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KUBIK: Jurnal Publikasi Ilmiah Matematika
Published by UIN Sunan Gunung Djati Bandung
ISSN : 23380896     EISSN : 26860341     DOI : 10.15575/kubik
Core Subject : Economy, Science, Education,
Computer Science & IT Economics, Econometrics & Finance Mathematics
Fuzzy Systems and its Applications Geometry Theories and its Applications Graph Theories and its Applications Real Analysis and its Applications Operation Research and its Applications Statistical Theories and its Applications Dinamical Systems and its Applications Mathematics Modeling and its Applications Discrete Mathematics and its Applications Computer Mathematics and its Applications Mathematics Actuaria and its Applications
Arjuna Subject : Matematika - Matematika Terapan
Articles 157 Documents
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On The Edge Irregularity Strength of Firecracker Graphs F2,m Rismawati Ramdani; Desi Laswati Suwandi
KUBIK Vol 7, No 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i1.18430

Abstract

Let  be a graph and k be a positive integer. A vertex k-labeling  is called an edge irregular labeling if there are no two edges with the same weight, where the weight of an edge uv is . The edge irregularity strength of G, denoted by es(G), is the minimum k such that  has an edge irregular k-labeling. This labeling was introduced by Ahmad, Al-Mushayt, and Bacˇa in 2014.  An (n,k)-firecracker is a graph obtained by the concatenation of n k-stars by linking one leaf from each. In this paper, we determine the edge irregularity strength of fireworks graphs F2,m.
Analisis Faktor-Faktor yang Mempengaruhi Risiko Gagal Bayar Debitur pada Lembaga Keuangan Mikro Menggunakan Regresi Logistik dan Ant Coloni Optimization (ACO) Ratih Hadiantini; Ayu Nike Retnowati
KUBIK Vol 7, No 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i1.13836

Abstract

Salah satu peranan langsung Lembaga Keuangan Mikro (LKM) terhadap industri kecil dan mikro adalah memberikan dana pinjaman berupa kredit kepada nasabah yang membutuhkan. Dalam hal ini nasabah LKM dapat mengajukan kredit dengan memenuhi persyaratan dari LKM lalu kredit didapatkan jika LKM menyetujui kesepakatan pinjaman. Dalam proses pemberian kredit yang dilakukan oleh LKM sering dihadapkan pada suatu risiko yang dikenal sebagai risiko kredit bermasalah (problem loans). Berdasarkan risiko gagal bayar tersebut, paper ini bertujuan untuk melakukan analisis faktor-faktor yang mempengaruhi risiko gagal bayar dari calon debitur. Metode yang digunakan adalah regresi logistic dan Ant Coloni Optimization (ACO).  Terdapat beberapa tahap dalam penelitian ini: (1) melakukan standarisasi data pada data faktor risiko calon debitur, (2) menetapkan asumsi model regresi logistic, (3) melakukan estimasi parameter model regresi logistik menggunakan algoritma Ant Coloni Optimization (ACO), dan (4) melakukan uji signifikansi setiap variabel. Dalam paper ini, data yang digunakan adalah data historis debitur pada LKM di Bandung, Indonesia. Hasilnya menunjukkan bahwa lima faktor yang dianalisis berpengaruh signifikan terhadap risiko gagal bayar, yaitu usia, jumlah tanggungan keluarga, nilai jaminan, besarnya kredit yang diajukan, dan jangka waktu pengembalian kredit. dengan kekuatan korelasi sebesar 93.5%. Menggunakan lima factor ini, yang digunakan untuk menentukan probabilitas gagal bayar dari calon debitur. Probabilitas risiko gagal bayar calon debitur ini, sangat berguna bagi LKM guna menentukan klasifikasi faktor kelayakan pemberian kredit berdasarkan predikat risiko calon debitur. Demikian sehingga, LKM dapat mengetahui faktor-faktor risiko gagal bayar dan mengambil keputusan pemberian kredit yang layak atau tidak layak. 
Modeling a Wave on Mild Sloping Bottom Topography and Its Dispersion Relation Approximation Faizal Ade Rahmahuddin Abdullah; Elvi Syukrina Erianto
KUBIK Vol 7, No 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i1.18419

Abstract

Linear wave theory is a simple theory that researchers and engineers often use to study a wave in deep, intermediate, and shallow water regions. Many researchers mostly used it over the horizontal flat seabed, but in actual conditions, sloping seabed always exists, although mild. In this research, we try to model a wave over a mild sloping seabed by linear wave theory and analyze the influence of the seabed’s slope on the solution of the model. The model is constructed from Laplace and Bernoulli equations together with kinematic and dynamic boundary conditions. We used the result of the analytical solution to find the relation between propagation speed, wavelength, and bed slope through the dispersion relation. Because of the difference in fluid dispersive character for each water region, we also determined dispersion relation approximation by modifying the hyperbolic tangent form into hyperbolic sine-cosine and exponential form, then approximated it with Padé approximant. As the final result, exponential form modification with Padé approximant had the best agreement to exact dispersion relation equation then direct hyperbolic tangent form.
Deteksi Covid-19 Menggunakan Citra X-Ray Metode Gray Level Co-Occurrence Matrix (GLCM) dan Adaptive Neuro Fuzzy Inference System (ANFIS) Fitri Mellynia Astiti; Noormann Atoillah; Rahmat Rizki Sinulingga; Achmad Room Fitrianto
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The first detected COVID-19 was in China, this virus has spread worldwide rapidly. COVID-19 is caused by the SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Corona Virus-2) or an acute infection that attacks the respiratory system. COVID-19 examination can be carried out by X-rays. The X-ray images will be identified using a CAD system or Computer-Aided Diagnosis. CAD has three processes consisting of preprocessing, feature extraction, and classification. This study compares 200 X-ray image data of COVID-19 data and 200 X-ray image data of non-COVID-19 data. Both groups of data were divided using the K-fold Cross Validation method where the K value used is 10 so that the distribution of training data is 90% and testing is 10%. The epoch used is 5 with 4 parameters (contrast, correlation, energy, and homogeneity). In the feature extraction process, GLCM is used by comparing every angle in the feature extraction, while Adaptive Neuro Fuzzy Inference System (ANFIS) is used for classification. The best results were obtained from GLCM at an angle of 0° with an accuracy value of 0.90, a sensitivity of 0.85 and a specificity of 0.95. This shows that the use of GLCM and ANFIS for COVID-19 detection performs well.
Penerapan Extreme Learning Machine Dalam Meramalkan Harga Minyak Sawit Mentah Siti Aisyah; Nurissaidah Ulinnuha; Abdulloh Hamid
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.20460

Abstract

The need for crude palm oil has increased due to the large demand for vegetable oils in various parts of the world. Beginning in March 2022, the price of crude palm oil set a record high which caused international cooking oil prices to soar, especially for Indonesia. This study aims to predict the price of crude palm oil with test parameters, namely hidden neurons and activation functions. The method used is Extreme Learning Machine (ELM). This method is a development of the artificial neural network (ANN) method which can overcome weaknesses in the learning speed process. There are several stages in this study: (1) pre-processing the data by normalizing the data and dividing the data using the time series split method, (2) analyzing the data using the ELM method by testing parameters, namely hidden neurons and activation functions, (3) analyzing the results of the best parameter trials, (4) calculating forecasting data using the best parameters that have been obtained, and (5) analyzing the forecasting results that have been obtained. This study uses daily data on the price of crude palm oil from April 1 2021 to April 14 2022 obtained from the Investing website. The results of the research that has been carried out obtained MAPE and RMSE values of 0.0173 and 0.0308 with the best parameters namely the number of hidden neurons of 5 and the binary sigmoid activation function. Based on the results obtained, it is hoped that it will make it easier for the government to determine the price of crude palm oil in the future.
Klusterisasi Penyandang Masalah Kesejahteraan Sosial (PMKS) Di Kabupaten Bojonegoro Menggunakan Algoritma K-Medoids Elisa Syafaqoh; Nurissaidah Ulinnuha; Lutfi Hakim
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.21653

Abstract

Persons with Social Welfare Problems (PMKS) are individuals, community groups, or families who cannot adequately and properly meet their economic, physical, mental, and social needs, both spiritually and physically, because of an obstacle, difficulty, or disturbance. This study aimed to classify sub-districts in Bojonegoro Regency based on the level of social welfare problems using the K-Medoids Clustering (PAM) Analysis method. There are 2 clusters formed with an Average Silhouette of 0.73. Cluster 1 is a sub-district group with common social welfare problems, and Cluster 2 is a sub-district group with high social welfare problems. Each silhouette value of the cluster is 0.74 and 0.70 with the specifications of a well-formed and strong structure.
Model Relaksasi dan Osilasi Menggunakan Persamaan Diferensial Orde Fraksional Tipe Caputo Wildy Ardan; Siti Fatimah; Kartika Yulianti
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.17929

Abstract

The phenomenon of relaxation and oscillation is a joint event that is often encountered. These properties can occur in viscoelastic materials even though they do not co-occur. Because the characteristics of viscoelastic materials are difficult to describe using classical-order differential equations, in this study, fractional-order differential equations were used to model each of the relaxation and oscillation phenomena in viscoelastic materials with the help of the Laplace transform as a solution method. The solution obtained characterizes the phenomenon of memory effect as well as viscoelastic materials in general. In addition to this phenomenon, several other variables were also found to influence the related material motion dynamics.
Perbandingan Metode Random Forest dan Naïve Bayes dalam Email Spam Filtering Maria Anita; Bambang Susanto; Lenox Larwuy
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.18933

Abstract

Email is an important tool not only for communicating and transferring files but also it can be used for advertising media over the Internet. Since the increase in email user numbers, many users send viruses, fraud, and even pornography contained emails. Those kinds of emails were called spam, where unexpected emails sent in bulk. Many email users are annoyed by the amount of time spent deleting individual spam messages. This study provides a comparison between the Random Forest and Naïve Bayes classification methods for email spam predicting. It aims for searching the most accurate method. The data used in this study is an email dataset totaling 2607 data with two variables, namely the body variable (which shows the contents of the email) and the label variable (which shows labeling) where 1 indicates spam and 0 indicates not spam. From the test result using the confusion matrix, it is known that the random forest method has the highest accuracy value, namely 98%, and Naïve Bayes 73%.
Optimal Control of Vaccination for Dengue Fever in SIR Model Nilwan Andiraja; Sri Basriati; Elfira Safitri; Rahmadeni Rahmadeni; Alfitra Martino
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.21397

Abstract

According to data from The Indonesian ministry of health, many of individuals suffere dengue fever until may 2023 in Indonesia. To reduce its cases, in this article, a single of control strategy of vaccination for infected human by dengue fever has been proposed. To obtain the optimal control, the SIR model has been modificated with single control and the new objective function has been made before the Pontryagin minimum principle is used in this article. According to the differential equation in the model of the dengue fever and the objective function, we made the Hamiltonian equation. Then, from it, the state equation, costate equation, and stationary condition has been made from the Hamiltonian equation so we obtained the optimal control in vaccination. In the end of this article, we did the numerical simulation using the sweep forward-backward method. Through numerical simulation, we find that the control succeed to reduce the infected human by dengue fever and also increase human recovery from this desease. Futhermore, the control of vaccination for infected human should be implemented not only in this mathematical model but also into real life to decrease the dengue fever case. 
Penyelesaian Masalah Transportasi dengan Degenerasi dan Siklus Berulang Menggunakan Minimum Demand Method dan Maximum Difference Extreme Difference Method Muhtarulloh, Fahrudin; Mardiah, Evi Wardah; Huda, Arief Fatchul; Zulkarnaen, Diny
KUBIK Vol 8, No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v8i1.30024

Abstract

The transportation problem is a linear programming model that can be used to regulate distribution from a source (product supply) to a destination that requires the product optimally with minimum costs. However, when carring out optimality tests, sometimes the optimal value cannot be determined due to degeneration and repeated cycles. The aim of this research is to overcome the problem of degeneration and repeated cycles that occur in optimization problems. The methods used in this research are Minimum Demand Method (MDM) and Maximum Difference Extreme Difference Method (MDEDM) as well as the optimality test, namely Modified Distribution (MODI). The results of data analysis show that analysis show that the Minimum Demand Method has more degeneration problems, namely 132 data in the balanced case and 137 data in the unbalanced case. The Maximum Difference Extreme Difference Method has more repeated cycle problems, namely 8 data in the balanced case and 9 data in the unbalanced case. From the calculation results it can be concluded that the Maximum Difference Extreme Difference Method is more optimal than the Minimum Demand Method.

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