Articles
<![CDATA[Desain Kontrol pada Model Gerak Lateral-Direksional Unmanned Aerial Vehicle (UAV) Menggunakan Output Feedback Control ]]>
<![CDATA[Wiwit Ratnasari]]>;
<![CDATA[Erna Apriliani]]>;
<![CDATA[Mardlijah Mardlijah]]>
<![CDATA[ Jurnal Sains dan Seni ITS Vol 11, No 2 (2022) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS ]]>
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DOI: 10.12962/j23373520.v11i2.75502
<![CDATA[Pengembangan teknologi di berbagai bidang dari tahun ke tahun semakin pesat, begitu pula pengembangan teknologi di bidang kedirgantaraan. Salah satu pengembangannya adalah pesawat tanpa awak atau Unmanned Aerial Vehicle (UAV). Dalam penelitian ini, dilakukan analisis sistem dan desain kontrol pada model gerak lateral-direksional UAV menggunakan Output Feedback Control. Sistem bersifat tidak stabil, terkontrol, dan teramati. Agar UAV menjadi stabil, maka dilakukan penerapan Pole Placement pada desain kontrol dengan 5 skenario feedback gain (K_1,K_2,K_3,K_4,K_5,) untuk memindahkan nilai eigen yang menyebabkan sistem UAV tidak stabil. Skenario pada sudut selip (β) paling baik adalah desain kontrol dengan K_4 yang waktu stabilnya paling cepat yaitu 322 s, begitu pula pada sudut roll (ϕ) skenario terbaik adalah desain kontrol dengan K_4 dimana pada waktu 172 s sudah stabil.]]>
<![CDATA[Kontrol Optimal Penyebaran COVID-19 Model SEIR di Jakarta ]]>
<![CDATA[Nada Fitriani Azzahra]]>;
<![CDATA[Hariyanto Hariyanto]]>;
<![CDATA[Mardlijah Mardlijah]]>
<![CDATA[ Jurnal Sains dan Seni ITS Vol 11, No 2 (2022) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS ]]>
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DOI: 10.12962/j23373520.v11i2.76998
<![CDATA[Penyakit coronavirus (COVID-19) masuk ke Indonesia dan pertama kali terdeteksi di Jakarta. Hingga Juli 2020, kasus positif COVID-19 di Jakarta menjadi penyumbang kasus positif terbanyak di Indonesia. Hal ini menunjukkan bahwa penyebaran COVID-19 semakin meningkat dan perlu penanganan yang lebih maksimal. Oleh karena itu, dalam penelitian ini dibahas tentang pemberian kontrol yang optimal untuk mengendalikan penyebaran COVID-19 di Jakarta dengan model SEIR (Susceptible Exposed Infected Recovered). Model SEIR yang digunakan merupakan hasil pengembangan dari model yang sudah ada dengan mengikuti kondisi penyebaran COVID-19 di Jakarta. Salah satu upaya yang dapat dilakukan untuk mengontrol penyebaran COVID-19 adalah dengan melakukan testing. Testing dilakukan pada populasi exposed dengan tujuan dapat mengurangi penyebaran COVID-19 di Jakarta. Kemudian menentukan kontrol optimal menggunakan Prinsip Maksimum Pontryagin dan diselesaikan secara numerik menggunakan program Matlab berdasarkan metode forward-backward sweep Runge-Kutta orde empat. Dari hasil analisis simulasi, didapat bahwa dengan melakukan testing pada populasi exposed yang mengakibatkan berkurangnya jumlah populasi exposed sebesar 99% sehingga dapat mengurangi penyebaran COVID-19 di Jakarta.]]>
<![CDATA[Optimization of fuzzy entropy on solar panel’s motor ]]>
<![CDATA[MUHAMMAD IKHWAN]]>;
<![CDATA[MARWAN RAMLI]]>;
<![CDATA[MARDLIJAH MARDLIJAH]]>
<![CDATA[ Jurnal Natural Volume 22 Number 1, February 2022 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.24815/jn.v22i1.23187
<![CDATA[Renewable energy has been in great demand by the public, even some countries have set regulations for substitution and transition from fossil energy to renewable energy. This study aims to modify the fuzzy control system with a metaheuristic method, namely fuzzy entropy. The entropy value of the fuzzy set in the previous stage becomes the basis for calculating the foot of uncertainty in the new fuzzy set. This process makes the entropy method parallel to other optimization methods that have been carried out on fuzzy control systems. The results obtained indicate that the modified fuzzy control system successfully controls the angle and angular velocity of the solar panel. The error value shown is very small and the time to reach stability is below 5 s. This is a rapid development of several previous studies. The modified system has no overshoot and steady state error below 1%. Based on these results, entropy research can be developed again by changing the fuzzy set to a more complex form.]]>
<![CDATA[Penerapan Metode Kalman Filter dalam Estimasi Harga Saham Menggunakan Model ARCH-GARCH ]]>
<![CDATA[Lusi Nur Rahmawati]]>;
<![CDATA[Mardlijah Mardlijah]]>;
<![CDATA[Amirul Hakam]]>
<![CDATA[ Jurnal Sains dan Seni ITS Vol 12, No 1 (2023) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS ]]>
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DOI: 10.12962/j23373520.v12i1.96240
<![CDATA[Saham merupakan produk pasar modal yang menjadi salah satu instrumen investasi. Banyak investor yang memilih saham sebagai instrumen investasi dikarenakan saham memberikan keuntungan yang menarik. Metode estimasi merupakan metode yang tepat bagi para investor untuk memprediksi harga saham sehingga dapat membantu mengoptimalkan keuntungannya. Penelitian ini bertujuan untuk menentukan model terbaik dari data harga saham menggunakan model ARCH-GARCH dan mendapatkan hasil estimasi harga saham menggunakan metode Kalman Filter dengan model ARCH-GARCH untuk periode selanjutnya. Adapun data harga saham yang digunakan yaitu data harga saham PT. Telkom Indonesia Tbk yang diambil dari website resmi Yahoo Finance. Data yang diambil adalah data harga saham saat penutupan (close) periode 29 Februari 2020 sampai 31 Agustus 2021. Pada data harga saham digunakan model ARIMA (Autoregressive Integrated Moving Average) dan terdeteksi terdapat unsur heteroskedastisitas, sehingga digunakan model time series ARCH-GARCH (Autoregressive Conditional Heteroskedasticity Generalized Autoregressive Conditional Heteroskedasticity). Didapatkan model terbaik yaitu GARCH (1,1) dengan model ARIMA (2,1,3). Pada penerapan metode Kalman Filter didapatkan hasil estimasi harga saham lebih akurat yaitu mendekati data aktual yang ditandai dengan nilai MAPE (Mean Absolute Percentage Error) pada GARCH-Kalman Filter lebih kecil dibandingkan nilai MAPE pada model GARCH (1,1).]]>
<![CDATA[Optimization of fuzzy entropy on solar panel’s motor ]]>
<![CDATA[MUHAMMAD IKHWAN]]>;
<![CDATA[MARWAN RAMLI]]>;
<![CDATA[MARDLIJAH MARDLIJAH]]>
<![CDATA[ Jurnal Natural Volume 22 Number 1, February 2022 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.24815/jn.v22i1.23187
<![CDATA[Renewable energy has been in great demand by the public, even some countries have set regulations for substitution and transition from fossil energy to renewable energy. This study aims to modify the fuzzy control system with a metaheuristic method, namely fuzzy entropy. The entropy value of the fuzzy set in the previous stage becomes the basis for calculating the foot of uncertainty in the new fuzzy set. This process makes the entropy method parallel to other optimization methods that have been carried out on fuzzy control systems. The results obtained indicate that the modified fuzzy control system successfully controls the angle and angular velocity of the solar panel. The error value shown is very small and the time to reach stability is below 5 s. This is a rapid development of several previous studies. The modified system has no overshoot and steady state error below 1%. Based on these results, entropy research can be developed again by changing the fuzzy set to a more complex form.]]>
<![CDATA[Mathematical Modelling of Inventory Costs in Supply Chains with Horizontal Cooperation ]]>
<![CDATA[Zahara, Chasna]]>;
<![CDATA[Mardlijah, Mardlijah]]>
<![CDATA[ International Journal of Global Operations Research Vol. 5 No. 2 (2024): International Journal of Global Operations Research (IJGOR)m May 2024 ]]>
Publisher : <![CDATA[iora ]]>
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DOI: 10.47194/ijgor.v5i1.283
<![CDATA[Efficiency in the supply chain has become very important for companies in the era of increasingly fierce business competition. This has encouraged some companies to start implementing the concept of collaboration between companies or commonly called horizontal cooperation. Horizontal cooperation is important because companies need to work together to manage complex supply chains. To manage production in a collaborative supply chain requires designing a cost-effective model. The design of this model is expected to optimise inventory costs to achieve common goals in horizontal cooperation. This model is a form of linear programme consisting of objective function and constraint function. The objective function is to minimise the inventory cost in a four-tier supply chain with horizontal cooperation on post-production final storage at the production level only. The model was tested with 3 suppliers, 3 materials, 3 factories, 4 products, 3 distributors, and 3 consumers. The model with horizontal cooperation resulted in a total inventory cost of 1,349,830. This amount is 8% lower than the total inventory cost without horizontal cooperation. Thus, horizontal cooperation in the supply chain drastically reduces inventory costs throughout the supply chain.]]>
<![CDATA[Optimizing Algal Bloom Through Bioenzyme and Harvesting Control for Bioenergy Purposes in Eutrophic Water Bodies ]]>
<![CDATA[Akbar, Fadilah]]>;
<![CDATA[Mardlijah, Mardlijah]]>
<![CDATA[ Jambura Journal of Biomathematics (JJBM) Volume 5, Issue 2: December 2024 ]]>
Publisher : <![CDATA[Department of Mathematics, Universitas Negeri Gorontalo ]]>
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DOI: 10.37905/jjbm.v5i2.26938
<![CDATA[This article discusses the optimization of algae growth for bioenergy purposes in eutrophic water bodies through bioenzyme control and harvesting. The study explores innovative approaches to manage algae growth in such water bodies. A mathematical model based on dynamical systems, specifically the NASC (Nutrients, Algae, Detritus, and Dissolved Oxygen) algae growth model, was used for the analysis. The results indicate that the system used is unstable, given the needs of algae growth over time. To optimize algae growth, this study proposes controlling the bioenzyme (u1) feeding to decompose detritus into nutrients and harvesting algae using (u2). The Pontryagin Maximum Principle (PMP) method was used to obtain optimization with control parameters u1=0.093 and u2=0.32. The results show that the optimal time to harvest algae is every 84 days or 2.8 months, with an estimated harvestable amount of 16.3667 . This discovery enhances our understanding of controlling algae growth in the context of renewable energy and reinforces the mathematical approach to managing eutrophic aquatic ecosystems.]]>
<![CDATA[LQR and Fuzzy-PID Control Design on Double Inverted Pendulum ]]>
<![CDATA[Damayanti, Erlyana Trie]]>;
<![CDATA[Mardlijah, Mardlijah]]>;
<![CDATA[Rohman Wijaya, Ridho Nur]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 1 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/ca.v9i1.22070
<![CDATA[Double inverted pendulum is a non-linear and unstable system. Double inverted pendulum can be stabilized in the upright position by providing control to the system. In this research we compare two types of controllers namely Linear Quadratic Regulator (LQR) and Fuzzy-PID. The objective is to determine the control strategy that provides better performance on the position of the cart and pendulum angle. We modelled the system which is then linearized and given control. From the simulation results, it is proven that LQR and Fuzzy-PID controllers have been successfully designed to stabilize the double inverted pendulum. However, when given a disturbance in the form of noise step, the LQR controller has not been able to achieve the desired reference for up to 20 seconds. In another hand, the Fuzzy-PID controller is able to achieve the desired reference after 8 seconds. Therefore, it can be concluded that the Fuzzy-PID controller when applied to the Double Inverted pendulum system has better performance than the LQR controller.]]>
<![CDATA[Optimal Feeding Strategy on Microalgae Growth in Fed-Batch Bioreactor Model ]]>
<![CDATA[Nailul Izzati]]>;
<![CDATA[Mardlijah Mardlijah]]>
<![CDATA[ (IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 1 No. 1 (2015) ]]>
Publisher : <![CDATA[LPPM Institut Teknologi Sepuluh Nopember ]]>
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<![CDATA[Some countries in the world turn to alternative energy source to fulfill their necessity of fuel. One of the alternative fuels is biodiesel. Raw material of biodiesel can be produced by microalgae cultivation in fed-batch bioreactor. To improve the productivity of microalgae cultivation, we need to determine the optimal control of microalgae growth. This paper discusses mathematical model of microalgae growth in fed-batch bioreactor, and solves the optimal feeding strategy problem by using Pontryagin Minimum Principle. Then we compare the controlled microalgae growth model with the uncontrolled one. Numerical simulation with DOTcvpSB shows that the controlled microalgae growth model yields more harvest and less cost function than the uncontrolled one.]]>
<![CDATA[The Effect of Collector in Solar Still for Water Productivity Using Runge-Kutta Method ]]>
<![CDATA[Mardlijah Mardlijah]]>;
<![CDATA[Achmad Fatoni]]>;
<![CDATA[Lukman Hanafi]]>
<![CDATA[ (IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 1 No. 1 (2015) ]]>
Publisher : <![CDATA[LPPM Institut Teknologi Sepuluh Nopember ]]>
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<![CDATA[Solar still is a renewable energy technology. It can reduce crisis of clean and healthy water in some countries. Solar still produces clean and healthy water using the sunlight, but the result of distillate water is not so much. Hence the need for modifications with the addition of collector can increase the yield of distillate water. Mathematical model of solar still with collector is in the form of system of differential equations. It can be solved numerically using Runge-Kutta method. From the simulation, we conclude that the collector increases the amount of distillate water in the solar still.]]>
