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<![CDATA[Tucker3 Tensor Decomposition for the Standardized Residual Hypermatrix on Three-Way Correspondence Analysis ]]>
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Yudhanegara, Mokhammad Ridwan]]>;
<![CDATA[Nugraha, Edwin Setiawan]]>;
<![CDATA[Sylviani, Sisilia]]>
<![CDATA[ Journal of the Indonesian Mathematical Society Vol. 31 No. 2 (2025): JUNE ]]>
Publisher : <![CDATA[IndoMS ]]>
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DOI: 10.22342/jims.v31i2.1491
<![CDATA[This study investigates the theoretical and practical mathematical aspects of Tucker3 tensor decomposition from the three-way correspondence analysis point of view. Since the standardized residual hypermatrix represents the association of the three categorical variables, this study focused on (1) Tucker3 tensor decomposition for the standardized residual hypermatrix, (2) some mathematical properties of Tucker3 tensor decomposition, and (3) constructing the correspondence plot via Tucker3 tensor decomposition. Some mathematical results are presented in lemmas, theorems and algorithms, while a practical result is exhibited at the end of the discussion.]]>
<![CDATA[Pemanfaatan Media Manipulatif “Mata Uanga” untuk Pembelajaran Siswa Di Sekolah Inklusi Karawang ]]>
<![CDATA[Attin Warmi]]>;
<![CDATA[Karunia Eka Lestari]]>;
<![CDATA[Dela Amelia Putri]]>;
<![CDATA[Melisa Kusumawardani]]>;
<![CDATA[Wiwin Wiwin]]>
<![CDATA[ J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 8, No 2 (2024): Oktober 2024 ]]>
Publisher : <![CDATA[IKIP PGRI Bojonegoro ]]>
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DOI: 10.30734/j-abdipamas.v8i2.4841
<![CDATA[ABSTRACTThis service takes the theme of currency introduction which is motivated by the importance of a student knowing money because money is a medium of exchange that is closely related to daily life. The media used in this activity are props / manipulative currency which consists of metal and paper money and displays from the smallest to the largest value. The purpose of this Abdimas activity is to introduce the types of money and practice their use. This Abdimas activity was carried out in one of the Inclusion schools in Karawang City. The methods used in this activity are in the form of discussions, lectures, mentoring and demonstrations of the use of money as a tool for buying and selling. The results obtained from this Abdimas activity are that students feel happy in learning money calculations using interesting props / manipulatives so that they are able to perform basic calculation operations using money. This media can attract students' attention, so that in its implementation it can run well and students quickly understand it. The school is happy with this activity and as a motivation for teachers to create interesting media for learning both mathematics and other subjects.Keywords: currency, manipulative moneyABSTRAKPengabdian ini mengambil tema pengenalan mata uang yang dilatarbelakangi oleh pentingnya seorang siswa mengenal uang karena uang merupakan alat tukar yang sanagt erat hubungannya dengan kehidupan sehari hari. Media yang digunakan dalam kegiatan ini yaitu alat peraga/manipulatif mata uang yang mana terdiri dari berupa uang logam dan kertas serta menampilkan dari yang bernilai terkecil hingga besar. Tujuan dari kegiatan Abdimas ini adalah untuk memperkenalkan jenis-jenis uang dan praktek penggunaanya. Kegiatan Abdimas ini dilaksanakan di salah satu sekolah Inkliusi di Kota Karawang. Metode yang digunakan dalam kegiatan ini adalah berupa diskusi, penyuludan, pendampingan dan demonstrasi penggunaan uang sebagai alat untuk jual beli. Hasil yang diperoleh dari kegiatan Abdimas ini yaitu siswa merasa senang dalam belajar perhitungan uang dengan menggunakan alat peraga/manipulatif yang menarik sehingga mereka mampu melakukan operasi perhitungan dasar dengan menggunakan uang. Media ini dapat menarik perrhatian siswa , sehingga dalam pelaksnaanya dapat berjalan dengan baik dan siswa cepat memahaminya. Sekolah merasa senang dengan adanya kegiatan ini dan sebagai motivasi untuk para guru untuk membuat media yang menarik untuk pembelajaran baik matematika maupun pelajaran lainnya.Keywords: Mata uang, alat peraga uang]]>
<![CDATA[Analisis Kemampuan Pemecahan Masalah Matematis Siswa SMP Dalam Menyelesaikan Soal Sistem Persamaan Linear Dua Variabel ]]>
<![CDATA[Cahyana, Yaya]]>;
<![CDATA[Lestari, Karunia Eka]]>;
<![CDATA[Abadi, Agung Prasetyo]]>
<![CDATA[ Jurnal Ilmiah Wahana Pendidikan Vol 11 No 3.B (2025): Jurnal Ilmiah Wahana Pendidikan ]]>
Publisher : <![CDATA[Peneliti.net ]]>
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<![CDATA[Kemampuan pemecahan masalah merupakan bagian penting dari kurikulum matematika karena memungkinkan siswa memperoleh pengalaman menggunakan pengetahuan dan keterampilan yang mereka miliki untuk memecahkan masalah yang tidak biasa. Hasil studi pendahuluan menunjukkan bahwa kemampuan pemecahan masalah matematis siswa kelas VIII masih tergolong rendah. Ini disebabkan oleh beberapa faktor berikut: (1) tahap pemahaman masalah, siswa belum sepenuhnya memahami masalah materi sistem persamaan linear dua variabel, (2) tahap merencanakan penyelesaian, siswa mengalami kesulitan dalam menulis strategi atau rencana untuk menyelesaikan masalah, (3) tahap penyelesaian, siswa gagal melakukan proses perhitungan dengan benar dan tidak menemukan solusi yang tepat, dan (4) tahap pengecekan, siswa hanya mengulangi masalah sampai mereka menemukan solusi tanpa memeriksa masalah sebelumnya. Berdasarkan hal tersebut perlu dilakukan analisis menyeluruh tentang bagaimana kemampuan siswa untuk memecahkan masalah matematis pada materi sistem persamaan linear dua variabel yang didasarkan pada langkah-langkah Polya. Jenis penelitian ini adalah deskriptif kualitatif dengan subjek penelitian siswa kelas VIII K SMPN 1 Kotabaru dan diambil tiga siswa terpilih. Pengambilan data diperoleh dari pemberian instrumen soal tes kemampuan pemecahan masalah berupa soal cerita SPLDV. Hasil penelitian menunjukkan bahwa semua siswa sudah mampu memahami apa yang dimaksud dari soal tersebut. Pada tahap merencanakan masalah terdapat dua siswa yang mampu merencanakan. Berikutnya pada tahap menyelesaikan masalah hanya satu siswa yang mampu menyelesaikan masalah dengan benar. Terakhir pada tahap memeriksa kembali hanya satu siswa yang dapat memberikan kesimpulan yang valid berdasarkan hasil yang diperoleh sebelumnya.]]>
<![CDATA[Identifikasi Karakteristik Siswa Berdasarkan Kemampuan Representasi dan Pembuktian Matematis Menggunakan Pengelompokan K-Means ]]>
<![CDATA[Maharani, Devy Sagita]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ Polinomial : Jurnal Pendidikan Matematika Vol. 4 No. 3 (2025) ]]>
Publisher : <![CDATA[Papanda ]]>
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DOI: 10.56916/jp.v4i3.1938
<![CDATA[This study aims to identify the characteristics of student groups based on mathematical representation and mathematical proof abilities. The approach in this research is quantitative with descriptive method. The population in this study was 11th-grade students of SMA Negeri 6 Karawang, with a sample of 71 students obtained using a random sampling technique based on the Slovin formula. The data collection technique used was filling out test instruments in the form of description questions. The instrument used consisted of three questions to measure mathematical representation ability and three questions to measure mathematical proof ability. The data analysis technique used was k-means clustering. The results showed that the student group was divided into three clusters. In cluster one, there were 16 students with the characteristics of the student group having a fairly good understanding of mathematical representation problems, but not understanding mathematical proof, so it is recommended to apply the problem posing learning model. In cluster two, there are 18 students with the characteristics of student groups lacking understanding of mathematical representation problems and having a fairly good understanding of mathematical proof problems, so it is recommended to apply the multi-recentacy discourse learning model. In cluster three, there are 37 students with the characteristics of the student group having a good understanding of mathematical representation problems and having a fairly good understanding of mathematical proof, so it is recommended to apply the inquiry-based learning model]]>
<![CDATA[Klasterisasi Siswa Sekolah Menengah Atas Berdasarkan Kemampuan Literasi Matematis dan Kemampuan Numerasi ]]>
<![CDATA[Azkannaila, Ara]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ Polinomial : Jurnal Pendidikan Matematika Vol. 4 No. 3 (2025) ]]>
Publisher : <![CDATA[Papanda ]]>
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DOI: 10.56916/jp.v4i3.1948
<![CDATA[Mathematical literacy is the ability of an individual to formulate, apply, and interpret mathematics in various contexts. Meanwhile, numeracy is the ability used to utilize numbers and arithmetic operation skills to solve numerical problems in the real world. Learning in the classroom must certainly be planned as well as possible and is one of the challenges for teachers in order to provide learning that is in accordance with the characteristics and needs of students. Therefore, this study aims to categorize students based on mathematical literacy and numeracy skills in order to map the pattern of student characteristics based on these two abilities. The approach of this research is quantitative with quantitative descriptive method, while the population of this research is class XI students of SMA Negeri 1 Tegalwaru with a sample of 96 students from three classes. The data collection technique used test instruments and data analysis was carried out by applying the k-means algorithm at the data mining stage. The results explained that students were divided into two clusters where cluster one contained 24 students and cluster two totaled 72 students. Cluster one consists of students who understand quite well in mathematical literacy skills, and cluster two consists of students who understand numeracy skills quite well. Based on the discussion, the conclusion of this study is that the characteristics of students are divided into two clusters in which researchers recommend learning models related to visuals and media such as picture to picture, as well as learning that can construct problems and student understanding, namely discovery learning models and problem-based learning models.]]>
<![CDATA[Model Persamaan Diskriminan untuk Prediksi Gaya Belajar Selmes Berdasarkan Kemampuan Metakognisi ]]>
<![CDATA[Arielhan, Fitri Nur]]>;
<![CDATA[Lestari, Karunia Eka]]>
<![CDATA[ Polinomial : Jurnal Pendidikan Matematika Vol. 4 No. 3 (2025) ]]>
Publisher : <![CDATA[Papanda ]]>
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DOI: 10.56916/jp.v4i3.2067
<![CDATA[This study aims to determine how the discriminant equation model can be used to predict the type of Selmes learning style based on students' metacognitive abilities in Junior High Schools. This study is an associational research type with a quantitative approach, involving a sample of 79 students selected using the cluster random sampling technique. The instruments used consisted of a metacognitive ability test in the form of three descriptive questions that measured indicators of understanding, strategy and connection, as well as a closed questionnaire to identify four groups of Selmes learning styles, namely surface, deep, hard work and organized. The data analysis technique used is Linear Discriminant Analysis (LDA), the results of the study showed four LDA equation functions, each representing each learning style. This model has an accuracy rate of 83.33% in predicting learning styles with the results of the multivariate significance test using Wilks' lambda producing a or of 0.0000<0.05 (alpha), so it can be concluded that the discriminant function coefficient is significant for predicting Selmes' learning styles based on metacognitive abilities.]]>
<![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.]]>
