Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624250
L. Di Nunzio
{"title":"Embedded Machine Learning for the implementation of Autonomous Mobile Sensor Nodes (AMSNs)","authors":"L. Di Nunzio","doi":"10.23919/eecsi53397.2021.9624250","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624250","url":null,"abstract":"","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125625550","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624309
Evasaria Magdalena Sipayung, Cut Fiarni, M. Febrian
In the last decade, wellness tourism becoming more popular and become competitive value that give impact in the country economic performance. Moreover, the trend of social media and influence also made this type of tourism developing very rapidly. Indonesia as country that rich with its culture and heritage has various beauty and health recipe that become the unique value in the blooming of spa industries. But it also needs to develop their service and strategic objective, primarily in wellness and beauty tourism at both national and international levels. One of its strategic objectives is digital marketing through Search Engine Optimization (SEO), to make the marketing information and websites can be accessed easily. This research was carried out to analyze and develop SEO on Indonesian Health and Beauty Spa, so it could become framework for strategic marketing in these industries. The steps of this research including keywords analytic, improving website structure, and adjusting its architecture. The results of applying SEO techniques made the SPA XYZ website appear on the first page of Google search and increase the number of visitors to the SPA XYZ website by 436%.
{"title":"Implementation of Search Engine Optimization (SEO) in Wellness and Beauty Tourism Industry","authors":"Evasaria Magdalena Sipayung, Cut Fiarni, M. Febrian","doi":"10.23919/eecsi53397.2021.9624309","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624309","url":null,"abstract":"In the last decade, wellness tourism becoming more popular and become competitive value that give impact in the country economic performance. Moreover, the trend of social media and influence also made this type of tourism developing very rapidly. Indonesia as country that rich with its culture and heritage has various beauty and health recipe that become the unique value in the blooming of spa industries. But it also needs to develop their service and strategic objective, primarily in wellness and beauty tourism at both national and international levels. One of its strategic objectives is digital marketing through Search Engine Optimization (SEO), to make the marketing information and websites can be accessed easily. This research was carried out to analyze and develop SEO on Indonesian Health and Beauty Spa, so it could become framework for strategic marketing in these industries. The steps of this research including keywords analytic, improving website structure, and adjusting its architecture. The results of applying SEO techniques made the SPA XYZ website appear on the first page of Google search and increase the number of visitors to the SPA XYZ website by 436%.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121621768","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624249
Yohannes, Wijang Widhiarso, I. Pratama
Brain tumors are a growth of abnormal cells in the intracranial tissue that can disrupt proper brain function. In general, brain tumors are classified into two main categories, benign and malignant. This research aims to classify three types of benign tumors, that are Meningioma (Mg), Glioma (Gl), and Pituitary (Pt) from MRI images. The benign tumors types are classified into four data categories, that are Mg-Gl, Mg-Pt, Gl-Pt, Mg-GI-Pt. The Feature extraction uses Discrete Wavelet Transform (DWT) and Gray Level Co-Occurrence Matrix (GLCM) variant combination as a hybrid feature for recognize and classifying benign tumors types. The classification uses Convolutional Neural Network (CNN) method with ten layers structure. From our experiments, the average accuracy value of DWT combined with four GLCM features, that are Contrast, Homogeneity, Correlation, and Energy is 78.03% in all data categories.
{"title":"Combination of DWT Variants and GLCM as a Feature for Brain Tumor Classification","authors":"Yohannes, Wijang Widhiarso, I. Pratama","doi":"10.23919/eecsi53397.2021.9624249","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624249","url":null,"abstract":"Brain tumors are a growth of abnormal cells in the intracranial tissue that can disrupt proper brain function. In general, brain tumors are classified into two main categories, benign and malignant. This research aims to classify three types of benign tumors, that are Meningioma (Mg), Glioma (Gl), and Pituitary (Pt) from MRI images. The benign tumors types are classified into four data categories, that are Mg-Gl, Mg-Pt, Gl-Pt, Mg-GI-Pt. The Feature extraction uses Discrete Wavelet Transform (DWT) and Gray Level Co-Occurrence Matrix (GLCM) variant combination as a hybrid feature for recognize and classifying benign tumors types. The classification uses Convolutional Neural Network (CNN) method with ten layers structure. From our experiments, the average accuracy value of DWT combined with four GLCM features, that are Contrast, Homogeneity, Correlation, and Energy is 78.03% in all data categories.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132979181","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624258
Hendra Angga Yuwono, A. H. Saputro, Sabar
The hyperspectral image technology contains information in spectral and spatial forms that produce a huge amount of data. This data becomes an additional load while data is processed. Deep learning is the latest method capable of processing large-scale data with a deep structure of artificial neural network (ANN) and improving the model performance of data analysis. Therefore, this study aims to get a deep learning model into hyperspectral image processing for quantitative measurements of moisture content in dried sea cucumbers study case. The sea cucumber used in this study is the dried sea cucumber (Holothuria scabra), commonly known as Beche-de-mer. This study used the 400–1000 nm wavelength range to measure the moisture content quickly and nondestructively. The proposed model is deep learning which is used to build a predictive model system for moisture content in dried sea cucumbers. The coefficient of determination and the root means square error evaluate the measurement system. The measurement results of moisture content, the coefficient of determination, and the root mean square error values for training data are 0.99 and 0.11%, while testing data are 0.92 and 0.29%.
{"title":"Hyperspectral and Deep Learning-based Regression Model to Estimate Moisture Content in Sea Cucumbers","authors":"Hendra Angga Yuwono, A. H. Saputro, Sabar","doi":"10.23919/eecsi53397.2021.9624258","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624258","url":null,"abstract":"The hyperspectral image technology contains information in spectral and spatial forms that produce a huge amount of data. This data becomes an additional load while data is processed. Deep learning is the latest method capable of processing large-scale data with a deep structure of artificial neural network (ANN) and improving the model performance of data analysis. Therefore, this study aims to get a deep learning model into hyperspectral image processing for quantitative measurements of moisture content in dried sea cucumbers study case. The sea cucumber used in this study is the dried sea cucumber (Holothuria scabra), commonly known as Beche-de-mer. This study used the 400–1000 nm wavelength range to measure the moisture content quickly and nondestructively. The proposed model is deep learning which is used to build a predictive model system for moisture content in dried sea cucumbers. The coefficient of determination and the root means square error evaluate the measurement system. The measurement results of moisture content, the coefficient of determination, and the root mean square error values for training data are 0.99 and 0.11%, while testing data are 0.92 and 0.29%.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127266211","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624281
H. Yudha, T. Dewi, P. Risma, Y. Oktarina, Suci Syalifa Dwi Zara, Inda Sartika
Corn is the common agriculture product in Palembang suburban, which can be utilized to boost the income of local residents. Appropriate technology application is beneficial to improve the productivity of the household scale industry. This paper proposed an automatic corn sheller to apply appropriate technology for post-harvesting of the agriculture industry in the Palembang suburban. The corn sheller design is kept simple to ensure its repeatability. Experiments using the design test-best were conducted to show the effectiveness of the proposed method. Data results show that the sheller effectively follows the FLC design. The average total time of the shelling process is 4.7 s which is fast; therefore, it can improve the productivity of household-scale industries. The data results show that the proposed method is effective in shelling average corn found in Palembang.
{"title":"Fuzzy Logic Controller Application to an Automatic Corn Sheller","authors":"H. Yudha, T. Dewi, P. Risma, Y. Oktarina, Suci Syalifa Dwi Zara, Inda Sartika","doi":"10.23919/eecsi53397.2021.9624281","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624281","url":null,"abstract":"Corn is the common agriculture product in Palembang suburban, which can be utilized to boost the income of local residents. Appropriate technology application is beneficial to improve the productivity of the household scale industry. This paper proposed an automatic corn sheller to apply appropriate technology for post-harvesting of the agriculture industry in the Palembang suburban. The corn sheller design is kept simple to ensure its repeatability. Experiments using the design test-best were conducted to show the effectiveness of the proposed method. Data results show that the sheller effectively follows the FLC design. The average total time of the shelling process is 4.7 s which is fast; therefore, it can improve the productivity of household-scale industries. The data results show that the proposed method is effective in shelling average corn found in Palembang.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726528","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624210
N. A. Yusri, S. M. Idrus, N. Mohamed, S. Ambran, F. Iqbal, A. Kanno, N. Shibagaki, K. Kashima, T. Kawanishi
A corner reflector is one of the best methods to calibrate a radar system. The calibration method to calculate the radar cross section of corner reflectors for viewing arbitrary aspect angles on the airport runway is proposed. This work was conducted on a real airport environment at Kuala Lumpur International Airport (KLIA). In addition, the measurement was carried out at 93.1 GHz frequency for a Frequency Modulated Continuous Wave (FM-CW) radar detection system. The backscattering characteristics of a radar target, specific development of triangular trihedral corner reflector, standard runway slope measurement, measured theoretical maximum RCS value and experiment site evaluation are presented in this paper.
{"title":"Calibration of 93.1GHz FOD Detection Radar on Airport Runway using Trihedral Corner Reflector","authors":"N. A. Yusri, S. M. Idrus, N. Mohamed, S. Ambran, F. Iqbal, A. Kanno, N. Shibagaki, K. Kashima, T. Kawanishi","doi":"10.23919/eecsi53397.2021.9624210","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624210","url":null,"abstract":"A corner reflector is one of the best methods to calibrate a radar system. The calibration method to calculate the radar cross section of corner reflectors for viewing arbitrary aspect angles on the airport runway is proposed. This work was conducted on a real airport environment at Kuala Lumpur International Airport (KLIA). In addition, the measurement was carried out at 93.1 GHz frequency for a Frequency Modulated Continuous Wave (FM-CW) radar detection system. The backscattering characteristics of a radar target, specific development of triangular trihedral corner reflector, standard runway slope measurement, measured theoretical maximum RCS value and experiment site evaluation are presented in this paper.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114188106","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624266
A. Wibawa, Rizky Eka Listanto
The rapid development of information technology and its applications with the emergence of internet media makes disseminating information more accessible, fast and creating huge data in any time. Government is one of important stakeholders that produce a big data every day. Big data is one combination with data analytics that plays an important role in data processing and new insight retrieving. In this study, text data from customers complaint regarding the services given by the Government organization namely Financial Monitoring and Development Agency was analyzed. Users can report various kinds of complaints related to the problems they experienced. In this study, new insights regarding the applications provided by the Government agency will be discussed. From the 15 thousand complaint data records, six groups of the most dominant complaint regarding the applications use were then categorized: SIMA applications, SIBIJAK applications, GDN applications, SADEWA applications, Lotus Notes, and Infrastructure. Latent Dirichlet Allocation (LDA) topic modeling with part-of-speech tagger techniques was used to disseminate information on the topics. The results showed that the SIMA application gave 52% of all complaints reports based on the method used. With the implementation of the LDA topic modeling, four topics were generated: complaints about using the SIMA application, the service and installation of the Lotus Notes and SADEWA application, and complaints related to the existing network infrastructure of Government Agency. In conclusion, inference LDA Topic modeling successfully provided insights to government organization regarding which aspects within organization that are needed to be improved.
{"title":"Complaint Data Text Analysis Concerning the Apps Provided by Government Agency using Inference LDA","authors":"A. Wibawa, Rizky Eka Listanto","doi":"10.23919/eecsi53397.2021.9624266","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624266","url":null,"abstract":"The rapid development of information technology and its applications with the emergence of internet media makes disseminating information more accessible, fast and creating huge data in any time. Government is one of important stakeholders that produce a big data every day. Big data is one combination with data analytics that plays an important role in data processing and new insight retrieving. In this study, text data from customers complaint regarding the services given by the Government organization namely Financial Monitoring and Development Agency was analyzed. Users can report various kinds of complaints related to the problems they experienced. In this study, new insights regarding the applications provided by the Government agency will be discussed. From the 15 thousand complaint data records, six groups of the most dominant complaint regarding the applications use were then categorized: SIMA applications, SIBIJAK applications, GDN applications, SADEWA applications, Lotus Notes, and Infrastructure. Latent Dirichlet Allocation (LDA) topic modeling with part-of-speech tagger techniques was used to disseminate information on the topics. The results showed that the SIMA application gave 52% of all complaints reports based on the method used. With the implementation of the LDA topic modeling, four topics were generated: complaints about using the SIMA application, the service and installation of the Lotus Notes and SADEWA application, and complaints related to the existing network infrastructure of Government Agency. In conclusion, inference LDA Topic modeling successfully provided insights to government organization regarding which aspects within organization that are needed to be improved.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128612611","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624251
M. R. Effendi, Naufal Abyan Faruqi, N. Ismail
Growing data triggers better performance on storage systems. The type of storage and the storage system used also affect storage performance. This study aims to analyze the comparison of the performance of block storage and object storage in running a virtual environment using the Ceph storage system. Performance measurement was carried out with several tests including Input-Output per Second and Throughput. The test was carried out using 2 client nodes with an rbd bench. Based on the measurement results, the Write-type on block storage had a value of 81.02 %, while the result of the Puts-type on object storage had a value of 41.02%. This fact showed that the Write-type of the storage process in block storage was better than the Puts-type in object storage. The result of the Read-type on block storage had a value of 31.59%, while the result of the Gets-type measurement on object storage had a value of 89.71 %. This showed that Puts-type process in object storage was better than Read-type in block storage. The conditions on the Ceph server are still in good condition.
{"title":"Performance Analysis of Storage Media Cluster Using Ceph Platform","authors":"M. R. Effendi, Naufal Abyan Faruqi, N. Ismail","doi":"10.23919/eecsi53397.2021.9624251","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624251","url":null,"abstract":"Growing data triggers better performance on storage systems. The type of storage and the storage system used also affect storage performance. This study aims to analyze the comparison of the performance of block storage and object storage in running a virtual environment using the Ceph storage system. Performance measurement was carried out with several tests including Input-Output per Second and Throughput. The test was carried out using 2 client nodes with an rbd bench. Based on the measurement results, the Write-type on block storage had a value of 81.02 %, while the result of the Puts-type on object storage had a value of 41.02%. This fact showed that the Write-type of the storage process in block storage was better than the Puts-type in object storage. The result of the Read-type on block storage had a value of 31.59%, while the result of the Gets-type measurement on object storage had a value of 89.71 %. This showed that Puts-type process in object storage was better than Read-type in block storage. The conditions on the Ceph server are still in good condition.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132378081","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624301
Israa Al Barazanchi, Wahidah Hashim, A. Alkahtani, H. Abbas, Haider Rasheed Abdulshaheed
The science of Wireless Body Area Network (WBAN) and its overwhelming potential over medical treatment and body testing has greatly improved over the years, and with the globalization phenomenon hospitals are now able to treat their patients remotely, and medical camps have proved to be much more productive than before. This paper will focus on the existing trends and literature survey, the pre-laying architecture, and the working WBAN system, along with its networking capabilities and practical applications. With the growing need for medical treatment and healthcare, WBAN has become a necessity at treating patients, then and there as required. The usage of the WBAN systems is not only limited to the healthcare field, but also for military and space training. The WBAN ideology and the networking methods can be implemented for various fields that includes distributed networking and organizational needs. This study aims to provide a detailed overview over the varying aspects, structures, and applications that the WBAN can satiate. The ability to autonomously operate and provide sensor data from various parts of the human body and transfer the data to a geographically far or remote location for real-time accessing and support, has made WBAN a lifesaver. Also, the various parts of the WBAN system can be added and removed as per the application requires greatly providing flexibility, and in-turn provide better real-world support than any other smart systems.
{"title":"Overview of WBAN from Literature Survey to Application Implementation","authors":"Israa Al Barazanchi, Wahidah Hashim, A. Alkahtani, H. Abbas, Haider Rasheed Abdulshaheed","doi":"10.23919/eecsi53397.2021.9624301","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624301","url":null,"abstract":"The science of Wireless Body Area Network (WBAN) and its overwhelming potential over medical treatment and body testing has greatly improved over the years, and with the globalization phenomenon hospitals are now able to treat their patients remotely, and medical camps have proved to be much more productive than before. This paper will focus on the existing trends and literature survey, the pre-laying architecture, and the working WBAN system, along with its networking capabilities and practical applications. With the growing need for medical treatment and healthcare, WBAN has become a necessity at treating patients, then and there as required. The usage of the WBAN systems is not only limited to the healthcare field, but also for military and space training. The WBAN ideology and the networking methods can be implemented for various fields that includes distributed networking and organizational needs. This study aims to provide a detailed overview over the varying aspects, structures, and applications that the WBAN can satiate. The ability to autonomously operate and provide sensor data from various parts of the human body and transfer the data to a geographically far or remote location for real-time accessing and support, has made WBAN a lifesaver. Also, the various parts of the WBAN system can be added and removed as per the application requires greatly providing flexibility, and in-turn provide better real-world support than any other smart systems.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131842836","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}
Pub Date : 2021-10-20DOI: 10.23919/eecsi53397.2021.9624300
Sutrisno, Widowati, R. H. Tjahjana
This paper proposed optimization-based decision-making support for solving the planning problems of raw material/product order allocation. A few parameters (prices, demand values, defective product rate, and late delivery) are uncertain and are treated as probabilistic or fuzzy depending on the data availability. Meanwhile, the parameters with historical/trial data are treated as probabilistic with some distribution functions. However, the parameters without any data are treated as fuzzy, and their corresponding membership functions are built by managers based on intuition and experience. Therefore, this study aims to determine optimal values for the decision variables, namely the number of raw materials planned to be ordered and its corresponding suppliers such that the total operational cost is expected to be minimal. These optimal decisions are calculated from the proposed optimization model in LINGO software by implementing the generalized Gradient algorithm. To evaluate and illustrate the proposed decision-making support, a numerical simulation was demonstrated. The results showed the optimal decisions were successfully attained and the expected minimal total operational cost was achieved. Furthermore, it proved that the proposed decision-making support could be implemented in manufacturing or retail industries to solve their order allocation problems.
{"title":"Optimization-based Decision-Making Support for Fuzzy and Probabilistic Order Allocation Planning","authors":"Sutrisno, Widowati, R. H. Tjahjana","doi":"10.23919/eecsi53397.2021.9624300","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624300","url":null,"abstract":"This paper proposed optimization-based decision-making support for solving the planning problems of raw material/product order allocation. A few parameters (prices, demand values, defective product rate, and late delivery) are uncertain and are treated as probabilistic or fuzzy depending on the data availability. Meanwhile, the parameters with historical/trial data are treated as probabilistic with some distribution functions. However, the parameters without any data are treated as fuzzy, and their corresponding membership functions are built by managers based on intuition and experience. Therefore, this study aims to determine optimal values for the decision variables, namely the number of raw materials planned to be ordered and its corresponding suppliers such that the total operational cost is expected to be minimal. These optimal decisions are calculated from the proposed optimization model in LINGO software by implementing the generalized Gradient algorithm. To evaluate and illustrate the proposed decision-making support, a numerical simulation was demonstrated. The results showed the optimal decisions were successfully attained and the expected minimal total operational cost was achieved. Furthermore, it proved that the proposed decision-making support could be implemented in manufacturing or retail industries to solve their order allocation problems.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128291184","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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