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COMPARISON OF FORECASTING VIOLENCE CASES NUMBER AGAINST WOMEN AND CHILDREN USING DOUBLE EXPONENTIAL SMOOTHING (DES) AND AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHODS Fadilah, Siti Nur; Intan, Putroue Keumala; Utami, Wika Dianita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.186 KB) | DOI: 10.30598/barekengvol16iss2pp443-450

Abstract

Violence is something that is being widely discussed. It is due to the increasing number of victims of violence in a scope where victims should feel safe. Therefore, the researchers took this case intending to predict the number of violence cases against women and children in Jakarta so that the government can anticipate the spike in cases and evaluate the policies that will be issued in this case. The data used was from the Office for the Empowerment of Child Protection and Population Control (DPPAPP) of DKI Jakarta Province from January 2018 to October 2021 to predict the number of cases in 2022. Based on the analysis results, it is known that the number of cases of violence against women and children has decreased throughout 2022. In addition, the accuracy of the model using the Double Exponential Smoothing (DES) method is 44.91%, and the Auto-Regressive Integrated Moving Average (ARIMA) is 39.03%.
OPTIMIZATION OF TUG SERVICES IN TANJUNG PERAK PORT USING ASSIGNMENT MODEL BASED ON FORECASTING RESULTS OF TUG SERVICES Ramadanti, Alvin Nuralif; Novitasari, Dian C. Rini; Wijaya, Indra Ariyanto; Swindiarto, Victory T. Pambudi; Utami, Wika Dianita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (827.772 KB) | DOI: 10.30598/barekengvol16iss1pp261-268

Abstract

Optimizing adequate tugboat services is very much needed to support the operational improvement of the Tanjung Perak port. This study uses the triple exponential smoothing method to predict the number of tug service requests in 2021 and the assignment model to determine the optimal level of operating tugboats. The data used in this study is data on demand for tugboat services for small, medium, and large vessels from 2019 to 2020. Forecasting results show that the highest demand for small boat services is 4551 and 3235. The highest demand for medium vessel services is 479 and the lowest is 365. Meanwhile, for the highest demand for large ship services 61 and the lowest 40. The assignment results show the optimization of Tanjung Perak port by operating 13 tugboats every day.
ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI) Imron, M.; Utami, Wika Dianita; Khaulasari, Hani; Armunanto, Firman
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.349 KB) | DOI: 10.30598/barekengvol16iss4pp1259-1270

Abstract

The Consumer Price Index (CPI) is a indicator used by Badan Pusat Statistik (BPS) which describes the average change in the prices paid by urban consumers for a market basket of consumer goods and services in a certain period. The case on Consumer Price Index (CPI) of Probolinggo City, if the Consumer Price Index (CPI) increase then describe inflation occurs and conversely. The Consumer Price Index (CPI) of Probolinggo City increase is not fixed. This study is to forecast the Consumer Price Index (CPI) that the results can be used as one of the considerations in carrying out economic development in the future. Research focused on the data of Consumer Price Index (CPI) of Probolinggo City from January 2014 to April 2022. Methodology implemented in this study is Autoregressive Integrated Moving Average (ARIMA). Result show that ARIMA without an outlier was the best model for predicting Consumer Price Index (CPI) of Probolinggo City for the next 8 months. This model shows the value of MAPE is . The value of forecasting results in each month has decreased and increased not so significantly where in May 2022 the forecasting value was 108,391 then in June 2022 the forecasting value became 108,411 and so on until December 2022 the forecasting results using ARIMA model of 107,845.
OPTIMAL CONTROL ANALYSIS OF HIV/AIDS DISEASE SPREAD MODEL IN INDONESIA Utami, Wika Dianita; Dzaky, Ahmad Naufal; Fanani, Aris
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0707-0716

Abstract

The Human Immunodeficiency Virus (HIV) is a contagious virus that weakens the immune system of infected individuals, making them more susceptible to various diseases. These individuals are referred to as those exposed to the AIDS disease, which unfortunately, cannot be cured. To effectively manage AIDS, prevention is crucial in slowing down the spread and growth of the HIV virus. Mathematical modeling can play a significant role in the optimal control of AIDS. In this study, the , , , , model with three different optimal controls were employed. Optimal control involves public health education campaigns, screening, and treatment. The goal is to minimize the number of individuals infected with HIV/AIDS using Pontryagin's Maximum Principle. This principle considers various factors, such as population class coefficients, cost weights, and control variables to determine the most effective approach. The simulation results indicate that counseling control in the exposed population class ( ) yields better outcomes compared to counseling control in the susceptible class and treatment control in the HIV-infected population class. This implies that focusing on educating and counseling individuals who are exposed to HIV can be more efficient in AIDS control than targeting those already infected or at risk. By applying these optimal control strategies, it may be possible to mitigate the impact of HIV/AIDS and improve public health outcomes.
Implementation of The Extreme Gradient Boosting Algorithm with Hyperparameter Tuning in Celiac Disease Classification Alfirdausy, Roudlotul Jannah; Ulinnuha, Nurissaidah; Utami, Wika Dianita
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4031

Abstract

Celiac Disease (CeD) is an autoimmune disorder triggered by gluten consumption and involves the immune system and HLA in the intestine. The global incidence ranges from 0.5%-1%, with only 30% correctly diagnosed. Diagnosis remains challenging, requiring complex tests like blood tests, small bowel biopsy, and elimination of gluten from the diet. Therefore, a faster and more efficient alternative is needed. Extreme Gradient Boosting (XGBoost), an ensemble machine learning technique that utilizes decision trees to aid in the classification of Celiac disease, was used. The aim of this study was to classify patients into six classes, namely potential, atypical, silent, typical, latent and none disease, based on attributes such as blood test results, clinical symptoms and medical history. This research method employs 5-fold cross-validation to optimize parameters that are max depth, n estimator, gamma, and learning rate. Experiments were conducted 96 times to get the best combination of parameters. The results of this research are highlighted by an improvement of 0.45% above the accuracy value with the default XGBoost parameter of 98.19%. The best model was obtained in the trial with parameters max depth of 3, n estimator of 100, gamma of 0, and learning rate of 0.3 and 0.5 after modifying the parameters, yielding an accuracy rate of 98.64%, a sensitivity rate of 98.43%, and a specificity rate of 99.72%. This research shows that tuning the XGBoost parameters for Celiac
Pengandalian Efek Moving Holiday dengan RegARIMA dalam Proses Peramalan Nilai Tukar Rupiah Terhadap US Dollar Tussholikhah, Anissa Nurul Farida; Ulinnuha, Nurissaidah; Utami, Wika Dianita; Intan, Putroue Keumala
Jurnal Matematika Integratif Vol 20, No 1: April 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n1.54416.63-80

Abstract

Naik turunnya nilai tukar rupiah merupakan salah satu elemen yang mempengaruhi keadaan ekonomi atau tingkat inflasi suatu negara. Fluktuasi nilai tukar mata uang juga dapat dipengaruhi oleh beberapa hari besar nasional, seperti Hari Raya Idul Fitri, yang memiliki periode yang tidak dapat diprediksi setiap tahunnya. Sehingga perlu dilakukan penelitian ini untuk mengetahui prediksi nilai tukar mata uang dengan mempertimbangkan efek moving holiday dan hasil akan dibandingkan dengan metode prediksi tanpa mempertimbangkan efek moving holiday. Dari banyaknya proses prediksi yang dapat dilakukan, penelitian ini menggunakan metode RegARIMA yang merupakan salah satu perkembangan dari ARIMA dengan pengendalian efek moving holiday. Perbandingan hasil diperoleh dari evaluasi ARIMA dengan RegARIMA, untuk mengetahui sebaik apa model menangani efek moving holiday. Berdasarkan nilai MAPE yang diperoleh, model RegARIMA lebih unggul dari ARIMA. MAPE dari RegARIMA bernilai lebih kecil, yakni sebesar 1.82% dibandingkan ARIMA yang memperoleh MAPE sebesar 2.43%. Sehingga model RegARIMA berhasil dalam menangani efek moving holiday dalam proses prediksi.
Cluster Analysis of Environmental Pollution in Indonesia Using Complete Linkage Method with Elbow Optimization Damayanti, Adelia; Utami, Wika Dianita; Novitasari, Dian Candra Rini; Intan, Putroue Keumala; Kurniawan, Mohammad Lail
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 2 (2023): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i2.12961

Abstract

The issue of environmental contamination remains unsolved. The problem continues to have a substantial detrimental impact. This research aimed to identify provinces in Indonesia with high or low levels of environmental pollution so that the government may offer treatment to provinces with high levels of pollution and seek a significant reduction in the incidence of environmental pollution in Indonesia. Clustering is required to identify provinces with high and low pollution levels using the complete linkage method because this method can provide tight clusters and is less impacted by outliers. The analysis of the complete linkage method with Elbow optimization revealed two optimal clusters, namely high and low clusters. The high cluster consists of three provinces: Central Java, West Java, and East Java. The low cluster consists of 31 provinces. This research used a Silhouette Coefficient validity test. The value of the Silhouette Coefficient is 0.75. The value indicates that the data object is in the correct cluster and that the cluster structure is relatively strong.
Breast Cancer Survival Analysis Using Cox Proportional Hazard Regression and Kaplan Meier Method Farida, Yuniar; Maulida, Eka Agustina; Desinaini, Latifatun Nadya; Utami, Wika Dianita; Yuliati, Dian
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 5, No 2 (2021): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v5i2.4653

Abstract

Breast cancer is one of the malignant tumors that begins in the breast cells that develop and attack the surrounding tissues; according to World Health Organization (WHO), breast cancer is globally declared the top five killer cancers. In Indonesia, breast cancer becomes the number one killer cancer.  One of the successes in breast cancer treatment is if the cure obtained by cancer patients can be proven to have the same life expectancy as those who do not have breast cancer.This study aims to know the probability of survival of breast cancer patients and know the factors that affect breast cancer patients' survival. The data were consist of 394 medical records of breast cancer patients at Dr. Soetomo Hospital Surabaya in the period January 2018 – December 2019, with variables used, i.e., initial age of infection, clinical stage, tumor size, metastatic to other organs, type of treatment, and patient status (life or death). This study using Kaplan Meier and Cox Proportional Hazard regression methods, and the result showed that the probability of survival of breast cancer patients (with data samples) was 0.737 or 73.7%. The variables that significantly affect breast cancer patients' survival are the initial age of infection, the clinic stage, and the tumor's size. This research provides information and motivation to the community related to life expectancy, especially in breast cancer patients, to stay motivated in the healing process. In addition, this research is also used to add insight to academics, especially the department of statistics, regarding the regression of Cox Proportional Hazard in analyzing the survival of breast cancer patients.