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Sa'adah, Aminatus
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Optimal control design of the COVID-19 model based on Lyapunov function and genetic algorithm Sa'adah, Aminatus; Saragih, Roberd; Handayani, Dewi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5117-5130

Abstract

Millions of people died worldwide as a result of the coronavirus disease 2019 (COVID-19) pandemic that started in early 2020. Examining the COVID-19 susceptible-exposed-infected-recovery (SEIR) mathematical model is one approach to developing the best control scenario for this disease. The study utilized two control variables, vaccination, and therapy, to construct a control function that relied on the quadratic Lyapunov function. The control objective was to lower the number of COVID-19 infections while maintaining system stability. A genetic algorithm (GA) is used as a novel method to estimate controller parameter value to replace the previously used parameter tuning procedure. Then, a numerical simulation was carried out implementing three control scenarios, namely vaccination control only, treatment control only, and vaccination and treatment control simultaneously. Based on the results, scenario 3 (vaccination and treatment simultaneously) showed the most significant decrease: the average decrease in the exposed human population was 98.29%, and the infected human population was 98.18%.
The Effect of Virotherapy, Chemotherapy, and Immunotherapy to Immune System: Mathematical Modelling Approach Sa'adah, Aminatus; Prihantini, Prihantini; Masulah, Bidayatul
KUBIK Vol 8, No 2 (2023): 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.v8i2.29521

Abstract

Medical research and therapeutic interventions continue to evolve, and one interesting area of study is the complex interaction among virotherapy, chemotherapy, and the immune system. Each treatment has its own advantages and disadvantages. In this study, a mathematical model was developed to describe how the immune system, tumor cells, and normal cells interact when all three types of therapy are used to treat cancer patients. To determine the effectiveness of various treatments, numerical simulations of eight different treatment strategies were performed. These simulations measured how much the concentration of immune cells, tumor cells, and normal cells decreased as a result of the treatment. Based on the numerical simulations performed, the application of the three types of therapy provided the greatest reduction (99%) in the concentration of tumour cells but also provided a significant reduction (68%) in the concentration of immune cells in the body.
Perbandingan Fuzzy Time Series Chen dan Cheng untuk Peramalan Harga Beras di Kabupaten Banyumas Sari, Dian Kartika; Sa'adah, Aminatus
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28012

Abstract

Indonesia is mostly an agricultural country. Most people here make a living from farming. Rice is a major crop in Indonesia. The price of rice is very important to the economy, especially in farming areas like Banyumas. Fluctuating rice prices can affect the economic lives of both farmers and consumers in the region. The rapid fluctuation in rice prices and the uncertainty of future prices demand the need for rice price forecasting. This study uses fuzzy time series to forecast rice prices. The prediction models used are the Chen model and the Cheng model. To calculate the accuracy of the models, MAPE calculations are employed. Based on the results, the MAPE value for the Chen model is 0.957539%, and for the Cheng model, it is 0.477921%. The results indicate that the accuracy of the Cheng model is higher than that of the Chen model, meaning that the Cheng model is better suited for forecasting rice prices in Banyumas Regency.
Penerapan Digitalisasi Dan Teknologi Branding Untuk Meningkatkan Potensi Wisata Dan Daya Saing UMKM Sa'adah, Aminatus; Permadi, Dimas Fanny Hebrasianto; Zen, Bita Parga
Dedikasi Sains dan Teknologi (DST) Vol. 4 No. 2 (2024): Artikel Riset Nopember 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dst.v4i2.4070

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peranan penting dalam pembangunan dan pertumbuhan ekonomi di Indonesia. Indonesia memiliki jumlah pengguna media sosial lebih dari 80 juta pengguna yang memunculkan behavior bertransaksi online dalam aspek kehidupan sehari-hari. UMKM perlu melakukan adaptasi terkait tantangan tersebut guna meningkatkan penjualan. Kegiatan PKM ini telah dilaksanakan dengan mengadakan seminar dan pelatihan bagi pelaku UMKM. Terdapat tiga materi inti yang disampaikan yaitu optimalisasi penggunaan whatsapp dan instagram dan foto produk menggunakan smartphone untuk mendukung marketing. Para pengelola wisata juga dibekali dengan pembuatan website wisata serta pengelolaannya dalam mendukung operasional dan promosi wisata. Dari seluruh rangkaian kegiatan pengabdian yang telah dilakukan, peserta mendapatkan manfaat secara spesifik dalam hal paid ads dan pengambilan foto produk menggunakan smartphone. Selain itu, website wisata yang telah dibuat juga meningkatkan dan memperluas promosi wisata desa.
OPTIMAL BLOOD GLUCOSE CONTROL IN TYPE 1 DIABETIC PATIENTS BY USING PONTRYAGIN’S MINIMUM PRINCIPLE AND EXTENDED KALMAN FILTER Sa'adah, Aminatus; Paramadini, Adanti Wido
Jurnal Matematika UNAND Vol. 14 No. 2 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.2.117-128.2025

Abstract

Artificial Pancreas (AP) is an advanced diabetes management technology. AP requires an automatic control algorithm to determine the level of insulin injection based on the glucose level calculated on the Continuous Glucose Monitoring (CGM) sensor. Bergman Minimal Model (BMM) is a basic model in describing the dynamics of glucose-insulin in the human body. This study aims to determine the optimal control using Pontryagin’s Minimum Principle (PMP), which is subject to reducing glucose levels in type 1 diabetes patients to be within the normal glucose level interval of 80-120 mg/dL. The BMM parameter values will be estimated using EKF to support the acquisition of precise and personal numerical simulations. Based on the control de sign simulation that has been obtained, the optimal control of insulin injection is given maximally (25 mU/L) during the first two hours of observation; then, the level decreases slowly until it reaches 0 at 12 hours of observation. This scenario successfully reduces the patient’s glucose levels at the end of the observation period from 170.4 mg/dL (with out control) to 121.2 mg/dL. This result providing a confident basis for initial future research and development in diabetes management.
Peningkatan Gaya Hidup Sehat Anak melalui Edukasi Pencegahan Diabetes Berbasis Multimedia Interaktif di Purbalingga Paramadini, Adanti Wido; Aldo, Dasril; Nur, Yohani Setiya Rafika; Firmansyah, Muhammad Raafi'u; Sa'adah, Aminatus; Fathan, Faizal Burhani Ulil; Sulaeman, Gilang; Faiz, M. Hanif Al; Hidayat, Afifah Naurah; Maulana, Ihsan; Fau, Andrew; Yasin, Feri; Suprapto, Amelia Rut; Muadin, Dika Alim
Jurnal Pengabdian Masyarakat: Pemberdayaan, Inovasi dan Perubahan Vol 5, No 4 (2025): JPM: Pemberdayaan, Inovasi dan Perubahan
Publisher : Penerbit Widina, Widina Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59818/jpm.v5i4.1685

Abstract

The incidence of type 2 diabetes mellitus among children is rising due to poor dietary habits and lack of physical activity from an early age. Health education remains suboptimal, especially in areas with limited access to health information. This community service activity aimed to raise awareness and understanding among elementary school children and their parents regarding early diabetes prevention through multimedia-based educational technology. The method used included interactive counseling, sugar content demonstrations in food, introduction of the Diabetes Detective educational app, and blood glucose screening using a digital glucometer. The activity took place in Muntang Village, Purbalingga, involving 30 children and 25 parents. Results showed an increase in children’s understanding from 49.5% (pre-test) to 85.5% (post-test), while 92% of parents stated the media was easy for children to understand. Children’s average blood glucose level was normal (92.5 mg/dL), while four parents were in the prediabetic range. The activity demonstrates that an interactive, contextual educational approach can enhance health literacy and promote healthy habits in families. This model can be replicated as a preventive strategy using digital technology in other regions.ABSTRAKKasus diabetes mellitus tipe 2 pada anak-anak meningkat seiring pola makan buruk dan kurangnya aktivitas fisik sejak dini. Edukasi mengenai gaya hidup sehat masih belum optimal, terutama di daerah dengan akses informasi kesehatan terbatas. Kegiatan pengabdian ini bertujuan meningkatkan kesadaran dan pemahaman anak-anak sekolah dasar serta orang tua mengenai pencegahan dini diabetes melalui media edukasi berbasis teknologi multimedia. Metode yang digunakan adalah penyuluhan interaktif, demonstrasi kandungan gula pada makanan, pengenalan aplikasi edukatif Diabetes Detective, dan pemeriksaan gula darah menggunakan glukometer digital. Kegiatan dilaksanakan di Desa Muntang, Purbalingga, dengan melibatkan 30 anak dan 25 orang tua. Hasil menunjukkan peningkatan pemahaman anak dari rata-rata 49,5% (pre-test) menjadi 85,5% (post-test), dan 92% orang tua menyatakan media mudah dipahami. Rata-rata kadar gula darah anak normal (92,5 mg/dL), sedangkan empat orang tua berada pada kategori prediabetes. Kegiatan ini membuktikan bahwa pendekatan edukatif yang interaktif dan kontekstual dapat meningkatkan literasi kesehatan anak dan keluarga serta dapat direplikasi sebagai strategi preventif berbasis teknologi di wilayah lain.
MATHEMATICAL MODELS OF DENGUE TRANSMISSION DYNAMICS WITH VACCINATION AND WOLBACHIA PARAMETERS AND SEASONAL ASPECTS Sa'adah, Aminatus; Sari, Dian Kartika
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2305-2316

Abstract

The Aedes aegypti mosquito is the main carrier of dengue virus transmission to humans. In this study, a mathematical model for the transmission of the dengue virus is constructed using vaccination and Wolbachia parameters in an attempt to control the virus's spread. Furthermore, the fundamental reproduction number is set as a parameter of the infection threshold. Based on the stability of the equilibrium point analysis, it is found that the disease-free equilibrium point is locally asymptotically stable if . Then, a mathematical model of dengue was created by examining the seasonal aspect and adding a periodic term to the mosquito birth rate. Dengue virus transmission in mosquito populations is controlled by air temperature in addition to seasonal variables. In this study, three weather scenarios were simulated: scenario 1 for cold weather (air temperature 14 °C), scenario 2 for hot weather (air temperature 26 °C), and scenario 3 for moderate weather (air temperature between 14 and 26 °C).
FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN Sari, Dian Kartika; Sa'adah, Aminatus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp503-510

Abstract

Indonesia is one of those countries where a majority of its population earns a living through agriculture. One of Indonesia's largest commodities is rice. Rice prices are a significant indicator in the economy, especially in agrarian areas like Banyumas Regency. Fluctuating rice prices can impact the economic livelihoods of both farmers and consumers in the region. The rapid fluctuations in rice prices and the uncertainty in the future necessitate the need for rice price forecasting. This study employs fuzzy time series to forecast rice prices. The fuzzy time series model used is the Chen model, and the accuracy of the predictions will be evaluated using the MAPE value. Based on the forecasting results using the fuzzy time series method with the Chen model, the predicted rice price for May 2024 is Rp 14,082. Furthermore, the accuracy level of the rice price forecasting using the fuzzy time series method with the Chen model shows highly accurate predictions, with an error based on the MAPE value of 0.957539%. The limitations of this study lie in the use of limited historical data and the assumption that price patterns will follow similar trends in the future. The contribution of this study is the application of the fuzzy time series method to rice commodities in Indonesia, which demonstrates high accuracy in conditions of high price fluctuation, thus providing valuable insights for policymakers and market participants in economic planning within the agricultural sector.
COMPARISON OF THE VOLATILITY OF GARCH FAMILY MODEL IN THE CRYPTOCURRENCY MARKET: SYMMETRY VERSUS ASYMMETRY Pasaribu, Asysta Amalia; Sa'adah, Aminatus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2571-2582

Abstract

Cryptocurrencies can be considered an individual asset class due to their distinct risk/return characteristics and low correlation with other asset classes. Volatility is an important measure in financial markets, risk management, and making investment decisions. Different volatility models are beneficial tools to use for various volatility models. The purpose of this study is to compare the accuracy of various volatility models, including GARCH, EGARCH, and GJR-GARCH. This study applies these volatility models to the Bitcoin, Ethereum, and Litecoin return data in the period January 1st, 2020, to December 31st, 2024. The performance of these models is based on the smallest AIC value for each model. The results of the study indicate that the GARCH (1,1) is the most suitable model for Bitcoin, Litecoin, and Ethereum returns.
Perbandingan Algoritma Support Vector Machine Dan Algoritma Random Forest Dalam Prediksi Hipertensi Zefanya Yuni Br, Syaloom; Aldo, Dasril; Sa'adah, Aminatus
eProceedings of Engineering Vol. 12 No. 4 (2025): Agustus 2025
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hipertensi merupakan salah satu penyakit tidakmenular yang berpotensi menimbulkan komplikasi serius danmenunjukkan tren peningkatan prevalensi baik secara globalmaupun nasional. Deteksi dini terhadap kondisi ini sangatpenting guna mencegah dampak kesehatan yang berbahaya.Penelitian ini bertujuan untuk membandingkan kinerja duaalgoritma machine learning, yaitu Support Vector Machine(SVM) dan Random Forest (RF), dalam memprediksi hipertensimenggunakan data rekam medis dari Puskesmas PurwokertoTimur I. Karena data hipertensi biasanya memiliki distribusikelas yang tidak seimbang, penelitian ini menerapkan teknikOversampling untuk menyeimbangkan data. Tahapanpenelitian mencakup preprocessing data, pembangunan modelmenggunakan algoritma SVM dan RF, serta evaluasi modeldengan metrik akurasi, presisi, recall, dan F1-score. Hasilpengujian menunjukkan bahwa algoritma RF memberikanhasil terbaik dengan akurasi mencapai 98,92%, sementaraSVM menghasilkan akurasi tertinggi sebesar 83,91%.Berdasarkan temuan tersebut, dapat disimpulkan bahwaalgoritma RF lebih efektif dalam melakukan prediksi hipertensipada data yang tidak seimbang, dan penerapan teknikOversampling secara signifikan dapat meningkatkan performamodel. Penelitian ini diharapkan dapat berkontribusi dalampengembangan sistem prediksi hipertensi yang lebih akuratuntuk mendukung upaya pencegahan dan pengelolaankesehatan masyarakat.Kata kunci—hipertensi, Prediksi, Oversampling, RandomForest, Support Vector Machine
Co-Authors Adanti Wido Paramadini Bita Parga Zen Dasril Aldo Dewi Handayani Dian Kartika Sari, Dian Kartika Dimas Fanny Hebrasianto Permadi Faiz, M. Hanif Al Fathan, Faizal Burhani Ulil Fau, Andrew Firmansyah, Muhammad Raafi'u Hidayat, Afifah Naurah Masulah, Bidayatul Maulana, Ihsan Muadin, Dika Alim Pasaribu, Asysta Amalia Prihantini Prihantini Sasmito, Ayomi Sulaeman, Gilang Suprapto, Amelia Rut Yasin, Feri Yohani Setiya Rafika Nur Zefanya Yuni Br, Syaloom