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All Journal Biospecies AL KAUNIYAH SPEKTRUM INDUSTRI TEKMAPRO Journal of Industrial Engineering and Management Inspiratif Pendidikan OPERATION EXCELLENCE: Journal of Applied Industrial Engineering PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Jurnal Penelitian Pendidikan IPA (JPPIPA) JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri Metode : Jurnal Teknik Industri Jurnal Biologi Tropis Tibuana : Journal of Applied Industrial Engineering Industri Inovatif : Jurnal Teknik Industri Matrik : Jurnal Manajemen dan Teknik Industri Produksi Dedikasi: Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Academia Open Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Indonesian Journal of Innovation Studies BIOMA : Jurnal Biologi dan Pembelajarannya Jurnal Pengabdian Masyarakat Akademisi PELS (Procedia of Engineering and Life Science) Takuana: Jurnal Pendidikan, Sains, dan Humaniora Jurnal Karya Abdi Masyarakat Journal of Fish Health Innovative Technologica: Methodical Research Journal Journal for Technology and Science IJOT Widya Teknik
Tedjo Sukmono
Universitas Muhammadiyah Sidoarjo
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Bahasa Indonesia Bahasa Indonesia Putri, Arinda Jayanti; Sukmono, Tedjo; Wicaksana, Ervan Johan
Jurnal Penelitian Pendidikan IPA Vol 9 No 9 (2023): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i9.4568

Abstract

This study aims to determine The Effect of Learning Models Problem Based Learning (PBL) Based on STEM Approach to E-Phase Critical Thinking Ability in Biology Learning. Research using type experimental research pretest-posttest control grup design with technique random sampling. So that phase E-5 was chosen as the experimental class, phase E-7 as the control class, with a total of 36 students in each class. The data analyzed were the results of the initial test and the final test on questions of critical thinking ability, with data analysis using the SPSS, testing the hypothesis using the ANOVA test. The results of the ANOVA test analysis show that the application of the Problem Based Learning (PBL) model based on the STEM approach has a significant effect on students' critical thinking skills at SMA Negeri 4 Jambi City. The data collection method used is a critical thinking ability test, response questionnaire, activity observation.
Effectiveness of CAD-CAM Application for the Development design and implementation of maintenance tools Budi, Yusuf Effri Prastyo; Sukmono, Tedjo
Jurnal Penelitian Pendidikan IPA Vol 9 No 9 (2023): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i9.4859

Abstract

This study aims to evaluate the effectiveness of using Computer-Aided Design and Computer-Aided Manufacturing (CAD-CAM) applications in developing the design and implementation of maintenance tools. The use of CAD-CAM has become a major trend in the modern manufacturing industry because it provides various advantages such as time efficiency, high precision and increased productivity. However, it is important to assess the true effectiveness of this technology in the context of maintenance tool development to fully understand its potential benefits. The literature review analysis method was used to compile an in-depth review of the latest research and publications related to the use of CAD-CAM in the design development and implementation of maintenance tools. A number of case studies and field experiments were also included in the analysis to provide further insight into the application of this technology in various industrial environments. The results of the analysis show that the use of CAD-CAM in the development of maintenance tool designs has brought significant positive changes. This application is able to reduce development cycle time, enable model-based engineering, and improve modeling accuracy. Apart from that, CAD-CAM also facilitates better collaboration between design teams, engineers and other stakeholders, which contributes to improving the quality of the final product. However, despite the many benefits offered by CAD-CAM, there are also challenges that need to be overcome to increase the effectiveness of its use. Some of these are high initial investment costs, the need for higher technical skills, and complex integration with existing infrastructure. In conclusion, CAD-CAM has proven effective in developing the design and implementation of maintenance tools. With this technology, companies can increase operational efficiency, improve product quality, and gain a competitive advantage in the market. By understanding the benefits and challenges of its use, professionals can more effectively adopt CAD-CAM and fully exploit its potential in the modern manufacturing industry.
Sand Supplier Selection Analysis Based on the Integration of Analytical Hierarchy Process (AHP) and Taguchi Quality Loss Function Methods: Analisa Pemilihan Supplier Pasir Berdasarkan Integrasi Metode Analytical Hierarchy Process (AHP) dan Taguchi Quality Loss Function Sofillauny, Zahara; Wahyuni, Hana Catur; Sukmono, Tedjo; Putra, Boy Isma
Indonesian Journal of Innovation Studies Vol. 21 (2023): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v21i.1043

Abstract

Supplier selection process is a step to evaluate and select the most suitable supplier to see the needs of the company or organization. This evaluation is important to ensure that the selected supplier is able to provide quality products or services, competitive prices, timely delivery, and meet ethical and sustainability standards. This research uses two methods, namely Analytical Hierarchy Process (AHP) and Taguchi Loss Function. AHP is used to calculate the weight of criteria, while the Taguchi Loss Function is used to estimate losses caused by suppliers. The criteria applied in supplier evaluation are quality criteria, product accuracy, delivery, price, warranty policy, and response to claims. The results obtained from this study PT. Bumi Makmur with a percentage loss of 21%, while the supplier that has the largest loss value is PT. Mergo Bopo with a percentage of 47%. Highlights : Integration of AHP and Taguchi Loss Function enhances supplier selection accuracy. Identified supplier exhibits substantial loss percentage, emphasizing the importance of thorough evaluation. Findings enable informed decision-making, facilitating risk mitigation and operational optimization Keywords :Supplier Evaluation; Sand; Analytical Hierarchy Process, Taguchi Loss Function
Fusing SVR with PSO Improves E-commerce Sales Prediction with 8.98% MAPE: Penggabungan SVR dengan PSO Meningkatkan Prediksi Penjualan E-commerce dengan MAPE 8,98% Angela, Fitrah Cornellya; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 2 (2024): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i2.1127

Abstract

This study explores the integration of Support Vector Regression (SVR) with Particle Swarm Optimization (PSO) to forecast clothing product sales at Nara Gallery Collection Boutique, addressing the challenge of achieving high forecast accuracy in e-commerce. Through literature review, direct observation, and interviews with a textile SME owner, SVR parameters are optimized using PSO. Results indicate a Mean Absolute Percentage Error (MAPE) value of 8.98% with optimized parameters (C = 34.3642, ε = 0.0110, σ = 0.3677, cLR = 0.1062, λ = 0.0117), enhancing decision-making in inventory management and strategic planning for e-commerce businesses. This research highlights the potential of integrating SVR with PSO for accurate sales forecasting and suggests avenues for further exploration in alternative forecasting methods and optimization techniques. Highlight: Enhanced Forecasting Accuracy: SVR and PSO integration improves e-commerce sales predictions. Parameter Optimization: PSO optimizes SVR parameters, reducing Mean Absolute Percentage Error. Strategic Inventory Management: Accurate forecasts aid in effective e-commerce inventory control. Keywoard: Support Vector Regression, Particle Swarm Optimization, Sales Forecasting, E-commerce, Inventory Management
Indonesia's Breakthrough in Efficient Shellfish Cleaning Transforms Seafood Industry: Terobosan Indonesia dalam Pembersihan Kerang yang Efisien Mengubah Industri Makanan Laut Setiawan, Ari Rio De; Jakaria, Ribangun Bamban; Sari , Indah Apriliana; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 2 (2024): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i2.1133

Abstract

This research aims to design an efficient cleaning tool for bloody cockles to help business actors meet high demand with limited production systems. Conducted in Sidoarjo, data was collected from literature, government reports, and interviews with local business actors, revealing that manual processing of 50 kg of cockles takes 6-8 hours. Using the morphological method, several design concepts were evaluated for maintenance ease, performance, safety, and durability. The selected design (concept 3) showed the highest efficiency with a 37.5% score. This tool is expected to reduce cleaning time and improve outcomes, enhancing productivity and quality in the seafood processing industry. Highlight: Efficient Design: Reduces cleaning time from 6-8 hours significantly. High Demand: Meets increased consumer demand with limited resources. Optimal Concept: Concept 3 excels in maintenance, safety, and efficiency. Keywoard: Bloody Cockles, Cleaning Tool, Morphological Method, Efficiency, Seafood Processing
Machine Learning Predicts Truck Breakdowns in Indonesia with 83% Accuracy: Machine Learning Memprediksi Kerusakan Truk di Indonesia dengan Akurasi 83% Rachman, Meisya Azzahra; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1156

Abstract

PT. Varia Usaha Beton, a cement product company, faces frequent breakdowns of mixer trucks, reducing reliability from the target 90% to 60%. This study aims to predict truck breakdowns using a machine learning model based on the K-NN algorithm within the CRISP-DM framework. Data from the company's maintenance records were cleaned and split into training and testing sets. With k=20, the model achieved 90% accuracy on training data and 83% on testing data. These results can help improve maintenance scheduling and resource planning, enhancing truck reliability. Future research should compare other algorithms and consider different programming environments. Highlights: High Accuracy: K-NN model achieved 90% training and 83% testing accuracy. Maintenance Aid: Improves scheduling and resource planning for truck maintenance. Future Research: Compare algorithms and explore different programming environments. Keywords: Predictive Maintenance, Mixer Trucks, K-NN Algorithm, CRISP-DM, Machine Learning
Unlocking Global Efficiency with Enhanced Milling Machines Worldwide: Membuka Efisiensi Global dengan Mesin Penggilingan Ditingkatkan di Seluruh Dunia Lestari, Wiwik Puji; Wulandari, Indah Apriliana Sari; Sukmono, Tedjo; Jakaria, Ribangun Bamban
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1157

Abstract

This study investigates the effectiveness of six milling machines at PT. INKA, a railroad car manufacturing company, focusing on CNC Plano 133 and Horizontal Milling 142. Utilizing Overall Equipment Effectiveness (OEE) and Age Replacement methods, the research aims to optimize machine performance and propose preventive maintenance strategies. Data spanning from January 2021 to December 2022 were collected and analyzed. Results indicate that both CNC Plano 133 and Horizontal Milling 142 exhibit suboptimal OEE values, primarily due to breakdown losses. Applying Age Replacement within 10 days significantly enhances reliability, with post-replacement reliability reaching 100%. The findings underscore the importance of preventive maintenance in improving milling machine reliability and overall productivity, thereby enhancing competitiveness and sustainability in the manufacturing sector. Highlight: Improved productivity: Preventive maintenance boosts milling machines' reliability and effectiveness. Resource efficiency: Analyzing OEE minimizes downtime, optimizes production output. Competitive edge: Enhanced performance sustains competitiveness, strengthens manufacturing sector's sustainability. Keyword: Milling machines, Overall Equipment Effectiveness (OEE), Preventive maintenance, Age Replacement, Manufacturing industry
Indonesia's Breakthrough in Optimized Yarn Forecasting for Textile Demand Accuracy: Terobosan Indonesia dalam Peramalan Benang yang Dioptimalkan untuk Akurasi Permintaan Tekstil Lindyawati, Lely; Sari W, Indah Apriliana; Cahyana , Atikha Sidhi; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1164

Abstract

PT. XY, a textile company specializing in woven sarongs, faces fluctuating demand during Islamic religious celebrations, impacting production. In Ramadhan 2023, production increased by 30%, but warp yarn availability was insufficient. This study forecasts warp yarn production over twelve periods, comparing Double Exponential Smoothing Holt’s (DES) and Holt-Winter’s Exponential Smoothing (WES) methods, optimized using the golden section method. Using historical data from January 2021 to April 2023, WES with golden section parameters (α1 = 0.67387, β1 = 0.08756, γ2 = 0.85408) achieved the best accuracy with a MAPE of 5.5437%. The WES method is recommended for improving production planning at PT. XY, with future research suggested to explore production correlations and procurement costs. Highlight: Demand Fluctuation: PT. XY experiences significant demand changes during Islamic religious celebrations. Forecasting Methods: Comparing DES and WES methods for predicting warp yarn production. Optimal Accuracy: WES with golden section optimization achieved the lowest MAPE of 5.5437%. Keywoard: Textile Industry, Warp yarn forecasting, Production Planning, Holt-Winter's method, Golden section optimization
Revolutionizing Crystal Guava Production through Six Sigma and Kaizen Insights: Merevolusi Produksi Jambu Kristal melalui Wawasan Six Sigma dan Kaizen Mauli, Fajar Dwi; Cahyana , Atikha Sidhi; Sukmono, Tedjo; Jakaria, Ribangun Bamban
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1169

Abstract

This study addresses the quality issues in crystal guava production at UD Bumiaji Sejahtera using the Six Sigma and Kaizen methodologies. By analyzing factors like non-uniform maturity, black spots, fruit rot, shape defects, and seed defects, this research aims to identify key areas for improvement. Results indicate that non-uniform maturity contributes significantly to defects, highlighting the need for improved pest control, efficient application methods, regular maintenance, material inspection, and enhanced standards for farmers and agricultural workers. These findings offer practical insights for enhancing crystal guava production quality and reducing defects at UD Bumiaji Sejahtera. Highlight: Six Sigma and Kaizen for Crystal Guava Quality Enhancement. Non-uniform Maturity Identified as Key Defect Contributor. Recommendations: Improved Pest Control, Application Methods, and Standards for Farmers. Keyword: Crystal Guava Production, Six Sigma, Kaizen, Quality Improvement, Defect Reduction
Markov Method Revolutionizes Paper Industry, Slashing Maintenance Costs Globally: Metode Markov Merevolusi Industri Kertas, Memangkas Biaya Pemeliharaan Secara Global Syaifullah, Dikril Ilham; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 4 (2024): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i4.1176

Abstract

Paper manufacturing industries rely on efficient machinery for production processes, yet neglecting maintenance can lead to substantial costs. This study addresses the maintenance cost optimization challenge in a Pasuruan paper company, where maintenance expenses exceed 20% of the standard. Utilizing the Markov chain method, the research identifies optimal paper machine maintenance costs, achieving a 32% cost reduction. By analyzing data from company documents and literature reviews, specific machine states are identified, recommending overhaul strategies to enhance operational efficiency. The study's implications underscore the method's effectiveness in reducing costs and improving productivity for paper manufacturing industries, offering valuable insights for similar sectors. Highlights: 1. Neglecting maintenance in paper manufacturing leads to substantial costs.2. Markov chain method optimizes paper machine maintenance, reducing expenses.3. Implementation of optimal maintenance strategies significantly enhances financial sustainability. Keywords: Paper manufacturing, Maintenance optimization, Markov chain method, Cost reduction, Operational efficiency.
Co-Authors Abdul Rohman Abdul Rohman Adistyas Nastiti, Octavia Afreni Hamidah Afrilia, Riska Agus Subagyo Ahmad Fikri Ardianto Alfian Fajar Gunawan Ali Mashar Ali Sadikin Amatullah, Dhiny Angela, Fitrah Cornellya Apriliana Sari Wulandari, Indah Arba, Risqi Mutia Asni Johari Azhari, Asri Bambang Haryadi Boy Isma Putra Budi, Yusuf Effri Prastyo Cahyana , Atikha Sidhi Dani Sartika Dawam Suprayogi Diwanti Faradiba, Nabila Dristiana, Fila Dwi Kakung Saputro Dzati Fauziyah Ervan Johan Wicaksana Erwin Widiantono Fila Dristiana Gusti Nurina Azhariani Hadian, Mohammad Ekki Hafizah, Mutia Hana Catur Wahyuni Harlis Harlis Hartanti, Lusia Permata Sari Hery Murnawan, Hery Ihsan, Mahya Jamaluddin Jamaluddin Khairatinisa, Khairatinisa Krisna Risky Putra Irawan Leksono, Rudy Bowo Lestari, Wiwik Puji Lindyawati, Lely M.Haris Efendi Hsb Mardhotillah, Bunga Marodiyah, Inggit Mauli, Fajar Dwi Mishani, Adinda Chamilia Mochammad Imam Mashuri Mohammad Buchori Much Syafiudin Muhammad Arizki Zainul Ramadhan Muhammad Dio Dwi Septian Mukhammad Surya Lesmana Muswita Muswita Nafis Khumaidah Natalia, Desfaur Nazifa, Boti Iffa Novi Prastyanda Putra Pratama Nugraha, A. Prima Nugroho, Dizsa Arliansyah Nurma M. Hidayatulloh Octavia Adistyas Nastiti Pangestu, Retno Putra, Tri Syukria Putri, Andini Faizatul Putri, Arinda Jayanti Putri, Melinda Aprilia Rachman, Meisya Azzahra Radiana Atika Sari Rany Riyantati, Dena Rasyid, Mohammad Andi Ribangun Bamban Jakaria Rizky Janatul Magwa Rudy Bowo Leksono Salsabila, Nisrina SANDI KURNIAWAN Sanjaya, Muhammad Erick Saputra, Nur Qomaruddin Sari , Indah Apriliana Sari W, Indah Apriliana Sari Wulandari, Indah Apriliana Setiawan, Ari Rio De Sigit Wahono sisiliani, fitria trisna Sofillauny, Zahara Suhadak Sulistiono Suzanti, Sriliah Syaifullah, Dikril Ilham Tia Wulandari Upik Yelianti Utomo, Pradita Eko Prasetyo Varid Jainuri Wahono, Sigit Wahyu Nugroho Wahyu Setiawan, Ardhi Wardhani, Devira Kusuma Wawan Kurniawan Wijatmiko, Erie Fadma Noer Fitriana Winda Dwi Kartika, Winda Dwi Wiwik Sulistiyowati Wulandari, Indah Apriliana Sari Yoppie Wulanda Zurweni Zurweni