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Journal of Mathematics Education and Science
Published by Universitas Nahdlatul Ulama Sunan Giri Bojonegoro
ISSN : 26211203     EISSN : 26211211     DOI : https://doi.org/10.32665/james
Core Subject : Education,
Education Mathematics
Journal of Mathematics Education and Science (JaMES) is a mathematical journal published biannually (April & October) by the Mathematics Educations Department, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro. Journal includes research papers, literature studies, analysis, and problem-solving in Mathematics Education or Mathematical Sciences (Algebra, Analysis, Statistics, Computing and Applied).
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 137 Documents
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Proses Berpikir Kreatif Siswa SMP Dalam Menyelesaikan Open–Ended Problem ditinjau dari Tingkat Berpikir Kreatif : Studi Deskriptif Kualitatif Indan Afifah Rahmawati; Setianingsih, Rini; Sulaiman, Raden
Journal of Mathematics Education and Science Vol. 8 No. 1 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i1.4521

Abstract

Students' level of creativity influences their creative thinking processes. Students with different levels of creativity tend to demonstrate variations in how they approach creative thinking. This study is a qualitative research with a descriptive approach, aiming to describe the creative thinking processes of junior high school students in solving open-ended mathematical problems. The subjects of this study consisted of three students: one with a highly creative thinking level, creative thinking level, and moderately creative thinking level. Data were collected through written tasks involving mathematical problem solving and follow-up interviews. The results revealed that the student with a highly creative thinking level demonstrated strong abilities in integrating various sources of information, generating ideas independently and flexibly, and producing accurate solutions. The student with a creative thinking level was able to construct and plan ideas effectively but tended to use familiar strategies without further exploration, resulting in correct yet less innovative solutions. Meanwhile, the student with a moderately creative thinking level was only able to generate a single, simple idea, used familiar strategies without systematic planning, and produced inaccurate solutions while lacking the ability to evaluate the outcomes effectively. The results of this study can be implemented in mathematics learning by providing students with opportunities to develop their creative ideas through open-ended problems, encouraging the exploration of various problem-solving strategies, and creating a learning environment that values original and flexible thinking processes.
Finding The Shortest Route Between East Oku's Islamic Boarding Schools Using The Dijkstra Algorithm Amanah Yulianti; Denix Aricho Sundawa; Beni Hermansyah
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.5265

Abstract

This study aims to measure the distance between Islamic boarding schools in East Oku, using the Dijkstra Algorithm method to make it easier to determine the shortest route from the point of the Nurul Huda Sukaraja Islamic Boarding School to the Subulussalam Sriwangi Islamic Boarding School. In previous research, namely determining the shortest route when distributing from vegetable gardens to warehouses between toll and non-toll routes to minimize costs. In graph theory, the Dijkstra algorithm efficiently calculates the shortest path between any pair of nodes in a weighted graph, both positive and negative. This algorithm works with the principle of dynamic programming and can overcome graphs with a negative weight as long as there are no negative cycles. In its implementation, the Dijkstra algorithm iteratively updates the shortest distance between nodes by directly comparing paths with paths passing through other nodes. The advantage of this algorithm lies in its simplicity and ability to calculate the shortest distance between all pairs of nodes in a single process. The study results show that the Dijkstra Algorithm can show the fastest and most efficient alternative routes compared to conventional routes. Calculations using the Dijkstra Algorithm method produce the shortest trajectory starting from point 1-4-5 with a distance of 48 km, the most optimal route between the location and destination points.
Graph Coloring on the Primary Dryland Forest Cover Map of Kalimantan Using the Greedy Algorithm Izzaty Farha; Putri Pita Mutia; Rachel Cornelia Simanjuntak; Desi Febriani Putri; Fidia Deny Tisna Amijaya
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.4628

Abstract

In graph theory, graph coloring is a popular approach, including in map creation, and this study aims to apply the Greedy algorithm to color forest land-cover maps while ensuring that adjacent areas do not share the same color. The data used consist of land-cover classification maps and the relationships between regions represented as planar graphs. The Greedy algorithm is implemented by arranging nodes based on their highest degrees and then coloring them sequentially. The coloring results show that the algorithm can provide an efficient solution with a minimum number of colors according to the upper bound of graph coloring, particularly for primary dry forest land-cover maps in East Kalimantan Province, achieving a chromatic number χ(G) = 4, ensuring no neighboring areas share the same color. Although it does not always yield an optimal solution, the algorithm proves effective, simple, and applicable to various other uses such as spatial analysis, regional clustering, or geographic information systems. The novelty of this study lies in its application to primary dry forests in Kalimantan, which have been rarely explored, and its contribution to spatial analysis and conservation efforts.
CLUSTERING DAERAH RAWAN BENCANA ALAM DI PROVINSI JAWA TIMUR MENGGUNAKAN METODE FUZZY C-MEANS Deni Setiawan; Kresna Oktafianto
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.5170

Abstract

Natural disasters are one of the most common problems in Indonesia. According to Data Informasi Bencana Indonesia (DIBI) from 2020 to 2024, East Java Province ranks third in terms of the frequency of natural disasters on the island of Java. Systematic mapping of disaster-prone areas is essential to support more effective mitigation and management efforts. This study aims to group 38 districts/cities in East Java Province based on their vulnerability to natural disasters. The methods used are Fuzzy C-Means for the grouping process and Silhouette Coefficient as a tool for evaluating cluster quality. The data used is secondary data with indicators of the number of incidents, number of victims, and amount of damage caused by floods, landslides, extreme weather, drought, earthquakes, volcanic eruptions, and forest and land fires. The clustering results produced three clusters, namely areas with high, medium, and low vulnerability levels. The clustering results were evaluated using the Silhouette Coefficient with a value of 0.2807, which indicates that the clustering results are in the fairly good category and indicate limitations in cluster separation due to the use of limited indicators and overlapping characteristics between regions. Nevertheless, the results of this study can contribute as a basis for consideration in the formulation of disaster mitigation policies, especially in determining intervention priorities and strengthening preparedness in areas with high disaster vulnerability.
Development of Ethnomathematics-Based Student Worksheets to Improve the Understanding of Concepts for Junior High School Grade IX Students Ayu Pitaloka Saragi; Rusi Ulfa Hasanah
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.5633

Abstract

Mathematics learning requires innovative and contextual teaching materials so that students can more easily understand concepts. However, the availability of teaching materials is still limited in schools. Often teachers only use package books as the only teaching materials used. This research aims to develop ethnomathematics-based Student Worksheets by integrating the Batak Gorga motif in the translation and reflection materials of grade IX of junior high school. The research model used is Research and Development (R&D) by adapting Borg and Gall's steps to the final product revision stage. The research instruments include expert validation, teacher and student response questionnaires, and concept understanding tests conducted through pre-tests and post-tests. The results of the study show that the average assessment from material and media experts is in the category of very valid. The responses of teachers and students gave an average assessment with a very practical category. In addition, the average results of the students' concept understanding test showed an increase from pre-test to post-test, so that the effectiveness of Student Worksheets was in the medium category. The integration of Gorga Batak motifs in the Student Worksheet is able to help students understand the concepts of translation and reflection more easily. This Student Worksheet can also be used by teachers as teaching materials based on local culture to increase the effectiveness of mathematics learning.
On Local Vertex Antimagic Total Coloring Of Path, Cycle, And Star Graphs With Comb Operation Taradita Ayitia Meisya Fendina; Desi Febriani Putri; Wasono; Maria Alensia Deltin Dala
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.4777

Abstract

Let G(V,E) be a graph consisting of a set of vertices V(G) and a set of edges E(G) where the number of vertices and edges are denoted by |V(G)| and |E(G)|, respectively. A bijective function f:V(G) \vee E(G) \to {1,2,3,...,(|V(G)|+|E(G)|)} is defined as a local vertex antimagic total coloring if there exist two adjacent vertex vx and vy with . Therefore, every local vertex antimagic total coloring produces a vertex coloring of the graph G, where each vertex v is assigned a color corresponding to its weight w(v). This research is essential as it contributes to development of graph coloring theory, particularly in the area of local vertex antimagic total coloring, which has been rarely studied. This research discusses the local vertex antimagic total coloring of and  which aims to determine the chromatic number. The result of the research is the chromatic number of local vertex antimagic total coloring of  and the chromatic number of local vertex antimagic total coloring , is if  is odd and  if  is even.
Effect of the Kahoot-Assisted Team Games Tournament Model on Mathematics Learning Outcomes of Grade XI Students Intan Puspita Devi; Novi Mayasari; Ari Indriani
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.5114

Abstract

The low learning outcomes of students, especially in mathematics learning, indicate the need to implement innovative learning models. This study aims to determine the effect of implementing the Team Games Tournament learning model with the help of Kahoot on the mathematics learning outcomes of XI grade students of SMA Negeri 1 Balen, especially on the tangent circle. This research is included in the quasi-experimental model by applying the cluster random sampling technique. This study included grade XI students at SMA Negeri 1 Balen in the 2024/2025 school year as the research population, comprising six classes with 206 students. Class XI-1 (experimental class) and class XI-2 (control class) were selected as the research samples. Test and documentation were chosen as the research data collection techniques. Based on the t-test results with alpha = 5% and DK =   the obtained tcount = 3.251. Because the tcount] falls within the critical region (DK), H0 is rejected and H1 is accepted. The data analysis shows an influence in implementing the Team Games Tournament (TGT) model on the learning outcomes of grade XI students on the circle tangent at SMA Negeri 1 Balen. The average posttest score for students in the experimental class was 84.056, whereas it was 77.706 in the control class it was 77.706, further confirming the positive influence of this learning model. Practically, the results of this study can be used as an alternative learning strategy for educators to increase active participation and student learning outcomes.
Machine Learning-Based Early Prediction of Kidney Failure: A Comparative Study of Artificial Neural Network and Random Forest Models Nur Mahmudah; Alif Yuanita Kartini; Muhammad Anshori
Journal of Mathematics Education and Science Vol. 8 No. 2 (2025): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v8i2.5598

Abstract

Chronic kidney disease (CKD) is a progressive condition with an increasing incidence rate in Indonesia, including in Bojonegoro Regency. This disease results from a gradual decline in kidney function, leading to the accumulation of metabolic waste and toxins in the body. Early detection is crucial to prevent complications and enhance treatment effectiveness. However, current diagnostic methods rely heavily on laboratory tests and medical anamnesis, which may not provide sufficient accuracy. This study aims to develop a predictive model for kidney failure using Artificial Neural Network (ANN) and Random Forest (RF) algorithms. The ANN is particularly effective in recognizing complex nonlinear patterns, while RF demonstrates robustness in classification tasks. The results show that the ANN model achieved an accuracy of 81%, with blood urea nitrogen (BUN), blood pressure, creatinine, and diabetes identified as dominant predictors. Meanwhile, the RF model achieved an accuracy of 80%, with blood pressure emerging as the most influential variable. Based on comparative performance, ANN was selected as the optimal model for the kidney failure prediction. Nonetheless, integrating both algorithms into a hybrid framework could further enhance predictive coverage and support early detection and clinical decision-making in kidney failure management.
Identifikasi Faktor yang Mempengaruhi Kemiskinan di Papua dengan Principal Component Analysis Ain, Dzuria Hilma Qurotu; Kusuma, Shalwa Oktavia; Zahrani, Vista Vanadya; Suryono, Alda Fuadiyah; Mardianto, M. Fariz Fadillah; Amelia, Dita; Ana, Elly
Journal of Mathematics Education and Science Vol. 7 No. 1 (2024): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v7i1.1336

Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor kemiskinan terhadap pengentasan kemiskinan di Provinsi Papua. Metode yang digunakan yaitu Analisis Komponen Utama (AKU). Cakupan data yang digunakan dalam penelitian ini adalah data statistik kesejahteraan rakyat Provinsi Papua pada bulan Maret tahun 2021 yang diperoleh dari Badan Pusat Statistik (BPS). Hasil penelitian ini menunjukkan bahwa faktor-faktor yang mempengaruhi kemiskinan di Kabupaten dan Kota Provinsi Papua dapat dikategorikan menjadi tiga komponen yaitu Komponen 1 : “Pendidikan dan Kependudukan“, Komponen 2 : ”Fasilitas Imunisasi dan Penerangan”, serta Komponen 3 :  “Fasilitas Teknologi dan Kesehatan”. Dengan demikian,  penelitian  ini  bermanfaat  bagi  para  pembuat  kebijakan  baik pemerintah  pusat maupun  daerah  untuk  memperhatikan  faktor-faktor  yang  mempengaruhi terjadinya peningkatan kemiskinan di Provinsi Papua. Kemiskinan merupakan prioritas pada SDGs yang dinyatakan pada poin pertama yaitu no poverty (tanpa kemiskinan).
Penerapan Metode Clustering untuk Pemetaan Daerah Rawan Bencana di Kabupaten Bojonegoro Kartini, Alif Yuanita; Fakhriyana, Deby
Journal of Mathematics Education and Science Vol. 7 No. 1 (2024): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v7i1.1448

Abstract

Saat ini data kejadian bencana yang ada di Badan Penanggulangan Bencana Daerah kabupaten Bojonegoro hanya berupa angka-angka kejadian bencana alam dan belum disajikan dalam bentuk peta. Olehkarena itu diperlukan penelitian untuk melakukan pemetaan daerah rawan bencana di kabupaten Bojonegoro. Dari penelitian ini akan menjadi acuan dalam mengakomodir kegiatan mitigasi bencana di kabupaten Bojonegoro. Pada penelitian ini menggunakan metode clustering yakni metode K-Means, K-Medoids, dan X-Means untuk melakukan evaluasi banyaknya cluster yang optimal dan mengembangkan hasil pengelompokan dalam bentuk peta. Data yang digunakan adalah data jumlah kejadian bencana di kabupaten Bojonegoro tahun 2022 yang meliputi jumlah kejadian akibat banjir, jumlah kejadian akibat cuaca ekstrim, jumlah kejadian akibat kebakaran hutan dan lahan, jumlah kejadian akibat kebakaran rumah, jumlah kejadian akibat kekeringan, jumlah kejadian akibat tanah longsor dan jumlah kejadian lain-lain. Berdasarkan nilai Davies Bouldin Index didapatkan hasil bahwa X-Means merupakan metode terbaik dalam pengelompokan wilayah rawan bencana di kabupaten Bojonegoro. Adapun banyaknya cluster yang terbentuk adalah 4 cluster yakni cluster 0 yang terdiri dari 18 kecamatan, cluster 1 yang terdiri dari 7 kecamatan, cluster 2 yang terdiri dari 1 kecamatan dan cluster 3 yang terdiri dari 2 kecamatan. Berdasarkan karakteristik dari hasil pengelompokan dapat disimpulkan bahwa daerah yang paling rawan terjadi bencana di kabupaten Bojonegoro adalah kecamatan Bojonegoro disusul dengan kecamatan Kedungadem dan Temayang.

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