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All Journal Jurnal Ilmu Dasar BERKALA SAINSTEK Jurnal Teknologi Informasi dan Ilmu Komputer Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA SISTEM INDUSTRI ILKOM Jurnal Ilmiah Teorema: Teori dan Riset Matematika Mathvision : Jurnal Matematika Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) InPrime: Indonesian Journal Of Pure And Applied Mathematics Range : Jurnal Pendidikan Matematika Majalah Ilmiah Matematika dan Statistika (MIMS) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Operations Research: International Conference Series Pattimura Proceeding : Conference of Science and Technology
Agustina Pradjaningsih
Jurusan Matematika FMIPA Universitas Jember
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Simulation of Cellular Network Model by Integer Programming Agustina Pradjaningsih
Jurnal ILMU DASAR Vol 10 No 2 (2009)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.249 KB)

Abstract

 Integer programming is a particular form or variety of the linear program, in which one or more of its values in the solution vector have integer. Integer programming can be applied on the network analysis and telecommunication. In this paper, integer programming is used to solve the problems of optimizing the route between cell i and HUB (Home Unit Base) j so that the cost for making a network model, especially cellular network, can be minimized.
Modified Migrating Birds Optimization Algorithm: Multi-Depot Capacitated Vehicle Routing Problem Dini Nur Wasilah; Agustina Pradjaningsih
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol 3, No 2 (2021)
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.v3i2.21257

Abstract

The multi-depot capacitated vehicle routing problem (MDCVRP) is a variation of the vehicle routing problem (VRP) modeled from distribution problems in the industrial world. This problem is a complex optimization problem in the field of operations research in applied mathematics. The MDCVRP is very interesting to discuss and find the best solution method. In this study, the authors apply the modified migrating birds' optimization (MMBO) algorithm, which is a hybrid of the migrating birds' optimization (MMBO) and iterated local search (ILS) algorithms. The purpose of this study is to analyze the results of applying the algorithm in solving MDCVRP. We used 20 MDCVRP data in simulation, grouped into four sizes (25, 50, 75, and 100 points). Based on the results of this research, it is known that the MMBO algorithm can produce the following solutions. First, on the data of 25 points, the experiment reaches the optimal value with small convergent iterations. Second, the best results on the data of 50 points have reached optimal value, but some other results have not been optimal. And, third, for data of 75 and 100 points, there is no optimal solution obtained by the MMBO algorithm. These results conclude that the MMBO algorithm effectively solves the MDCVRP problem with small data, but the bigger data, the more ineffective.Keywords: MDCVRP; VRP; optimization; operation research; applied Mathematics; MMBO. AbstrakMulti-depot capacitated vehicle routing problem (MDCVRP) adalah salah satu variasi dari vehicle routing problem (VRP) yang dimodelkan dari permasalahan distribusi di dunia industri. Permasalahan ini merupakan permasalahan optimasi kompleks dalam bidang riset operasi ilmu matematika terapan. MDCVRP sangat menarik untuk dibahas dan dicari metode penyelesaian terbaik. Dalam penelitian ini, penulis menerapkan algoritma modified migrating birds optimization (MMBO) yang merupakan hybrid algoritma migrating birds optimization (MBO) dan iterated local search (ILS). Tujuan penelitian ini adalah menganalisis hasil penerapan algoritma dalam menyelesaikan MDCVRP. Untuk simulasi, penulis menggunakan 20 data MDCVRP yang dikelompokkan menjadi empat ukuran (25, 50, 75, dan 100 titik). Berdasarkan hasil penelitian yang telah dilakukan, diketahui bahwa algoritma MMBO mampu menghasilkan solusi sebagai berikut. Pertama, Pada data 25 titik, percobaan mencapai nilai optimal dengan iterasi konvergen yang kecil. Kedua, Hasil terbaik pada data 50 titik telah mencapai nilai optimal namun sebagain hasil lainnya belum optimal. Dan ketiga, untuk data 75 dan 100 titik, tidak terdapat solusi optimal yang dihasilkan algoritma MMBO. Dari hasil tersebut dapat disimpulkan bahwa algoritma MMBO efektif untuk menyelesaikan MDCVRP data kecil, namun semakin besar datanya menjadi kurang efektif.Kata kunci: MDCVRP; VRP; optimasi; riset operasi; matematika terapan; MMBO. 
Penerapan Algoritma Elephant Herding Optimization (EHO) pada Masalah Hybrid Flowshop Scheduling (HFS) Ahmad Kamsyakawuni; Khurnia Palupi; Agustina Pradjaningsih
Journal of Applied Informatics and Computing Vol 4 No 1 (2020): Juli 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (717.361 KB) | DOI: 10.30871/jaic.v4i1.1834

Abstract

The industry is the driving force for the economy in Indonesia. One of the problems faced by industrial companies in the production process is determining the production schedule. The production schedule that is not according to the specified target can cause losses to the company. Scheduling is the allocation of resources to carry out a set of work at a specified time. The problem solved in this article is hybrid flowshop scheduling (HFS), it’s will be applied to companies engaged in bread making. A solution to solve the HFS problem using elephant herding optimization (EHO) algorithm. For the company to complete the production process by minimizing makespan, effective scheduling is needed, taking into account the number of parallel machines. The results of this article are 9 jobs and makespan 11.270 seconds using the MATLAB software.
PENERAPAN FUZZY LINEAR PROGRAMMING UNTUK OPTIMASI PRODUKSI TAHU Anisa Wahyu Illahi; Agustina Pradjaningsih; Abduh Riski
Pattimura Proceeding 2021: Prosiding KNM XX
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1050.758 KB) | DOI: 10.30598/PattimuraSci.2021.KNMXX.277-284

Abstract

Permasalahan yang terjadi pada industri tahu yang ada di desa Tanjungrejo antara lain menentukan jumlah tahu yang akan diproduksi, kendala terkait bahan baku, dan biaya produksi yang tinggi. Permasalahan-permasalahan tersebut jika tidak ditangani dengan tepat bukan keuntungan yang didapat melainkan kerugian. Hal ini tentunya berkaitan dengan optimasi serta efisiensi penyediaan modal, bahan baku, waktu, pegawai dan gaji pegawai agar mendapatkan keuntungan yang optimal. Tujuan dari penelitian ini adalah pengoptimalan hasil produksi pada industri tahu yang ada di desa Tanjungrejo dengan menggunakan metode fuzzy linear programming. Fuzzy linear programming adalah pengembangan dari program linear yang diaplikasikan dengan lingkungan fuzzy untuk mencapai tujuan memaksimalkan atau meminimumkan suatu masalah. Dengan menggunakan fuzzy linear programming dapat diperoleh nilai optimum jumlah produk tahu mentah dan tahu goreng yang diproduksi sesuai permintaan dan ketersediaan sumber daya produksi. Sumber daya yang diteliti adalah keuntungan, waktu kerja, dan bahan baku. Penyelesaian metode fuzzy linear programming dilakukan menggunakan software Lindo. Hasil yang diperoleh pada penelitian ini menunjukkan bahwa keempat industri mendapatkan keuntungan optimal dengan catatan ada penambahan bahan baku, dan λ merupakan nilai keanggotaan fuzzy yang berada direntang 0 sampai 1
Application of Markov Chain in Predicting Sugar Production at Candi Baru Sugar Factory, Sidoarjo Agustina Pradjaningsih; Ardelia Nani Vidatiyasa; Kiswara Agung Santoso
Pattimura Proceeding 2023: Prosiding KNM XXI
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/PattimuraSci.2023.KNMXXI.1-8

Abstract

Granulated sugar is a sugar commonly used daily to manufacture food and beverages. The demand for granulated sugar continues to increase, but the number of sugar factories and the area of ​​sugar cane in Indonesia is decreasing. This causes a gap between the demand for sugar which continues to increase, and the production of granulated sugar continues to decline, resulting in Indonesia being the largest country importer of sugar. The imbalance between the demand and production of granulated sugar At Candi Baru Sugar Factory, Sidoarjo, East Java, resulted in not achieving the target to meet these needs. Therefore, predictions are made to get an overview of production planning to optimize granulated sugar production so that sugar needs can be met. The prediction method used at the Candi Baru sugar factory, Sidoarjo, East Java, for the 2022 milling period is the Markov Chain method with a four-state divisor, namely drastically down, down, up, and up drastically. The application of Markov Chains produces predictions for each state. It is predicted that the production of sugar with the highest percentage for May – December upstate.
OPTIMASI PRODUKSI SUWAR-SUWIR MENGGUNAKAN METODE GOAL PROGRAMMING (STUDI KASUS : PABRIK SARI RASA, KABUPATEN JEMBER) Nilamsari, Fania Tasya; Santoso, Kiswara Agung; Pradjaningsih, Agustina
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 15 No 1 (2023): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2023.15.1.7243

Abstract

ABSTRACT. Production planning is an important thing in maintaining the suistainability of the company. The preparation of production planning is related to the optimization of a company’s production, so that a company can run effective and have low cost production activities. The preparation of production planning need to pay attention at many things because a company has various goals to achieve. Goal programming is a method to model a problem that has many goals so that the optimal solution will be obtained from many targets at once. This study aims to optimize the production of suwar-suwir at the Sari Rasa Factory located in Jember Regency by applying the goal programming method. Existing data will used to create a model using goal programming method to get the optimization results. The goal programming formulation is formed by determining the decision variables, goal constraints, and objective functions. The optimization calculation in the goal programming method will use the LINDO (Linear Interactive Discrete Optimizer) software. The results in this study show that production cost can be minimized from Rp 57.616.000 to Rp 51.782.000, existing raw materials can be minimized from 104 recipes to 94 recipes, and the optimal profit is Rp 18.508.000.Keywords: optimization, production, goal programming. ABSTRAK. Perencanaan produksi merupakan suatu hal yang penting dalam mempertahankan keberlangsungan perusahaan. Penyusunan perencanaan produksi berkaitan dengan optimasi produksi suatu perusahaan, agar suatu perusahaan dapat berjalan secara efektif dan kegiatan produksi tercapai dengan tingkat biaya yang rendah. Penyusunan perencanaan produksi perlu memperhatikan banyak hal karena suatu perusahaan memiliki berbagai tujuan yang ingin dicapai. Goal programming merupakan suatu metode yang dapat digunakan memodelkan suatu masalah yang mempunyai banyak tujuan sehingga akan didapatkan solusi optimal dari banyak target sekaligus. Penelitian ini bertujuan mengoptimalkan produksi suwar-suwir di Pabrik Sari Rasa yang terletak di Kabupaten Jember dengan menerapkan metode goal programming. Data yang didapat dimodelkan dengan metode goal programming untuk diperoleh hasil optimasinya. Formulasi goal programming dibentuk dengan menentukan variabel keputusan, goal constraint, dan fungsi tujuan. Penyelesaian masalah optimasi metode goal programming menggunakan software LINDO (Linear Interactive Discrete Optimizer). Hasil yang diperoleh pada penelitian ini menunjukkan bahwa biaya produksi dapat diminimumkan dari Rp 57.616.000 menjadi Rp 51.782.000, ketersediaan bahan baku dapat diminimumkan dari 104 resep menjadi 94 resep, dan keuntungan yang diperoleh sudah optimal yaitu sebesar Rp 18.508.000. Kata Kunci: optimasi, produksi, goal programming.
Snack Production Planning Strategy using Goal Programming Method Umama, Nadya; Pradjaningsih, Agustina; Riski, Abduh
BERKALA SAINSTEK Vol 12 No 1 (2024)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v12i1.45345

Abstract

UD Surya Snack Banyuwangi is one of the Banyuwangi snack shops that produces several kinds of snacks such as dry sponge cake, Bagiak, sato, sale, and others. Production at the factory is closely related to meeting market demand. Therefore, factories must carry out production planning so that they can produce products in sufficient quantities to meet market demand. Production planning involves making decisions regarding the number of products produced, resource allocation, and setting up the production process to achieve effectiveness and efficiency in the process. The article based on this research aims to obtain optimization values in production planning to meet market demand using the Goal Programming method. Goal Programming is a method that aims to minimize deviations from all goals by adjusting decision variables to achieve conformity with the specified goals. This research was carried out by direct observation at UD Surya Snack which was in direct contact with the factory owner. The data and information used in this research include production volume, production value, profits, production costs, and labor costs in one month. The data was then modeled using the Goal Programming method to determine decision variables, constraint functions, and objective functions and solved with the help of Excel Solver. The results obtained show that the application of Goal Programming in UD. Surya Snack production planning shows optimal values. The total profit earned was IDR 17.078.000 in one month after deducting production costs and labor costs. The deviation values of all constraints that must be minimized in the objective function have been met.
IMPLEMENTASI METODE GOAL PROGRAMMING UNTUK OPTIMASI OLAHAN INDUSTRI KERIPIK PISANG Pradjaningsih, Agustina; Dwidayanti, Frisca Puji; Riski, Abduh
JURNAL REKAYASA SISTEM INDUSTRI Vol 10 No 1 (2024): November 2024
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jrsi.v10i1.9255

Abstract

The production of chips, especially bananas, is the focus of the AROMA company in Lumajang. This business faces challenges in optimizing the use of raw materials to achieve maximum production. This challenge impacts production costs and profits, so proper production planning is needed. The goal programming method will be applied to handle this optimization problem involving various goals. This method aims to minimize deviations from each goal that has been set. The goal programming process involves identifying decision variables, goal constraints, and goal functions. The decision variables in this study included various flavors of banana chips such as chocolate, strawberry, durian, sweet, salty, chocolate-coated, and lime. Optimization problems are solved with LINDO software. The research results show that the production of banana chips can be optimized by increasing the output of lime-flavored banana chips by 200 packs. The optimization results also show total production costs of IDR 12,585,600 and profits of IDR 8,250,400.  
Application of Metaheuristic Algorithm for Solving Fully Fuzzy Linear Equations System Puspita Sari, Merysa; Pradjaningsih, Agustina; Ubaidillah, Firdaus
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.170

Abstract

A linear equation is an equation in which each term contains a constant with a variable of degree one or single and can be described as a straight line in a Cartesian coordinate system. A Linear equations system is a collection of several linear equations. A system of linear equations whose coefficients and variables are fuzzy numbers is called a fully fuzzy linear equation system. This study aims to apply a metaheuristic algorithm to solve a system of fully fuzzy linear equations. The objective function used is the minimization objective function. At the same time, the metaheuristic algorithms used in this research are Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Cuckoo Search (CS). The input in this research is a fully fuzzy linear equation system matrix and parameters of the PSO, FA, and CS algorithms. The resulting output is the best objective function and the variable value of the fully fuzzy linear equations system. The work was compared for accuracy with the Gauss-Jordan elimination method from previous studies with the help of the Matlab programming language. The results obtained indicate that the Particle Swarm Optimization (PSO) algorithm is better at solving fully fuzzy linear equation systems than the Firefly Algorithm (FA) and Cuckoo Search (CS). This case can be seen from the value of the resulting objective function close to the value of the Gauss-Jordan elimination methodKeywords: Mathematics, investation
Penerapan Goal Programming untuk Optimalisasi Penjadwalan Jam Kerja Satuan Pengamanan Pradjaningsih, Agustina; Rohmatul Aulia, Indriyani; Riski, Abduh
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5322

Abstract

One common challenge in security system management is the scheduling of security guards' work. Proper work scheduling is essential to prevent physical and psychological fatigue, which can negatively impact their performance. The scheduling process is influenced by factors such as the number of security personnel and the shift arrangements. This study aims to apply the goal programming method to optimize the scheduling of security guards. The research utilizes LINGO 17.0 software for assistance. The research process includes problem identification, data collection, determination of variables and parameters, formulation of goal programming models, solving these models using LINGO 17.0 software, analysis of the results, and the compilation of work schedules for security guards. The study's findings indicate that the established constraints have been met, and the number of working hours and days off for security guards has been optimized, resulting in an efficient schedule.
Co-Authors Abduh Riski Abduh Riski, Abduh Ahmad Kamsyakawuni Akhsan, Mokhamad Andora, Ela Anggraeni, Dyan Mei Anisa Wahyu Illahi Apriani Soepardi Ardelia Nani Vidatiyasa B., Rika N. Delenia, Erick Dewi, Theresia Trias Candra Dini Nur Wasilah Durratul Sayyidah Adilah Munawaroh Dwidayanti, Frisca Puji Fadri, Firda Firdaus Ubaidillah, Firdaus Fitriya, Fitriya I Made Tirta Islamiyah, Syayidah Umrotul Khurnia Palupi Kiswara Agung Santoso Kiswara Agung Santoso M. Isnaini Moh. Hasan Mutiarasari, Yusna Nilamsari, Fania Tasya Nuranggraini, Laras Vegi Puspita Sari, Merysa Putriana, Novia Ayu Rianingsih, Wahyu Rohmatul Aulia, Indriyani Rusli Hidayat Sari, Merysa Puspita Sukma Lailatul Fadillah Taufiqi Fadhilah Amieni Umama, Nadya Wasilah, Dini Nur Yuliani Setia Dewi Yusnita, Ade Ratna