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All Journal International Journal of Science and Engineering (IJSE) Waste Technology Journal of Engineering and Technological Sciences Proceeding of the Electrical Engineering Computer Science and Informatics International Journal of Supply Chain Management M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika PRISMATIKA: Jurnal Pendidikan dan Riset Matematika Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sains dan Edukasi Sains Journal of Applied Data Sciences Journal of Fundamental Mathematics and Applications (JFMA) International Journal of Computing Science and Applied Mathematics-IJCSAM
Widowati, Widowati
Department Of Mathematics, Faculty Of Sciences And Mathematics, Diponegoro University, Semarang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Physics Transportation Other

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MODELING PREDICTIVE TRACKING CONTROL FOR MAX-PLUS LINEAR SYSTEMS IN MANUFACTURING Lathifatul Aulia; Widowati Widowati; R. Heru Tjahjana; Sutrisno Sutrisno
Journal of Fundamental Mathematics and Applications (JFMA) Vol 3, No 2 (2020)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (491.691 KB) | DOI: 10.14710/jfma.v3i2.8605

Abstract

Discrete event systems, also known as DES, are class of system that can be applied to systems having an event that occurred instantaneously and may change the state. It can also be said that a discrete event system occurs under certain conditions for a certain period because of the network that describes the process flow or sequence of events. Discrete event systems belong to class of nonlinear systems in classical algebra. Based on this situation, it is necessary to do some treatments, one of which is linearization process. In the other hand, a Max-Plus Linear system is known as a system that produces linear models. This system is a development of a discrete event system that contains synchronization when it is modeled in Max-Plus Algebra. This paper discusses the production system model in manufacturing industries where the model pays the attention into the process flow or sequence of events at each time step. In particular, Model Predictive Control (MPC) is a popular control design method used in many fields including manufacturing systems. MPC for Max-Plus-Linear Systems is used here as the approach that can be used to model the optimal input and output sequences of discrete event systems. The main advantage of MPC is its ability to provide certain constraints on the input and output control signals. While deciding the optimal control value, a cost criterion is minimized by determining the optimal time in the production system that modeled as a Max-Plus Linear (MPL) system. A numerical experiment is performed in the end of this paper for tracking control purposes of a production system. The results were good that is the controlled system showed a good performance.
Service quality model analysis on the acceptance of information system users’ behavior Rina Fiati; Widowati Widowati; Dinar Mutiara Kusumo Nugraheni
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp444-450

Abstract

Website technology have created both opportunities and challenges for higher education. Information systems as online learning medium need to pay attention to access, quality and user needs in order to improve the quality of e-learning services. The research objective is to determine user acceptance of the system. The service quality method as identification in solving problems. The research focus on the analysis of five dimensions namely measurable, reliability, responsiveness, assurance and empathy. The research was conducted at the research college at Muria Kudus University. The results state that the assessment model of a system on the website can be completed properly. The level of effectiveness is carried out with respondents as users through the distribution of questionnaires. The results of the analysis with a statistical correlation performance test of 0.985 were declared accepted with a validity level of 97% indicating that the success of the system implemented was from the acceptance side. The higher the empathy with service quality and performance expectations, the greater the student's intention to receive online education services. This research is a reference for developing information systems on e-learning.
Local Stability Analysis of Mathematic Model SEIHR-VW on Dengue Haemorrhagic Fever Transmission Nolaika Arsiani Norramandhany; Widowati Widowati; Redemtus Heru Tjahjana
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 11 No. 2 (2025)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v11i2.6054

Abstract

Dengue fever is caused by the dengue virus (DENV) and is mainly transmitted by mosquitoes, particularly Aedes aegypti. In this study, we develop a mathematical model to describe and analyze how dengue spreads within a population. The mathematical model is expressed as a nonlinear system of differential equations and consists of seven compartments (SEIHRVW): susceptible, exposed, infected, hospitalized, and recovered humans, along with susceptible and infected mosquitoes. The model has two possible equilibrium points: a non-endemic and endemic equilibrium point. To better understand the dynamics of the model, we calculate the basic reproduction number (R0) using the Next Generation Matrix (NGM) method, and then the Routh-Hurwitz criterion method is applied to analyze the local stability of both equilibrium points. The results indicate that the nonendemic equilibrium point is asymptotically stable when R0 < 1, while the endemic equilibrium point becomes asymptotically stable when R0 > 1. In general, our analysis concludes that the proposed dengue transmission model is asymptotically stable at the endemic equilibrium point, with R0 = 3.85011.
Hybrid Machine Learning for Early Prediction of At-Risk Students with Imbalanced Data Esti Wijayanti; Widowati Widowati; Catur Edi Widodo
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1368

Abstract

The phenomenon of student dropout remains a major challenge for higher education institutions because it impacts academic performance and institutional reputation. Identification of students at risk of dropping out is often hampered by data imbalance, where the number of dropouts is far fewer than active students, so conventional prediction models tend to be biased towards the majority class. This study aims to develop an accurate and reliable prediction framework for students at risk of dropping out to detect at-risk students through a hybrid machine learning approach with data balancing techniques. The main contribution of this study is the integration of Support Vector Machine and Extreme Gradient Boosting in a stacked ensemble architecture supported by data balancing optimization techniques. The proposed model leverages the ability of Support Vector Machine to separate complex classification patterns, while Extreme Gradient Boosting improves prediction accuracy through iterative learning and modeling interactions between variables. The problem of data imbalance is addressed through oversampling techniques for the minority class so that the model learning process becomes more balanced. The model framework is tested using a dataset consisting of 3,652 students with academic, socioeconomic, and behavioral variables. Experimental results show that the proposed hybrid model outperforms the single model, with an accuracy rate of 97 percent, a precision rate of 94 percent, and a recall rate of 95 percent. These findings suggest that a combination of complementary machine learning methods, coupled with data optimization, can significantly improve the predictive ability of student dropout. The practical implication of this research is the availability of a robust decision support system for universities in designing timely and targeted interventions. By identifying students at risk of dropping out, institutions can strengthen retention strategies, improve student academic success, and reduce dropout rates more effectively.
Optimal Control of The Spread of COVID-19 in Jakarta Rizki Chika Audita Ariyani; Widowati Widowati; Uvi Dwian Kencono; Lucky Cahya Wanditra; Dhimas Mahardika
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 11 No. 2 (2026): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v11i2.1145

Abstract

SARS-CoV-2 is the virus that causes COVID-19. In Indonesia, the highest number of COVID-19 cases is in the Jakarta province. It is necessary to restrict the virus's transmission. This research purposes to determine optimal control strategies (self-prevention, vaccination, and cure) of the SEAIQHRD model to reduce disease spread. Optimal control analysis is solved utilising Pontryagin's Minimum Principle. In this study, numerical simulations were conducted using COVID-19 outbreak data from Jakarta province from March 1 to August 31, 2022. Based on the analysis results, the basic reproduction number ℜ0 = 2,1316. Since ℜ0 > 1 at the EE point, the COVID-19 spread model is asymptotically stable, indicating that the virus persists in the population. The application of control steps combining all three strategies was shown to reduce the subpopulations of exposed, infected, hospitalized, and deceased individuals. Simultaneous optimal control is more effective at controlling the spread than using a control step. The simultaneous implementation of optimal controls has proven an effective strategy for reducing COVID-19 transmission in Jakarta.
Co-Authors A. Jauhar Mahya Aulia, Lathifatul Bambang Riyanto Catur Edi Widodo Dhimas Mahardika Dinar Mutiara Kusumo Nugraheni Esti Wijayanti Fuad Muhammad Hari Muhammad Lucky Cahya Wanditra Nolaika Arsiani Norramandhany Okky Widya Arditya Priyo Sidik Sasongko Redemtus Heru Tjahjana Rina Fiati Rizki Chika Audita Ariyani Sapto P. Putro Shabrina Zata Yumni Suhartana Suhartana Sunarsih Sunarsih Sutimin Sutimin Sutrisno Sutrisno Sutrisno, Sutrisno Uvi Dwian Kencono