Papers by Nursyiva Irsalinda
International Journal of Research in Community Service, Apr 5, 2024
Taman Kelulut Ayoh Ku Bee Farming Community in Pengkalan Gelap, Kuala Setiu, Terengganu, Malaysia... more Taman Kelulut Ayoh Ku Bee Farming Community in Pengkalan Gelap, Kuala Setiu, Terengganu, Malaysia, is a group of Trigona sp. honey beekeepers which faces challenges related to the availability of packaging facilities for kelulut honey. This community service activity is important to provide education and training to improve packaging facilities through diversification and labeling on honey product. The activity was carried out offline on August 8-9th, 2023. The results of the activity showed that the training on diversifying honey product packaging increased the knowledge and skills of 92.5% of participants, while the training on labeling honey product packaging increased the knowledge and skills of 80% of participants. The solutions presented can increase the knowledge and skills of community members, motivate the enthusiasm of farmers, and increase the selling value of honey products produced by the Taman Kelulut Ayoh Ku Bee Farming Community.
Emerging science journal, Apr 1, 2024
Deep learning, specifically the Convolutional Neural Network (CNN), has been a significant techno... more Deep learning, specifically the Convolutional Neural Network (CNN), has been a significant technology tool for image processing and human health. CNNs, which mimic the working principles of the human brain, can learn robust representations of images. However, CNNs are susceptible to noise interference, which can impact classification performance. Choosing the right activation function can improve CNNs performance and accuracy. This research aims to test the accuracy of CNN with ResNet50, VGG16, and GoogleNet architectures combined with several activation functions such as ReLU, Leaky ReLU, Sigmoid, and Tanh in the classification of images that experience Poisson noise. Poisson noise is applied to each test data to evaluate CNN accuracy. The data used in this study consists of three scenarios of different numbers of classes, namely 3 classes, 5 classes, and 10 classes. The results showed that combining ResNet50 with the ReLU activation function produced the best performance in class recognition in each scenario of the number of classes experiencing Poisson noise interference. The model achieved 97% accuracy for 3-class data, 95% for 5-class data, and 90% for 10-class data. These results show that using ResNet50 with the ReLU activation function can provide excellent resistance to Poisson noise in image processing. It was found that as the number of classes increases, the accuracy of image recognition tends to decrease. This shows that the more complex the image classification task is with a larger number of classes, the more difficult it is for CNNs to distinguish between different classes.
Penyelesaian Permasalahan Optimasi Global Menggunakan Algoritma Koloni Lebah Buatan
Konvergensi, Oct 1, 2013
Eksperimen numerik ini bertujuan untuk mengetahui algoritma koloni lebah buatan ( Artificial Bee ... more Eksperimen numerik ini bertujuan untuk mengetahui algoritma koloni lebah buatan ( Artificial Bee Colony Algorithm ) secara singkat ditulis algoritma ABC dan pengaruh parameter kontrol ( Solution Number) dan ( Maximum Cycle Number) terhadap efektivitas kinerja algoritma tersebut. Algoritma ABC merupakan salah satu metode heuristik berdasar populasi digunakan untuk menyelesaikan masalah optimasi global khususnya dalam proses minimalisasi. Memiliki dua parameter kontrol yaitu jumlah dan . Proses algoritma ABC menggunakan bilangan-bilangan random yang berubah-ubah setiap prosesnya, oleh karena itu tugas akhir ini meneliti pengaruh parameter kontrol terhadap keefektivan kinerja algoritma ABC. Algoritma ABC diujikan untuk menyelesaikan beberapa fungsi Benchmark. Untuk mengetahui pengaruh , maka dilakukan perhitungan algoritma ABC dalam berbagai yaitu dan 200 dengan MCN yang sama yaitu 100 dan 20 iterasi. Sedangkan untuk untuk mengetahui pengaruh , maka dilakukan perhitungan algoritma ABC dalam berbagai yaitu dan 200 dengan yang sama yaitu 20 dan 200. Setiap perhitungan nilai optimal dilakukan sebanyak 10 kali dan diperoleh mean dan standar deviasinya. Dari eksperimen numerik yang dilakukan, dapat diketahui bahwa semakin banyak dan , kinerja algoritma ABC akan semakin efektiv karena menghasilkan nilai optimum yang semakin mendekati nilai eksak.
Understanding student engagement: an examination of the moderation effect of professional teachers' competence
Journal of Education and Learning (edisi elektronik)/Journal of Education and Learning, Feb 2, 2025
Cauchy, Mar 11, 2022
The existence of viral mutations in various infectious diseases can make it difficult to overcome... more The existence of viral mutations in various infectious diseases can make it difficult to overcome outbreaks caused by these viruses. In this paper, we introduce an optimal control problem in a two-strain SIR epidemic model with viral mutation and vaccine administration. The purpose of this study was to investigate the efficacy and cost-effectiveness of two disease prevention strategies, namely restriction of community mobility to prevent disease transmission and vaccine intervention. We consider the time-dependent control case, and we use Pontryagin's Maximum Principle to derive necessary conditions for the optimal control of the disease. We also calculate the Average Cost-Effectiveness Ratio (ACER) and the Incremental Cost-Effectiveness Ratio (ICER) to investigate the cost-effectiveness of all possible strategies of the control measures. The results of this study indicate that the most cost-effective disease control strategy is a combination of mobility restriction and vaccination.
An epidemic model with viral mutations and vaccine interventions
Mathematical Modeling and Computing
In this paper, we introduce a two-strain SIR epidemic model with viral mutation and vaccine admin... more In this paper, we introduce a two-strain SIR epidemic model with viral mutation and vaccine administration. We discuss and analyze the existence and stability of equilibrium points. This model has three types of equilibrium points, namely disease-free equilibrium, dominance equilibrium point of strain two, and coexistence endemic equilibrium point. The local stability of the dominance equilibrium point of strain two and coexistence endemic equilibrium point are verified by using the Routh--Hurwitz criteria, while for the global stability of the dominance equilibrium point of strain two, we used a suitable Lyapunov function. We also carried out the bifurcation analysis using the application of center manifold theory, and we obtained that the system near the disease-free equilibrium point always has supercritical bifurcation. Finally, the numerical simulations are provided to validate the theoretical results. Continuation of the supercritical bifurcation point results in two Hopf bifu...
Jurnal Berdaya Mandiri
Usaha mikro kecil dan menengah (UMKM) merupakan salah satu penggerak roda perekonomian di masyara... more Usaha mikro kecil dan menengah (UMKM) merupakan salah satu penggerak roda perekonomian di masyarakat. Kotagede merupakan salah satu kecamatan di kota Yogyakarta yang memiliki UMKM dengan jumlah 497 usaha. Dalam upaya mempromosikan dan mempublikasikan produk-produk yang ada di Kecamatan Kotagede dan menunjang program Kecamatan Kotagede menuju Smart District maka diperlukan analisis khusus UMKM Kecamatan Kotagede untuk menciptakan suatu Platform yang memuat informasi UMKM baik pelaku maupun produk yang dihasilkan serta fasilitas lain yang dibutuhkan oleh pelaku UMKM maupun masyarakat. Hasil analisis data UMKM yang telah dilakukan menunjukkan bahwa UMKM dengan modal dibawah Rp. 250.000.000 sebesar 80%. Oleh karena itu, dalam rangka mengembangkan UMKM diwilayahnya pihak kecamatan sebaiknya membuat platform perizinan untuk mempermudah proses perizinan UMKM.
Prosiding Seminar Nasional Hasil Pengabdian Kepada Masyarakat Universitas Ahmad Dahlan, Oct 23, 2021
Barekeng, Sep 29, 2023
Article History: Time series data represents measurements taken over a specific period and is oft... more Article History: Time series data represents measurements taken over a specific period and is often employed for forecasting purposes. The typical approach in forecasting involves the analysis of relationships among estimated variables. In this study, we apply Fuzzy Time Series (FTS) to water level data collected every 10 minutes at the Irish Achill Island Observation Station. The FTS, which is based on Fuzzy C-Means (FCM), is hybridized with the Cat and Mouse Based Optimizer (CMBO). This hybridization of FCM with the CMBO optimizer aims to address weaknesses inherent in FTS, particularly concerning the determination of interval lengths, with the ultimate goal of enhancing prediction accuracy. Before conducting forecasts, we execute the FCM-CMBO process to determine the optimal centroid used for defining interval lengths within the FTS framework. Our study utilizes a dataset comprising 52,562 data points obtained from the official Kaggle website. Subsequently, we assess forecasting accuracy using the Mean Absolute Percentage Error (MAPE), where a smaller percentage indicates superior performance. Our proposed methodology effectively mitigates the limitations associated with interval length determination and significantly improves forecasting accuracy. Specifically, the MAPE percentage for FTS-FCM before the optimization is 20.180%, while that of FCM-CMBO is notably lower at 18.265%. These results highlight the superior performance of the FCM-CMBO hybrid approach, which achieves a forecasting accuracy of 81.735% compared to actual data.
Bulletin of Applied Mathematics and Mathematics Education, Feb 4, 2023
Dengue Hemorrhagic Fever (DHF) is an infection caused by the Dengue Virus (Windawati et al., 2020... more Dengue Hemorrhagic Fever (DHF) is an infection caused by the Dengue Virus (Windawati et al., 2020). There are two living populations that play a role in the spread of DHF, namely humans and mosquitoes that carry the dengue virus (Sabran & Jannah, 2020). Dengue is a viral disease transmitted by Aedes mosquitoes, namely mosquitoes which annually cause infection of nearly 390 million humans (Iin et al., 2020). There are several types that transmit the dengue virus, including Aedes aegypti and Aedes albopictus (Dania, 2016). DHF has symptoms similar to dengue fever, but DHF has additional symptoms such as pain in the pit of the stomach, bleeding in the nose, mouth, and gums, or bruising on the skin (Ministry of Health, 2017). The spread of DHF can be studied through mathematical modeling. Various mathematical models of DHF have been studied by several researchers, as in (Onyejekwe et al., 2019, Khan & Fatmawati, 2021) Onyejekwe et al by applying optimal control theory. In this study, prevention of DHF was carried out by educating the public and treating it. In this study it is also assumed that
Science and technology Indonesia, Jul 28, 2022
Pattern recognition is a scientific discipline usually used to classify objects into a number of ... more Pattern recognition is a scientific discipline usually used to classify objects into a number of categories or classes through a feature extraction method applied to recognize an object accurately. Meanwhile, Local Binary Pattern (LBP) is a texture analysis method which uses statistical and structural models for feature extraction. Moreover, a Support Vector Machine (SVM) method is normally used to solve non-linear problems in high dimensions to obtain an optimal solution by finding the best hyperplane through the maximizing of the margin between two data classes. Pattern recognition in paintings using machine learning has never been done in any research. Meanwhile it is very important in the future to be able to serve as a verification system for novelty works of art at the stage of filing for intellectual property rights. Therefore, this study aimed to apply pattern recognition with LBP feature extraction method and multiclass SVM classification method to classify the flow of several classes of painting works including expressionism, fauvism, naturalism, realism, and romanticism. The best evaluation results using this method were obtained in the training and testing data combination of 90:10 with an accuracy rate of 83%. Therefore, it can be concluded that machine learning in pattern recognition of painting works can be applied.
Bulletin of Applied Mathematics and Mathematics Education
Dengue hemorrhagic fever (DHF) is an infection caused by the dengue virus which is transmitted by... more Dengue hemorrhagic fever (DHF) is an infection caused by the dengue virus which is transmitted by the Aedes aegypti mosquito. In this paper, a model of the spread of dengue disease is developed using optimal control theory by dividing the population into Susceptible, Exposed, Infected, and Recovered (SEIR) sub-populations. The Pontryagin minimum principle of the fourth-order Runge-Kutta method is used in the model of the spread of dengue disease by incorporating control factors in the form of education and vaccination of susceptible human populations, as well as treatment of infected human populations. Optimum control aims to minimize the infected human population in order to reduce the spread of DHF. Simulations were carried out for two cases, namely when the basic reproduction number is less than one for disease-free conditions and greater than one for endemic conditions. Based on numerical simulations of the SEIR epidemic model with controls, it results that the optimal strate...
Bulletin of Applied Mathematics and Mathematics Education
The Covid-19 pandemic had an impact on the joints of socio-economic life, especially in fulfillin... more The Covid-19 pandemic had an impact on the joints of socio-economic life, especially in fulfilling the basic needs. It also caused the declining of global food security, especially in Indonesia. This study aims to develop regional mapping to determine food security priorities and to achieve equal distribution of food security throughout Indonesia. The research method used in this research is quantitative research with the Elbow method. The Elbow method is used to find the optimal cluster size. The data used are from the Food Security Agency of the Indonesian Ministry of Agriculture and Central Statistics Agency in a range of 2020 to 2021. In the process to identify priority areas in Indonesia, it is necessary to have provincial clustering. It is also necessary to minimize food budget allocations that are not well-targeted, causing losses, and not achieving an equal distribution of food security programs. Looking from a more visionary perspective, the success of clustering provides a...
Jurnal Ilmiah Matematika
Forecasting is an activity to predict what will happen in the future by paying attention to infor... more Forecasting is an activity to predict what will happen in the future by paying attention to information from the past and the present. A regression model that explains the past movement of the variable itself and also all other variables without distinguishing which endogenous and exogenous variables are called Vector Autoregressive (VAR). But in practice, endogenous variables are supported by exogenous variables. The Vector Autoregressive Exogenous (VARX) model is a development of the VAR with the addition of exogenous variables. The purpose of this study is to form the best model in the VAR method with the addition of an exogenous variable in the form of an effect calendar for forecasting the number of tourists coming to the Special Region of Yogyakarta (DIY). The data used in this study are time series data for 10 years from January 2009 to December 2018 in the form of tourist visit data in the Special Region of Yogyakarta (DIY). The results obtained indicate that the effect calendar variable that affects tourist visitor data in DIY is at Christmas. After being analyzed using MAPE, the best model is the VARX (1.0) model which produces a smaller. So, it can be concluded that the VARX model with the addition of an effects calendar is suitable for predicting tourist visits. This is an open access article under the CC-BY-SA license.
IOS Press eBooks, Oct 18, 2022
COVID-19 detection is an interesting field of study in the medical world and the commonly used me... more COVID-19 detection is an interesting field of study in the medical world and the commonly used method is classification. In determining the best detection model, several classification architectures, such as SVM, KNN, and CNN were utilized. The CNN is a changeable architecture due to having combinations of varying numbers of hidden layers or different activation and optimizer functions. Therefore, this study uses a deep CNN architecture with a combination of Leaky ReLU activation functions and 3 different optimizers, which include Adagrad, Adadelta, and Adamax. The results showed that the combination of the Leaky ReLU activation function and the Adamax optimizer produced good and stable accuracy in the CRX and CT datasets.
Pattern Recognition using Multiclass Support Vector Machine Method with Local Binary Pattern as Feature Extraction
Science and Technology Indonesia
Corn is an essential agricultural commodity since it is used in animal feed, biofuel, industrial ... more Corn is an essential agricultural commodity since it is used in animal feed, biofuel, industrial processing, and the manufacture of non-food industrial commodities such as starch, acid, and alcohol. Early detection of diseases and pests of corn aims to reduce the possibility of crop failure and maintain the quality and quantity of crop yields. A decision tree is a nonparametric classification model in statistical machine learning that predicts target variables using tree-structured decisions. The performance of this model can increase significantly if the continuous predictor variables are discretized into valid categories. However, in some cases, the result does not provide satisfactory performance. The possible cause is the ambiguity in discretizing predictor variables. The incorporation of fuzzy membership functions into the model to resolve discretization ambiguity issues. This work aims to classify diseases and pests of corn plants using the decision tree model and improve the ...
INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021
Jurnal Ilmiah Matematika dan Pendidikan Matematika, 2018
Artificial Bee Colony (ABC) algorithm is one of metaheuristic optimization technique based on pop... more Artificial Bee Colony (ABC) algorithm is one of metaheuristic optimization technique based on population. This algorithm mimicking honey bee swarm to find the best food source. ABC algorithm consist of four phases: initialization phase, employed bee phase, onlooker bee phase and scout bee phase. This study modify the onlooker bee phase in selection process to find the neighborhood food source. Not all food sources obtained are randomly sought the neighborhood as in ABC algorithm. Food sources are selected by comparing their objective function values. The food sources that have value lower than average value in that iteration will be chosen by onlooker bee to get the better food source. In this study the modification of this algorithm is called New Modification of Artificial Bee Colony Algorithm (MB-ABC). MB-ABC was applied to 4 Benchmark functions. The results show that MB-ABC algorithm better than ABC algorithm
Chicken Swarm as a Multi Step Algorithm for Global Optimization
A new modified of Chicken Swarm Optimization (CSO) algorithm called multi step CSO is proposed fo... more A new modified of Chicken Swarm Optimization (CSO) algorithm called multi step CSO is proposed for global optimization. This modification is reducing the CSO algorithm’s steps by eliminates the parameter roosters, hens and chicks. Multi step CSO more efficient than CSO algorithm to solve optimization problems. Experiments on seven benchmark problems and a speed reducer design were conducted to compare the performance of Multi Step CSO with CSO algorithms and the other algorithms based population such as Cuckoo Search (CS),Particle Swarm Optimization (PSO), Differential Evolution (DE) and Genetic Algorithm (GA). Simulation results show that Multi step CSO algorithm performs better than those algorithms. Multi step CSO algorithm has the advantages of simple, high robustness, fast convergence, fewer control.
The earthquake is shocks or vibrations in the earth's surface because of shifting layers of r... more The earthquake is shocks or vibrations in the earth's surface because of shifting layers of rock at the base of the earth's surface. This natural phenomenon is common in Indonesia because it lies between Australian, Eurasian, Pacific plates, and it location surrounded by a ring of fire precisely. Therefore, this study aims to cluster earthquake events in Indonesia and describe the characteristics of each group based on clustering results. The method used is the Fuzzy K-Means Clustering. The clustering results obtained from clustering based on the depth, longitude, and latitude. In this study, the data used is the earthquake's data, which has a magnitude greater than or equal to 5 SR and only clumped by depth. Based on the Davies-Bouldin and Dunn index, the best clustering is 2 clusters which researchers cluster earthquake data in Indonesia into deep and shallow clusters.
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Papers by Nursyiva Irsalinda