Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal JRST (Jurnal Riset Sains dan Teknologi) International Journal of Computing Science and Applied Mathematics-IJCSAM
Wika Dianita Utami
Universitas Islam Negeri Sunan Ampel Surabaya
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Mathematics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Prediksi Jumlah Gempa Tektonik di Wilayah Jawa Timur dengan Menggunakan Metode ARIMA Box Jenkins dan Kalman Filter Zufatul Aizzah; Putroue Keumala Intan; Wika Dianita Utami
JRST (Jurnal Riset Sains dan Teknologi) Volume 5 No. 2 September 2021: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (844.131 KB) | DOI: 10.30595/jrst.v5i2.9701

Abstract

Indonesia merupakan negara yang tercangkup dalam wilayah cincin api pasifik aktif (Ring of Fire). Dengan demikian, gempa bumi menjadi fenomena alam yang sudah tidak asing lagi terjadi di Indonesia. Gempa dengan kekuatan magnitudo yang cukup besar akan beresiko merusak sumber daya alam, manusia, dan infastruktur bangunan. Dalam hal ini, sangat perlu dilakukan studi penelitian untuk memprediksi gempa bumi sebagai upaya mitigasi bencana. Metode prediksi yang diterapkan pada studi ini adalah metode ARIMA yang akan diperbaharui dengan estimasi Kalman Filter. Pada perhitungan ARIMA didapatkan model terbaik yaitu ARIMA(0,1,1) dengan perolehan MAPE yang cukup besar yakni 50.5788 sedangkan hasil pembaharuan model ARIMA-KF(0,1,1) memperoleh MAPE yang sangat baik yakni 0.0071. Oleh karena itu, etimasi Kalman Filter dapat dikatakan cukup mumpuni dalam pembaharuan model prediksi ARIMA. Prediksi jumlah gempa tektonik di wilayah Provinsi Jawa Timur pada tahun 2018 paling banyak terjadi pada bulan Juli yakni sebanyak 114 kejadian sedangkan paling sedikit pada bulan Januari yakni 13 kejadian.
Optimal control using pontryagin’s maximum principle: Tuberculosis spread case Muhammad Iqbal Widiaputra; Ahmad Hanif Asyhar; Wika Dianita Utami; Putroue Keumala Intan; Dian Yuliati; Muhammad Fahrur Rozi
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 10 No. 2 (2024)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v10i2.4602

Abstract

Tuberculosis is one of the deadliest infectious diseases in the world. In 2020, 9.9 million people were infected and 1.5 million died. East Java province ranks third with 43,268 tuberculosis cases. This research aims to determine the results of the tuberculosis disease model and simulation without and with the use of optimal control. The mathematical model SEIR is a model that can analyze the spread of the disease tuberculosis. In this research, a variable treatment compartment to the SEIR model. It used 4 antibiotics in the intensive phase and added Isoniazid and Rifampicin in the advanced phase as the optimal control parameters. Optimal control uses Pontriagin’s maximum principle as the derivative to modify the SEIR model and is described by a Runge-Kutta order 4 scheme. It shows both the useful parameters in the optimal control with a maximum value of 1 and plots where the effect of optimal control exists further constrained the people infected with Tuberculosis.
Prediction of Vaccine Inventory in Infants with Holt-Winter's Exponential Smoothing Method (Case Study: East Java Province) Dian Puspita Sari; Aris Fanani; Susilo Ari Wardani; Wika Dianita Utami
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 2 September 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i2.23659

Abstract

Infant vaccination is important in supporting growth and strengthening the immune system. One of the challenges faced is the imbalance between vaccine supply and demand in various regions, which can lead to distribution shortages. This study aims to predict the supply of infant vaccines to reduce distribution gaps using the Holt-Winters Exponential Smoothing method. This method is applied using two approaches: an additive and a multiplicative model based on monthly data from 2021 to 2024. The results show that the multiplicative model is more accurate for the bivalent oral polio vaccine (BOPV), hepatitis B (HBO), and measles-rubella (MR) vaccines because demand exhibits significant fluctuations. The additive model is more accurate for Bacillus Calmette-Guérin (BCG), diphtheria-pertussis-tetanus (DPT), and inactivated poliovirus vaccine (IPV) because demand tends to be stable around a constant average value. The BOPV vaccine yields perfect accuracy (MAPE< 10%) and reasonably good accuracy for the HBO vaccine (MAPE< 20%). The BCG and MR vaccines have low accuracy levels (MAPE< 50%). The DPT and IPV vaccines have bad accuracy levels (MAPE> 50%). Accuracy levels can be influenced by demand fluctuations, uneven distribution, and adjustments to the α, β, and ꝩ parameters. The results of this study indicate that the Holt-Winters Exponential Smoothing method can help predict vaccine supply fluctuations more accurately, thereby supporting more even distribution across all regions.
Co-Authors Ahmad Hanif Asyhar Aris Fanani Dian Puspita Sari Dian Yuliati Muhammad Fahrur Rozi Muhammad Iqbal Widiaputra Putroue Keumala Intan Susilo Ari Wardani Zufatul Aizzah