined using graph complement approach. The result of the research are the complexity of pencil graph and line pencil graph.
Students' Metacognition in Solving HOTS Questions in the Context of the Flag Ceremony Yard Based on Initial Mathematical Abilities Murtafiah, Wasilatul; Yunitasari, Anisa; Gembong, Sardulo; Alvarez, Joel I.; Yahya, Faridah Hanim
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 19 No. 2: December 2024
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v19i2.76120

Abstract

This study aims to determine the ability of metacognition in solving HOTS problems in the context of problem related to activities in the context of the flag ceremony yard in solving problems based on initial mathematics ability. This research approach was descriptive qualitative involving 3 students as research subjects who were selected based on high, medium, and low initial mathematics abilities. The data were validated by using method triangulation techniques, namely tests and interviews. The results showed that students with high initial mathematics ability showed good metacognition skills in solving HOTS problems in planning, monitoring, and evaluating activities. However, they still need to improve their ability to evaluate the repair strategy if there is an error. Students with medium initial mathematical ability showed good metacognition skills in several aspects but needed to improve some aspects. Students with moderate mathematics ability have a good basic understanding of metacognition in planning activities. However, they need to improve their metacognition skills in monitoring and evaluating when solving HOTS problems. Meanwhile, students with low initial mathematical ability show limitations in utilizing metacognition skills in planning, monitoring, and evaluating activities, as a result, students experience difficulties in solving problems. So, teachers need to design teaching materials that can improve students' mathematical abilities and metacognition.
Comparative Analysis of Local Polynomial Regression and ARIMA in Predicting Indonesian Benchmark Coal Price Mahadesyawardani, Arinda; Maulidya, Utsna Rosalin; Marbun, Barnabas Anthony Philbert; Pratama, Fachriza Yosa; Chamidah, Nur
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 19 No. 1: June 2024
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v19i1.74889

Abstract

As one of the world's biggest coal producers, it is essential for Indonesia to follow the trend of benchmark coal price fluctuations for any future possibilities. This study compared two methods of forecasting benchmark coal prices to evaluate the accuracy of the predictions used a nonparametric regression based on the local polynomial estimator and a parametric ARIMA method. Local polynomial analysis obtained a MAPE of 2.929278% using a CV method based on optimal bandwidth of 5.06 at order 2 with a cosine kernel, which means highly accurate forecasting accuracy. As for the ARIMA analysis, the data does not meet the assumption of normality, but forecasting is still continued with the best model ARIMA (1,2,1) model so that the MAPE is 12.6327%, which means good forecasting accuracy. Therefore in this study, the use of nonparametric regression methods using local polynomial estimators on data with non-normal distribution are more suitable to obtain accurate prediction results.

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