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<![CDATA[Pengaruh Pembelajaran Berbasis Masalah Terbuka Pada Kemampuan Representasi Beragam Matematis Siswa Sekolah Menengah Pertama ]]>
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>
<![CDATA[ Pasundan Journal of Mathematics Education : Jurnal Pendidikan Matematika Vol. 3 No. 1 (2013): Pasundan Journal of Mathematics Education : Jurnal Pendidikan Matematika ]]>
Publisher : <![CDATA[Program Magister Pendidikan Matematika, Pascasarjana, Universitas Pasundan in collaboration with Asosiasi Guru Matematika Indonesia (AGMI) and Indonesian Mathematics Educators' Society (IMES) ]]>
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DOI: 10.23969/pjme.v3i1.2481
<![CDATA[Penelitian ini dilatarbelakangi berdasarkan laporan hasil The Third International Mathematics and Sciense Study bahwa kemampuan siswa Sekolah Menengah Pertama di Indonesia dalam merepresentasikan ide atau konsep matematis masih tergolong rendah. Penelitian ini menerapkan pembelajaran berbasis masalah terbuka, yaitu pembelajaran yang masalahnya memiliki alternatif ragam stragtegi penyelesaian namun tertuju dalam satu jawaban atau alternatif ragam stragtegi penyelesaian atau jawaban. Metode dalam penelitian ini adalah eksperimen dengan desain penelitian berbentuk pretest-postest-control group design. Instrumen yang digunakan berupa tes representasi beragam metematis, dan non tes berupa angket, pedoman observasi, dan wawancara. Hasil dari pengolahan data gain ternormalisasi, dengan taraf signifikansi 0,05 kemampuan representasi beragam matematis siswa yang diberikan pembelajaran berbasis masalah terbuka lebih baik daripada yang siswa yang diberikan pembelajaran konvensional. Pada taraf signifikansi 0,05, kelompok siswa yang diberikan pembelajaran berbasis masalah terbuka menunjukkan adanya perbedaan peningkatan kemampuan representasi yang signifikan antara kelompok kemampuan pandai, sedang dan kurang. Ternyata kemampuan representasi kelompok kemampuan pandai lebih baik daripada kelompok sedang dan kelompok kurang. Berdasarkan hasil analisis data non tes diperoleh respon positif dari siswa mengenai pembelajaran berbasis masalah terbuka.]]>
<![CDATA[SIMPLE ALGORITHM TO CONSTRUCT CIRCULAR CONFIDENCE REGIONS IN CORRESPONDENCE ANALYSIS USING R ]]>
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Utami, Marsah Rahmawati]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol16iss1pp065-074
<![CDATA[Correspondence analysis has been widely applied in various fields as a graphical method to depict the association structure between two categorical random variables on a low-dimensional plot. This study built a simple algorithm to determine the principal coordinates and construct the circular confidence regions on the correspondence plot. In this algorithm, the determination of the standard residual matrix and the principal coordinates is built directly from the contingency table (without calculating a correspondence matrix). The algorithm was developed using R and applied to data on Covid-19 cases in West Java.]]>
<![CDATA[POISSON REGRESSION MODELLING OF AUTOMOBILE INSURANCE USING R ]]>
<![CDATA[Vantika, Sandy]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol16iss4pp1399-1410
<![CDATA[Automobile insurance benefits are protecting the vehicle and minimizing customer losses. Insurance companies must provide funds to pay customer claims if a claim occurs. Insurance claims can be modelled by Poisson regression. Poisson regression is used to analyze the count data with Poisson distributed data responses. this paper, the data model of sample is automobile insurance claims from the companies in one year (in 2021) of observation which contains three types of insurance products, i.e., Total Loss Only (TLO), All Risk, and Comprehensive. The results of data analysis show that the highest number of claims comes from Comprehensive insurance products, especially if the premium value gets more extensive. In contrast, the least comes from TLO insurance products.]]>
<![CDATA[PREDICTIVE DISTRIBUTION TO DETERMINE LEARNING MODEL AT THE STRATEGIC COMPETENCE LEVEL OF STUDENTS IN STATISTICS GROUP COURSE ]]>
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0313-0322
<![CDATA[The problem of this research comes from a situation or condition that is not static. The description of these problems is the condition of the learning system, which tends to change due to the Covid-19 pandemic, causing learning conditions to be dynamic. From a statistical perspective, the dynamic situation can be modeled using a predictive distribution approach, so its characteristics can be studied. The purpose is to provide policy recommendations on appropriate learning models for lecturers in improving students' strategic competence, which is an ability that students need to master in solving various mathematical problems. The main discussion of this paper consists of three parts: clustering, predictive distribution, and statistical inference. The purpose of clustering is to group students based on test results to determine the level of strategic competence. In addition, clustering is also used as an initial process to predict students' strategic competence level if the learning used is still the same. The benefits of statistical inference in the distribution procedure in this study are used to determine the type of data distribution from each arrival of new information or data. The results of the statistical inference determine whether or not it is necessary to update the learning model of the lecturer. This research produce a new alternative statistical inference needed to make decisions. Based on the simulation results and discussion, the use of a predictive distribution approach to predict dynamic data is very appropriate. Distribution approach can use for detecting changes in new data distribution with historical data for the dynamic condition. If the changes are insignificant, direct instruction can still be used for the learning model in statistics course. A new learning model is recommended for the statistics group course at a higher level when the changes are significant.]]>
<![CDATA[CORRESPONDENCE ANALYSIS ON STATISTICAL LITERACY AND GENDER: EMBEDDING E-CAMPUS PLATFORM WITH RANDOM ASSIGNMENT OF MATCHED SUBJECT IN EXPLANATORY ANALYSIS ]]>
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Risnawita, Risnawita]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Nugraha, Edwin Setiawan]]>;
<![CDATA[Sylviani, Sisilia]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss3pp1975-1988
<![CDATA[This study aims to evaluate the embedding of e-campus platforms during the pandemic in dealing with gender disparities in statistical literacy and shed light on the association structure between statistical literacy and gender disparities. A mixed methods approach with sequential explanatory analysis was performed among 42 pairs (man-woman) sample of sophomore students enrolled in the Inferential Statistics course selected from a random assignment of matched subjects. The two main instruments, the placement test, and the statistical literacy test, were analyzed quantitatively using the Mann-Whitney test and correspondence analysis, followed by qualitative analysis using image and text analysis. The findings reveal that the e-campus platform has increased women's statistical literacy. Specifically, there is a statistically significant difference (1) between men's and women's statistical literacy scores, (2) an association between statistical literacy level and gender, and (3) different tendencies between men's and women's statistical literacy in various ways. The e-campus platform is an excellent solution for the teaching and learning process during the COVID-19 pandemic and beyond. Likewise, it can overcome gender disparities in literacy statistics. Since these findings lead to a higher statistical literacy rate for women than men, this could break the stereotype that women are less statistically literate than men.]]>
<![CDATA[RETROSPECTIVE ANALYSIS IN HYPOTHESIS TESTING TO EVALUATE INDONESIA'S GINI RATIO AFTER COVID-19 PANDEMIC ]]>
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Agustina, Fitriani]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Nugraha, Edwin Setiawan]]>;
<![CDATA[Sylviani, Sisilia]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss4pp2517-2530
<![CDATA[The study highlighted three essential roles of retrospective analysis in hypothesis testing, particularly as a priori analysis, post hoc analysis, and sensitivity analysis. These approaches were applied to the Gini ratio data sourced from the National Socioeconomic Survey Indonesia 2023 to examine the income inequality level in Indonesia. The sample size, statistical power, and effect size for the one-sample t-test are evaluated by aid G*Power software. The test results show that for a sample size of 10, at the 95% confidence interval, there is not enough evidence to show that the Gini ratio in 2023 is smaller than 0.4. A retrospective analysis using G*power software reveals that for a sample size of 20 at the same confidence interval, there is enough evidence to suggest that the Gini ratio is statistically significant at less than 0.4 with a power of analysis of 90.8% and an effect size of 0.76. This study has important implications in hypothesis testing, especially in retrospective analysis, since understanding the effect of sample size and effect size makes it possible for academics or practitioners to optimize hypothesis testing and generate more accurate and reliable test results.]]>
<![CDATA[K-MEANS CLUSTERING ANALYSIS OF THE RELATIONSHIP BETWEEN CRITICAL AND METAPHORICAL THINKING ABILITIES ]]>
<![CDATA[Putri, Amanda Mutiara]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>
<![CDATA[ EMTEKA: Jurnal Pendidikan Matematika Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Metro ]]>
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DOI: 10.24127/emteka.v6i2.7963
<![CDATA[The low level of metaphorical thinking ability affects students' ability to solve complex mathematical problems. This study aims to examine the strength of the relationship between critical thinking ability and metaphorical thinking ability. Data were collected from the mid-semester assessment of the SPLDV (Simultaneous Linear Equations with Two Variables) topic. The population in this study consisted of 170 ninth-grade students from SMP Negeri 2 Pangkalan in the 2024/2025 academic year, with a sample of 63 students selected using a simple random sampling technique. The objectives of this study include categorizing students' abilities using the K-means clustering method and determining the relationship, direction, strength, and coefficient of determination between critical thinking ability and metaphorical thinking ability through Spearman’s rank correlation analysis. The results show that 37 students fall into the high ability category, 20 into the moderate ability category, and 6 into the low ability category. The Spearman’s rank correlation analysis yielded a correlation coefficient of 0.632 for the entire dataset and 0.482 for Cluster 1, indicating a significant positive (direct) relationship between critical thinking ability and metaphorical thinking ability, with a moderately strong correlation. The coefficient of determination shows that critical thinking and metaphorical thinking abilities influence 39.9% of the overall data and 23.2% of Cluster 1, while the remaining variance is influenced by other factors beyond these two cognitive abilities.]]>
<![CDATA[PELATIHAN PENGGUNAAN ALGORITMA K-MEANS CLUSTERING UNTUK MENGIDENTIFIKASI KARAKTERISTIK SISWA ]]>
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ JALIYE: Jurnal Abdimas, Loyalitas, dan Edukasi Vol. 3 No. 1 (2024): JALIYE: Jurnal Abdimas, Loyalitas, dan Edukasi ]]>
Publisher : <![CDATA[Fakultas Keguruan dan Ilmu Pendidikan UNIVA Medan ]]>
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DOI: 10.47662/jaliye.v3i1.710
<![CDATA[Salah satu bentuk inovasi di bidang pendidikan adalah pengembangan aplikasi yang dapat digunakan baik dalam pembelajaran maupun administrasi sekolah. Pengelompokkan siswa berdasarkan kondisi siswa dengan berbagai macam karakteristiknya sangatlah penting. Informasi dari pengelompokkan tersebut dapat dijadikan sebagai acuan bahan pertimbangan bagi guru atau pihak sekolah untuk melakukan langkah secara terstruktur dalam rangka meningkatkan kualitas siswa dan standar mutu sekolah. Clustering adalah metode yang dapat digunakan untuk membagi kumpulan data (objek) ke dalam kelompok (cluster) berdasarkan kemiripan antar objek. Kegiatan pelatihan yang merupakan bagian dari program pengabdian kepada masyarakat ini dilaksanakan di SDN Karanganyar 01 Karawang. Kegiatan pelatihan ini diikuti oleh 25 peserta yang sebagian besar adalah Guru. Data yang digunakan berupa data hasil nilai mata pelajaran IPA dan IPS siswa. Data dianalis menggunakan metode k-means clustering menggunakan aplikasi XLSTAT. Pelatihan pengklasteran dengan menggunakan metode k-means diharapkan mempermudah para guru maupun tenaga pendidik dalam mengidentifikasi karakteristik siswa.]]>
<![CDATA[GERAKAN STATISTIKA MASUK DESA ]]>
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>
<![CDATA[ JALIYE: Jurnal Abdimas, Loyalitas, dan Edukasi Vol. 3 No. 1 (2024): JALIYE: Jurnal Abdimas, Loyalitas, dan Edukasi ]]>
Publisher : <![CDATA[Fakultas Keguruan dan Ilmu Pendidikan UNIVA Medan ]]>
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DOI: 10.47662/jaliye.v3i1.711
<![CDATA[Salah satu permasalahan yang dihadapi oleh aparatur pemerintah desa, pelaku usaha, guru, dan tata usaha di sekolah pada saat adalah terbatasnya kemampuan dalam menganalisis/mengolah data khususnya mengenai inferensi statistik. Hal ini menjadi permasalahan yang sangat serius. Karena dengan tidak cakapnya menganalisis data, dapat mengakibatkan terhambatnya kemajuan suatu instansi maupun bidang usaha. Selain itu, kemampuan dalam menggunakan perangkat lunak statistika juga sangat minim terutama pada kalangan aparatur pemerintah desa dan pelaku usaha. Pelatihan analisis data mengenai inferensi statistik ini merupakan solusi dari permasalahan tersebut. Pelaksanaan pelatihan yang diselenggarakan yaitu memuat materi statistika dan penggunaan perangkat lunak statistika.]]>
<![CDATA[Pengaruh Pemahaman Konsep Matematis dengan Model Pembelajaran Contextual Teaching and Learning terhadap Hasil Belajar Siswa Kelas VII pada Materi Bentuk Aljabar ]]>
<![CDATA[Sofiyani, Sofi]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>
<![CDATA[ Jurnal Ilmiah Dikdaya Vol 14, No 1 (2024): April ]]>
Publisher : <![CDATA[Universitas Batanghari Jambi ]]>
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DOI: 10.33087/dikdaya.v14i1.611
<![CDATA[This research was motivated by students' lack of understanding of mathematical concepts which affected student learning outcomes. This research aims to determine how much influence students' understanding of mathematical concepts with the Contextual Teaching and Learning learning model has on the learning outcomes of class VII students in algebra material. The research method used is a survey method using a test instrument of 5 questions and a questionnaire of 20 statements. With a sample size of 50 students, using random sampling techniques. In the normality and linearity test using Chi Square, and the multiple linear regression test, it was concluded that the data had a normal and linear distribution. In hypothesis testing using the coefficient of determination, an R square value of 0.883 was obtained. From this research it can be concluded that there is a significant influence between understanding mathematical concepts and the Contextual Teaching and Learning learning model on the learning outcomes of class VII students in algebra material.]]>
