Articles
<![CDATA[Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Teguh Baroto]]>;
<![CDATA[Dewi Maharani]]>;
<![CDATA[Fathiha Raudhatul Jannah]]>;
<![CDATA[Ricca Andhini Octaria]]>
<![CDATA[ Jurnal Litbang Industri Vol 9, No 1 (2019) ]]>
Publisher : <![CDATA[Institution for Industrial Research and Standardization of Industry - Padang ]]>
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DOI: 10.24960/jli.v9i1.4775.69-78
<![CDATA[Industri manufaktur akhir-akhir ini dituntut untuk memperhatikan isu lingkungan. Pemakaian energi pada produksi umumnya menghasilkan emisi karbon. Emisi karbon ini menjadi permasalahan di lingkungan. Untuk mengurangi pemakaian emisi karbon, penelitian ini menggabungkan metode penjadwalan dan emisi karbon sebagai solusi dalam masalah lingkungan. Kasus pada artikel ini adalah flow shop dependent sequence set-up. Jurnal ini mengusulkan algoritma baru Ant Lion Optimizer (ALO) yang terinspirasi oleh alam untuk meminimasi emisi karbon. Beberapa percobaan numerik dilakukan untuk mengetahui parameter terbaik dari Algoritma ALO. Untuk menguji keefektifan dari algoritma, Algoritma ALO ini dibandingkan dengan beberapa algoritma populer saat ini. Hasil percobaan numerik menunjukan algoritma ALO efektif untuk meminimasi emisi karbon.ABSTRACTManufacture industry recently is required to pay attention of enviromental issue. The use of energy in production generally produces carbon emissions. This carbon emission is a problem in the environment. This study combines scheduling methods and carbon emissions as a solution to environmental issues to reduce the use of carbon emissions. The case in this article is the flow shop dependent sequence set-up. This journal proposes a new Ant Lion Optimizer (ALO) algorithm inspired by nature to minimize carbon emissions. Several numerical experiments were conducted to determine the best parameters of the ALO algorithm. This ALO algorithm is compared with several popular algorithms today. The numerical experiment results show that the ALO algorithm is useful for minimizing carbon emissions.]]>
<![CDATA[Program Kemitraan Masyarakat Industri Keripik Tempe Desa Bakalan Krajan Kecamatan Sukun ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Teguh Baroto]]>
<![CDATA[ ETHOS (Jurnal Penelitian dan Pengabdian) Vol 8 No.2 (Juni, 2020) Ethos: Jurnal Penelitian dan Pengabdian kepada Masyarakat (Sains & Teknologi ]]>
Publisher : <![CDATA[Universitas Islam Bandung ]]>
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DOI: 10.29313/ethos.v8i2.5379
<![CDATA[Abstract. Indonesian community are known as a community that likes to consume Tempe. Tempe chips are one of the special food from Malang. Community partnership Activities (PKM) are carried out in Bakalankrajan of sukun in Malang. The partners of Community Partnership Activities (PKM) is “Londho” Tempe chips. Problems that must be resolved immediately include: 1) increasing the quality and production capacity that is more effective and efficient production, especially in the packaging process. 2) Improving the management production of marketing properly to increase the sales of Tempe chips. The Implementation method of PKM is through the participatory Rural Apprasial (PRA). The result of continuous sealer appropriate technology (TTG) assistance shows that there is an increase of Tempe chips production. The result of marketing management training shows that there is an increase in business marketing management knowledge. Furthermore, the result of marketing management training can increase product sales turnover.Keywords: PKM, Chips, Marketing, TTG.Abstrak. Masyarakat Indonesia dikenal dengan masyarakat yang gemar mengonsumsi tempe. Keripik tempe merupakan salah satu makanan dan oleh-oleh khas Kota Malang. Kegiatan Program Kemitraan Masyarakat (PKM) dilaksanakan di Kelurahan Bakalankrajan Kecamatan Sukun Kota Malang. Mitra di kegiatan PKM ini adalah keripik tempe “Londho”. Masalah yang harus diselesaikan segera diantaranya 1). peningkatkan kualitas dan kapasitas produksi yang lebih efektif dan efisien khususnya pada proses pengemasan. 2). Peningkatan pengelolaan manajemen pemasaran dengan baik sehingga dapat meningkatkan penjualan keripik tempe. Metode pelaksanaan kegiatan PKM ini melalui Participatory Rural Apprasial (PRA). Hasil bantuan teknologi tepat guna (TTG) continious sealer menunjukan terdapat peningkatan produksi keripik tempe. Hasil pelatihan manajemen pemasaran menunjukan terdapat peningkatan pengetahuan manajemen pemasaran usaha. Lebih lanjut, hasil pelatihan manajemen pemasaran dapat meningkatkan omzet penjualan produk.Kata Kunci: PKM, Keripik, Pemasaran, TTG.]]>
<![CDATA[LPT-Branch and Bound Algorithm in Flexible Flowshop Scheduling to Minimize Makespan ]]>
<![CDATA[Dana Marsetiya Utama]]>
<![CDATA[ PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Vol 2 No 1 (2018): June ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Sidoarjo ]]>
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DOI: 10.21070/prozima.v2i1.1527
<![CDATA[This article discussed the problem of flow shop scheduling to minimize the makespan. The purpose of this article is to develop the LPT and Branch And Bound (LPT-Branch And Bound) algorithms to minimize the makespan. The proposed method is Longest Processing Time (LPT) and Branch And Bound. Stage settlement is divided into 3 parts. To proved the proposed algorithm, a numerical experiment was conducted by comparing the LPT-LN algorithm. The result of the numerical experiment shows that LPT-Branch And Bound's proposed algorithm is more efficient than the LPT-LN algorithm.]]>
<![CDATA[Penguatan Aspek Manajemen Produksi dan Kualitas Tempe Pada UKM Tempe ]]>
<![CDATA[Dana Marsetiya Utama]]>
<![CDATA[ JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) VOL. 3 NOMOR 1 MARET 2019 JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) ]]>
Publisher : <![CDATA[Lembaga Publikasi Ilmiah dan Penerbitan (LPIP) ]]>
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DOI: 10.30595/jppm.v3i1.3641
<![CDATA[Kegiatan ini dilaksanakan di Kelurahan Bakalankrajan Kecamatan Sukun Kota Malang. Mitra dari kegiatan PKM ini adalah UKM tempe “Londho”. Masalah yang terjadi di mitra adalah usaha belum membuat standart prosedur produksi yang jelas. Sehingga terkadang kualitas tempe tidak terjaga. Kegiatan ini bertujuan meningkatkan manajemen produksi dan kualitas usaha pada industri tempe di Kelurahan Bakalankrajan Kecamatan Sukun Kota Malang. Metode pelaksanaan kegiatan ini melalui Participatory Rural Apprasial (PRA). Pelaksanaan kegiatan dilakukan dengan pelatihan dan pendampingan manajemen produksi dan kualitas usaha pada industri tempe. Pelatihan diberikan kepada 10 peserta. Materi yang disampaikan pada kegiatan tersebut adalah memberikan gambaran tahapan proses produksi yang baik dan lama proses perebusan kedelai untuk mendapatkan kualitas tempe yang baik.Kesuksesan PKM diukurmelalui peningkatan pengetahuan mitra tentang manajemen produksi dan kualitas usaha pada industri tempe. Hasil pelatihan tersebut menunjukan peningkatan kuantitas produksi, pengetahuan dan keterampilan manajemen produksi dan kualitas usaha industri tempe. Hasil ini menunjukan program PKM efektif untuk meningkatkan kuantitas produksi serta manajemen keuangan usaha.]]>
<![CDATA[A Modified Camel Algorithm for Optimizing Green Vehicle Routing Problem with Time Windows ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Wa Ode Nadhilah Safitri]]>;
<![CDATA[Annisa Kesy Garside]]>
<![CDATA[ Jurnal Teknik Industri Vol. 24 No. 1 (2022): June 2022 ]]>
Publisher : <![CDATA[Institute of Research and Community Outreach - Petra Christian University ]]>
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DOI: 10.9744/jti.24.1.23-36
<![CDATA[In recent years, the issue of fuel depletion has become a significant problem in the world. The logistics sector is one of the sectors with an increase in fuel consumption. Therefore, route optimization is one of the attempts to solve the problem of minimization fuel consumption. In addition, this problem generally also has time windows. This study aimed to solve the Green Vehicle Routing Problem with Time Windows (GVRPTW) using the Camel Algorithm (CA). The objective function in this problem was to minimize the total cost of distribution, which involves the cost of fuel consumption and the cost of late delivery. The CA parameter experiment was conducted to determine the effect of the parameter on distribution cost and the computation time. In addition, this study also compared the CA algorithm's performance with the Local search algorithm, Particle Swarm Optimization, and Ant Colony Optimization. Results of this study indicated that the use of Camel population parameters and the total journey step affected the quality of the solution. Furthermore, the research results showed that the proposed algorithm had provided a better total distribution cost than the comparison algorithm.]]>
<![CDATA[Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Teguh Baroto]]>;
<![CDATA[Dewi Maharani]]>;
<![CDATA[Fathiha Raudhatul Jannah]]>;
<![CDATA[Ricca Andhini Octaria]]>
<![CDATA[ Jurnal Litbang Industri Vol 9, No 1 (2019) ]]>
Publisher : <![CDATA[Institution for Industrial Research and Standardization of Industry - Padang ]]>
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DOI: 10.24960/jli.v9i1.4775.69-78
<![CDATA[Industri manufaktur akhir-akhir ini dituntut untuk memperhatikan isu lingkungan. Pemakaian energi pada produksi umumnya menghasilkan emisi karbon. Emisi karbon ini menjadi permasalahan di lingkungan. Untuk mengurangi pemakaian emisi karbon, penelitian ini menggabungkan metode penjadwalan dan emisi karbon sebagai solusi dalam masalah lingkungan. Kasus pada artikel ini adalah flow shop dependent sequence set-up. Jurnal ini mengusulkan algoritma baru Ant Lion Optimizer (ALO) yang terinspirasi oleh alam untuk meminimasi emisi karbon. Beberapa percobaan numerik dilakukan untuk mengetahui parameter terbaik dari Algoritma ALO. Untuk menguji keefektifan dari algoritma, Algoritma ALO ini dibandingkan dengan beberapa algoritma populer saat ini. Hasil percobaan numerik menunjukan algoritma ALO efektif untuk meminimasi emisi karbon.ABSTRACTManufacture industry recently is required to pay attention of enviromental issue. The use of energy in production generally produces carbon emissions. This carbon emission is a problem in the environment. This study combines scheduling methods and carbon emissions as a solution to environmental issues to reduce the use of carbon emissions. The case in this article is the flow shop dependent sequence set-up. This journal proposes a new Ant Lion Optimizer (ALO) algorithm inspired by nature to minimize carbon emissions. Several numerical experiments were conducted to determine the best parameters of the ALO algorithm. This ALO algorithm is compared with several popular algorithms today. The numerical experiment results show that the ALO algorithm is useful for minimizing carbon emissions.]]>
<![CDATA[An Energy-Efficient No Idle Permutations Flow Shop Scheduling Problem Using Grey Wolf Optimizer Algorithm ]]>
<![CDATA[Cynthia Novel Al-Imron]]>;
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Shanty Kusuma Dewi]]>
<![CDATA[ Jurnal Ilmiah Teknik Industri Vol. 21, No. 1, June 2022 ]]>
Publisher : <![CDATA[Department of Industrial Engineering Universitas Muhammadiyah Surakarta ]]>
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DOI: 10.23917/jiti.v21i1.17634
<![CDATA[Energy consumption has become a significant issue in businesses. It is known that the industrial sector has consumed nearly half of the world's total energy consumption in some cases. This research aims to propose the Grey Wolf Optimizer (GWO) algorithm to minimize energy consumption in the No Idle Permutations Flowshop Problem (NIPFP). The GWO algorithm has four phases: initial population initialization, implementation of the Large Rank Value (LRV), grey wolf exploration, and exploitation. To determine the level of machine energy consumption, this study uses three different speed levels. To investigate this problem, 9 cases were used. The experiments show that it produces a massive amount of energy when a job is processed fast. Energy consumption is lower when machining at a slower speed. The performance of the GWO algorithm has been compared to that of the Cuckoo Search (CS) algorithm in several experiments. In tests, the Grey Wolf Optimizer (GWO) outperforms the Cuckoo Search (CS) algorithm.]]>
<![CDATA[A Novel Hybrid Archimedes Optimization Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Ayu An Putri Salima]]>;
<![CDATA[Dian Setiya Widodo]]>
<![CDATA[ International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
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<![CDATA[The manufacturing sector accounts for a dominant proportion of global energy consumption. This sector has become the center of attention since the concern of the energy crisis rose. One of the strategies proposed to overcome this issue is implementing appropriate scheduling, such as Hybrid Flow Shop Scheduling. This research aimed to develop a Hybrid Archimedes Optimization Algorithm (HAOA) to solve Energy-Efficient Hybrid Flow Shop Scheduling (EEHFSP). In this research, three stages of EEHFSP are considered in a problem that involves sequence-dependent setup time in the second stage. The removal time also is involved in the second stage. The results indicated that the iteration and the population of HAOA did not affect the removal and processing energy consumptions but affected the setup and idle energy consumptions. The algorithm comparison of ten cases showed that the proposed HAOA resulted in an optimum TEC compared to the other algorithms. The manufacturing sector accounts for a dominant proportion of global energy consumption. This sector has become the center of attention since the concern of the energy crisis rose. One of the strategies proposed to overcome this issue is implementing appropriate scheduling, such as Hybrid Flow Shop Scheduling. This research aimed to develop a Hybrid Archimedes Optimization Algorithm (HAOA) to solve Energy-Efficient Hybrid Flow Shop Scheduling (EEHFSP). In this research, three stages of EEHFSP are considered in a problem that involves sequence-dependent setup time in the second stage. The removal time also is involved in the second stage. The results indicated that the iteration and the population of HAOA did not affect the removal and processing energy consumptions but affected the setup and idle energy consumptions. The algorithm comparison of ten cases showed that the proposed HAOA resulted in an optimum TEC compared to the other algorithms.]]>
<![CDATA[Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model ]]>
<![CDATA[Dana Marsetiya Utama]]>;
<![CDATA[Imam Santoso]]>;
<![CDATA[Yusuf Hendrawan]]>;
<![CDATA[Wike A. P. Dania]]>
<![CDATA[ Indonesian Journal of Science and Technology Vol 8, No 2 (2023): (ONLINE FIRST) IJOST: September 2023 ]]>
Publisher : <![CDATA[Universitas Pendidikan Indonesia ]]>
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DOI: 10.17509/ijost.v8i2.54056
<![CDATA[An adequate sustainable production inventory model is expected to represent complex real-life cases involving fuel, emissions, and electricity costs as well as multi-materials, quality degradation, and probabilistic demand. Therefore, this study was conducted to develop this kind of model to determine the number of raw material shipments (), production cycle time (), and the number of finished goods delivered (n) to maximize the Expected Total Profit (ETP). The proposed model is based on a bibliometric literature analysis of the sustainable production-inventory problem which is visualized using the VOSviewer. Moreover, a sophisticated Harris-Hawks Optimization (HHO) algorithm was proposed to solve the problems identified in the sustainable production inventory model optimization. It is also important to note that three numerical cases were provided to evaluate the performance of the algorithm. The findings showed that the suggested HHO method outperforms the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in maximizing ETP and this means it is better for ETP optimization. It was also discovered from the sensitivity analysis that an increase in the rate of quality degradation (k) led to a reduction in both the ETP and T.]]>
<![CDATA[No-Wait Flowshop Permutation Scheduling Problem : Fire Hawk Optimizer Vs Beluga Whale Optimization Algorithm ]]>
<![CDATA[Muhammad Aghniya Baihaqi]]>;
<![CDATA[Dana Marsetiya Utama]]>
<![CDATA[ Jurnal Ilmiah Teknik Industri Vol. 22, No. 1, June 2023 ]]>
Publisher : <![CDATA[Department of Industrial Engineering Universitas Muhammadiyah Surakarta ]]>
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DOI: 10.23917/jiti.v22i1.21128
<![CDATA[No-Wait Flowshop Permutation Scheduling Problem (NWPFSP) is a scheduling problem that states that every job completed on machine n must be processed immediately on the next machine. The NWPFSP problem is an extension of the flowshop problem. This article proposes two new algorithms fire hawk optimization and beluga whale optimization, to solve the NWPFSP problem and minimize makespan. The two new algorithms developed to solve the NWPFSP problem are tested on three different cases. Each algorithm was run 30 times and was compared using an independent sample t-test. The results were also compared with the Campbell Dudek Smtih algorithm. In addition, the effectiveness of the FHO and BWO algorithms was assessed against the CDS algorithm using the Relative Error Percentage (REP) method. The results show that the FHO and BWO algorithms are better at solving NWPFSP problems when compared to the CDS algorithm. However, the BWO algorithm is more recommended in cases with large data because it can provide better results.]]>
