Pub Date : 2024-02-02DOI: 10.20895/infotel.v16i1.1070
Imam Adi Nata, Muhammad Rifqi Maarif
This research employs Natural Language Processing (NLP) techniques to evaluate customer reviews obtained from online marketplaces. It uses keyword extraction and clustering to identify thematic clusters in the data. These clusters reveal shared contextual significance and provide a higher-level perspective on customer perceptions of local fashion products. Sentiment analysis is also conducted within each theme to understand customer sentiment. This approach goes beyond binary sentiment classification and offers a more nuanced analysis. By incorporating keyword extraction, clustering, and sentiment analysis, this research offers a thorough framework for comprehending customer perceptions in the digital marketplace. It contributes to the field of e-commerce by offering a robust methodology for decoding customer sentiments towards local fashion products. The findings have substantial implications for marketers, designers, and platform providers in online marketplaces, leading to a more consumer-centric e-commerce ecosystem.
{"title":"Understanding Customer Perception of Local Fashion Product on Online Marketplace through Content Analysis","authors":"Imam Adi Nata, Muhammad Rifqi Maarif","doi":"10.20895/infotel.v16i1.1070","DOIUrl":"https://doi.org/10.20895/infotel.v16i1.1070","url":null,"abstract":"This research employs Natural Language Processing (NLP) techniques to evaluate customer reviews obtained from online marketplaces. It uses keyword extraction and clustering to identify thematic clusters in the data. These clusters reveal shared contextual significance and provide a higher-level perspective on customer perceptions of local fashion products. Sentiment analysis is also conducted within each theme to understand customer sentiment. This approach goes beyond binary sentiment classification and offers a more nuanced analysis. By incorporating keyword extraction, clustering, and sentiment analysis, this research offers a thorough framework for comprehending customer perceptions in the digital marketplace. It contributes to the field of e-commerce by offering a robust methodology for decoding customer sentiments towards local fashion products. The findings have substantial implications for marketers, designers, and platform providers in online marketplaces, leading to a more consumer-centric e-commerce ecosystem.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"123 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140462217","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 : 2024-02-02DOI: 10.20895/infotel.v16i1.1029
Dewi Purnamasari, Didin Herlinudinkhaji, Astrie Kusuma Dewi, Muhammad Zairon Mauludin
Data theft from year to year has increased in the era of big data and society 5.0. One area that requires data security is patient medical data. Medical image data security must be done to protect medical data security from data theft by third parties so that they cannot access the data. The development of Diabetic Retinopathy (DR) is also increasing every year. Determining the severity of DR is done by detecting the Foveal Avascular Zone (FAZ). Encryption is the process of changing a plain image into a cipher image. In this study, we compared the results of image quality and encryption time between the Vigenere Cipher method and a combination of pixel scrambling. The average encryption time of the tested FAZ images is 3.20 seconds. This result proves that the pixel combination method has a faster encryption time than the Vigenere Cipher. Vigenere Cipher encryption time is 4.96 seconds. The existence of the FAZ area with the pixel combination randomization method of the encryption process is also invisible, so third parties will not know about its existence.
在大数据和社会 5.0 时代，数据盗窃逐年增加。患者医疗数据就是一个需要数据安全的领域。必须做好医学影像数据安全，以保护医疗数据安全，防止数据被第三方窃取，使其无法访问数据。糖尿病视网膜病变（DR）的发病率也在逐年上升。通过检测眼窝血管区（FAZ）来确定糖尿病视网膜病变的严重程度。加密是将普通图像变为密码图像的过程。在这项研究中，我们比较了 Vigenere 密码方法和像素加扰组合方法在图像质量和加密时间方面的结果。测试的 FAZ 图像的平均加密时间为 3.20 秒。这一结果证明，像素组合方法的加密时间比维基纳尔密码方法更快。维基解密的加密时间为 4.96 秒。采用像素组合随机化方法加密的 FAZ 区域的存在也是不可见的，因此第三方不会知道它的存在。
{"title":"Foveal Avascular Zone Image Encryption using Pixel Scrambling Combination Technique for Medical Image Security","authors":"Dewi Purnamasari, Didin Herlinudinkhaji, Astrie Kusuma Dewi, Muhammad Zairon Mauludin","doi":"10.20895/infotel.v16i1.1029","DOIUrl":"https://doi.org/10.20895/infotel.v16i1.1029","url":null,"abstract":"Data theft from year to year has increased in the era of big data and society 5.0. One area that requires data security is patient medical data. Medical image data security must be done to protect medical data security from data theft by third parties so that they cannot access the data. The development of Diabetic Retinopathy (DR) is also increasing every year. Determining the severity of DR is done by detecting the Foveal Avascular Zone (FAZ). Encryption is the process of changing a plain image into a cipher image. In this study, we compared the results of image quality and encryption time between the Vigenere Cipher method and a combination of pixel scrambling. The average encryption time of the tested FAZ images is 3.20 seconds. This result proves that the pixel combination method has a faster encryption time than the Vigenere Cipher. Vigenere Cipher encryption time is 4.96 seconds. The existence of the FAZ area with the pixel combination randomization method of the encryption process is also invisible, so third parties will not know about its existence.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"141 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140462561","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 : 2024-01-25DOI: 10.20895/infotel.v16i1.1049
Muhammad Zakariyah, Umar Zaky, Muhammad Nurjaman, Agil Ghani Istikmal, Hafizh Athallah Widianto
Heart rate variability (HRV) is a parameter to measure fluctuations in the interval between heartbeats. HRV provides essential insights into the cardiovascular function and autonomic nervous system. Electrocardiograms (ECG) on wearable devices are often recorded at low sampling rates, limiting temporal resolution and information. Resampling is a technique of changing the sampling rate from a high sampling rate to a lower sampling rate and vice versa. This research aims to evaluate the effect of resampling ECG data with a low sampling rate on HRV features. ECG data consists of 50 Hz and 100 Hz sampling rates. Data with a 50 Hz sampling rate is up-sampled up to 100 Hz, while 100 Hz data is down-sampled up to 50 Hz and up-sampled up to 250 Hz using the Fast Fourier Transform Interpolation Method. Upsampling from 50 Hz to 100 Hz shows unsatisfactory results, except for some HRV features such as NN20, pNN20, and CVI. Better results were found when up sampling from 100 Hz up to 250 Hz, with some HRV features showing good concordance values. However, downsampling from 100 Hz up to 50 Hz is unsuitable for HRV feature analysis. To obtain accurate HRV analysis results in all domains, it is highly recommended to use a sampling rate above 100 Hz.
{"title":"Resampling Strategies and their Influence on Heart Rate Variability Features in Low Sampling Rate Electrocardiogram Data","authors":"Muhammad Zakariyah, Umar Zaky, Muhammad Nurjaman, Agil Ghani Istikmal, Hafizh Athallah Widianto","doi":"10.20895/infotel.v16i1.1049","DOIUrl":"https://doi.org/10.20895/infotel.v16i1.1049","url":null,"abstract":"Heart rate variability (HRV) is a parameter to measure fluctuations in the interval between heartbeats. HRV provides essential insights into the cardiovascular function and autonomic nervous system. Electrocardiograms (ECG) on wearable devices are often recorded at low sampling rates, limiting temporal resolution and information. Resampling is a technique of changing the sampling rate from a high sampling rate to a lower sampling rate and vice versa. This research aims to evaluate the effect of resampling ECG data with a low sampling rate on HRV features. ECG data consists of 50 Hz and 100 Hz sampling rates. Data with a 50 Hz sampling rate is up-sampled up to 100 Hz, while 100 Hz data is down-sampled up to 50 Hz and up-sampled up to 250 Hz using the Fast Fourier Transform Interpolation Method. Upsampling from 50 Hz to 100 Hz shows unsatisfactory results, except for some HRV features such as NN20, pNN20, and CVI. Better results were found when up sampling from 100 Hz up to 250 Hz, with some HRV features showing good concordance values. However, downsampling from 100 Hz up to 50 Hz is unsuitable for HRV feature analysis. To obtain accurate HRV analysis results in all domains, it is highly recommended to use a sampling rate above 100 Hz.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495753","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 : 2024-01-25DOI: 10.20895/infotel.v15i4.988
R. Gustriansyah, N. Suhandi, Shinta Puspasari, A. Sanmorino
Malnutrition is one of the leading health problems experienced by toddlers in various countries. Based on the 2022 Indonesian Nutritional Status Survey results, malnutrition in children under five in Indonesia is higher than the average malnutrition in Africa and globally. Therefore, a way is needed to predict the nutritional status of children under five early and quickly so that the Government (through District Health Office) can immediately provide the necessary treatment. This study aims to predict or classify the toddlers’ nutritional status based on age, body mass index (BMI), weight, and body length using various machine learning (ML) methods, namely naïve Bayes, linear discriminant analysis, decision tree, k-nearest neighbor, random forest, and support vector machine. The predictive performance of each ML method was evaluated based on accuracy, sensitivity, specificity, the area under curve, and Cohen's Kappa coefficient. The test results show that the RF method is the most recommended for predicting toddlers' nutritional status. The study's contribution is to obtain information about toddlers' nutritional status easier.
营养不良是各国幼儿面临的主要健康问题之一。根据 2022 年印度尼西亚营养状况调查结果，印度尼西亚五岁以下儿童的营养不良率高于非洲和全球的平均营养不良率。因此，需要一种方法来及早、快速地预测五岁以下儿童的营养状况，以便政府（通过地区卫生局）立即提供必要的治疗。本研究旨在使用各种机器学习（ML）方法，即天真贝叶斯、线性判别分析、决策树、k-近邻、随机森林和支持向量机，根据年龄、体重指数（BMI）、体重和身长对幼儿的营养状况进行预测或分类。根据准确度、灵敏度、特异性、曲线下面积和科恩卡帕系数对每种 ML 方法的预测性能进行了评估。测试结果表明，最推荐使用 RF 方法预测幼儿的营养状况。该研究的贡献在于更容易获得幼儿营养状况的信息。
{"title":"Machine Learning Method to Predict the Toddlers’ Nutritional Status","authors":"R. Gustriansyah, N. Suhandi, Shinta Puspasari, A. Sanmorino","doi":"10.20895/infotel.v15i4.988","DOIUrl":"https://doi.org/10.20895/infotel.v15i4.988","url":null,"abstract":"Malnutrition is one of the leading health problems experienced by toddlers in various countries. Based on the 2022 Indonesian Nutritional Status Survey results, malnutrition in children under five in Indonesia is higher than the average malnutrition in Africa and globally. Therefore, a way is needed to predict the nutritional status of children under five early and quickly so that the Government (through District Health Office) can immediately provide the necessary treatment. This study aims to predict or classify the toddlers’ nutritional status based on age, body mass index (BMI), weight, and body length using various machine learning (ML) methods, namely naïve Bayes, linear discriminant analysis, decision tree, k-nearest neighbor, random forest, and support vector machine. The predictive performance of each ML method was evaluated based on accuracy, sensitivity, specificity, the area under curve, and Cohen's Kappa coefficient. The test results show that the RF method is the most recommended for predicting toddlers' nutritional status. The study's contribution is to obtain information about toddlers' nutritional status easier.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"49 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140495954","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}
Buying and selling goods now is more interesting through e-commerce or marketplaces because of the ease of carrying out online transactions. Each transaction usually generates a response from the customer. The transaction response on the Shopee platform is still in paragraph form and needs to be more specific. Therefore, this research aims to build a model analysis of customer satisfaction using the best algorithm between support vector machine (SVM), random forest, and logistic regression. This research method uses sentiment classification with logistic regression because the logistic regression algorithm has the best accuracy, with an accuracy of 90.5. Meanwhile, the SVM algorithm achieved an accuracy of 90.4, and random forest reached 90.2. The three algorithms were tested three times, splitting data train:test at 80:20, 70:30, and 60:40. The best results were obtained by splitting data at 60:40. The best model is used to predict data without labels. The prediction produces 12,844 positive sentiment comment data, 112 negative sentiment comment data, and 70 neutral sentiment comment data. The results of this research continued to topic modeling using latent dirichlet allocation (LDA) to generate a trending topic of customer satisfaction on sales products. Implications of discussing each trend topic can be used as a reference for improving products and services, especially in communicating with customers.
{"title":"Topic Sentiment Using Logistic Regression and Latent Dirichlet Allocation as a Customer Satisfaction Analysis Model","authors":"Puji Winar Cahyo, Ulfi Saidata Aesyi, Bagas Dwi Santosa","doi":"10.20895/infotel.v16i1.1081","DOIUrl":"https://doi.org/10.20895/infotel.v16i1.1081","url":null,"abstract":"Buying and selling goods now is more interesting through e-commerce or marketplaces because of the ease of carrying out online transactions. Each transaction usually generates a response from the customer. The transaction response on the Shopee platform is still in paragraph form and needs to be more specific. Therefore, this research aims to build a model analysis of customer satisfaction using the best algorithm between support vector machine (SVM), random forest, and logistic regression. This research method uses sentiment classification with logistic regression because the logistic regression algorithm has the best accuracy, with an accuracy of 90.5. Meanwhile, the SVM algorithm achieved an accuracy of 90.4, and random forest reached 90.2. The three algorithms were tested three times, splitting data train:test at 80:20, 70:30, and 60:40. The best results were obtained by splitting data at 60:40. The best model is used to predict data without labels. The prediction produces 12,844 positive sentiment comment data, 112 negative sentiment comment data, and 70 neutral sentiment comment data. The results of this research continued to topic modeling using latent dirichlet allocation (LDA) to generate a trending topic of customer satisfaction on sales products. Implications of discussing each trend topic can be used as a reference for improving products and services, especially in communicating with customers.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"56 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140498726","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 : 2023-11-13DOI: 10.20895/infotel.v15i4.949
Shinta Puspasari, R. Gustriansyah, A. Sanmorino
This paper aims to evaluate the performance of a machine learning model for predicting the number of visitors to a museum after the COVID-19 pandemic. The easing of policies that began to be implemented by the Palembang city government after the end of the pandemic at the end of 2022 became a momentum in predicting the number of visits to the SMBII museum. During the pandemic the museum experienced a very drastic decline due to closures and restrictions on activities at the museum and had an impact on achieving the museum's targets in the fields of tourism and education. Museum managers need to establish a strategy as an effort to achieve the targets set during the post-pandemic period. This study predicts the number of visits to the SMBII museum in post-pandemic years by applying the double exponential smoothing (ESM) model. The dataset used is SMBII museum visit data which is divided into three categories of visitors, namely students, local and foreign. The evaluation results show that the double ESM model has the best performance with MSE = 3.8 and a = 0.9. The phenomena that occurred in the student visitor category affected ESM's performance in predicting visits where MSE in the post-pandemic period had a 200% higher value than before the pandemic which was influenced by the implementation of post-pandemic policies in museums. With the forecasting results in this study, it is hoped that it can become information in developing strategies and improving the performance of post-pandemic museums
{"title":"Forecasting a museum visit post pandemic using exponential smoothing model","authors":"Shinta Puspasari, R. Gustriansyah, A. Sanmorino","doi":"10.20895/infotel.v15i4.949","DOIUrl":"https://doi.org/10.20895/infotel.v15i4.949","url":null,"abstract":"This paper aims to evaluate the performance of a machine learning model for predicting the number of visitors to a museum after the COVID-19 pandemic. The easing of policies that began to be implemented by the Palembang city government after the end of the pandemic at the end of 2022 became a momentum in predicting the number of visits to the SMBII museum. During the pandemic the museum experienced a very drastic decline due to closures and restrictions on activities at the museum and had an impact on achieving the museum's targets in the fields of tourism and education. Museum managers need to establish a strategy as an effort to achieve the targets set during the post-pandemic period. This study predicts the number of visits to the SMBII museum in post-pandemic years by applying the double exponential smoothing (ESM) model. The dataset used is SMBII museum visit data which is divided into three categories of visitors, namely students, local and foreign. The evaluation results show that the double ESM model has the best performance with MSE = 3.8 and a = 0.9. The phenomena that occurred in the student visitor category affected ESM's performance in predicting visits where MSE in the post-pandemic period had a 200% higher value than before the pandemic which was influenced by the implementation of post-pandemic policies in museums. With the forecasting results in this study, it is hoped that it can become information in developing strategies and improving the performance of post-pandemic museums","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"19 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139278160","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 : 2023-09-13DOI: 10.20895/infotel.v15i3.966
Yuliarman Saragih, Ibrahim Lammada, Ridwan Satrio Hadikusuma, Kayat Handayana, Agatha Elisabeth
This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.
{"title":"Design of a microcontroller-based quadcopter prototype module Fly Sky XL163RX take off and landing","authors":"Yuliarman Saragih, Ibrahim Lammada, Ridwan Satrio Hadikusuma, Kayat Handayana, Agatha Elisabeth","doi":"10.20895/infotel.v15i3.966","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.966","url":null,"abstract":"This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139340313","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 : 2023-09-05DOI: 10.20895/infotel.v15i3.977
James Julian, Annastya Bagas Dewantara, F. Wahyuni
Lack of clean water has become a problem in the world, and it is estimated that by 2025 there will be 2.8 billion people who will experience a shortage of clean water. The high demand for clean water and the limited water sources with proper potency is one of the main reasons for the need for a device capable of measuring the potability level of water that is flexible to carry and does not require high costs in the manufacturing process. In this paper, the design of machine learning-based potability devices with recursive feature elimination with cross-validation (RFECV) is carried out as a guide in making the design of a water potability detection system, and the results obtained from RFECV with the Random Forest (RF) algorithm have a higher accuracy value. 15.71% better than the RF model, 6.85% better than the Support Vector Machine (SVM) model, and 8.57% better than the Artificial Neural Network (ANN) model trained without RFECV. The water potability prediction system's design selection is based on feature elimination results in the RFECV process. It is based on a literature review on device selection. The proposed water potability detection system consists of ESP32 as the primary computing device, electrochemical spectroscopy-based Al/PET sensor to detect sulfate values with a sensitivity of 0.874 Ω/ppm, PH4502C as a pH measuring instrument with an accuracy of up to 98.10%, WD-35802-49 electrode. as a device for measuring hardness in water with a measurement range of 0.4 – 40,000 ppm, a total dissolved solids sensor to determine the solids content in water with an accuracy of up to 97.80%, as well as a carbon-based sensor for measuring chloramines with a reading capacity of 186 nA/ppm.
{"title":"Design of machine learning-based water quality prediction system with recursive feature elimination cross-validation","authors":"James Julian, Annastya Bagas Dewantara, F. Wahyuni","doi":"10.20895/infotel.v15i3.977","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.977","url":null,"abstract":"Lack of clean water has become a problem in the world, and it is estimated that by 2025 there will be 2.8 billion people who will experience a shortage of clean water. The high demand for clean water and the limited water sources with proper potency is one of the main reasons for the need for a device capable of measuring the potability level of water that is flexible to carry and does not require high costs in the manufacturing process. In this paper, the design of machine learning-based potability devices with recursive feature elimination with cross-validation (RFECV) is carried out as a guide in making the design of a water potability detection system, and the results obtained from RFECV with the Random Forest (RF) algorithm have a higher accuracy value. 15.71% better than the RF model, 6.85% better than the Support Vector Machine (SVM) model, and 8.57% better than the Artificial Neural Network (ANN) model trained without RFECV. The water potability prediction system's design selection is based on feature elimination results in the RFECV process. It is based on a literature review on device selection. The proposed water potability detection system consists of ESP32 as the primary computing device, electrochemical spectroscopy-based Al/PET sensor to detect sulfate values with a sensitivity of 0.874 Ω/ppm, PH4502C as a pH measuring instrument with an accuracy of up to 98.10%, WD-35802-49 electrode. as a device for measuring hardness in water with a measurement range of 0.4 – 40,000 ppm, a total dissolved solids sensor to determine the solids content in water with an accuracy of up to 97.80%, as well as a carbon-based sensor for measuring chloramines with a reading capacity of 186 nA/ppm.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139342651","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 : 2023-09-05DOI: 10.20895/infotel.v15i3.1016
Jihad Sindhu Gossa, K. M. Ngafidin, S. T. Safitri
E-commerce became one of the technological developments in Indonesia in the fourth industrial revolution. Since then, the daily needs transaction process has become accessible through the e-commerce platform. The rapid development of e-commerce is predicted to increase and thus encourage the development of courier services over the past period, making courier services an essential element that affects customer satisfaction in e-commerce services. An analysis of customer satisfaction in several e-commerce service providers towards customer reviews on Google Play conducted by Sasmita and a statement by the Ministry of Trade through a consumer complaint report in 2021 stated that complaints about problems in the e-commerce sector have increased, which includes courier services incorporated with e-commerce service providers. Gulc argued that at least seven factors determine the quality of courier service based on the customer's perspective. The AHP method assists courier services affiliated with e-commerce services in recognizing which of these seven factors of courier service quality dimensions require attention to create a sustainable competitive advantage. This research aims to measure the priority level of criteria in determining the quality of courier services on e-commerce platforms, thus providing recommendations for the appropriate service priorities for courier service companies. The calculation results using AHP on the seven factors determining the quality of courier service according to the Manager Assistant of the Service Department at the Central Purwokerto Branch of the Kantor POS Indonesia show that the responsiveness criterion is more important than the other six criteria.
在第四次工业革命中，电子商务成为印度尼西亚的技术发展之一。从那时起，日常需求的交易过程就可以通过电子商务平台实现。据预测，电子商务的快速发展将在过去一段时间内促进快递服务的发展，从而使快递服务成为影响电子商务服务客户满意度的重要因素。萨斯米塔（Sasmita）对几家电子商务服务提供商在 Google Play 上的客户评价进行了客户满意度分析，贸易部在 2021 年通过消费者投诉报告发表声明称，有关电子商务领域问题的投诉有所增加，其中包括与电子商务服务提供商结合在一起的快递服务。Gulc 认为，从客户的角度来看，至少有七个因素决定了快递服务的质量。AHP 方法可帮助与电子商务服务相关的快递服务机构识别快递服务质量维度的七个因素中哪些因素需要关注，以创造可持续的竞争优势。本研究旨在衡量电子商务平台上快递服务质量判定标准的优先级别，从而为快递服务公司提供适当的服务优先级建议。根据印度尼西亚 Kantor POS 公司 Purwokerto 中心分部服务部经理助理的意见，使用 AHP 对决定快递服务质量的七个因素进行计算的结果表明，响应能力标准比其他六个标准更重要。
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Pub Date : 2023-09-04DOI: 10.20895/infotel.v15i3.991
S. Budiyanto, L. M. Silalahi, Dadang Gunawan, Erry Yulian Triblas Adesta
This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.
{"title":"An enhancement to the FLC-based baby incubator system using genetic algorithm","authors":"S. Budiyanto, L. M. Silalahi, Dadang Gunawan, Erry Yulian Triblas Adesta","doi":"10.20895/infotel.v15i3.991","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.991","url":null,"abstract":"This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139343007","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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