Article Per Year (5 Year)
p-Index From 2021 - 2026
5.109
P-Index
This Author published in this journals
All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) JURNAL SILOGISME : Kajian Ilmu Matematika dan Pembelajarannya InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Riset Mahasiswa Matematika Journal of Research on Community Engagement
Evawati Alisah
Jurusan Matematika Fakultas Sains Dan Teknologi Universitas Islam Negeri Maulana Malik Ibrahim Malang
Arts Humanities Computer Science & IT Mathematics Social Sciences

Published : 43 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 43 Documents
Search

 1   2   3   4   5 
Optimal Control of a Modified Mathematical Model of Social Media Addiction Juhari, Juhari; Alisah, Evawati; Safitri, Alisa Ayu; Sujarwo, Imam
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol. 6 No. 2 (2024)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/inprime.v6i2.41438

Abstract

This research investigates the application of optimal control in the Susceptible, Exposed, Addicted, Recovery, Quit (SEA_1 A_2 RQ) model to address social media addiction. The primary objective is to develop an effective control strategy to reduce the prevalence of social media addiction. The methodology employs Pontryagin's maximum principle to formulate the optimal control problem, incorporating two time-dependent control variables: control (u_1) and treatment (u_2). The optimal control model is numerically simulated using the 4th-order Runge-Kutta method. Comparative analysis of the simulation results, with and without control, demonstrates significant differences in all population groups after four years. The findings reveal that implementing control (u_1) and treatment (u_2) markedly decreases the number of individuals addicted to social media, highlighting the efficacy of the proposed strategy in mitigating social media addiction.Keywords: optimal control; social media addiction model; Pontryagin maximum principle. AbstrakPenelitian ini mengkaji penerapan kontrol optimal pada model Susceptible, Exposed, Addicted, Recovery, model Quit (SEA_1 A_2 RQ)  untuk menangani kecanduan sosial media. Tujuan utama penelitian ini adalah untuk mengembangkan strategi kontrol yang efektif untuk mengurangi jumlah individu yang mengalami kecanduan media sosial. Metodologi penelitian ini menggunakan prinsip maksimum Pontryagin untuk merumuskan masalah kontrol optimal, yang menggabungkan dua variabel kontrol bergantung pada waktu: pengendalian (u_1) dan pengobatan (u_2). Model kontrol optimal disimulasikan secara numerik menggunakan metode Runge-Kutta orde 4. Analisis komparatif dari hasil simulasi, dengan dan tanpa kontrol, menunjukkan perbedaan yang signifikan pada semua kelompok populasi setelah empat tahun. Temuan tersebut mengungkapkan bahwa penerapan pengendalian (u_1) dan pengobatan (u_2) secara signifikan mengurangi populasi pengguna kecanduan sosial media, yang menyoroti kemanjuran strategi yang diusulkan untuk mengurangi kecanduan sosial media.Kata Kunci: kontrol optimal; model kecanduan media sosial; prinsip maksimum Pontryagin. 2020MSC: 49N90, 91D10, 92B05.
Perbandingan Uji Akurasi Fuzzy Time Series Model Cheng Dan Lee Dalam Memprediksi Perkembangan Harga Cabai Rawit Dewi Ismiarti; Jami'atu Sholichati Nafisah; Evawati Alisah; Imam Sujarwo
Jurnal Riset Mahasiswa Matematika Vol 2, No 4 (2023): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v2i4.16808

Abstract

Fuzzy Time Series is a method used to predict data. Fuzzy Time Series is a development of time series analysis, where Fuzzy Time Series uses the concept of fuzzy sets as the basis for its calculations. In addition, Fuzzy Time Series has various methods such as Cheng and Lee Fuzzy Time Series. In this study, Fuzzy Time Series is used to predict data on the price development of cayenne pepper in Indonesia. By using these two methods, an analysis of the level of accuracy is then carried out using several methods. So that the results obtained in this study are the MAE value of the Cheng method 669,162 and the Lee method 502,285, the MSE value of the Cheng method 1.261.393 and the Lee method 699.030.1, the MPE value of the Cheng method 0,01% and the Lee method -0,02%, and The MAPE value of the Cheng method is 1,24% and the Lee method is 0.92%. The Lee method has a smaller error value than the Cheng method, so that the Lee method is declared to be better than the Cheng method.
Perbandingan Akurasi Fuzzy Time Series Chen Berbasis FCM dan Fuzzy Time Series Lee pada Peramalan Harga Batu Bara Juliani Juliani; Evawati Alisah; Abdussakir Abdussakir
Jurnal Riset Mahasiswa Matematika Vol 5, No 1 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v5i1.33349

Abstract

Fuzzy time series is a forecasting method that handles data uncertainty by applying fuzzy set theory. This study compares the forecasting accuracy of the Chen fuzzy time series method, modified using Fuzzy C-Means (FCM), and the Lee method in predicting Indonesian coal prices from January 2019 to December 2023. The Chen method is en hanced by generating fuzzy intervals through FCM to better reflect data distribution, while the Lee method uses weighted fuzzy logical relationships. Forecast accuracy is measured using Mean Absolute Percentage Error (MAPE). The modified Chen method achieves a MAPE of 2.56% compared to 5.07% for the Lee method. These results show that cluster ing techniques like FCM can improve fuzzy time series forecasting. This contrasts with earlier studies that favored the Lee method and highlights the potential of adaptive interval construction for volatile commodity prices. The proposed modification offers a promising alternative for improving prediction accuracy in economic time series.
Co-Authors Abdul Aziz Abdul Aziz Abdussakir Abdussakir Abdussakir Abdussakir Achmad Nasichuddin Ahmed Syarief Marzuki Ainindita Aghniacakti Ainur Isa, Rafi Aji Sailendra, Alfi Istijap Al-adawiyah, Syavira Habib Alfi Istijap Aji Sailendra Allifia Nur Chasamah Aminahtuz Zahro Anthasyah, Indah Ayu Zurike Arfiana, Nur Misbahul Aufia, Zulfatul Bella Nafa Savitri Chasamah, Allifia Nur Dewi Ismiarti Elva Ravita Sari Fachrur Rozi Fauzan, Hakmi Rais Fikrina, Zulfa Akfi Hakmi Rais Fauzan Heni Widayani Hisyam Fahmi Imam Sujarwo Ismiarti, Dewi Izdhihar, Fairuz Nadhif Jamhuri, Muhammad Jami'atu Sholichati Nafisah Juhari - Juhari Juhari Juhari Juhari, Juhari Juliani Juliani Karinina, Olivia Lailatul Maziyah Wildan Mufaridho Marzuki, Ahmed Syarief Miskaram, Muh Syarifuddin Syafiqy Moh. Miftakhul Ulum Mohammad Jamhuri Mohammad Nafie Jauhari Muhammad Jamhuri Muhammad Khudzaifah Muzafanti, Rahmah Navi'ah Nasichuddin, Achmad Nur Misbahul Arfiana Pamungkas, Syahrul Aziz Reta, Tre Hayu Ria Ria Dhea Layla Nur Karisma Rika Dina Amalia, Dina Amalia Risna Zulfa Musriroh Sa'adah, Maria Syifaus Sa'adati, Hawzah Safitri, Alisa Ayu Savitri, Bella Nafa Sawitri Sawitri Sholehurrohman, Ridho Syavira Habib Al-adawiyah Tre Hayu Ria Reta Turmudi Turmudi, Turmudi Zulfatul Aufia