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All Journal Jurnal Ilmiah Teknik Industri Makara Journal of Technology
Amar Rachman
Program Studi Teknik Industri, Universitas Indonesia
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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 1 
MODEL PERAMALAN KONSUMSI BAHAN BAKAR JENIS PREMIUM DI INDONESIA DENGAN REGRESI LINIER BERGANDA Farizal, Farizal; Rachman, Amar; Rasyid, Hadi Al
Jurnal Ilmiah Teknik Industri Vol. 13, No.2, Desember 2014
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

Energy consumption forecasting, especially premium, is an integral part of energy management. Premium is a type of energy that receives government subsidy. Unfortunately, premium forecastings being performed have considerable high error resulting difficulties on reaching planned subsidy target and exploding the amount. In this study forecasting was conducted using multilinear regression (MLR) method with ten candidate predictor variables. The result shows that only four variables which are inflation, selling price disparity between pertamanx and premium, economic growth rate, and the number of car, dictate premium consumption. Analsys on the MLR model indicates that the model has a considerable low error with the mean absolute percentage error (MAPE) of 5.18%. The model has been used to predict 2013 primium consumption with 1.05% of error. The model predicted that 2013 premium consumption was 29.56 million kiloliter, while the reality was 29.26 million kiloliter.   
MODEL PERAMALAN KONSUMSI BAHAN BAKAR JENIS PREMIUM DI INDONESIA DENGAN REGRESI LINIER BERGANDA Farizal, Farizal; Rachman, Amar; Rasyid, Hadi Al
Jurnal Ilmiah Teknik Industri Vol. 13, No.2, Desember 2014
Publisher : Muhammadiyah University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v13i2.635

Abstract

Energy consumption forecasting, especially premium, is an integral part of energy management. Premium is a type of energy that receives government subsidy. Unfortunately, premium forecastings being performed have considerable high error resulting difficulties on reaching planned subsidy target and exploding the amount. In this study forecasting was conducted using multilinear regression (MLR) method with ten candidate predictor variables. The result shows that only four variables which are inflation, selling price disparity between pertamanx and premium, economic growth rate, and the number of car, dictate premium consumption. Analsys on the MLR model indicates that the model has a considerable low error with the mean absolute percentage error (MAPE) of 5.18%. The model has been used to predict 2013 primium consumption with 1.05% of error. The model predicted that 2013 premium consumption was 29.56 million kiloliter, while the reality was 29.26 million kiloliter.   
Multi-Project Scheduling Cost Optimization in a Machine Manufacturer Engineer-to-Order Farizal, Farizal; Rachman, Amar; Tandean, Tifani; Sudarto, Sumarsono; Takahashi, Katsuhiko
Makara Journal of Technology Vol. 20, No. 1
Publisher : UI Scholars Hub

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Abstract

This paper discusses the utilization of mixed integer linear programming (MILP) model to optimize cost for multiproject scheduling in a machine maker company. The objective is to minimize total project’s penalty cost and labor cost. The model formulated shows how to achieve the objective i.e. whether to use outsourcing or overtime to finish all projects. The model of multi-project scheduling was solved by Branch & Bound algorithm coded in Lingo 14.0 software. The case study shows that if a company wants to minimize lateness, it should use overtime instead of outsourcing, which minimize total lateness of projects by 144 days or 73.5%. Whereas, if a company wants to optimize cost, they should use outsourcing instead of overtime, which reduces total cost of about 10,873,000 IDR or 28.5%. These results indicate that the model developed is applicable for optimizing multi-project scheduling.
Optimization of Electricity Generation Schemes in the Java-Bali Grid System with Co2 Reduction Consideration Farizal, Farizal; Septia, Wenty Eka; Rachman, Amar; Nasruddin, Nasruddin; Mahlia, Teuku Meurah Indra
Makara Journal of Technology Vol. 20, No. 2
Publisher : UI Scholars Hub

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Abstract

This research considers the problem of reducing CO2 emissions from the Java-Bali power grid system that consists of a variety of power-generating plants: coal-fired, natural gas, oil, and renewable energy (PV, geothermal, hydroelectric, wind, and landfill gas). The problem is formulated as linear programming and solved using LINGO 10. The model was developed for a nation to meet a specified CO2 emission target. Two carbon dioxide mitigation options are considered in this study, i.e. fuel balancing and fuel switching. In order to reduce the CO2 emissions by 26% in 2021, State Electric Supply Company (PLN) has to generate up to 30% of electricity from renewable energy (RE), and the cost of electricity (COE) is expected to increase to 617.77 IDR per kWh for a fuel balancing option, while for fuel switching option, PLN has to generate 29% of electricity from RE, and the COE is expected to increase to 535.85 IDR per kWh.
Indonesia’s Municipal Solid Waste 3R and Waste to Energy Programs Farizal, Farizal; Aji, Radityo; Rachman, Amar; Nasruddin, Nasruddin; Indra Mahlia, Teuku Meurah
Makara Journal of Technology Vol. 21, No. 3
Publisher : UI Scholars Hub

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Abstract

Like most cities in the world, population in Indonesia continues to grow every year. Problems that can arise from this are the increasing amount of municipal solid waste (MSW) production and the growing demand for electricity. To deal with the problems, Indonesian government runs 3R (Reduce, Reuse and Recycle) and WTE (Waste to Energy) Programs simultaneously. 3R program aims to reduce the number of waste, while WTE program aims to generate electricity as an alternative energy source. This study aims to find out the optimal proportion of MSW treated through the 3R and WTE programs. For the purpose, a goal programming model has been developed and solved using LINGO 11. The results showed that the optimal proportion of MSW through the 3R program is 49.90%, 12.37% through WTE program. This leaves 37.73% of waste untreated. The electricity generated from WTE program reached 1,229.695 GWh, total emissions that can be saved is 1,809,208.2 tons CO2 equivalent and total land-use for the programs is 4,036,239.1 m2. This study was enriched by performing some scenarios, i.e. adding budget allocation of WTE program, tightening the limit of total emission from waste management and reducing the limit of land-use for waste treatment.
Co-Authors Adizty Suparno Aji, Radityo Arian Dhini Farizal Farizal Hadi Al Rasyid, Hadi Al Indra Mahlia, Teuku Meurah Isti Surjandari Katsuhiko Takahashi, Katsuhiko Mahlia, Teuku Meurah Indra Nasruddin Nasruddin Purdianta Purdianta Septia, Wenty Eka Sumarsono Sudarto, Sumarsono Tifani Tandean, Tifani