Claim Missing Document
Check
Articles

Found 22 Documents
Search

Perancangan Perangkat Pembelajaran Internet of Things (IoT) dan Pengenalan Robotika Kepada Siswa Sekolah Menengah di Surakarta Sekitarnya Laksono, Pringgo Widyo; Damayanti, Retno Wulan; Rosyidi, Cucuk Nur; Pujiyanto, Eko; Jauhari, Wakhid Ahmad; Dwicahyani, Anindya Rachma
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Vol. 2, No. 2: August 2023
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.adipati.2023.v2i2.4784

Abstract

Pemahaman dan keterampilan pada siswa sekolah menengah mengenai Internet of Things (IoT) dan teknologi robotika adalah hal yang penting untuk menjawab tantangan global. Melalui pengenalan IoT dan robotika, siswa mendapatkan kesempatan untuk merancang, membangun, dan memprogram perangkat IoT dan robot secara langsung. Tujuan program ini adalah untuk memperkenalkan siswa pada konsep dan penerapan teknologi serta membantu mereka mengembangkan keterampilan yang relevan untuk dunia kerja abad ke-21. Siswa diharapkan dapat meningkatkan pemahaman mereka tentang IoT dan robotika, sehingga mereka lebih siap menghadapi tuntutan dunia kerja yang semakin berkembang di era revolusi industri 4.0. Selain itu, mitra industri yang terlibat dalam program ini, CV Enuma Technology, akan mendapatkan manfaat dalam mengembangkan produk media pembelajaran yang dapat dikomersilikilkan di pasar secara lebih luas. Melalui program ini, mitra industri dapat meningkatkan kualitas produk yang dibutuhkan oleh konsumen serta meningkatkan daya saing di pasar teknologi yang terus berkembang.
A Mixed Integer Linear Programming Model of Order Allocation Involving Mass Customization Logistic Service (MCLS) Rosyidi, Cucuk Nur; Sulistiani, Nina Salsabila; Laksono, Pringgo Widyo
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i3.15398

Abstract

In an increasing business competition, a company has to improve its competitiveness by focus more on supply chain management. One of the crucial problems in supply chain deals with the allocation of orders. More and more companies are starting to adoptMass Customization Logistics Service (MCLS) mode to determine the optimal allocations of order both from suppliers and to customized logistics services at the possible lowest cost. For this purpose, a third party is needed, namely Logistic Service Integrator (LSI) in providing logistics services. However, since LSI cannot meet all customer needs, LSI chooses to outsource logistics tasks to a Functional Logistics Service Provider (FLSP). This research was developed to help decision-makers ofmanufacturing companies in making optimal decision concerning order allocations that minimize the total supply chain costs involving Mass Customization Logistics Service (MCLS).
Penerapan Sistem Kontrol Kualitas dengan Mengunakan Model CNN Transfer Learning VGG 19 pada Inspeksi Kain di Industri Tekstil Nauval Hernandoko; Pringgo Widyo Laksono; Cucuk Nur Rosyidi
Performa: Media Ilmiah Teknik Industri Vol 23, No 2 (2024): Performa: Media Ilmiah Teknik Industri
Publisher : Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/performa.23.2.86589

Abstract

Industri tekstil dan produk tekstil (TPT) merupakan salah satu industri tertua di Indonesia. Tujuan industri ini dibangun awalnya yaitu untuk memenuhi kebutuhan dalam negeri dan ekspor. Kualitas produk dan produktivitas merupakan menjadi kunci keberhasilan sistem produksi dalam dunia industri. Hasil produk atau jasa yang memiliki kualitas tinggi menjadi faktor utama agar industri tersebut dapat bersaing dalam bisnis serta prospek jangka panjang. Adanya kontrol kualitas secara otomatis akan membantu dalam pekerjaan bagian inspeksi karena dalam industri tekstil proses inspeksi dilakukan tanpa teknik sampling sehingga kualitas inspeksi yang dilakukan manusia akan menurun seiring waktu inspeksi yang semakin banyak. Hasil dari penelitian ini yaitu model CNN VGG19 dapat dijadikan sebagai model untuk otomatisasi proses inspeksi yang dilakukan di industri tekstil karena akurasi testing yang mencapai 88% serta tidak terjadinya overffiting dalam proses training validation.
Effect of Chip Breaker Geometries on Cutting Force A Finite Element Analysis Fawzi Zamria, Mohd; Nor Sufyan Sudin, Mohd; Nur Rosyidi, Cucuk; Bin Yusoff, Ahmad Razlan
Indonesian Journal of Computing, Engineering, and Design (IJoCED) Vol. 7 No. 1 (2025): IJoCED
Publisher : Faculty of Engineering and Technology, Sampoerna University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35806/ijoced.v7i1.505

Abstract

Continuous chip formation during metal cutting operations poses substantial challenges, from deteriorating surface finish to accelerated tool wear. Our research examines how six chip breaker geometric parameters of insert rake angle, land, radius, width, height, and nose radius influence cutting forces in turning operations. Using DEFORM-3D, we simulated 27 distinct chip breaker configurations based on Taguchi's L27 orthogonal array while maintaining constant cutting parameters of 275 mm/min speed, 0.2 mm/rev feed, and 1.0 mm depth. ANOVA findings showed that nose radius was most influential with F-ratio equal to 27.41, followed by insert width and rake angle. The optimized geometry of the rake angle is 16°, the land is 0.1 mm, the radius is 0.5 mm, width is 2.0 mm, height is 0.25 mm, and the nose radius is 0.8 mm achieved the lowest cutting force of 798 N, a 15.8% reduction from the experimental average. This research replaces traditional trial-and-error approaches with systematic optimization, providing manufacturers with specific guidelines for enhancing chip control, surface quality, and tool life in industrial applications.
An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company Cucuk Nur Rosyidi; Erina Annastya Octaviani; Pringgo Widyo Laksono
Jurnal Optimasi Sistem Industri Vol. 22 No. 2 (2023): Published in December 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v22.n2.p142-152.2023

Abstract

Recognizing the paramount importance of operational effectiveness and resource management in supply chain management (SCM) of the fashion industry, this study addresses a specific challenge faced by a prominent Indonesian fashion footwear company. The inefficiency is due to repetitive sorting and packaging processes during product distribution, which significantly impact optimal production mixes and product distribution from the distribution center to the point of sale. A crucial aspect is also the optimization of the delivery route. To address these challenges and minimize the total cost of ownership, the study proposes an integrated optimization model. This model simultaneously determines the optimal production quantity, assortment packaging, and distribution channels, taking into account decision variables related to distribution in configuration boxes, overload and underload products, as well as production numbers that respond to store-specific demand fluctuations. A notable contribution of this research is the integration of product mix decisions into the assortment packaging and distribution model, which represents a novel approach. The optimal solution determined using the LINGO 18.0 software highlights the significant influence of product penalty costs and product demand parameters on the objective function, while shipping costs have no noticeable influence. By emphasizing the integration of product mix decisions into the optimization framework, this research contributes significantly to improving the understanding and practical application of efficient supply chain management in the fashion industry.
Order Allocation Model Considering Transportation Alternatives and Lateral Transhipment Ashylla Maharani; Cucuk Nur Rosyidi; Pringgo Widyo Laksono
Jurnal Optimasi Sistem Industri Vol. 21 No. 1 (2022): Published in April 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v21.n1.p38-45.2022

Abstract

Intense competition among companies encourages them to provide the best quality of products in competitive price. It is important for company to manage supply chain properly in order to achieve that. Selecting the best reliable supplier is the key to reduce purchasing cost, increase customer satisfaction and improve the competitive ability. In this study, we develop an order allocation model in multi echelon environment which includes supplier, manufacturer, and retailer. We consider transportation alternatives for the shipment from supplier to manufacturer and also the shipment from manufacturer to retailer. This model allows lateral transshipment between retailers. A Mixed Integer Linear Programming (MILP) is used to model the system. Sensitivity analysis is conducted at the end of the research. The result shows that the retailer demand, lead time, material variable price are sensitive to the objective function while the transportation costs from supplier to manufacturer, from manufacturer to retailers, and between retailers are not sensitive to the objective function. Retailer demand parameter is also sensitive to all decision variables. The transportation cost from supplier to manufacturer, material prices, and lead time are sensitive to the order allocation from manufacturer to supplier, while transportation cost from manufacturer to retailers and transportation cost between retailers are sensitive to the allocation of product sent from the manufacturer to retailers and the allocation of product sent between retailers.
A Framework for Sustainable Supplier Selection Integrating Grey Forecasting and F-MCDM Methods: A Case Study Enty Nur Hayati; Wakhid Ahmad Jauhari; Retno Wulan Damayanti; Cucuk Nur Rosyidi; Muhammad Hafidz Fazli Bin Md Fauadi
Jurnal Optimasi Sistem Industri Vol. 24 No. 1 (2025): Published in June 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v24.n1.p63-83.2025

Abstract

Selecting appropriate suppliers is critical for healthcare organizations to ensure high-quality, reliable, and sustainable patient care services. In an increasingly competitive environment, hospitals must optimize supplier selection not only based on economic factors but also by integrating environmental and social sustainability considerations. This study aims to create a strong system for choosing sustainable suppliers in healthcare by combining fuzzy-based multi-criteria decision-making (MCDM) methods with Grey Forecasting GM(1,1) to handle uncertainty and changes in performance over time. The proposed framework applies the Fuzzy Best-Worst Method (F-BWM) to determine the relative importance of sustainability criteria, while the Fuzzy Additive Ratio Assessment (F-ARAS) method is used to rank suppliers based on these weighted criteria. Grey Forecasting GM(1,1) is employed to predict supplier performance for future periods, with forecasting accuracy evaluated through Mean Absolute Percentage Error (MAPE). All supplier forecasts achieved MAPE values below 5%, indicating very high prediction reliability. Empirical results from a case study at a general hospital in Indonesia confirm that social aspects, such as patient safety and reputation, are prioritized over economic and environmental considerations. Practically, the proposed framework enables healthcare institutions to holistically evaluate suppliers, specifically reducing risks related to supply disruptions and quality inconsistencies. The model performs best under conditions of limited or uncertain data availability, where supplier historical performance trends can be leveraged to forecast future reliability and sustainability outcomes. The prioritization of sustainability criteria yields social criteria (weight = 0.3703) as the most important, followed by economic (0.3609) and environmental (0.2688) criteria.
Pelatihan Pengenalan Dasar Produk Berbasis Kecerdasan Buatan untuk Membekali Siswa Sekolah Menegah Atas Solo Raya Menyosong Era Revolusi Industri 5.0 Pringgo Widyo Laksono; Cucuk Nur Rosyidi; Retno Wulan Damayanti; Wakhid Ahmad Jauhari; Eko Pujiyanto; Andreas Wegiq Adia Hendix; Era Febriana Aqidawati
SEMAR (Jurnal Ilmu Pengetahuan, Teknologi, dan Seni bagi Masyarakat) Vol 14, No 2 (2025): November
Publisher : LPPM UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/semar.v14i2.94863

Abstract

Revolusi Industri 5.0 membawa dampak yang signifikan bagi masyarakat dalam berbagai aspek kehidupan, termasuk ekonomi, sosial, budaya, dan lingkungan. Meskipun demikian, pendidikan di Indonesia masih belum siap untuk beradaptasi dengan teknologi kunci dari revolusi ini, seperti kecerdasan buatan, energi terbarukan, dan keberlanjutan. Salah satu hambatannya adalah kurangnya fasilitas dan materi yang memadahi dalam pembelajaran. Oleh karena itu, sebuah pengabdian dilakukan untuk membantu sekolah- sekolah di sekitar UNS, khususnya SMA dan SMK di Solo Raya, dalam memulai pembelajaran berorientasi Revolusi Industri 5.0. Kegiatan pengabdian meliputi workshop, sosialisasi, pelatihan singkat, dan pemberian paket trainer. SMANRA dipilih sebagai sekolah pertama yang akan menerima pengabdian ini. Permasalahan yang dihadapi oleh SMANRA adalah kurangnya fasilitas yang memadahi dan sumber daya manusia yang belum menguasai dasar-dasar kecerdasan buatan dan internet of things. Solusi yang ditawarkan meliputi workshop dan sosialisasi tentang Revolusi Industri 5.0, serta pemberian paket trainer yang berisi perangkat keras, perangkat lunak, buku, dan materi pembelajaran terkait. Metode pelaksanaan kegiatan tersebut meliputi identifikasi kebutuhan, perencanaan kegiatan, pelaksanaan workshop dan sosialisasi, pemberian paket trainer, dan pendampingan teknis.Kata kunci : revolusi  industri 5.0, kecerdasan buatan, internet of things, inovasi, pembelajaran. 
Supplier Selection and Order Allocation in A Pharmaceutical Wholesaler Hikmah Fadilla, Ryan; Rosyidi, Cucuk Nur; Jauhari, Wakhid Ahmad
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 27 No. 1 (2025): June 2025
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.27.1.137-150

Abstract

Supplier selection is essential for any organization , as it plays a significant role in enhancing productivity. This study focuses on a local pharmaceutical wholesaler (PW) company, which places orders with other local PWs to meet its demand. Typically, pharmaceutical companies rely on multiple suppliers to satisfy their needs. However, due to an inadequate evaluation of supplier criteria, a Multi-Criteria Decision Making (MCDM) approach has been implemented to assist the PW in selecting superior suppliers and ensuring an efficient selection process. A key issue in this case study is the lack of a structured method for assessing supplier criteria, resulting in a subjective and lengthy selection process. The criteria for supplier selection encompass quality, flexibility, price, delivery, service, and supplier profile. Furthermore, alongside supplier selection, optimizing order allocation is essential for reducing purchasing costs while maximizing supplier scores. This research proposes a model designed to aid PW in addressing both supplier selection and order allocation challenges. The MCDM framework commences with the Best Worst Method (BWM) to establish the weight of each criterion. These weights then serve as input for the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which ranks and prioritizes suppliers based on their evaluation scores. Subsequently, the results from TOPSIS inform the determination of optimal order allocation through a Multi-Objective Optimization (MOO) method. As part of the system modeling, a sensitivity analysis was performed to explore the effects of specific parameters on the objective function and decision variables, assessing variations in inventory costs, shortage costs, and demand. The findings indicated that only the demand parameter had a significant effect on decision variables, particularly regarding inventory levels and shortages. This research offers a comprehensive solution for the PW to tackle supplier selection and optimal order allocation. By employing MCDM and multi-objective optimization strategies, the company can achieve lower purchasing costs while selecting optimal suppliers based on their evaluation scores. The optimization model presented has dual objective functions: minimizing costs and maximizing total supplier value. Consequently, the model achieved a total purchasing cost of Rp. 340,196,740 and a total supplier value of 5,265,032.
The Development of Order Quantity Optimization Model for Growing Item Considering the Imperfect Quality and Incremental Discount in Three Echelon Supply Chain Sitanggang, Indah Valentinova; Rosyidi, Cucuk Nur; Aisyati, Azizah
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 23 No. 2 (2021): Dec 2021
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.23.2.101-110

Abstract

This research develops an optimization model for determining the order quantity for growing items by considering the imperfect quality and incremental discount by involving three supply chain members: farmers, processors, and retailers. The farmers are responsible for caring for the newborn items until they reach their ready-to-eat weight. The processors perform two roles, namely processing and screening. In the processing role, the processors process the grown items by a slaughtering and packaging process. Afterward, they inspected the processed items and categorized the items into good and poor quality. Finally, they shipped the end products to retailers. The retailers are responsible for selling good-quality items to the final consumers.  This research considers two kinds of poor quality. First is the poor quality of growing items in terms of mortality rate. The second is the poor quality of final products on the processor side. The processed items with poor quality are then sold to the secondary market at lower prices in one batch at the end of the period. This model also considers the incremental discounts offered by vendors to farmers and retailers to consumers for specific amounts of purchases. The model's objective function is to maximize the total supply chain profit, with the number of orders quantity, cycle time, and the number of batches delivery set as the decision variables. The sensitivity analysis results show that the most sensitive parameter in the model is the probability that the live items survive throughout the growth period.