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"ABSTRAKPLTU Banten 2 Labuan beroperasi dengan menggunakan batubara nilai kalor rendah dan batubara nilai kalor menegah. Pada skenario pembebanan yang fluktuatif dari P2B. PLTU Banten 2 Labuan harus siap memenuhi sistem dengan kondisi persediaan batubara yang ada. Pembebanan yang fluktuatif dan tidak sesuai dengan perencanaan operasi berdampak pula terhadap persediaan batubara sehingga persediaan minimum batubara sering tidak memenuhi persyaratan keamanan persediaan untuk unit beroperasi. Tujuan dari penelitian ini adalah untuk mendapatkan metode pengelolaan persediaan batubara pada PLTU Banten 2 Labuan. Penelitian ini merupakan penelitian empiris, menggunakan metode scientific dengan menggunakan perumusan matematika terhadap data di lapangan. Metode yang digunakan untuk perhitungan optimasi adalah metode simulasi probabilistik yaitu dengan menurunkan perumusan matematis dari literatur maupun kondisi lapangan dan selanjutnya disimulasikan dengan menggunakan peringkat lunak Crystall Ball- OptQuest. Hasil penelitian menunjukkan bahwa perencanaan jumlah penerimaan batubara dengan mempertimbangkan stok minimum persediaan dapat dilakukan untuk mendapatkan total biaya persediaan paling optimum. Dari penelitian juga didapatkan bahwa kapasitas persediaan paling optimum untuk mendapatkan total biaya persediaan paling minimum diperoleh pada penggunaan batubara dengan jenis kalori 4800 kcal/kg dibandingkan dengan penggunaan batubara dengan nilai kalori yang lebih rendah. 4200 dan 4600 kcal/kg. Dari penelitian didapatkan hasil bahwa simulasi probablistik dapat digunakan untuk optimasi sistem persediaan batubara di PLTU Banten 2 Labuan. Kata kunci: PLTU; batubara; manajemen persediaan; optimasi; metode

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ABSTRACTAbstract Labuan Banten power plant operates by using two types of coal as fuel. namely low calorific value coal and medium calorific value coal In the fluctuating loading scenario scenario of P2B. PLTU Banten 2 Labuan has to face a coal mixing system to meet customer demand. But on the other hand. the fulfillment of the such loading impact on coal consumption. Fluctuating loading and incompatible with operating planning also impacts coal inventories so that the minimum coal supply often does not meet the safety requirements of inventories for the unit in operation.The purpose of this research is to get the method of managing coal supply at PLTU Banten 2 Labuan. This research is empirical research. using mathematical formulation to data in field. The method used for the calculation of optimization in coal supply management is probabilistic simulation method that is by formulating the mathematical equation of the literature and the condition of the field. unpredicted parameters can be forecasted and then simulated by using OptQuest software.The result shows that storage cost is the most sensitive component to total inventory cost. In addition Planning of the amount of coal supply entrance by taking into account the minimum stock of inventory can be done to obtain the most optimum total inventory cost. The research also found that the most optimum inventory capacity to get the minimum total inventory cost is obtained on the use of coal with the type of calories 4800 kcal kg compared with the use of coal with lower caloric value. 4200 and 4600 kcal kg.This research shows that probablistic simulation method can be used to optimize the coal inventory management at PLTU Banten 2 Labuan. Keywords power plant coal. inventory management optimization method."

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Salah satu teknik analisis yang dapat digunakan pada data mining dalam mengelompokkan data adalah Triclustering. Triclustering merupakan metode pengelompokan secara bersamaan pada data tiga dimensi yang terdiri dari observasi, atribut, dan konteks. Triclustering kerap digunakan pada bidang bioinformatika untuk mengelompokkan data ekspresi gen di titik waktu tertentu pada suatu kondisi eksperimen. Triclustering yang diajukan pada penelitian ini menggunakan metode Hybrid  – TRIMAX Binary Particle Swarm Optimization. Particle Swarm Optimization (PSO) adalah teknik pengelompokan yang terinspirasi oleh perilaku biologis populasi ikan atau kawanan burung yang bergerak untuk menuju sumber makanan. Setiap individu di dalam populasi disebut sebagai partikel yang didefinisikan sebagai kandidat solusi (tricluster). Istilah “Binary” mengartikan bahwa partikel yang bergerak di ruang pencarian berbentuk vektor biner (bit) yang bernilai 0 atau 1. Tahap inisiasi populasi dilakukan dengan menggunakan algoritma nodes deletion pada  – TRIMAX untuk menghasilkan populasi awal yang homogen.  Metode  – TRIMAX dapat menghasilkan tricluster dengan nilai Mean Residual Square (MSR) lebih kecil dari threshold 𝛿 sehingga dapat meningkatkan efektifitas komputasi dari metode Hybrid  – TRIMAX Binary Particle Swarm Optimization. Algoritma gabungan kemudian diimplementasikan pada data ekspresi gen tiga dimensi sel kanker pankreas PANC-1 yang diberikan obat kemoterapi ATO, JQ1, dan kombinasi keduanya pada 3 titik waktu. Diperoleh tricluster optimum dengan skenario  0,0003;  0,8;   0,2; dan tipe neighbourhood = “Gbest”. Tricluster tersebut memiliki nilai TQI sebesar 1,427E-09 dan volume tricluster sebesar 169.410. Berdasarkan tricluster optimum, diperoleh informasi mengenai kumpulan gen yang tidak merespon baik terhadap pengobatan JQ1 dan JQ1+ATO pada jangka waktu menengah dan panjang. Hasil analisis ontologi gen menunjukkan tiga aspek ontologi yang signifikan dengan p-value < 0,05, yaitu proses biologi, fungsi molekuler, dan komponen seluler. Diperoleh gen yang resisten terhadap pengobatan terlibat dalam proses biologi metabolisme sel dan pengembangan sel yang mempertahankan kehidupan sel. Pada aspek fungsi molekuler, gen berperan dalam proses pengikatan, seperti pengikatan ion, senyawa organik siklik, dan senyawa heterosiklik, serta aktivitas katalitik. Selain itu, juga ditemukan bahwa sebagian besar gen berlokasi pada sitoplasma, organel, dan nukleus dalam komponen seluler. Aspek-aspek dari ontologi gen dapat berkontribusi pada resistensi kumpulan gen dalam sel kanker PANC-1 terhadap pengobatan.

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One of the analysis techniques that can be used in data mining to group data is Triclustering. Triclustering is a method of simultaneously grouping three-dimensional data consisting of observations, attributes, and context. Triclustering analysis is often used in the field of bioinformatics to group gene expression data at certain time points under experimental conditions. The triclustering analysis proposed in this study used the Hybrid  – TRIMAX Binary Particle Swarm Optimization method. Particle Swarm Optimization (PSO) is a clustering technique inspired by the biological behavior of fish populations or flocks of birds that move towards food sources. Each individual in the population is referred as particles which are defined as candidate solutions (tricluster). The term "Binary" means that the particles move in the search space in the form of binary vectors (bits) with a value of 0 or 1, the number "1" represents that an individual is present in the particle. The population initialization stage is carried out using the nodes deletion algorithm in δ-TRIMAX to produce a homogeneous initial population.  The δ-TRIMAX method can generate a tricluster with a Mean Residual Square (MSR) value smaller than the threshold 𝛿 so that it can increase the computational effectiveness of the Hybrid δ-TRIMAX Binary Particle Swarm Optimization method. The combined algorithm then implemented on three-dimensional gene expression data of PANC-1 pancreatic cancer cells given ATO, JQ1, and a combination of both chemotherapy drugs at three time points. The optimum tricluster was obtained with scenario  0,0003;  0,8;   0,2; and neighborhood type = "Gbest". The tricluster has a TQI value of 1.427E-09 and a tricluster volume of 169,410. Based on the optimum tricluster, information was obtained about the gene pools that did not respond well to JQ1 and JQ1+ATO treatment in the medium and long term. The results of gene ontology analysis showed three significant ontological aspects with p-value <0.05, namely biological processes, molecular functions, and cellular components. It was found that treatment-resistant genes are involved in the biological process of cell metabolism and cell development that maintains cell life. In the aspect of molecular function, genes play a role in binding processes, such as ion binding, cyclic organic compounds, and heterocyclic compounds, as well as catalytic activity. In addition, it was also found that most genes are located in the cytoplasm, organelles, and nucleus in cellular components. These aspects of the gene ontology may contribute to the resistance of the gene pool in PANC-1 cancer cells to treatment.

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"This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems."

"This book collects chapters dealing with some of the theoretical aspects needed to properly discuss the dynamics of complex engineering systems. The book illustrates advanced theoretical development and new techniques designed to better solve problems within the nonlinear dynamical systems. Topics covered in this volume include advances on fixed point results on partial metric spaces, localization of the spectral expansions associated with the partial differential operators, irregularity in graphs and inverse problems, Hyers-Ulam and Hyers-Ulam-Rassias stability for integro-differential equations, fixed point results for mixed multivalued mappings of Feng-Liu type on Mb-metric spaces, and the limit q-Bernstein operators, analytical investigation on the fractional diffusion absorption equation."

"This book presents a comprehensive introduction to design sensitivity analysis theory as applied to electromagnetic systems. It treats the subject in a unified manner, providing numerical methods and design examples. The specific focus is on continuum design sensitivity analysis, which offers significant advantages over discrete design sensitivity methods. Continuum design sensitivity formulas are derived from the material derivative in continuum mechanics and the variational form of the governing equation. Continuum sensitivity analysis is applied to Maxwell equations of electrostatic, magnetostatic and eddy-current systems, and then the sensitivity formulas for each system are derived in a closed form; an integration along the design interface.The book also introduces the recent breakthrough of the topology optimization method, which is accomplished by coupling the level set method and continuum design sensitivity. This topology optimization method enhances the possibility of the global minimum with minimised computational time, and in addition the evolving shapes during the iterative design process are easily captured in the level set equation. Moreover, since the optimization algorithm is transformed into a well-known transient analysis algorithm for differential equations, its numerical implementation becomes very simple and convenient.Despite the complex derivation processes and mathematical expressions, the obtained sensitivity formulas are very straightforward for numerical implementation. This book provides detailed explanation of the background theory and the derivation process, which will help readers understand the design method and will set the foundation for advanced research in the future."