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Nur Aini Masruroh
Fakultas Teknik, Jurusan Teknik Mesin Dan Industri, Universitas Gadjah Mada Jl. Grafika 2, Kampus UGM, Yogyakarta 55281
Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Model Penjadwalan Pengiriman Pasokan pada Strategi Multi-Supplier dengan Variasi Harga dan Lead Time untuk Permintaan Stokastik Masruroh, Nur Aini; Prasetyorini, Anggita Virgiana
Jurnal Teknik Industri Vol 17, No 1 (2015): JUNE 2015
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.646 KB) | DOI: 10.9744/jti.17.1.35-46

Abstract

Multi-supplier is one of the strategies to minimize holding cost and average stock-out cost as long as to stabilize the supply of raw materials. The common problems that the firms may face when applying the multi-supplier strategy are determining the right schedule and quantity ordered for each supplier. Complexity of the problem increases with the facts that each supplier may have different parameters, demand is uncertain, and the firms’ constraints. Thus, this research is done to answer two main objectives: (1) to determine the optimum safety time (minimum raw material inventory) to prevent the stockout due to the demand uncertainty and (2) to determine the right schedule and quantity ordered for each supplier considering the different suppliers parameters: price, lead time, and supply capacity. The problem is modeled in Mixed Integer Linear Programming with total minimum inventory cost as the objective. With the aim of testing the model, a case of multinational company that apply the multi-supplier strategy is used.
ON MODELLING AND SOLVING HETEROGENEOUS VEHICLE ROUTING PROBLEM WITH MULTI-TRIPS AND MULTI-PRODUCTS Setiawan, Fran; Masruroh, Nur Aini; Pramuditha, Zita Iga
Jurnal Teknik Industri Vol 21, No 2 (2019): JTI Dec 2019
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (672.059 KB) | DOI: 10.9744/jti.21.2.91-104

Abstract

Vehicle routing problem (VRP) is a model to determine an optimal routing plan for a fleet of homogeneous vehicles to serve a set customer which some operational constraints are satisfied. In most practical distribution problems, customer demands are served using heterogeneous fleet of vehicles. This kind of VRP is called Heterogeneous Vehicle Routing Problem (HVRP). HVRP has evolved into a rich research area because of its practical. There were many studies of rich extensions of the standar HVRP. This research aims to enrich the extentions of HVRP which is motivated by real case in one of pharmacy distribution company in Indonesia which is delivered multi-products to its 55 customers by allowing some vehicles which has small capacity to perform multi-trips. This problem is called Heterogeneous Vehicle Routing Problem with Multi-Trips and Multi-Products (HVRPMTMP).The mixed integer linear programming is developed based on four-index vehicle flow formulation. The model can be used generally in the same context of distribution problem. HVRPMTMP is generally NP-Hard problem, so the computational time using branch and bound in LINGO 16.0 is increasing exponentially by increasing the number of customers. Genetic algorithm is proposed to solve the real case. The result of the proposed GA can reduce the total cost from Rp 352540.6,- to Rp 180555,- or 48.78% from the current company policy.
THE DETERMINATION OF VEGETABLE PRICING IN THE SUPERMARKET IN YOGYAKARTA Suci Miranda; Nur Aini Masruroh
Teknoin Vol. 22 No. 2 (2016)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknoin.vol22.iss2.art4

Abstract

Penelitian ini menjelaskan faktor - faktor yang mempengaruhi penentuan harga sayuran di supermarket di Yogyakarta. Diketahui bahwa harga sayuran di supermarket merupakan penjumlahan dari harga sayuran supplier dan mark up dari harga supplier tersebut. Hasil penelitian menunjukkan bahwa harga supplier merupakan salah satu variabel yang berpengaruh secara langsung terhadap harga sayuran di supermarket. Faktor - faktor yang mempengaruhi besaran mark up merupakan data kualitatifberdasarkan hasil wawancara dengan supplier dan survery di supermarket: segmentasi konsumen, pengaruh harga pasar, pengaruh harga impor, dan packaging. Hasil PCA memberikan  informasi variabel penting  terhadap besaran mark up harga sayuran  yaitu Pengaruh Harga Pasar, Pengaruh Harga Impor, dan Packaging. Ketiga variabel ini berkorelasi tinggi baik terhadap mark up maupun harga sayuran di supermarket. Segmentasi Pasar tidak berkorelasi secara signifikan terhadap besaran mark up dan harga sayuran di supermarket. Terakhir, dengan menggunakan Partial Least Squares (PLS) dibangun model matematis penentuan harga sayuran di supermarket. Model 1 dengan 25 data dan Model 2 dengan 14 data sayuran. Y sebagai mark up, dan X adalah variabel Segmentasi Konsumen, Pengaruh Harga Pasar, Pengaruh Harga Impor, dan Packaging. Diberikan contoh perhitungan harga sayuran di supermarket menggunakan model yang dibangun.
Penentuan Faktor Prioritas Penganggaran Partisipatif IKM Andalan Provinsi Kalimantan Barat dengan Metode AHP Susana Evayanti; Niken Siwi Pamungkas; Nur Aini Masruroh; Anna Maria Sri Asih
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2018
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

SIMULATION MODEL DEVELOPMENT FOR FIRE WATER PIPING NETWORK WITH NEWTON-RAPHSON ITERATION Ari Ariangga Orranius Putra Patarru; Joko Waluyo; Nur Aini Masruroh
ASEAN Journal of Systems Engineering Vol 5, No 1 (2021): ASEAN Journal of Systems Engineering
Publisher : Master in Systems Engineering

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Abstract

The oil and gas industry is an industry that possesses various risks. The most significant risk in this sector is fire. To support the oil and gas production activities, it is necessary to install permanent and non-permanent fire extinguishers to prevent and deal with fire accidents. The firewater network system has a role in supplying flow rates with a certain pressure to protect the production process in a fire. The flow rate and pressure must be able to preserve the process area. Therefore the performance of firewater network system must be monitored. Over time, the performance degradation of the firewater network system is unavoidable.  This decrease is due to scaling or leak minor at pipe and the decreasing performance of the diesel fire pump.This research aims to create a model of simulation fire water network system using newton-raphson iteration. The simulation model that is formed will be used to vary the flow rate against pressure. Based on iteration show the flow rate at platform 4 is 198.9 m3/h. The discharge variation is carried out to see the pressure on platform 4, the variation of the discharge of 2,000 m3/h gives a pressure of 150.45 psig, the variation of the discharge of 1,500 m3/h gives a pressure of 130.85 psig, and the variation of the discharge of 500 m3/h gives a pressure of 24.26 psig. The results of the discharge variation are used to see the performance of the fire water network system. Performance with a discharge of 2,000 m3/h decreased by 9.74%, and performance with a discharge of 1,000 m3/h decreased by 8.81%.
MODEL OF VEHICLE ROUTING PROBLEM WITH SPLIT DELIVERY, MULTI TRIPS, MULTI PRODUCTS AND COMPARTMENTS FOR DETERMINING FUEL DISTRIBUTION ROUTES Dinda Safitri Ramadhani; Nur Aini Masruroh; Joko Waluyo
ASEAN Journal of Systems Engineering Vol 5, No 2 (2021): ASEAN Journal of Systems Engineering
Publisher : Master in Systems Engineering

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Abstract

The industrial development in Indonesia encourages companies to have high sensitivity in competing to meet consumer demands promptly by considering minimum distribution costs. One of the factors that can affect distribution costs is route determination. Determining the distribution route is the Vehicle Routing Problem (VRP). The purpose of VRP is to arrange the order of distribution routes to produce a minimum total distance. This study aims to determine the fuel distribution route at TBBM Rewulu in one delivery period to obtain the optimal distribution route and minimize the vehicle mileage. Delivery is carried out using three types of tanker trucks with heterogeneous capacities. This study uses a mathematical model of Mixed Integer Linear Programming (MILP) by considering split delivery, multi trips, multi-products, and compartments.The branch and bound method in the LINGO solver has been used to solve this problem. This model was tested on a simple case using data of 8 customers with different distances and demand shipped by truck. The results obtained indicate that no boundaries are violated, and all consumers are served. The mathematical model built is still general, so it can solve similar cases. A model can be developed for further research by adding VRP variants such as time windows and adding the product types to represent the entire existing system.
Evaluasi Medical Response Preparedness Pada Unit Gawat Darurat (Studi Kasus di IGD Rumah Sakit Umum Pusat Dr. Sardjito Yogyakarta) Indah Puspitasari; Nur Aini Masruroh
Forum Teknik Vol 36, No 1 (2015)
Publisher : Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10808.834 KB)

Abstract

     In the last decade, there were 2 disasters that killed many people in Yogyakarta, such as earthquake in 2006 and Merapi eruption in 2010. Therefore, as one of reference hospitals,RSUP Dr. Sardjito must have good medical response preparedness to handle victims that were evacuated to RSUP Dr. Sardjito, therefore evaluation of medical response preparedness that has been applied in RSUP Dr. Sardjito is needed, in purpose deciding resources allocation.Simulation is used to evaluate medical response preparedness. Model is built based on real system when Merapi eruption is happened and on extreme points of arrival rate of victims to RSUP Dr. Sardjito, that is on 5 and 7 November 2010. Then the model is simulated and evaluated by using average waiting time for victims to be handled as indicator. The evaluation result will decide resources allocation that is needed. simulation of model 5 November results average waiting time for patient with severity 1, 2, 3, and 4 is 2991,26; 72,19; 0; 0 minutes. While model 7 November results waiting time for patient with severity 2, 3, and 4 is 0,22; 0; 0 minutes. From the results, sensitivity analysis is used to decide resources allocation needs.Keywords: medical responses, emergency department, simulation, disaster, system improvement
OPERATIONS RESEARCH STRATEGI EFISIENSI BERMULA DARI PERANG Nur Aini Masruroh
Jurnal Teknosains Vol 3, No 2 (2014): June
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.6028

Abstract

Penggunaan nama operations research inimemang tidak dapat lepas dari sejarah awalperkembangan ilmu ini. Berawal dari zamanperang dunia kedua, ketika pemerintahanInggris dan Amerika menghadapi permasalahanterbatasnya ketersediaan logistikperang yang harus dialokasikan ke beberapaoperasi militer dan aktivitas lain yangmendukung operasi militer ini sehinggamemerlukan sebuah strategi distribusilogistik yang efektif dan efisien. Gunamerumuskan strategi ini, maka dibentuklahtim yang terdiri dari sejumlah ilmuwanuntuk mengaplikasikan pendekatan ilmiahuntuk memecahkan permasalahan ini. Timini diberi tugas untuk melakukan research on(military) operations. Tim ilmuwan inilah yangselanjutnya dikenal sebagai tim operationsresearch (OR) yang pertama kali. Salah satuhasil dari tim ini adalah hasil risetnya tentangstrategi pengaturan operasi kapal selam yangmenghasilkan kemenangan dalam perang diAtlantik utara.
PENGEMBANGAN MODEL MATEMATIKA JARINGAN SUPPLY CHAIN DENGAN MEMPERTIMBANGKAN EMISI PADA INDUSTRI DAUR ULANG KERTAS Asgar Ali; Nur Aini Masruroh
Jurnal Teknosains Vol 5, No 2 (2016): June
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.8526

Abstract

Recycling is part of the green supply chain management which is developed base on the concept of environmentally friendly industry to respond the various issues regarding the environmental problems of the world. Distribution of recycled products starts from consumers and ends to manufacturing. The objective is to limit the waste in order to save energy and prevent the dumping of hazardous materials into the environment. However there are complexities in the supply chain because of some uncertainties such as the return of recycled product and the environmental impact resulting from the operation of supply chain. In this research, linear programming optimization method is proposed to overcome that problem with maximizing profit is set as the objective function. Emissions resulting from the recycling process are considered in the model. These results indicate that the mathematical model provides profit of Rp. 37.909.659, with 1.137.760 grams of CO2 emissions from the production process, 38.473,4 grams of CO and 5.884,9 grams HC + NOX of transport. While the proposed strategy is use the right vehicles and select the most efficient route according to the paper collected from consumers and sold to manufacturing. For the production process, it is required to add 3 pressing machines and 1 chopped machine, so the capacity of the working hours of 384 hours per month can be increased to 960 hours per month.
APLIKASI JARINGAN SARAF TIRUAN DAN PARTICLE SWARM OPTIMIZATION UNTUK PERAMALAN INDEKS HARGA SAHAM BURSA EFEK INDONESIA Desy Wartati; Nur Aini Masruroh
Jurnal Teknosains Vol 6, No 1 (2016): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.27616

Abstract

Jakarta Composite Index (JCI) is the main stock index in Indonesia Stock Exchange, which indicates the movement of the performance of all stocks listed. The data of stock price index often experience rapid fluctuations in a short time, so it is needed to carry out an analysis to help investor making the right investment decisions. Forecasting JCI is one of the activities that can be done because it helps to predict the value of the stock price in accordance with the past patterns, so it can be a consideration to make a decision. In this research, there are two forecasting models created to predict JCI, which are Artificial Neural Network (ANN) model with (1) Backpropagation algorithm (BP) and (2) Backpropagation algorithm model combined with Particle Swarm Optimization algorithm (PSO). The development of both models is done from the stage of the training process to obtain optimal weights on each network layer, followed by a stage of the testing process to determine whether the models are valid or not based on the tracking signals that are generated. ANN model is used because it is known to have the ability to process data that is nonlinear such as stock price indices and PSO is used to help ANN to gain weight with a fast computing time and tend to provide optimal results. Forecast results generated from both models are compared based on the error of computation time and forecast error. ANN model with BP algorithm generates computation time of training process for 4,9927 seconds with MSE of training and testing process is respectively 0,0031 and 0,0131, and MAPE of forecast results is 2,55%. ANN model with BP algorithm combined with PSO generates computation time of training process for 4,3867 seconds with MSE of training and testing process is respectively 0,0030 and 0,0062, and MAPE of forecast result is 1,88%. Based on these results, it can be concluded that ANN model with BP algorithm combined with PSO provides a more optimal result than ANN model with BP algorithm.
Co-Authors Anggita Virgiana Prasetyorini Anggita Virgiana Prasetyorini, Anggita Virgiana Anna Maria Sri Asih Annisa Dewi Akbari Ari Ariangga Orranius Putra Patarru Aris Prasetiyo Asgar Ali Budi Hartono Desy Wartati Dinda Safitri Ramadhani Dzakiyah Widyaningrum Hari Agung Yuniarto Indah Puspitasari Irwan Aufi Joko Waluyo Joko Wintoko Kusnanto Kusnanto Miranda, Suci Niken Siwi Pamungkas Pramuditha, Zita Iga Putri Vicky Hapsari Rochim Bakti Cahyono Rony Arjuna Setiawan, Fran Setiawan, Fran Subagyo . Susana Evayanti Trifandi Lasalewo Zita Iga Pramuditha