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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Fourier INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Mathematics, Computation and Statistics (JMATHCOS)

Wika Dianita Utami

Prodi Matematika Jurusan Matematika FMIPA Universitas Brawijaya

Author-ID : 408874

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 15 Documents Claim Missing Document

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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

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

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

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

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

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

Co-Authors Abdulloh Hamid Agustina, Ade Candra Alfirdausy, Roudlotul Jannah Aqilah Khansa, Shafa Fitria Aris Fanani Armunanto, Firman Auditiyah, Cellyn Dwiana, Fadiah Irine Dzaky, Ahmad Naufal Fadilah, Siti Nur Hani Khaulasari Hapsari, Nabilla Windy Inayah, Jauharotul Intan, Putroue M. Imron Nanang Widodo Nanda, Nafa Nur Adifia Nurissaidah Ulinnuha Putroue Keumala Intan Ramadanti, Alvin Nuralif Sari, Dian Candra Rini Novita Sriasih Swindiarto, Victory T. Pambudi Wardani, Susilo Ari Wijaya, Indra Ariyanto Yuliawanti, Felia Dria Yuniar Farida, Yuniar

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