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Studi Komparasi Keterampilan Menulis dan Karakteristik Teks Berita di Boarding School Ma'ruf, Anas; Sudaryanto, Memet; Bivit Anggoro Prasetyo
GHANCARAN: Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol. 5 No. 1 (2023)
Publisher : Tadris Bahasa Indonesia, Fakultas Tarbiyah, Institut Agama Islam Negeri Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19105/ghancaran.v5i1.8418

Abstract

This research was motivated by the implementation of the boarding school education system. In boarding schools, there are students living in dormitories and outside dormitories. This does not deny that there will be differences in the condition of the student. No exception to the writing skills and characteristics of news texts. This study aims to determine the comparison of writing skills and news text characteristics between boarding and non-boarding students. This research is a comparative research with a qualitative descriptive approach conducted at MTs Al Ikhsan Beji, Kedungbanteng. Data collection techniques in this study used performance, documentation, and interview methods. The results showed that; (1) there are differences in the writing skills of news texts of boarding and non-boarding students; (2) the news text writing skills of boarding students are slightly better than non-boarding students; and (3) the most striking characteristic differences between boarding and non-boarding student news texts are in the selection of venues and topics. The conclusion of this study provides related suggestions when learning to write news texts, teachers should use methods that make students feel happy, and in writing news texts, teachers should also assign news text editing, so that student news text results are minimal.
A Model of Proactive-Reactive Job Shop Scheduling to Tackle Uncertain Events with Greedy Randomized Adaptive Search Procedure Nisar, Muhammad Usman; Ma'ruf, Anas; Cakravastia, Andi; Halim, Abdul Hakim
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22208

Abstract

Despite substantial research on job shop scheduling (JSS), there is a gap owing to the lack of a unified framework that considers exact, heuristic, and metaheuristic methods for JSS. This study addressed this gap by presenting a comprehensive approach. The study offered following contributions in this regard: analyzed the exact optimization method for benchmarking, investigated a greedy algorithm (G_r A) for faster solutions, and implemented a novel Greedy Randomized Adaptive Search Procedure (GRASP) to achieve high-quality solutions with computational effectiveness. Additionally, this study considered serious dynamic events (SDE) such as new job arrivals (NJA), rush order (RO), machine failures (MF), and scheduled machine maintenance (SMM), as scheduling disruptions and proposed a proactive-reactive rescheduling strategy, with right-shift (RF) and regeneration (Reg) methods using a hybrid (periodic and event-driven) policy to tackle them. Results showed that the exact methods are optimal but computationally intensive, G_r A are faster but suboptimal, and GRASP strike a balance, delivering high-quality solutions with only a 3.43% gap from exact methods while maintaining computational efficiency. Additionally, RF method effectively handled MF, while Reg efficiently integrated NJA, RO, and SMM. Overall, this study offered a comprehensive approach to JSS, enhancing applicability in manufacturing environments.
Rubber (Latex) Cutting Process Considering the Cost of the Double Cut Alternative (DCA) Process in Human and Robot Collaboration Akbar, Adi; Ma'ruf, Anas
Journal of Research in Industrial Engineering and Management Vol 2 No 2 (2024): November 2024
Publisher : Program Studi Teknik Industri, Fakultas Teknologi Industri, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61221/jriem.v2i2.41

Abstract

Technological developments allow human-robot collaboration resources to be carried out in the rubber (latex) cutting process in plantations. The human-robot collaboration activities are carried out simultaneously in each rubber tree but have different work tasks. Research regarding human-robot collaboration resource costs in the rubber (latex) cutting process activity is still minimal, so it is necessary to discuss and calculate the resource costs of human-robot collaboration by developing mathematical models. Research regarding the resource costs of human-robot collaboration in the rubber (latex) cutting process is still minimal, so discussion and calculations are needed with the development of mathematical models. Mathematical model development is not just a theoretical exercise. The practical goal is to minimize costs by considering human resources, robots, and human-robot collaboration. Through rigorous testing, we aim to minimize the cost of each resource. Test results show that human-robot collaboration resources can significantly influence cost minimization. Cost minimization is accomplished by programming an algorithm in optimization software. This program is used to make it easier to complete the optimal solution in terms of relatively fast time, which refers to the precedence diagram of the rubber (latex) cutting process.Based on the results of experimental data, the development of a mathematical model functions logically to solve resource placement problems, resulting in a minimum cost of IDR 1,618,234,564,595, total human resources of 1 person and robot resources of 1 unit.
A Model of Proactive-Reactive Job Shop Scheduling to Tackle Uncertain Events with Greedy Randomized Adaptive Search Procedure Nisar, Muhammad Usman; Ma'ruf, Anas; Cakravastia, Andi; Halim, Abdul Hakim
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22208

Abstract

Despite substantial research on job shop scheduling (JSS), there is a gap owing to the lack of a unified framework that considers exact, heuristic, and metaheuristic methods for JSS. This study addressed this gap by presenting a comprehensive approach. The study offered following contributions in this regard: analyzed the exact optimization method for benchmarking, investigated a greedy algorithm (G_r A) for faster solutions, and implemented a novel Greedy Randomized Adaptive Search Procedure (GRASP) to achieve high-quality solutions with computational effectiveness. Additionally, this study considered serious dynamic events (SDE) such as new job arrivals (NJA), rush order (RO), machine failures (MF), and scheduled machine maintenance (SMM), as scheduling disruptions and proposed a proactive-reactive rescheduling strategy, with right-shift (RF) and regeneration (Reg) methods using a hybrid (periodic and event-driven) policy to tackle them. Results showed that the exact methods are optimal but computationally intensive, G_r A are faster but suboptimal, and GRASP strike a balance, delivering high-quality solutions with only a 3.43% gap from exact methods while maintaining computational efficiency. Additionally, RF method effectively handled MF, while Reg efficiently integrated NJA, RO, and SMM. Overall, this study offered a comprehensive approach to JSS, enhancing applicability in manufacturing environments.
Development of genetic algorithm for human-robot collaboration assembly line design Ma'ruf, Anas; Budhiarti, Diniarie
International Journal of Industrial Optimization Vol. 5 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v5i2.10027

Abstract

An assembly line requires flexibility due to a shorter product life cycle. A way to increase flexibility is to utilize collaborative robots or cobots. Due to frequent product changes, redesigning an assembly line requires an efficient algorithm. This research aims to develop a genetic algorithm (GA) for solving a human-cobots assembly line design. The setup time of cobots is considered due to the flexibility of conducting multiple tasks by exchanging tools / end-effectors. The main contribution of the research is the efficient GA for solving assembly lines considering setup time. Secondly, the study proposed an upper limit parameter that enables faster computation without sacrificing the quality of the solution. The computational results showed that the algorithm could achieve an optimal solution with the number of tasks less than 35. Experiments of several data prove the proposed GA obtained solutions with an average gap of 3.83% to the optimal solution. Also, a faster computation time with an average difference of 64.66%. The proposed GA obtained a reasonable solution with fast computing time that helps improve efficiency and effectiveness in decision-making related to frequent redesigning of assembly lines.
Fixture Planning for Multi-Workpiece Setup for Make-to-Order Industry Ma'ruf, Anas; Siregar, Edwin Syalli
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 26 No. 1 (2024): June 2024
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.26.1.1-8

Abstract

An alternative method to reduce setup time is to simultaneously carry out fixture planning for several parts in one setup planning. This is possible due to the size of parts which are relatively small to the size of the machine work bed, typically found in a make-to-order industry. This research proposed a fixture planning method for multi-workpiece setup. The fixture planning method comprised two stages: 1) multi-workpiece layout and 2) 3-2-1 pin location. An example of multiple workpiece setup is illustrated in this paper to point out the method's applicability. Future research activity will integrate the proposed collaborative human-robot assembly design system method.