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Kubik
Published by Universitas Islam Negeri Sunan Gunung Djati Bandung
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Core Subject : Education,
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Articles 6 Documents
 1 
Search results for , issue "Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika" : 6 Documents clear
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; A 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. 

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