Pub Date : 2024-07-11DOI: 10.47709/cnahpc.v6i3.4202
Achmad Adbillah Dwisyahputra, Rakhmat Kurniawan
Social media platform Twitter had become one of the most popular platforms for communication and information sharing. In the context of entertainment events such as music concerts, Twitter became a bustling place with various comments and opinions from the public regarding their experiences attending a concert. Many fans shared their experiences about Coldplay concerts on Twitter. These comments were highly varied and required a thorough understanding to interpret the overall public sentiment. Event organizers and Coldplay's band managers needed to understand public feelings about their concerts. This information was crucial for the evaluation and improvement of future events. Comments on Twitter were often brief and diverse, making manual data processing inefficient and necessitating automated tools to understand the sentiment within them. Sentiment analysis, or opinion mining, was the process used to understand, extract, and process text data automatically to gather information about the sentiment contained in opinion sentences. Research on sentiment analysis frequently focused on opinions that contained positive or negative sentiments. To classify these positive and negative sentiments, the Naive Bayes (NB) classification method was employed. The purpose of this study was to analyze the sentiment of public comments about Coldplay concerts on Twitter using the Naive Bayes method. The expected outcome was to provide insights into public sentiment towards Coldplay concerts, which would be valuable for event organizers and the band's managers in evaluating and improving future events.
{"title":"Sentiment Analysis of Public Comments on Coldplay Concerts on Twitter Using the Naïve Bayes Method","authors":"Achmad Adbillah Dwisyahputra, Rakhmat Kurniawan","doi":"10.47709/cnahpc.v6i3.4202","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4202","url":null,"abstract":"Social media platform Twitter had become one of the most popular platforms for communication and information sharing. In the context of entertainment events such as music concerts, Twitter became a bustling place with various comments and opinions from the public regarding their experiences attending a concert. Many fans shared their experiences about Coldplay concerts on Twitter. These comments were highly varied and required a thorough understanding to interpret the overall public sentiment. Event organizers and Coldplay's band managers needed to understand public feelings about their concerts. This information was crucial for the evaluation and improvement of future events. Comments on Twitter were often brief and diverse, making manual data processing inefficient and necessitating automated tools to understand the sentiment within them. Sentiment analysis, or opinion mining, was the process used to understand, extract, and process text data automatically to gather information about the sentiment contained in opinion sentences. Research on sentiment analysis frequently focused on opinions that contained positive or negative sentiments. To classify these positive and negative sentiments, the Naive Bayes (NB) classification method was employed. The purpose of this study was to analyze the sentiment of public comments about Coldplay concerts on Twitter using the Naive Bayes method. The expected outcome was to provide insights into public sentiment towards Coldplay concerts, which would be valuable for event organizers and the band's managers in evaluating and improving future events.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"119 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656984","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 : 2024-07-07DOI: 10.47709/cnahpc.v6i3.4203
Raditia Vindua, Dede Handayani, Ardilla Ekrinifda
DRs Snack has been making and selling snacks in the vicinity. However, they face problems in manually recording sales and generating accurate reports. Therefore, this project aims to design and implement a mobile-based sales system application that will help DRs Snack in managing sales and recording reports more efficiently. The main objective of this project is to design and develop a mobile-based sales system application with Dart programming language and Flutter framework that can help dRs Snack in recording sales transactions in real-time, generate sales and financial reports quickly and accurately, improve operational efficiency and decision making. The method used for system development is Extreme Programing, where this method has a development target through the determination of unclear needs or changes to the needs very quickly and through a small to medium-sized team. The results of this study can manage menus and orders that have been proven to increase operational efficiency. The implementation of this system is able to reduce the time required for order processing and improve the accuracy of data related to stock and revenue. With an integrated system, customer service can be improved and reduce human error in summarizing total payments and ensure accuracy in payments. The system enables better data analysis, especially in monitoring order history and sales recap to improve sales reports. Suggestions from researchers to maximize the features of existing features and add features to complement the features that are already running.
{"title":"Implementation of Dart Programming Language in Mobile-Based DRs Snack Sales Application Design","authors":"Raditia Vindua, Dede Handayani, Ardilla Ekrinifda","doi":"10.47709/cnahpc.v6i3.4203","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4203","url":null,"abstract":"DRs Snack has been making and selling snacks in the vicinity. However, they face problems in manually recording sales and generating accurate reports. Therefore, this project aims to design and implement a mobile-based sales system application that will help DRs Snack in managing sales and recording reports more efficiently. The main objective of this project is to design and develop a mobile-based sales system application with Dart programming language and Flutter framework that can help dRs Snack in recording sales transactions in real-time, generate sales and financial reports quickly and accurately, improve operational efficiency and decision making. The method used for system development is Extreme Programing, where this method has a development target through the determination of unclear needs or changes to the needs very quickly and through a small to medium-sized team. The results of this study can manage menus and orders that have been proven to increase operational efficiency. The implementation of this system is able to reduce the time required for order processing and improve the accuracy of data related to stock and revenue. With an integrated system, customer service can be improved and reduce human error in summarizing total payments and ensure accuracy in payments. The system enables better data analysis, especially in monitoring order history and sales recap to improve sales reports. Suggestions from researchers to maximize the features of existing features and add features to complement the features that are already running.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671081","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 : 2024-07-07DOI: 10.47709/cnahpc.v6i3.4206
Md. Wira Putra Dananjaya, Gede Humaswara Prathama, Kadek Darmaastawan
In the increasingly digital era, user interface (UI) and user experience (UX) design have become crucial factors in application development. The success of an application is not only determined by its functionality, but also by how well users can interact with the application. User Centered Design (UCD) is an approach that places users as the main focus in every stage of design, from initial research to final evaluation, to ensure that the resulting product truly meets user needs and expectations. This study applies the UCD approach to the UI and UX design of the Sculptify application, which is designed to facilitate the buying and selling of sculptures and other three-dimensional works of art. Given the complexity and uniqueness of art product transactions, effective UI and UX design is very important. This study involves the active participation of potential users through methods such as interviews, surveys, and usability testing to create an intuitive interface and provide a satisfying experience for users. The research stage begins with research to understand user needs and preferences, followed by initial design and a series of tests and iterations based on user feedback. The final evaluation is carried out to measure the extent to which the final design meets user needs and expectations. The results of the UCD implementation are expected to provide valuable insights into the importance of placing users at the center of the design process and how this can improve the quality of interactions and overall user satisfaction.
{"title":"User-Centered Design Approach in Developing User Interface and User Experience of Sculptify Mobile Application","authors":"Md. Wira Putra Dananjaya, Gede Humaswara Prathama, Kadek Darmaastawan","doi":"10.47709/cnahpc.v6i3.4206","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4206","url":null,"abstract":"In the increasingly digital era, user interface (UI) and user experience (UX) design have become crucial factors in application development. The success of an application is not only determined by its functionality, but also by how well users can interact with the application. User Centered Design (UCD) is an approach that places users as the main focus in every stage of design, from initial research to final evaluation, to ensure that the resulting product truly meets user needs and expectations. This study applies the UCD approach to the UI and UX design of the Sculptify application, which is designed to facilitate the buying and selling of sculptures and other three-dimensional works of art. Given the complexity and uniqueness of art product transactions, effective UI and UX design is very important. This study involves the active participation of potential users through methods such as interviews, surveys, and usability testing to create an intuitive interface and provide a satisfying experience for users. The research stage begins with research to understand user needs and preferences, followed by initial design and a series of tests and iterations based on user feedback. The final evaluation is carried out to measure the extent to which the final design meets user needs and expectations. The results of the UCD implementation are expected to provide valuable insights into the importance of placing users at the center of the design process and how this can improve the quality of interactions and overall user satisfaction.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 45","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671794","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 : 2024-07-07DOI: 10.47709/cnahpc.v6i3.4137
Yessy Phalentina br Sagala, Roman Samosir, Yonata Laia
Medan city is currently experiencing a troubling rise in the prevalence of drug abuse, necessitating effective strategies for detection and intervention. This research aims to improve the accuracy of identifying drug users in Medan using the Support Vector Machine (SVM) method. Data for the study were sourced from reputable institutions including the National Narcotics Agency (BNN), North Sumatra Regional Police (Polda Sumut), and the Health Office of Medan City. SVM was employed to analyze these datasets and distinguish between drug users and non-users. The study revealed that SVM achieved an impressive detection accuracy of 98.0%, a notable improvement compared to earlier approaches like Convolutional Neural Networks (CNN), which attained 83.33% accuracy.These findings highlight SVM's effectiveness as a robust tool for accurately identifying drug users. The outcomes of this study are anticipated to aid government entities in crafting targeted policies and strategies to combat drug abuse in Medan. By harnessing SVM technology, law enforcement and healthcare authorities can bolster their capabilities in swiftly and precisely detecting and responding to drug-related issues. This research contributes significantly to advancing methodologies in drug abuse detection, emphasizing SVM's pivotal role in achieving superior detection rates. In conclusion, the application of SVM in this study not only enhances detection accuracy but also underscores its potential as a reliable technology for addressing the growing challenge of drug abuse in urban settings like Medan. Future research could further refine SVM models and explore additional datasets to validate its efficacy in real-world scenarios, thereby strengthening efforts to mitigate the societal impact of drug misuse.
{"title":"Investigation of The Increase in Drug Use in Medan City Using The Support Vector Machine (SVM) Method","authors":"Yessy Phalentina br Sagala, Roman Samosir, Yonata Laia","doi":"10.47709/cnahpc.v6i3.4137","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4137","url":null,"abstract":"Medan city is currently experiencing a troubling rise in the prevalence of drug abuse, necessitating effective strategies for detection and intervention. This research aims to improve the accuracy of identifying drug users in Medan using the Support Vector Machine (SVM) method. Data for the study were sourced from reputable institutions including the National Narcotics Agency (BNN), North Sumatra Regional Police (Polda Sumut), and the Health Office of Medan City. SVM was employed to analyze these datasets and distinguish between drug users and non-users. The study revealed that SVM achieved an impressive detection accuracy of 98.0%, a notable improvement compared to earlier approaches like Convolutional Neural Networks (CNN), which attained 83.33% accuracy.These findings highlight SVM's effectiveness as a robust tool for accurately identifying drug users. The outcomes of this study are anticipated to aid government entities in crafting targeted policies and strategies to combat drug abuse in Medan. By harnessing SVM technology, law enforcement and healthcare authorities can bolster their capabilities in swiftly and precisely detecting and responding to drug-related issues. This research contributes significantly to advancing methodologies in drug abuse detection, emphasizing SVM's pivotal role in achieving superior detection rates. In conclusion, the application of SVM in this study not only enhances detection accuracy but also underscores its potential as a reliable technology for addressing the growing challenge of drug abuse in urban settings like Medan. Future research could further refine SVM models and explore additional datasets to validate its efficacy in real-world scenarios, thereby strengthening efforts to mitigate the societal impact of drug misuse.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 82","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671045","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}
Universities must provide good education so that they can produce good graduates.There are many factors that influence student graduation rates, one of the problems faced by an educational institution, especially at universities, whether state or private, is finding predictions of student graduation rates on time.One of the technological advances currently available is a system that can predict whether students will graduate on time or not. One of the machine planning algorithms that can be used is the Support Vector Machine.The results of this research were carried out by predicting the on-time graduation rate of students at Nurul Jadid University, Faculty of Engineering, Informatics Study Program. By using the Support Vector Machine method, this research used testing data of 20% of the data from 612 student data with the same 7 attributes. The data obtained 123 data which resulted in 72 student data being on time, 45 student data being late, 4 student data being correct. time and 2 students' data was late. From the results, the accuracy of the training data was 94%, while the results of the accuracy of the testing data received a score of 95%. And based on the validity test of the Support Vector Machine algorithm, the presentation results obtained were Accuracy levels of 96%, Recall 98%, and Precision 94% from 123 testing data. Next, the model is deployed using Streamlit. Streamlit is an open source Python-based framework designed to help developers build interactive web-based programs in the fields of data science and machine learning. The accuracy rate is very good, this shows that SVM can be applied to predict student graduation rates.
{"title":"Application of The Support Vector Machine Algorithm for Timely Student Graduation Prediction Based on Streamlit Web at The Faculty of Informatics Engineering Nurul Jadid University","authors":"Yati Yati, Moh Ainol Yaqin, Anis Yusrotun Nadhiroh","doi":"10.47709/cnahpc.v6i3.3918","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.3918","url":null,"abstract":"Universities must provide good education so that they can produce good graduates.There are many factors that influence student graduation rates, one of the problems faced by an educational institution, especially at universities, whether state or private, is finding predictions of student graduation rates on time.One of the technological advances currently available is a system that can predict whether students will graduate on time or not. One of the machine planning algorithms that can be used is the Support Vector Machine.The results of this research were carried out by predicting the on-time graduation rate of students at Nurul Jadid University, Faculty of Engineering, Informatics Study Program. By using the Support Vector Machine method, this research used testing data of 20% of the data from 612 student data with the same 7 attributes. The data obtained 123 data which resulted in 72 student data being on time, 45 student data being late, 4 student data being correct. time and 2 students' data was late. From the results, the accuracy of the training data was 94%, while the results of the accuracy of the testing data received a score of 95%. And based on the validity test of the Support Vector Machine algorithm, the presentation results obtained were Accuracy levels of 96%, Recall 98%, and Precision 94% from 123 testing data. Next, the model is deployed using Streamlit. Streamlit is an open source Python-based framework designed to help developers build interactive web-based programs in the fields of data science and machine learning. The accuracy rate is very good, this shows that SVM can be applied to predict student graduation rates.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141672009","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 : 2024-07-03DOI: 10.47709/cnahpc.v6i3.4171
Dimas Reza Nugraha, Ahmad Turmudi Zy, Aswan Supriyadi Sunge
Life expectancy is defined as information that illustrates the age of the death of a population. Life expectancy is a general picture of the state of a region. If the infant mortality rate is high, then the life expectancy in the area is low. And vice versa, if the infant mortality rate is low, the life expectancy in the region is high. Life expectancy is also a benchmark for government actions in improving the welfare of society and the human development index. For this reason, it is necessary to group life expectancy data to make it easier to determine the provinces with high, middle, and low life expectancy. The results of cluster testing using the silhouette score method showed that two subjects had a low silhouette score level, which caused the cluster value to be less than optimal, namely East Java & Gorontalo. The clustering results found that the cluster was divided into 3, namely cluster 1, with a high level of life expectancy consisting of 10 provinces, namely East Java, Riau, North Sulawesi, Bali, North Kalimantan, DKI Jakarta, West Java, Central Java, East Kalimantan and Special Region of Yogyakarta. Cluster 2 has a level of middle-life expectancy consisting of 18 provinces, namely Gorontalo, North Maluku, Central Sulawesi, South Kalimantan, North Sumatra, Bengkulu, West Sumatra, Central Kalimantan, Aceh, South Sumatra, Banten, Kep. Riau, South Sulawesi, Kep. Bangka Belitung, Lampung, West Kalimantan, Southeast Sulawesi and Jambi. Cluster 3, with a low level of life expectancy, consists of 6 provinces, namely West Sulawesi, Papua, Maluku, West Papua, West Nusa Tenggara, and East Nusa Tenggara.
{"title":"The Use of K-Means Algorithm Clustering in Grouping Life Expectancy (Case Study: Provinces in Indonesia)","authors":"Dimas Reza Nugraha, Ahmad Turmudi Zy, Aswan Supriyadi Sunge","doi":"10.47709/cnahpc.v6i3.4171","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4171","url":null,"abstract":"Life expectancy is defined as information that illustrates the age of the death of a population. Life expectancy is a general picture of the state of a region. If the infant mortality rate is high, then the life expectancy in the area is low. And vice versa, if the infant mortality rate is low, the life expectancy in the region is high. Life expectancy is also a benchmark for government actions in improving the welfare of society and the human development index. For this reason, it is necessary to group life expectancy data to make it easier to determine the provinces with high, middle, and low life expectancy. The results of cluster testing using the silhouette score method showed that two subjects had a low silhouette score level, which caused the cluster value to be less than optimal, namely East Java & Gorontalo. The clustering results found that the cluster was divided into 3, namely cluster 1, with a high level of life expectancy consisting of 10 provinces, namely East Java, Riau, North Sulawesi, Bali, North Kalimantan, DKI Jakarta, West Java, Central Java, East Kalimantan and Special Region of Yogyakarta. Cluster 2 has a level of middle-life expectancy consisting of 18 provinces, namely Gorontalo, North Maluku, Central Sulawesi, South Kalimantan, North Sumatra, Bengkulu, West Sumatra, Central Kalimantan, Aceh, South Sumatra, Banten, Kep. Riau, South Sulawesi, Kep. Bangka Belitung, Lampung, West Kalimantan, Southeast Sulawesi and Jambi. Cluster 3, with a low level of life expectancy, consists of 6 provinces, namely West Sulawesi, Papua, Maluku, West Papua, West Nusa Tenggara, and East Nusa Tenggara.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"85 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682855","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 : 2024-07-03DOI: 10.47709/cnahpc.v6i3.4162
Gusti Ngurah, Darma Paramartha, Yohanes Samuel Sofyan, Gusi Putu, Lestara Permana
Recent technological advancements have significantly transformed human life, particularly with the advent of the Fourth Industrial Revolution, which has profoundly influenced the use of the internet for business and economic activities. E-commerce has emerged as a crucial medium for online buying and selling, propelled by these digital advancements. This growth is especially evident in Indonesia, which ranks among the countries with the highest number of internet users globally. This study aims to identify the dominant factors influencing user journey mapping and their impact on the user experience of Tokopedia mobile application users. The research sample comprises 125 users of the Tokopedia application, with data collected through questionnaires distributed via Google Forms. The analysis involves factor analysis and simple linear regression. The findings reveal that the dominant factors influencing user journey mapping are user persona and opportunity. Furthermore, the study demonstrates that user journey mapping positively impacts the user experience for Tokopedia application users. This research underscores the importance of understanding user journey mapping in enhancing the overall user experience, which is crucial for e-commerce platforms like Tokopedia. The insights gained from this study can assist developers and marketers in better tailoring their strategies to improve user engagement and satisfaction. This study provides valuable perspectives on how user journey mapping can be utilized as a strategic tool to optimize user interactions and ensure that each step in the user journey delivers maximum value. Thus, user journey mapping not only enhances individual experiences but also contributes to the overall success of e-commerce platforms in an increasingly competitive market.
{"title":"Analysis of User Journey Mapping Factors to Enhance User Experience in the Tokopedia Mobile E-Commerce Application","authors":"Gusti Ngurah, Darma Paramartha, Yohanes Samuel Sofyan, Gusi Putu, Lestara Permana","doi":"10.47709/cnahpc.v6i3.4162","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.4162","url":null,"abstract":"Recent technological advancements have significantly transformed human life, particularly with the advent of the Fourth Industrial Revolution, which has profoundly influenced the use of the internet for business and economic activities. E-commerce has emerged as a crucial medium for online buying and selling, propelled by these digital advancements. This growth is especially evident in Indonesia, which ranks among the countries with the highest number of internet users globally. This study aims to identify the dominant factors influencing user journey mapping and their impact on the user experience of Tokopedia mobile application users. The research sample comprises 125 users of the Tokopedia application, with data collected through questionnaires distributed via Google Forms. The analysis involves factor analysis and simple linear regression. The findings reveal that the dominant factors influencing user journey mapping are user persona and opportunity. Furthermore, the study demonstrates that user journey mapping positively impacts the user experience for Tokopedia application users. This research underscores the importance of understanding user journey mapping in enhancing the overall user experience, which is crucial for e-commerce platforms like Tokopedia. The insights gained from this study can assist developers and marketers in better tailoring their strategies to improve user engagement and satisfaction. This study provides valuable perspectives on how user journey mapping can be utilized as a strategic tool to optimize user interactions and ensure that each step in the user journey delivers maximum value. Thus, user journey mapping not only enhances individual experiences but also contributes to the overall success of e-commerce platforms in an increasingly competitive market.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"16 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141681579","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 : 2024-07-02DOI: 10.47709/cnahpc.v6i3.3979
Din Nuryanto, Susanna Dwi Yulianti Kusuma
Inspections are carried out to check objects to ensure that they meet certain standards. Laboratory officers have difficulty in the reporting process requested by the head of the section quickly, because officers must compare all gas detection device data. And laboratory officers sometimes leave the completeness of other supporting devices. So that each equipment officer has difficulty determining which units are damaged or repaired. Application research methods include literature study analysis, interviews, observations, while the development method used is the waterfall model. The design of the application displayed uses the android platform, the software used in building the application is android studio with the java programming language, while MySQL as a database. The purpose of this research is to provide information needed by PT Saka Tunggal Manadiri Jaya in improving product quality. The results achieved at the end of the study are the application of the gas detection device problem report in providing characteristic inspection information, making it easier for users to obtain inspection report information searches along with product items produced in accordance with the provisions and standards of inspection control of one very important component. By utilizing android-based technology through mobile devices. In order to find out the types of inspections in quality control either functional or tool change.
{"title":"Design of an Android-based Troubled Gas Detection Tool Report Application at PT. Saka Tunggal Mandiri Jaya","authors":"Din Nuryanto, Susanna Dwi Yulianti Kusuma","doi":"10.47709/cnahpc.v6i3.3979","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.3979","url":null,"abstract":"Inspections are carried out to check objects to ensure that they meet certain standards. Laboratory officers have difficulty in the reporting process requested by the head of the section quickly, because officers must compare all gas detection device data. And laboratory officers sometimes leave the completeness of other supporting devices. So that each equipment officer has difficulty determining which units are damaged or repaired. Application research methods include literature study analysis, interviews, observations, while the development method used is the waterfall model. The design of the application displayed uses the android platform, the software used in building the application is android studio with the java programming language, while MySQL as a database. The purpose of this research is to provide information needed by PT Saka Tunggal Manadiri Jaya in improving product quality. The results achieved at the end of the study are the application of the gas detection device problem report in providing characteristic inspection information, making it easier for users to obtain inspection report information searches along with product items produced in accordance with the provisions and standards of inspection control of one very important component. By utilizing android-based technology through mobile devices. In order to find out the types of inspections in quality control either functional or tool change.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685899","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 : 2024-07-02DOI: 10.47709/cnahpc.v6i3.3969
Safira Fegi Nisrina, Mohammad Alfian Mudzakir, Basuki Rahmat
Solar panels are a medium that can convert solar energy into electrical energy. In this research, the solar panel system in the fish pond is used as air requirements for the survival of the fish so that the air supply is sufficient. The problem is that fish farming has cloudy water due to decreasing temperatures due to lack of irrigation. This condition really requires water flow using a pump to circulate water in the fish pond. Therefore, solar panels are needed to drive the water circulation pump, where these solar panels are an alternative energy source to replace electricity from the State Electricity Company (PLN).The purpose of using a solar panel system is as alternative energy that can supply a pump motor which functions to channel water from the well to the pond to keep it flowing. This is used as alternative electrical energy to replace energy sources originating from the State Electricity Company (PLN) and to reduce operational costs of electrical energy. The method used is to assemble and install 2 units of 100WP solar panels, then testing is carried out to measure the panel output power from 06.00 to 17.00. The average result of measuring solar panel power every 30 minutes is 24.48Watts per day, this condition was when the test was carried out when the weather was less sunny. However, this can still change to get maximum power depending on weather conditions, especially when the sun is hot.
{"title":"Utilization of Solar Panel Technology to Save Electricity Costs in Fish Farm Irrigation","authors":"Safira Fegi Nisrina, Mohammad Alfian Mudzakir, Basuki Rahmat","doi":"10.47709/cnahpc.v6i3.3969","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.3969","url":null,"abstract":"Solar panels are a medium that can convert solar energy into electrical energy. In this research, the solar panel system in the fish pond is used as air requirements for the survival of the fish so that the air supply is sufficient. The problem is that fish farming has cloudy water due to decreasing temperatures due to lack of irrigation. This condition really requires water flow using a pump to circulate water in the fish pond. Therefore, solar panels are needed to drive the water circulation pump, where these solar panels are an alternative energy source to replace electricity from the State Electricity Company (PLN).The purpose of using a solar panel system is as alternative energy that can supply a pump motor which functions to channel water from the well to the pond to keep it flowing. This is used as alternative electrical energy to replace energy sources originating from the State Electricity Company (PLN) and to reduce operational costs of electrical energy. The method used is to assemble and install 2 units of 100WP solar panels, then testing is carried out to measure the panel output power from 06.00 to 17.00. The average result of measuring solar panel power every 30 minutes is 24.48Watts per day, this condition was when the test was carried out when the weather was less sunny. However, this can still change to get maximum power depending on weather conditions, especially when the sun is hot.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"28 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685455","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 : 2024-07-02DOI: 10.47709/cnahpc.v6i3.3999
Ayu Mahriza Agustin Efendi, Sriani Sriani, Muhammad Siddik Hasibuan
Watermelons had high appeal due to their sweet taste, refreshing nature, and numerous benefits. However, consumers often faced difficulties in selecting suitable fruit because of the subtle differences between fully ripe and half-ripe watermelons. One important indicator of a watermelon’s ripeness was the yellowish pattern on its skin. In this study, the proposed use of digital image processing methods, specifically the HSV Color Space Transformation, was aimed at extracting watermelon images and employing the K-Nearest Neighbor (K-NN) method to classify them into two categories: "Ripe" and "Half-Ripe." HSV (Hue Saturation Value) was a color extraction method used to convert colors from the RGB model. The Hue component indicated the type of color, Saturation measured the purity of the color, and Value measured the brightness of the color on a scale from 0 to 100%. In this research, the K-Nearest Neighbor (K-NN) method was applied to classify watermelon images based on the extraction of skin color features. This method compared a new image (test data) with training images to determine classification based on the nearest distance with a parameter of k=3. The data used consisted of 120 images, with 92 images used as training data and 28 images as test data. Experimental results showed an accuracy of 89%, with 25 images correctly classified and 3 images misclassified.
{"title":"Classification of Watermelon Ripeness Levels Using HSV Color Space Transformation and K-Nearest Neighbor Method","authors":"Ayu Mahriza Agustin Efendi, Sriani Sriani, Muhammad Siddik Hasibuan","doi":"10.47709/cnahpc.v6i3.3999","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i3.3999","url":null,"abstract":"Watermelons had high appeal due to their sweet taste, refreshing nature, and numerous benefits. However, consumers often faced difficulties in selecting suitable fruit because of the subtle differences between fully ripe and half-ripe watermelons. One important indicator of a watermelon’s ripeness was the yellowish pattern on its skin. In this study, the proposed use of digital image processing methods, specifically the HSV Color Space Transformation, was aimed at extracting watermelon images and employing the K-Nearest Neighbor (K-NN) method to classify them into two categories: \"Ripe\" and \"Half-Ripe.\" HSV (Hue Saturation Value) was a color extraction method used to convert colors from the RGB model. The Hue component indicated the type of color, Saturation measured the purity of the color, and Value measured the brightness of the color on a scale from 0 to 100%. In this research, the K-Nearest Neighbor (K-NN) method was applied to classify watermelon images based on the extraction of skin color features. This method compared a new image (test data) with training images to determine classification based on the nearest distance with a parameter of k=3. The data used consisted of 120 images, with 92 images used as training data and 28 images as test data. Experimental results showed an accuracy of 89%, with 25 images correctly classified and 3 images misclassified.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"335 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686636","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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