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Unisda Journal of Mathematics and Computer Science (UJMC)
ISSN : 24603333     EISSN : 2579907X     DOI : -
Core Subject : Science, Education,
Unisda Journal of Mathematics and Computational Science (UJMC) is a research journal published by Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan with the scope of pure mathematics, applied science, education, statistics
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Articles 6 Documents
Search results for , issue "Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science" : 6 Documents clear
Penerapan Metode Inquiry-Based Learning Dalam Upaya Peningkatan Hasil Belajar Matematika Tentang Himpunan Sungkono Sungkono
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2091

Abstract

In mathematics learning especially in the material of assemblies in class VII-B MTs Negeri 2 Mojokerto in the 2018/2019 academic year, there are many obstacles. The lack of students' ability to understand the set material can be seen from the results of initial observations by the researcher. The subject of this research are 37 students consisting of 9 boys and 28 girls, the initial student abilities were identified as follows: (a) very good of 7 people or 18.92%; (b) either of 7 people or 18.92%; (c) sufficient of 5 people or 13.51%; (d) less of 13 people or 35.14%; and (e) very less of 5 people or 13.51%. This research applied the inquiry-based learning method to improve mathematics learning outcomes. This research was conducted with a classroom action research design with two cycles. Based on the results and discussion, it was concluded that student learning outcomes before using the inquiry-based learning method were categorized as poor with a percentage of 59.56%. After using the inquiry-based learning method in learning, there was an increase in learning outcomes in a good category, reaching 75.80% in cycle I, and an increase in cycle II reaching a percentage of 83.40%. The level of student learning success in cycle I was 80.67%, increasing to 86.13% in cycle II.
Analisis Diskriminan Terhadap Pengelompokan Mutu Pendidikan Sekolah Menengah Atas di Kabupaten Lamongan Mu’tasim Billah; Novita Eka Chandra; Siti Amiroch
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2094

Abstract

Quality of education is the educational services ability that can fill the needs or expectations, satisfaction internally and externally which includes educational inputs, processes and outputs. The purpose of this reserach is to classify the quality of high school education in Lamongan District using factor, cluster and discriminant analysis. The dominant factors of 12 education quality variables can be known from the results of factor analysis using the PCA (Principal Component Analysis) method. The grouping of 48 high schools did by cluster analysis using 5 hierarchical methods. The validity index used to determine the optimal group number of the five hierarchical methods is RMSSTD (Root Mean Square Standard Deviation). The classification accuracy testing uses discriminant analysis based on the results of factor analysis and cluster analysis. Grouping the quality of education is influenced by dominant factors such as the number of classrooms, the value of accreditation, the number of certification and non-certification teachers, the number of education staff, the ratio of students to teachers, the number of laboratory rooms that can be known from the results of factor analysis. In cluster analysis, using the Mahalanobis distance because there is multicollinearity and the smallest RMSSTD index value obtained in the Complete Linkage method with 5 clusters. So, with discriminant analysis, it can be concluded that the grouping based on factor analysis and cluster analysis is 58.3% of the 48 processed data that has been entered in the group that matches the original data.
Expected Value Premium Principle Pada Data Reasuransi Radot Mh Siahaan; Dian Anggraini; Andi Fitriawati; Dani Al Makhya
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2116

Abstract

The amount of stop loss cover reinsurance using krone as Danish currency. The stop loss cover reinsurance scheme with a retention value of r = 50 million krone from fire insurance data in Denmark from 1980-1990 with truncate date at 10 million krone, resulting in a conditional expected value that decreases in value when the higher the threshold value. This is indicated by the threshold value of 1 = 2.976 resulting in pure premium of 1 = 0.1217, a threshold value of 2 = 10.0539 resulting in pure premium 2 = 0.0867 and a threshold value of 3 = 26.199 resulting in pure premium 3 = 0.0849. The use of expected value premium principle with the loading factor () is weighted to the value of the pure premium represented by. This is indicated by the weight of premium 1 = 0.13387, the weight of the premium 2 = 0.09537 and the weight of premium 3 = 0.09339.
Implementasi Algoritma Greedy Pada Pewarnaan Wilayah Kecamatan Sukodadi Lamongan Umi Maftukhah; Siti Amiroch; Mohammad Syaiful Pradana
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2391

Abstract

Graph theory can be applied in various fields of science such as transportation problems, communication networks, operations research, chemistry, cartography and so on. Graph theory does not only represent structure but in its application, a graph can also be colored. Many problems have graph coloring characteristics such as regional coloring. This regional coloring theory was applied to the map area of ​​Sukodadi District which consists of 20 villages. In this area coloring uses the Greedy algorithm by first making a dual graph consisting of 20 vertices and 43 edges. Based on the results of regional coloring, the minimum number of colors is 4, namely red, blue, green and yellow, with each neighboring village having a different color.
Implementasi Fuzzy C-Means dan Possibilistik C-Means Pada Data Performance Mahasiswa Gadis Retno Apsari; Mohammad Syaiful Pradana; Novita Eka Chandra
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2392

Abstract

Students are the most important component in a university, especially private universities especially Universitas Islam Darul ‘ulum (Unisda) Lamongan. One of the most important roles of students for higher education is achievement. This study aims to determine the role of Fuzzy Clustering in classifying student performance data. The data includes GPA (Grade Point Average), ECCU (Extra-Curricular Credit Unit), attendance, and students' willingness to learn. So that groups of students who have the potential to have achievements can be identified. In this case, the grouping of student performance data uses Fuzzy Clustering by applying the Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) algorithms with the help of Matlab. In the FCM algorithm, the membership degree is updated so as to produce a minimum objective function value. Meanwhile, the PCM algorithm uses a T matrix, which shows the peculiarities of the data which are also based on minimizing the objective function.
Pemodelan Regresi Cox Proportional Hazard Pada Data Perceraian Haykal Abidin; Novita Eka Chandra; Mohammad Syaiful Pradana
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 6 No 2 (2020): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v6i2.2393

Abstract

The purpose of this research is modeling the Cox proportional hazard regression form on divorce data in Pelaihari sub-district, Tanah Laut district, South Kalimantan province. The source of the data comes from the Court Decision in Pelaihari District, Tanah Laut Regency, South Kalimantan. The data analysis technique uses software R with the steps, namely data description, Log-Rank test, checking proportional hazard assumptions, Cox regression model parameter estimation, backward selection with AIC, the best model parameter significance test, calculating Hazard ratio and interpretation of each predictor variable. Based on the results of the analysis and discussion, it was found that for the Log-Rank test, the variable survival time for domestic violence, forced marriage, lying and stories of disgrace differed significantly. While the model that meets the criteria after iteration up to 15 times is the 15th model with the smallest AIC value and p-value <0.05 with factors that significantly influence divorce in Pelaihari sub-district based on modeling results using Cox proportional Hazard regression. are the variables of cheating, gambling, domestic violence, forced marriage, lies, jealousy and disgrace story variables

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