Vitamin and mineral deficiency are often ignored because they do not have a direct impact on body health. However, prolonged deficiency can cause various diseases from mild to serious illness. Some previous research in computer science already conducted to make early detection of vitamin and mineral deficiency, but no one has produced an adaptive model to find out the most dominant type of deficiency. Therefore, the goal of this research is to develop an adaptive model using an artificial neural network (ANN) with Linear Vector Quantization (LVQ) as the learning algorithm to make early detection of vitamin and mineral deficiency. LVQ consists of three layers: an input layer that represents the features, output layer that represent the class label, and the competitive layer. The competitive layer will save the distance between the input vector and the codebook vector from each class. The distance will calculate using Euclidean Distance. LVQ also involves some parameters in the training process, like epsilon value, learning rate, codebook vector, epoch, and window size which obtained by trial and error experiment. This research will also compare the performance of some version of LVQ. The experiment results show that the maximum accuracy level obtained by the system is 85.71% by using LVQ3. The dataset used split into data training and data testing with a ratio 84:16 respectively. From our scenario, the optimum model was achieved by using 20 codebook vectors with the number of epochs is 3400 and the value of the learning rate parameter (&agr;) of 0.4, window size (ō) of 0.3, and epsilon (ε) of 0.2.
{"title":"The Comparison of Some Version of Linear Vector Quantization (LVQ) for Vitamin and Mineral Deficiency Early Detection","authors":"N. Sevani, I. A. Soenandi, R. K. Sali","doi":"10.1145/3429789.3429869","DOIUrl":"https://doi.org/10.1145/3429789.3429869","url":null,"abstract":"Vitamin and mineral deficiency are often ignored because they do not have a direct impact on body health. However, prolonged deficiency can cause various diseases from mild to serious illness. Some previous research in computer science already conducted to make early detection of vitamin and mineral deficiency, but no one has produced an adaptive model to find out the most dominant type of deficiency. Therefore, the goal of this research is to develop an adaptive model using an artificial neural network (ANN) with Linear Vector Quantization (LVQ) as the learning algorithm to make early detection of vitamin and mineral deficiency. LVQ consists of three layers: an input layer that represents the features, output layer that represent the class label, and the competitive layer. The competitive layer will save the distance between the input vector and the codebook vector from each class. The distance will calculate using Euclidean Distance. LVQ also involves some parameters in the training process, like epsilon value, learning rate, codebook vector, epoch, and window size which obtained by trial and error experiment. This research will also compare the performance of some version of LVQ. The experiment results show that the maximum accuracy level obtained by the system is 85.71% by using LVQ3. The dataset used split into data training and data testing with a ratio 84:16 respectively. From our scenario, the optimum model was achieved by using 20 codebook vectors with the number of epochs is 3400 and the value of the learning rate parameter (&agr;) of 0.4, window size (ō) of 0.3, and epsilon (ε) of 0.2.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132543368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Eridani, I. P. Windasari, Risma Septiana, Jojor Kakanda Purba, Fanny Hasbi, Dita Ananda Elisa Reviana
ISO 45001 is a standard that provides a framework for an organization to manage risks and opportunities to help prevent work-related injury and ill-health to workers. There is also an injury in the campus area, and ill-health possibilities happened to the student, lecturer, laboratory assistant, or other academic staff, especially in laboratories. This work proposes developing an occupational health and safety management system in the Engineering Faculty of Diponegoro University. The methodology used is Scrum Model. The Test Case is also used to make sure the application meets the Client expectation. The result showed that the method leads to an application that meets Client expectations.
ISO 45001是一个标准，为组织提供了一个框架来管理风险和机会，以帮助预防与工作有关的伤害和工人的健康问题。校园区域也有伤害，学生、讲师、实验室助理或其他学术人员(特别是实验室人员)可能会受到伤害。这项工作建议在迪波涅戈罗大学工程学院建立职业健康和安全管理体系。使用的方法是Scrum模型。测试用例还用于确保应用程序满足客户期望。结果表明，该方法生成的应用程序满足客户的期望。
{"title":"Occupational Health and Safety Management System in Engineering Faculty of Diponegoro University Using Scrum Model","authors":"D. Eridani, I. P. Windasari, Risma Septiana, Jojor Kakanda Purba, Fanny Hasbi, Dita Ananda Elisa Reviana","doi":"10.1145/3429789.3429793","DOIUrl":"https://doi.org/10.1145/3429789.3429793","url":null,"abstract":"ISO 45001 is a standard that provides a framework for an organization to manage risks and opportunities to help prevent work-related injury and ill-health to workers. There is also an injury in the campus area, and ill-health possibilities happened to the student, lecturer, laboratory assistant, or other academic staff, especially in laboratories. This work proposes developing an occupational health and safety management system in the Engineering Faculty of Diponegoro University. The methodology used is Scrum Model. The Test Case is also used to make sure the application meets the Client expectation. The result showed that the method leads to an application that meets Client expectations.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132880700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the online marketplace and beauty care services is growing rapidly, many customers are booking services and buying products online, as it is more convenient. KerenAja is a platform where customers can book services and buy products that is aimed towards male. But as online marketplace's structure is kind of confusing, users tends to leave. Therefore, it is important to measure the user experience of the user when using the online marketplace, so the user experience can be improved. So, user experience questionnaire is used to measure the user experience of vendors and customers when using KerenAja. Later on, after gathering the data from customers and vendors, the user experience can then be evaluated. The result shows that the user experience of KerenAja's customer side is above average, while the user experience of KerenAja's vendor side is below average.
{"title":"User Experience (UX) Evaluation of Online Marketplace for Beauty Care Services: Case Study Kerenaja","authors":"Arvan Halim, Kho I Eng, James Purnama","doi":"10.1145/3429789.3429828","DOIUrl":"https://doi.org/10.1145/3429789.3429828","url":null,"abstract":"As the online marketplace and beauty care services is growing rapidly, many customers are booking services and buying products online, as it is more convenient. KerenAja is a platform where customers can book services and buy products that is aimed towards male. But as online marketplace's structure is kind of confusing, users tends to leave. Therefore, it is important to measure the user experience of the user when using the online marketplace, so the user experience can be improved. So, user experience questionnaire is used to measure the user experience of vendors and customers when using KerenAja. Later on, after gathering the data from customers and vendors, the user experience can then be evaluated. The result shows that the user experience of KerenAja's customer side is above average, while the user experience of KerenAja's vendor side is below average.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116262790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Drought is one of the triggers for forest fires due to depletion of surface water reserves. Along with the frequent drought, the incidence of forest fires has also increased. Therefore, it is important to know or forecast drought to take precautions. In this study, drought forecasting was carried out by applying the concept of data mining classification methods and forecasting methods. This classification uses the decision tree (CART) method, which is a method that aims to see the rules resulting from the classification of existing data. While forecasting uses the SARIMA method, this method is used to predict the factors that cause drought (temperature, humidity, and rainfall). Furthermore, the rule of the classification results is used to classify the results of forecasts. Based on the implementation of the CART algorithm which is evaluated using a confusion matrix is able to achieve an accuracy of 91.33%. Based on the implementation of the SARIMA method, a model is obtained for each variable to build forecasting. Each model was selected based on AIC criteria, and evaluated using MSE. The optimal model for temperature (Tx) is SARIMA (1, 1, 0) x (0, 1, 1, 12) with the MSE value of 0.15. While the selected model for humidity (RH_avg) is SARIMA (0, 1, 1) x (1, 1, 1, 12) with the MSE value of 3.85, and the optimal model for rainfall (RR) is SARIMA (0, 1, 1) x (0, 1, 1, 12) with the MSE value of 8.61.
由于地表水储量的枯竭，干旱是引发森林火灾的因素之一。随着干旱的频繁发生，森林火灾的发生率也有所增加。因此，了解或预测干旱，采取预防措施是很重要的。本研究运用数据挖掘的概念、分类方法和预测方法进行干旱预测。这种分类使用决策树(CART)方法，这是一种旨在查看由现有数据分类产生的规则的方法。虽然预报使用SARIMA方法，但该方法用于预测导致干旱的因素(温度、湿度和降雨)。在此基础上，利用分类结果规则对预测结果进行分类。基于CART算法的实现，使用混淆矩阵进行评估，能够达到91.33%的准确率。在SARIMA方法实现的基础上，对每个变量建立模型进行预测。根据AIC标准选择每个模型，并使用MSE进行评估。温度(Tx)的最优模型为SARIMA (1,1,0) x (0,1,1,12)， MSE值为0.15。湿度(RH_avg)优选模型为SARIMA (0,1,1) x (1,1,1,12)， MSE值为3.85;降雨(RR)优选模型为SARIMA (0,1,1) x (0,1,1,12)， MSE值为8.61。
{"title":"A Hybrid of Seasonal Autoregressive Integrated Moving Average (SARIMA) and Decision Tree for Drought Forecasting","authors":"Yasnita, E. Sutoyo, Ahmad Musnansyah","doi":"10.1145/3429789.3429870","DOIUrl":"https://doi.org/10.1145/3429789.3429870","url":null,"abstract":"Drought is one of the triggers for forest fires due to depletion of surface water reserves. Along with the frequent drought, the incidence of forest fires has also increased. Therefore, it is important to know or forecast drought to take precautions. In this study, drought forecasting was carried out by applying the concept of data mining classification methods and forecasting methods. This classification uses the decision tree (CART) method, which is a method that aims to see the rules resulting from the classification of existing data. While forecasting uses the SARIMA method, this method is used to predict the factors that cause drought (temperature, humidity, and rainfall). Furthermore, the rule of the classification results is used to classify the results of forecasts. Based on the implementation of the CART algorithm which is evaluated using a confusion matrix is able to achieve an accuracy of 91.33%. Based on the implementation of the SARIMA method, a model is obtained for each variable to build forecasting. Each model was selected based on AIC criteria, and evaluated using MSE. The optimal model for temperature (Tx) is SARIMA (1, 1, 0) x (0, 1, 1, 12) with the MSE value of 0.15. While the selected model for humidity (RH_avg) is SARIMA (0, 1, 1) x (1, 1, 1, 12) with the MSE value of 3.85, and the optimal model for rainfall (RR) is SARIMA (0, 1, 1) x (0, 1, 1, 12) with the MSE value of 8.61.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128565032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Current consumer demands make product development and delivery's period becomes shorter so that the product life cycle is shorter, especially for fashion items that have a short lifecycle. Collaborate with customers in product development is essential to accelerate the product development's process. Combination of customer satisfaction methodologies, Kano and QFD make easier to capture customer qualifications, determine which components to develop also repair it, and helps practitioners and researchers know the life cycle every design attributes. The results of this study resulted in a framework that makes use of n integration method Kano, customer's satisfaction, and QFD.
{"title":"New Product Development with Kano Model to Supports Supply Chain Performance of Jewelry Industry in Indonesia","authors":"Jennifer, M. Hartono","doi":"10.1145/3429789.3429873","DOIUrl":"https://doi.org/10.1145/3429789.3429873","url":null,"abstract":"Current consumer demands make product development and delivery's period becomes shorter so that the product life cycle is shorter, especially for fashion items that have a short lifecycle. Collaborate with customers in product development is essential to accelerate the product development's process. Combination of customer satisfaction methodologies, Kano and QFD make easier to capture customer qualifications, determine which components to develop also repair it, and helps practitioners and researchers know the life cycle every design attributes. The results of this study resulted in a framework that makes use of n integration method Kano, customer's satisfaction, and QFD.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydropower is one of the renewable energy widely available in countries. The resource of hydropower in a remote area is promising. Many rivers with low heads have not been utilized. Simple construction and low manufacturing cost are necessary to build a hydropower plant in a remote area. Vortex turbine is one hydropower turbine type that can generate electric power with low heads and suitable for remote areas. Vortex turbine is utilizing the water flow kinetic force of a whirlpool and transforms into shaft rotation. In this research, a laboratory-scale vortex turbine power plant was developed. Three different runners made of rust-resistant materials, SS-304, AA-5057, and Polyvinyl Chloride (PVC), were tested and generated electric power of 3.98 W, 3.47 W, and 3.3 W, respectively. It can turn on a 3 W LED lamp. Compared to the calculated potential hydraulic power of 12.5 Watt, the maximum efficiency is up to 31.8%. The runner weight significantly affects the electric power generated. Havier runner has a more significant moment of inertia, which results in higher torque, ultimately more power, as long as the flowing water can rotate the runner.
{"title":"Analysis of Gravitational Water Vortex Turbine Performance","authors":"D. L. Zariatin, Tri Murniati, D. Antoro","doi":"10.1145/3429789.3429862","DOIUrl":"https://doi.org/10.1145/3429789.3429862","url":null,"abstract":"Hydropower is one of the renewable energy widely available in countries. The resource of hydropower in a remote area is promising. Many rivers with low heads have not been utilized. Simple construction and low manufacturing cost are necessary to build a hydropower plant in a remote area. Vortex turbine is one hydropower turbine type that can generate electric power with low heads and suitable for remote areas. Vortex turbine is utilizing the water flow kinetic force of a whirlpool and transforms into shaft rotation. In this research, a laboratory-scale vortex turbine power plant was developed. Three different runners made of rust-resistant materials, SS-304, AA-5057, and Polyvinyl Chloride (PVC), were tested and generated electric power of 3.98 W, 3.47 W, and 3.3 W, respectively. It can turn on a 3 W LED lamp. Compared to the calculated potential hydraulic power of 12.5 Watt, the maximum efficiency is up to 31.8%. The runner weight significantly affects the electric power generated. Havier runner has a more significant moment of inertia, which results in higher torque, ultimately more power, as long as the flowing water can rotate the runner.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132274121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Working ergonomically can reduce the risk of pain, increase the sense of comfort at work, reduce stress and cause increased productivity. However, working ergonomically has not been implemented maximally when working, especially people who work in the office, where the fact that skeletal muscle disorders are the biggest enemy of office workers, around 40--50% of workers report complaints. And worse conditions are predicted while working from home. Musculoskeletal Disorders (MSDs) related to work are disorders of the musculoskeletal system caused or exacerbated by the interaction of the work environment. Musculoskeletal Disorders can be caused by the contribution of various risk factors including individual factors, occupational or biomechanical factors and psychosocial factors. This study wanted to find out ergonomic risk factors and work styles for musculoskeletal disorders in students especially those carrying out distance learning. Structural Equation Modeling (SEM) method is used to process the Workstyle model with the addition of work posture factors, and musculoskeletal pain. Structural Equation Modeling (SEM) is a statistical method used to test the relationship between variables, such as between manifest and latent variables, the relationship between latent variables, and measuring measurement error variables on several independent and dependent variables in a model (Hair, 2010). The analysis was carried out by distributing questionnaires to 200 respondents. Respondents are shown to UI students who are carrying out distance learning and using laptops or computers while doing work / assignments. The results of the study indicate that there are several workstyle factors that contribute to student musculoskeletal disorders.
{"title":"Ergonomics and Workstyle Risk Factors Analysis of Musculoskeletal Disorders in Students Conducting Distance Learning","authors":"Mimin Edwar, B. N. Moch, E. Muslim","doi":"10.1145/3429789.3429796","DOIUrl":"https://doi.org/10.1145/3429789.3429796","url":null,"abstract":"Working ergonomically can reduce the risk of pain, increase the sense of comfort at work, reduce stress and cause increased productivity. However, working ergonomically has not been implemented maximally when working, especially people who work in the office, where the fact that skeletal muscle disorders are the biggest enemy of office workers, around 40--50% of workers report complaints. And worse conditions are predicted while working from home. Musculoskeletal Disorders (MSDs) related to work are disorders of the musculoskeletal system caused or exacerbated by the interaction of the work environment. Musculoskeletal Disorders can be caused by the contribution of various risk factors including individual factors, occupational or biomechanical factors and psychosocial factors. This study wanted to find out ergonomic risk factors and work styles for musculoskeletal disorders in students especially those carrying out distance learning. Structural Equation Modeling (SEM) method is used to process the Workstyle model with the addition of work posture factors, and musculoskeletal pain. Structural Equation Modeling (SEM) is a statistical method used to test the relationship between variables, such as between manifest and latent variables, the relationship between latent variables, and measuring measurement error variables on several independent and dependent variables in a model (Hair, 2010). The analysis was carried out by distributing questionnaires to 200 respondents. Respondents are shown to UI students who are carrying out distance learning and using laptops or computers while doing work / assignments. The results of the study indicate that there are several workstyle factors that contribute to student musculoskeletal disorders.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130410866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Handayani, W. Kusuma, Z. F. Rosyada, Y. Widharto, Ajeng Hanifah
"Inventory Management System" is a website-based information system for disaster relief goods inventory designed for the Sleman Regency Regional Disaster Management Agency. Usability interface measurement has not been done when designing the information system. The usability interface is a quality attribute that is used to evaluate the convenience of people in obtaining information on a product, system, or service. This study aims to measure the usability of the existing website design interface and compare the usability value with the improved website design interface. Heuristic evaluation and usability testing methods are used to determine the usability interface design, both before and after repair. The results show that there were 18 problems found by evaluators. After interface improvements, the level of efficiency, effectiveness, satisfaction on all tasks, and usability values based on web-use have increased.
{"title":"Usability Evaluation of \"Inventory Information System\" Design of Disaster Management in Yogyakarta Province - Indonesia","authors":"N. Handayani, W. Kusuma, Z. F. Rosyada, Y. Widharto, Ajeng Hanifah","doi":"10.1145/3429789.3429843","DOIUrl":"https://doi.org/10.1145/3429789.3429843","url":null,"abstract":"\"Inventory Management System\" is a website-based information system for disaster relief goods inventory designed for the Sleman Regency Regional Disaster Management Agency. Usability interface measurement has not been done when designing the information system. The usability interface is a quality attribute that is used to evaluate the convenience of people in obtaining information on a product, system, or service. This study aims to measure the usability of the existing website design interface and compare the usability value with the improved website design interface. Heuristic evaluation and usability testing methods are used to determine the usability interface design, both before and after repair. The results show that there were 18 problems found by evaluators. After interface improvements, the level of efficiency, effectiveness, satisfaction on all tasks, and usability values based on web-use have increased.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131215848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inbound logistic activity in the mining company has an essential role in receiving, store, and disseminate input from suppliers to the point of use in production operations. In the case of one of the mining companies in Indonesia, inbound logistic performance has not yet reached the optimal target. This research builds an appropriate method to measure inbound logistic processes and then design strategies based on the results of the most critical performance indicators to improve performance indicators in the inbound logistic processes. The study begins with the collection of performance indicators and criteria for measuring the performance of the mining company's inbound logistic processes. The first questionnaire is filled and processed to determine the chosen performance indicators for the study. To assess the relationships among the performance indicators, the second questionnaire is filled. The results are then processed using Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) to confirm the causal relationship, identify the major performance indicators, and develop strategies accordingly. Based on the result, vessel capacity utilization (31.24%) is the first performance indicator that should be the priority, followed by material availability (12.18%), delivery cycle time (12.01%), and performance in making purchase orders (10.92%). The proposed strategies recommendations are container space optimization, a specialized standard operating procedure for fast-moving goods, implementation of Radio Frequency Identification (RFID) technology for each handling unit, and differentiation in purchasing strategy based on purchasing portfolio.
{"title":"Designing Strategies for Inbound Logistics Performance Indicator Improvement in the Indonesian Mining Industry","authors":"Fadhilah M Karimah, I. M. Hakim","doi":"10.1145/3429789.3429849","DOIUrl":"https://doi.org/10.1145/3429789.3429849","url":null,"abstract":"Inbound logistic activity in the mining company has an essential role in receiving, store, and disseminate input from suppliers to the point of use in production operations. In the case of one of the mining companies in Indonesia, inbound logistic performance has not yet reached the optimal target. This research builds an appropriate method to measure inbound logistic processes and then design strategies based on the results of the most critical performance indicators to improve performance indicators in the inbound logistic processes. The study begins with the collection of performance indicators and criteria for measuring the performance of the mining company's inbound logistic processes. The first questionnaire is filled and processed to determine the chosen performance indicators for the study. To assess the relationships among the performance indicators, the second questionnaire is filled. The results are then processed using Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) to confirm the causal relationship, identify the major performance indicators, and develop strategies accordingly. Based on the result, vessel capacity utilization (31.24%) is the first performance indicator that should be the priority, followed by material availability (12.18%), delivery cycle time (12.01%), and performance in making purchase orders (10.92%). The proposed strategies recommendations are container space optimization, a specialized standard operating procedure for fast-moving goods, implementation of Radio Frequency Identification (RFID) technology for each handling unit, and differentiation in purchasing strategy based on purchasing portfolio.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132020690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Supply Chain has components such as vendors, manufacturers, factories, warehouses retailers, customers, etc. Every relationship between components must have good information in order to create informed business decisions. Sales forecast are part of a decline in supply chain function and are a way to predict future product sales. The large gap between demand forecasting and actual demand proves that the forecasting method used in forecasting is not quite right so it can cause high error rates. In this study, the calculation of demand forecasting using the Artificial Neural Network (ANN) method was chosen as a good method because ANN learning method that works through an iterative process using training data comparing the predicted value of the network each sample of data and the weight of the network relation in each process is modified to minimize the value of Mean Squared Error (MSE). With the right parameters and good training in the data, the error number at the ANN calculation output using MATLAB will produce demand forecasting numbers that are getting closer to the actual demand numbers. The application of the ANN method to demand forecasting can make improvements to the error value performance using the MSE, MAD equation. and MAPE. The decline in MSE in 2018 from 1,894,299,389 to 26,612,567, in 2019 from 1,035,177,794 to 16,889,433, and in 2020 from 426,876,921 to 2,647,350. The decline in MAD in 2018 from 42,089 to 3,324, in 2019 from 26,924 to 2,888, and in 2020 from 20,661 to 1,627. MAPE reduction in 2018 from 23% to 2%, 2019 from 15% to 2%, and in 2020 from 11% to 1%.
{"title":"Demand Forecasting for Drinking Water Products to Reduce Gap Between Estimation and Realization of Demand Using Artificial Neural Network (ANN) Methods in PT. XYZ","authors":"R. Syafitri, A. Ridwan, Nia Novitasari","doi":"10.1145/3429789.3429844","DOIUrl":"https://doi.org/10.1145/3429789.3429844","url":null,"abstract":"Supply Chain has components such as vendors, manufacturers, factories, warehouses retailers, customers, etc. Every relationship between components must have good information in order to create informed business decisions. Sales forecast are part of a decline in supply chain function and are a way to predict future product sales. The large gap between demand forecasting and actual demand proves that the forecasting method used in forecasting is not quite right so it can cause high error rates. In this study, the calculation of demand forecasting using the Artificial Neural Network (ANN) method was chosen as a good method because ANN learning method that works through an iterative process using training data comparing the predicted value of the network each sample of data and the weight of the network relation in each process is modified to minimize the value of Mean Squared Error (MSE). With the right parameters and good training in the data, the error number at the ANN calculation output using MATLAB will produce demand forecasting numbers that are getting closer to the actual demand numbers. The application of the ANN method to demand forecasting can make improvements to the error value performance using the MSE, MAD equation. and MAPE. The decline in MSE in 2018 from 1,894,299,389 to 26,612,567, in 2019 from 1,035,177,794 to 16,889,433, and in 2020 from 426,876,921 to 2,647,350. The decline in MAD in 2018 from 42,089 to 3,324, in 2019 from 26,924 to 2,888, and in 2020 from 20,661 to 1,627. MAPE reduction in 2018 from 23% to 2%, 2019 from 15% to 2%, and in 2020 from 11% to 1%.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125096098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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