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Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika
Published by Universitas Bina Bangsa
ISSN : 27218929     EISSN : 27218937     DOI : 10.46306/lb
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Education Mathematics
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Lebesgue Adalah Jurnal Ilmiah yang terbit secara daring pada bulan April, Agustus dan Desember. untuk menyebarluaskan hasil-hasil penelitian dalam bidang matematika, statistika, aktuaria, matematika terapan, matematika komputasi, Model Pembelajaran Matematika dan pendidikan matematika.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 65 Documents
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Search results for , issue "Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik" : 65 Documents clear
TRACE MATRIKS FLDcircr BENTUK KHUSUS BERPANGKAT DUA Ade Novia Rahma; Sri Sukmawati; Rahmawati Rahmawati
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.424

Abstract

Tracking the matrix is ​​the sum of the elements on the main diagonal of the matrix. This study aims to determine the Trace of a specially shaped quadratic FLDcircr matrix. In determining the Trace of a squared FLDcircr matrix, there are a number of steps to be take. First determine the special shape of the to 8x8 FLDcircr,  matrix so that the general shape of FLDcircr, is formed to form a special quadratic.Furthermore, from the equations obtained, we can determine the Trace of the FLDcircr matrix in the form of a special quadratic order of the matrix  to , Having obtained the general form of Trace from the FLDcircr matrix, we can prove it by direct proof
ANALISIS MATEMATIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN MS GLOW Annisa Nur Afifah Kusuma Sayekti; A’yunin Sofro
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.437

Abstract

In this increasingly advanced era, beauty products are increasing. Not only women, men also enjoy the development of this beauty product. One beauty brand that keeps up with current developments is the MS Glow brand. The MS Glow brand not only offers types of skincare that are suitable for men and women. This brand offers skincare that is licensed by BPOM and Halal MUI. Even though this brand is well known to the general public, it is necessary to identify the factors that influence customers' decisions in purchasing MS Glow products. This can help increase the popularity of MS Glow products. The cultural factor used in this research is the attitude of wanting to own what other people have or just following trends in the surrounding area. From this factor it can be concluded that the cultural factor is a "following" trend. Lifestyle factors in this research are defined as observations/interactions of customers who want to buy products. In this modern lifestyle, many customers always want products that are attractive or because of the quality of the product. According to Joesyiana, one of the most effective and efficient ways of marketing goods or services is through the word-of-mouth communication process using online media. With this marketing method, the brand owner gets the advantage that his product is better recognized by the public
PEMODELAN DEA AGGRESSIVE - BOOTSTRAP REGRESSION PADA FAKTOR YANG MEMPENGARUHI EFISIENSI PERBANKAN SYARIAH INDONESIA Rendra Erdkhadifa
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.442

Abstract

Data Envelopment Analysis is a non-parametric method developed based on linear programs with objective functions and weight functions. DEA is an analytical technique used to measure the efficiency of a process which the decision making units (DMUs) are homogeneous. The application of the DEA method in various fields yields in steps in determining policies in a process. This study aims to measure the efficiency of Indonesian Islamic banking by applying DEA method with aggressive weighting. The efficiency result of the method is then combined with bootstrap regression method to find out the variables that significantly influence the efficiency value. The data in the research process was taken from the monthly financial reports of Indonesian Islamic banking from 2018 to 2022 with a quantitative research approach and associative research type. The input variables used to measure efficiency include total assets, total labor, labor operating costs, total deposits, and fixed assets.While the output variables include total financing funds, net operating margin, and other operating income. Meanwhile, the independent variables to estimate the factors that influence the efficiency value of DEA include capital adequacy ratio, return on assets, company size, and financing to deposit ratio.The result of the analysis shows the goodness of the model which is the coefficient of determination worth 40.95%. Independent variables that significantly affect the efficiency of DEA aggressive are capital adequacy ratio, return on assets, and financing to deposit ratio
PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN POLA BILANGAN BERBANTUAN ISPRING SUITE TERHADAP HASIL BELAJAR MATEMATIKA SISWA Nurfika Mato; Syamsu Qamar Badu; Franky Alfrits Oroh
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.444

Abstract

The purpose of this study was to determine the effect of the use of ispring suite assisted number pattern learning media on the mathematics learning outcomes of class VIII students. This research is a quantitative research using experimental methods and using a pretest-posttest control group design. Sampling used the Random Sampling technique and the selected classes were class VIII-6 as the experimental class and class VIII-4 as the control class. The research instrument uses a learning achievement test in the form of a description/essay. Inferential analysis was performed using the anacova test. The results showed that there was a positive and significant effect on the use of iSpring Suite assisted number pattern learning media on students' mathematics learning outcomes
PENGARUH MODEL PEMBELAJARAN AIR BERBANTU MEDIA LAGU MATERI ALJABAR TERHADAP KEMAMPUAN PEMAHAMAN KONSEP Nur Latifah; Nur Baiti Nasution
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.445

Abstract

The purpose of this study was to analyze and improve the concept understanding abilities of class VII students using the AIR learning model assisted by algebra song. This research uses a type of experimental research with a one group pretest-posttest design. This type of experimental research is included in quantitative research methods. The sampling technique uses cluster random sampling technique. The instrument for collecting data in this research is a test instrument in the form of pretest and posttest questions. All students in class VII F were given pretest questions on real numbers and their operations. At the next 2 meetings, treatment was given in the form of learning algebra material using the AIR learning model assisted by algebra song. After the treatment was carried out, posttest questions on algebra material were given to students. Next, analysis of all data is carried out using the following steps: analysis of initial and final data, data presentation stage, and conclusions. The results of the research show that there is an increase in students' ability to understand concepts by using the AIR learning model assisted by algebra song media. The use of the AIR learning model assisted by algebra song is said to be significant in improving the ability to understand concepts because the proportion of students after being given the AIR learning model assisted by algebra song who completed it exceeded the KKM score (>70) of more than 75% of the total number of students
MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA MELALUI MODEL ACCELERATED LEARNING BERBANTUAN MEDIA INTERAKTIF Sitria Jemin; Tedy Machmud; Lailany Yahya
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.446

Abstract

This research aims to improve students’ mathematical problem solving abilities in quadratic equation material through an accelerated learning model assisted by interactive media. This classroom action research was conducted at SMP Negeri 8 Gorontalo City for the 2023/2024 academic year. The research subjects were 25 students in class IX-4. The data collection techniques used are observations and tests. This research lasted for 2 cycles. From the results of observations, teacher activities increased, from 67,31% in cycle I of 87,5% in cycle II with an increase 0f 20,19%. Furthermore, the results of observations of student activities increased, from 66,27% in cycle I to 85,41% in cycle II with an increase of 19,14%. Students’ mathematical problem solving abilities also increased from 56% in cycle I to 84% in cycle II with an increase of 28%. From the research above, it can be conclued that the accelerated learning model asissted by interactive media can improve students’s mathematical problem solving abilities in quadratic equation
KOMBINASI ALGORITMA BRANCH AND BOUND DAN CHEAPEST INSERTION HEURISTIC DALAM MENGOPTIMALKAN RUTE DISTRIBUSI KURIR PAKET JNT DI KECAMATAN BATANG CENAKU Elfira Safitri; Sri Basriati; Winda Widiarti; Sri Sukmawati
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.472

Abstract

Traveling Salesman Problem (TSP) is a problem faced by salesmen who only visit each city once and then return to their hometown with the shortest distance. The aim of this research is to determine the shortest route for the distribution journey of JNT package couriers.The method used in this research is a combination of the Branch and Bound Algorithm and the Cheapest Insertion Heuristic. Data analysis was carried out by interpreting the problem in graph form, next use the Googling application to search and determine distances. Based on the research results, it was found that the shortest route for JNT package courier distribution District is JNT Belilas → Kuala Kilan → Bukit Lipai → Aur Cina → Pejangki → Petaling Jaya → Puntianai → Lahai → Talang Mulya → Talang Bersemi → Anak Talang → Kepayang sari → Alim 2 → Sipang → Alim 1 → Batu Papan → Cenaku Kecil → Pematang Manggis → Kerubung Jaya → Bukit Lingkar → Bukit Indah → Kuala Gading → JNT Belilas with total distance 172 km
PENGGEROMBOLAN KECAMATAN DI PROVINSI JAWA BARAT BERDASARKAN AKSES PENDIDIKAN MENENGAH ATAS (SMA-SEDERAJAT) DENGAN K-PROTOTYPES Sofia Octaviana; Ahmad Syauqi; Anwar Fitrianto; Erfiani Erfiani; Alfa Nugraha Pradana
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.478

Abstract

Education is an important element for the Indonesian nation and must be felt by all citizens. The availability of educational facilities is important for the realization of overall educational equality for the Indonesian people. The aim of this research is to group sub-districts in West Java Province according to their level of access to Senior High School (SHS-equivalent). The data included in this study comprises both numerical and categorical variables, which were obtained from the 2021 Village Potential Data Collection (PODES) conducted by the Central Statistics Agency. A cluster analysis method that can be used to group objects based on numerical and categorical data is K-Prototypes. The results of the grouping divide the data into 2 groups, where the first group has the characteristics of an urban subdistrict, the topographic area is plain, access to the nearest high school is very easy, and has an average number of high school and equivalent schools of 22 schools per subdistrict, and has an average distance to the nearest high school of 1,86 km. Meanwhile, the second group has the characteristics of subdistricts with rural areas, topography in the form of slopes, easy access to the nearest high school, and has an average number of high schools of 7 per subdistrict, and the average distance to the nearest high school is 4,06 km. The second group is sub-districts that need to be given special attention because they have relatively fewer high schools and the distance to the nearest high school is further
ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR SEISMIC ANOMALY DETECTION IN INDONESIA: UNVEILING PATTERNS IN THE PACIFIC RING OF FIRE Gregorius Airlangga
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.489

Abstract

This study presents an integrated analysis of machine learning algorithms for the detection of seismic anomalies in Indonesia, a region within the volatile Pacific Ring of Fire. Employing Local Outlier Factor, Isolation Forest, and Elliptic Envelope algorithms, we processed a comprehensive dataset of seismic events characterized by latitude, longitude, depth, and magnitude. Our methodology involved standardizing these features and aggregating model predictions to establish a consensus mechanism for outlier detection. The results indicated that the vast majority of seismic events are consistent with the expected geological patterns, with a negligible percentage exhibiting anomalous behavior across the models. Through statistical analysis and visual mapping, we discerned that while anomalies are varied, they may correlate with specific seismic event features such as higher magnitudes or unique geographic locations. The consensus approach revealed a high-confidence subset of outliers, offering a focused direction for further seismological scrutiny. The study's implications extend to enhancing seismic risk assessment and early warning systems, providing a methodological framework for identifying seismic events that deviate from normative patterns. By outlining a scalable approach for anomaly detection, this research contributes to the predictive analytics tools available for disaster risk management and emergency preparedness, aiming to mitigate the impact of seismic hazards in seismically active regions
ADVANCED MACHINE LEARNING TECHNIQUES FOR SEISMIC ANOMALY DETECTION IN INDONESIA: A COMPARATIVE STUDY OF LOF, ISOLATION FOREST, AND ONE-CLASS SVM Gregorius Airlangga
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.490

Abstract

This study presents a comprehensive comparison of three machine learning algorithms for anomaly detection within seismic data, focusing on the unique geographical and geological context of Indonesia, a region prone to frequent seismic events. Local Outlier Factor (LOF), Isolation Forest, and One-Class SVM were assessed using a meticulously curated dataset from the Indonesian Meteorology, Climatology, and Geophysical Agency, standardized to ensure consistent feature scale. Our analysis encompassed both statistical metrics and visualizations to evaluate the performance of each algorithm. The One-Class SVM emerged as the most effective method, achieving the highest silhouette score, indicative of its superior cluster formation and clear distinction between inliers and outliers. The Isolation Forest also demonstrated strong performance with a favorable silhouette score and Davies-Bouldin index, suggesting effective anomaly isolation capabilities. In contrast, the LOF algorithm showed less precision, as indicated by lower silhouette scores and a higher Davies-Bouldin index, suggesting potential challenges in distinguishing between normal and anomalous seismic patterns. Statistical validation using the Kruskal-Wallis H-test confirmed significant differences in the anomaly score distributions of the three algorithms, with a p-value of 0.0. Visualizations through PCA and t-SNE reinforced the quantitative findings, displaying a clear demarcation of anomalies by the One-Class SVM and Isolation Forest, unlike the LOF.The findings underscore the importance of selecting appropriate anomaly detection methods for seismic data analysis, highlighting the robustness of One-Class SVM and Isolation Forest for such applications. The implications of this research are profound for seismic risk management, providing insights that enhance the accuracy and reliability of earthquake prediction systems, which is vital for regions with high seismic activity such as Indonesia.

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