Pub Date : 2024-05-20DOI: 10.47709/cnahpc.v6i2.3834
Ridho Wahyudi Pulungan, Sriani Sriani, A. Armansyah
The Nile tilapia, also known as Oreochromis niloticus, was a freshwater fish species first produced in East Africa in 1969. It became a popular aquaculture fish in freshwater ponds across Indonesia. Besides its delicious taste, the Nile tilapia is rich in nutrients essential for human health. However, cultivating Nile tilapia was challenging due to frequent bacterial diseases. These diseases often led to mass fish deaths, causing financial losses, especially for new fish farmers. The rapid spread of diseases emphasized the need for prompt intervention to prevent further losses. Farmers needed adequate knowledge about Nile tilapia diseases, but often struggled to absorb information provided by the government. Hence, the presence of experts or veterinarians was crucial in assisting farmers to address these issues. Farmers of Nile tilapia sought assistance from experts or veterinarians, but this was not easy. It involved substantial costs and time, while quick intervention was necessary to mitigate losses. The solution proposed was the development of an expert system for diagnosing and treating Nile tilapia diseases. Thus, an expert system was built to assist fish farmers in identifying fish diseases and their treatments by implementing the naïve Bayes method. The expert system transferred human knowledge to computers, enabling them to solve problems like experts, thereby making expert knowledge accessible to non-experts. Naïve Bayes was implemented to determine the highest probability based on input symptoms. This research used five test data samples to apply the naïve Bayes method to diagnose Nile tilapia diseases, resulting in an accuracy rate of 80%. Therefore, the implementation of naïve Bayes in diagnosing Nile tilapia diseases is considered reasonably effective.
{"title":"Implementation of Naïve Bayes Method Diagnosing Diseases Nile Tilapia","authors":"Ridho Wahyudi Pulungan, Sriani Sriani, A. Armansyah","doi":"10.47709/cnahpc.v6i2.3834","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i2.3834","url":null,"abstract":"The Nile tilapia, also known as Oreochromis niloticus, was a freshwater fish species first produced in East Africa in 1969. It became a popular aquaculture fish in freshwater ponds across Indonesia. Besides its delicious taste, the Nile tilapia is rich in nutrients essential for human health. However, cultivating Nile tilapia was challenging due to frequent bacterial diseases. These diseases often led to mass fish deaths, causing financial losses, especially for new fish farmers. The rapid spread of diseases emphasized the need for prompt intervention to prevent further losses. Farmers needed adequate knowledge about Nile tilapia diseases, but often struggled to absorb information provided by the government. Hence, the presence of experts or veterinarians was crucial in assisting farmers to address these issues. Farmers of Nile tilapia sought assistance from experts or veterinarians, but this was not easy. It involved substantial costs and time, while quick intervention was necessary to mitigate losses. The solution proposed was the development of an expert system for diagnosing and treating Nile tilapia diseases. Thus, an expert system was built to assist fish farmers in identifying fish diseases and their treatments by implementing the naïve Bayes method. The expert system transferred human knowledge to computers, enabling them to solve problems like experts, thereby making expert knowledge accessible to non-experts. Naïve Bayes was implemented to determine the highest probability based on input symptoms. This research used five test data samples to apply the naïve Bayes method to diagnose Nile tilapia diseases, resulting in an accuracy rate of 80%. Therefore, the implementation of naïve Bayes in diagnosing Nile tilapia diseases is considered reasonably effective.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"25 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141122371","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}
The technological advancements of the past have transformed various sectors, including information, education, and commerce. Many utilized the internet to enhance business and trade efficiency. Pantai Gading Village was a significant contributor to agricultural production. Its residents traditionally sold agricultural products locally, resulting in a narrow market scope. Consequently, a web-based E-commerce platform was developed using the User Experience Design Process to aid farmers and expand the market for agricultural products in the village. E-commerce facilitated cost reduction for companies, consumers, and management while enhancing service quality and speed. Through this platform, farmers could promote and sell their products online, overcoming the limitations of the local market and enhancing the village's global visibility. User Experience Design (UXD) improved user satisfaction with products through enhanced usability, accessibility, and satisfaction in interactions. This approach yielded designs that were neat, simple, intuitive, flexible, and appealing, providing users with a unique experience and differentiating products or services from competitors. The author of this study employed the Research and Development (R&D) methodology and the Waterfall development method. The system developed incorporated user experience design processes derived from questionnaire results. Users expressed the need for features such as live chat for each product, shipping options, displaying reviews, and offering Cash on Delivery payment method. This system facilitated and streamlined the marketing of agricultural products, thus boosting sales in Pantai Gading Village.
过去的技术进步改变了各个领域，包括信息、教育和商业。许多人利用互联网来提高商业和贸易效率。Pantai Gading 村是农业生产的重要贡献者。该村居民传统上在当地销售农产品，导致市场范围狭窄。因此，该村利用 "用户体验设计流程 "开发了一个基于网络的电子商务平台，以帮助农民扩大农产品市场。 电子商务有利于降低企业、消费者和管理部门的成本，同时提高服务质量和速度。通过这一平台，农民可以在网上推广和销售他们的产品，克服了当地市场的局限性，提高了该村在全球的知名度。用户体验设计（UXD）通过提高产品的可用性、易用性和交互满意度，提高了用户对产品的满意度。这种方法所产生的设计整洁、简洁、直观、灵活、吸引人，为用户提供了独特的体验，并使产品或服务与竞争对手区别开来。本研究的作者采用了研究与开发（R&D）方法和瀑布式开发方法。所开发的系统结合了从问卷调查结果中得出的用户体验设计流程。用户表达了对各种功能的需求，如每件产品的即时聊天、运输选项、显示评论以及提供货到付款方式。该系统促进并简化了农产品的营销，从而提高了 Pantai Gading 村的销售额。
{"title":"Implementation of User Experience Design Approach in Web Based E-Commerce for the Agricultural Sector","authors":"Saprida Saprida, Raissa Amanda Putri, Aninda Muliani Harahap","doi":"10.47709/cnahpc.v6i2.3809","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i2.3809","url":null,"abstract":"The technological advancements of the past have transformed various sectors, including information, education, and commerce. Many utilized the internet to enhance business and trade efficiency. Pantai Gading Village was a significant contributor to agricultural production. Its residents traditionally sold agricultural products locally, resulting in a narrow market scope. Consequently, a web-based E-commerce platform was developed using the User Experience Design Process to aid farmers and expand the market for agricultural products in the village. E-commerce facilitated cost reduction for companies, consumers, and management while enhancing service quality and speed. Through this platform, farmers could promote and sell their products online, overcoming the limitations of the local market and enhancing the village's global visibility. User Experience Design (UXD) improved user satisfaction with products through enhanced usability, accessibility, and satisfaction in interactions. This approach yielded designs that were neat, simple, intuitive, flexible, and appealing, providing users with a unique experience and differentiating products or services from competitors. The author of this study employed the Research and Development (R&D) methodology and the Waterfall development method. The system developed incorporated user experience design processes derived from questionnaire results. Users expressed the need for features such as live chat for each product, shipping options, displaying reviews, and offering Cash on Delivery payment method. This system facilitated and streamlined the marketing of agricultural products, thus boosting sales in Pantai Gading Village.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"101 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141126183","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 : 2024-05-12DOI: 10.47709/cnahpc.v6i2.3825
Iqbal Maulana Syahputra, Triase Triase, Septiana Dewi Andriana
The business sector faced intensifying competition due to significant advancements in information systems and technology. PT. Florindo Makmur, a leading private company in the cassava processing industry producing tapioca flour, has proven to implement quality standards to uphold product quality and ensure customer satisfaction. The product quality inspection process had to meet standards before packaging; however, reporting remained manual using paper sheets, elevating the risk of data loss and reducing monthly evaluation efficiency due to manual calculations. The aim of this research was to design an efficient information system for monitoring product quality at PT. Florindo Makmur, utilizing the Statistical Quality Control (SQC) method. The quality control monitoring system played a central role in gathering quality control data to support management decisions regarding product quality certainty. Therefore, obtaining monitoring information promptly was crucial to ensure products met quality standards and reduce rejected product quantities. The research approach included observation, interviews, and literature review as data collection strategies, while the system development method used was the waterfall method encompassing system requirement analysis, design, coding, and implementation. This information system enabled PT. Florindo Makmur to efficiently monitor its products by applying SQC concepts such as data analysis and creating control charts to swiftly identify improvements in product defects and take appropriate actions.
{"title":"Implementation of Statistical Quality Control Method in Product Quality Monitoring Information System","authors":"Iqbal Maulana Syahputra, Triase Triase, Septiana Dewi Andriana","doi":"10.47709/cnahpc.v6i2.3825","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i2.3825","url":null,"abstract":"The business sector faced intensifying competition due to significant advancements in information systems and technology. PT. Florindo Makmur, a leading private company in the cassava processing industry producing tapioca flour, has proven to implement quality standards to uphold product quality and ensure customer satisfaction. The product quality inspection process had to meet standards before packaging; however, reporting remained manual using paper sheets, elevating the risk of data loss and reducing monthly evaluation efficiency due to manual calculations. The aim of this research was to design an efficient information system for monitoring product quality at PT. Florindo Makmur, utilizing the Statistical Quality Control (SQC) method. The quality control monitoring system played a central role in gathering quality control data to support management decisions regarding product quality certainty. Therefore, obtaining monitoring information promptly was crucial to ensure products met quality standards and reduce rejected product quantities. The research approach included observation, interviews, and literature review as data collection strategies, while the system development method used was the waterfall method encompassing system requirement analysis, design, coding, and implementation. This information system enabled PT. Florindo Makmur to efficiently monitor its products by applying SQC concepts such as data analysis and creating control charts to swiftly identify improvements in product defects and take appropriate actions.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128773","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 : 2024-02-26DOI: 10.47709/cnahpc.v6i1.3570
Asri Wahyuni, Dzoen Nuraeni Badarul Zaman
In today's technological developments, many people are using technology to make work easier, as is PT. PLN Persero Customer Service Implementation Unit (UP3) Tasikmalaya. Several parts of this company, especially the section for recording expenses and customers by the PDKB Team, still use manual methods, namely by calculating using a calculator. This method is very risky, especially as it has the potential for errors in calculations or writing of the recorded numbers. Given these problems, a desktop-based load and customer calculation application information system (SIAPEL) was built. Information system solutions for related load and customer data calculation applications (SIAPEL) so that the results obtained are faster and more accurate. By making direct observations or observations, actively communicating with related fields through the interview process, and looking for research materials that support building an application as a solution to the problems faced. The load and customer calculation application information system (SIAPEL) is an application that can calculate load and customer data and can store the data as a form of company archive. The system development used is waterfall with stages or processes carried out sequentially from the system. The software used to build the load and customer calculation application information system (SIAPEL) is NetBeans 8.2, Java Development Kit 1.8, and MySql. Users can process load calculation data and process customer calculation data. And users can print reports from data that has been entered into the system database. With SIAPEL, it is hoped that it can reduce the risk of information errors and make it easier for users to calculate, store and process data. And it can be used as a more effective way to process data compared to using manual methods
{"title":"Design a Desktop-Based Load and Customer Calculation Application Information System (SIAPEL)","authors":"Asri Wahyuni, Dzoen Nuraeni Badarul Zaman","doi":"10.47709/cnahpc.v6i1.3570","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i1.3570","url":null,"abstract":"In today's technological developments, many people are using technology to make work easier, as is PT. PLN Persero Customer Service Implementation Unit (UP3) Tasikmalaya. Several parts of this company, especially the section for recording expenses and customers by the PDKB Team, still use manual methods, namely by calculating using a calculator. This method is very risky, especially as it has the potential for errors in calculations or writing of the recorded numbers. Given these problems, a desktop-based load and customer calculation application information system (SIAPEL) was built. Information system solutions for related load and customer data calculation applications (SIAPEL) so that the results obtained are faster and more accurate. By making direct observations or observations, actively communicating with related fields through the interview process, and looking for research materials that support building an application as a solution to the problems faced. The load and customer calculation application information system (SIAPEL) is an application that can calculate load and customer data and can store the data as a form of company archive. The system development used is waterfall with stages or processes carried out sequentially from the system. The software used to build the load and customer calculation application information system (SIAPEL) is NetBeans 8.2, Java Development Kit 1.8, and MySql. Users can process load calculation data and process customer calculation data. And users can print reports from data that has been entered into the system database. With SIAPEL, it is hoped that it can reduce the risk of information errors and make it easier for users to calculate, store and process data. And it can be used as a more effective way to process data compared to using manual methods","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"32 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140429476","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 : 2024-02-19DOI: 10.47709/cnahpc.v6i1.3565
Arief Yulianto
Foreign tourist visits to Yogyakarta, Indonesia have increased in 2022 and 2023 after Covid-19. Many tourists are seeking unique experiences, such as riding on bicycles to enjoy the beautiful scenery and interact with local residents. Towilfiets, a pioneer in onthel bicycle tourism, has been operating in Bantar Hamlet, Kulon Progo for around 10 years. With the growing demand for this activity, Towilfiets needed to innovate their promotion methods, specifically in the digital industry. The development of a user-interface design-based application became crucial to enhance and facilitate the onthel bicycle tourism experience at Towilfiets. The research conducted used a mixed method approach with a phenomenological qualitative method to gather interview data. The prototype method was chosen to allow for intensive and better communication between developers and users. The validation of the questionnaire data was calculated using the Scalable Usage System and received a good score 75 up to score 100 point, indicating acceptable usability. By focusing on user needs and the unique characteristics of tourist destinations, this application aims to increase user engagement and provide relevant and useful information about bicycle tourist attractions in the area. Ultimately, the research aims to develop an innovative and contextualized user interface design application that supports the growth of onthel bike tourism in Towilfiets, located in Dusun Bantar, Kulon Progo, Yogyakarta, Indonesia.
{"title":"User Interface Design Prototype Application Special Onthel Bicycle Tourism in Towilfiets Yogyakarta","authors":"Arief Yulianto","doi":"10.47709/cnahpc.v6i1.3565","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i1.3565","url":null,"abstract":"Foreign tourist visits to Yogyakarta, Indonesia have increased in 2022 and 2023 after Covid-19. Many tourists are seeking unique experiences, such as riding on bicycles to enjoy the beautiful scenery and interact with local residents. Towilfiets, a pioneer in onthel bicycle tourism, has been operating in Bantar Hamlet, Kulon Progo for around 10 years. With the growing demand for this activity, Towilfiets needed to innovate their promotion methods, specifically in the digital industry. The development of a user-interface design-based application became crucial to enhance and facilitate the onthel bicycle tourism experience at Towilfiets. The research conducted used a mixed method approach with a phenomenological qualitative method to gather interview data. The prototype method was chosen to allow for intensive and better communication between developers and users. The validation of the questionnaire data was calculated using the Scalable Usage System and received a good score 75 up to score 100 point, indicating acceptable usability. By focusing on user needs and the unique characteristics of tourist destinations, this application aims to increase user engagement and provide relevant and useful information about bicycle tourist attractions in the area. Ultimately, the research aims to develop an innovative and contextualized user interface design application that supports the growth of onthel bike tourism in Towilfiets, located in Dusun Bantar, Kulon Progo, Yogyakarta, Indonesia.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"170 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140451228","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 : 2024-02-18DOI: 10.47709/cnahpc.v6i1.3611
Agung Prabowo, Sumita Wardani, Abdul Muis, Radiman Gea, Nathanael Atan Baskita Tarigan
Chronic Kidney Disease (CKD) is. In the past, several learners have been applied for prediction of CKD but there is still enough space to develop classi?ers with higher accuracy. The study utilizes chronic kidney disease dataset from UCI Machine Learning Repository. In this paper, individual approaches, viz., linear-SVM, kernel methods including polynomial, radial basis function, and sigmoid have been used while among ensembles majority voting and stacking strategies have been applied. Stacked Ensemble is based on various types of meta-learners such as C4.5, NB, k-NN, SMO, and logit-boost. The stacking approach with meta-learner Logit-Boost (ST-LB) achieves accuracy 98,50%, sensitivity 98,50%, false positive rate 20,00%, precision 98,50%, and F-measure 98,50% demonstrating that it is the best classi?er as compared to any of the individual and ensemble approaches
{"title":"Diagnosis and Prediction of Chronic Kidney Disease Using a Stacked Generalization Approach","authors":"Agung Prabowo, Sumita Wardani, Abdul Muis, Radiman Gea, Nathanael Atan Baskita Tarigan","doi":"10.47709/cnahpc.v6i1.3611","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i1.3611","url":null,"abstract":"Chronic Kidney Disease (CKD) is. In the past, several learners have been applied for prediction of CKD but there is still enough space to develop classi?ers with higher accuracy. The study utilizes chronic kidney disease dataset from UCI Machine Learning Repository. In this paper, individual approaches, viz., linear-SVM, kernel methods including polynomial, radial basis function, and sigmoid have been used while among ensembles majority voting and stacking strategies have been applied. Stacked Ensemble is based on various types of meta-learners such as C4.5, NB, k-NN, SMO, and logit-boost. The stacking approach with meta-learner Logit-Boost (ST-LB) achieves accuracy 98,50%, sensitivity 98,50%, false positive rate 20,00%, precision 98,50%, and F-measure 98,50% demonstrating that it is the best classi?er as compared to any of the individual and ensemble approaches","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959150","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 : 2024-02-18DOI: 10.47709/cnahpc.v6i1.3600
Doughlas Pardede, Aulia Ichsan, Sugeng Riyadi
Machine learning plays a crucial role in identifying patterns within data, with classification being a prominent application. This study investigates the use of Multilayer Perceptron (MLP) classification models and explores preprocessing techniques, particularly K-Means clustering, to enhance model performance. Overfitting, a common challenge in MLP models, is addressed through the application of K-Means clustering to streamline data preparation and improve classification accuracy. The study begins with an overview of overfitting in MLP models, highlighting the significance of mitigating this issue. Various techniques for addressing overfitting are reviewed, including regularization, dropout, early stopping, data augmentation, and ensemble methods. Additionally, the complementary role of K-Means clustering in enhancing model performance is emphasized. Preprocessing using K-Means clustering aims to reduce data complexity and prevent overfitting in MLP models. Three datasets - Iris, Wine, and Breast Cancer Wisconsin - are employed to evaluate the performance of K-Means as a preprocessing technique. Results from cross-validation demonstrate significant improvements in accuracy, precision, recall, and F1 scores when employing K-Means clustering compared to models without preprocessing. The findings highlight the efficacy of K-Means clustering in enhancing the discriminative power of MLP classification models by organizing data into clusters based on similarity. These results have practical implications, underlining the importance of appropriate preprocessing techniques in improving classification performance. Future research could explore additional preprocessing methods and their impact on classification accuracy across diverse datasets, advancing the field of machine learning and its applications
{"title":"Enhancing Multi-Layer Perceptron Performance with K-Means Clustering","authors":"Doughlas Pardede, Aulia Ichsan, Sugeng Riyadi","doi":"10.47709/cnahpc.v6i1.3600","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i1.3600","url":null,"abstract":"Machine learning plays a crucial role in identifying patterns within data, with classification being a prominent application. This study investigates the use of Multilayer Perceptron (MLP) classification models and explores preprocessing techniques, particularly K-Means clustering, to enhance model performance. Overfitting, a common challenge in MLP models, is addressed through the application of K-Means clustering to streamline data preparation and improve classification accuracy. The study begins with an overview of overfitting in MLP models, highlighting the significance of mitigating this issue. Various techniques for addressing overfitting are reviewed, including regularization, dropout, early stopping, data augmentation, and ensemble methods. Additionally, the complementary role of K-Means clustering in enhancing model performance is emphasized. Preprocessing using K-Means clustering aims to reduce data complexity and prevent overfitting in MLP models. Three datasets - Iris, Wine, and Breast Cancer Wisconsin - are employed to evaluate the performance of K-Means as a preprocessing technique. Results from cross-validation demonstrate significant improvements in accuracy, precision, recall, and F1 scores when employing K-Means clustering compared to models without preprocessing. The findings highlight the efficacy of K-Means clustering in enhancing the discriminative power of MLP classification models by organizing data into clusters based on similarity. These results have practical implications, underlining the importance of appropriate preprocessing techniques in improving classification performance. Future research could explore additional preprocessing methods and their impact on classification accuracy across diverse datasets, advancing the field of machine learning and its applications","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"4 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959238","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 : 2024-02-12DOI: 10.47709/cnahpc.v6i1.3519
Muhammad Sabir Ramadhan, Harmayani Harmayani
The discovery of errors in the delivery of Multimedia Technology and Animation course material is indirectly caused by the implementation of lectures for the course, which should be given for 2 semesters compressed into 1 semester only. The limited learning time prevents some course material from being delivered to students. This limitation was also triggered by the absence of teaching modules that support condensed learning due to the implementation of lectures for 1 semester. Seeing these problems makes the development of a teaching module in the Multimedia and Animation Technology course with Project-Based Learning to support the implementation of lectures a solution that can be done to overcome existing problems. The feasibility test results show that the teaching module is valid. In contrast, the results of the feasibility test by media experts show that 95.14% of the module is very valid, and seen from the results of the feasibility test by material experts show that 97.14% of the module is very valid for use in learning for 1 semester. In the trial involving students, it shows that through the results of individual trials, it can be seen that 94.17% of the teaching modules developed are very feasible to use in the learning process. In addition, through the results of the small group trial, it can be seen that the teaching module is 85.18% very feasible to use, as well as the results of the usage trial show that the teaching module is 87.45% very feasible to use in learning. Based on the data obtained, it can be concluded that the Multimedia and Animation Technology module with Project-Based Learning is very feasible to be used as a reference and in the learning process of Multimedia and Animation Technology courses.
{"title":"Development of The Project-Based Learning Model In Making Teaching Modules for Courses Multimedia Technology and Animation","authors":"Muhammad Sabir Ramadhan, Harmayani Harmayani","doi":"10.47709/cnahpc.v6i1.3519","DOIUrl":"https://doi.org/10.47709/cnahpc.v6i1.3519","url":null,"abstract":"The discovery of errors in the delivery of Multimedia Technology and Animation course material is indirectly caused by the implementation of lectures for the course, which should be given for 2 semesters compressed into 1 semester only. The limited learning time prevents some course material from being delivered to students. This limitation was also triggered by the absence of teaching modules that support condensed learning due to the implementation of lectures for 1 semester. Seeing these problems makes the development of a teaching module in the Multimedia and Animation Technology course with Project-Based Learning to support the implementation of lectures a solution that can be done to overcome existing problems. The feasibility test results show that the teaching module is valid. In contrast, the results of the feasibility test by media experts show that 95.14% of the module is very valid, and seen from the results of the feasibility test by material experts show that 97.14% of the module is very valid for use in learning for 1 semester. In the trial involving students, it shows that through the results of individual trials, it can be seen that 94.17% of the teaching modules developed are very feasible to use in the learning process. In addition, through the results of the small group trial, it can be seen that the teaching module is 85.18% very feasible to use, as well as the results of the usage trial show that the teaching module is 87.45% very feasible to use in learning. Based on the data obtained, it can be concluded that the Multimedia and Animation Technology module with Project-Based Learning is very feasible to be used as a reference and in the learning process of Multimedia and Animation Technology courses.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":"10 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139964836","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 : 2024-02-05DOI: 10.47709/cnahpc.v6i1.3508
Qurani Awaliyana, Ali Ikhwan
The aim of this research is to obtain a lending and payment application that can be applied to the Bandar Telu Plantation BUMDes. This research uses the RnD research method and the Waterfall development method. Data collection was carried out by means of observation, interviews and literature study. This results of this research show that BUMDes was established to help the community meet their needs by borrowing from the community. The websote-based application for borrowing and payment for the BUMDes Plantation Village in Bandar Telu produces an application that can be accessed by administrators or members. Where the management uses a website based system, and members use a mobile-based system that can be accessed via the internet and applications. With this application, it can make it easier for administrators and members to obtain information about ongoing loans and payments, so that there is no longer a need for general ledger recapitulation which is at risk of errors in calculating interest or accumulating the amount of members bills.
本研究的目的是获得可应用于 Bandar Telu 种植园 BUMDes 的借贷和支付应用程序。本研究采用 RnD 研究方法和瀑布式开发方法。数据收集通过观察、访谈和文献研究等方式进行。研究结果表明，BUMDes 的建立是为了通过向社区借力来帮助社区满足其需求。位于 Bandar Telu 的 BUMDes 种植园村基于网站的借贷和付款应用程序可由管理员或成员访问。其中，管理人员使用基于网站的系统，而成员则使用可通过互联网和应用程序访问的移动系统。有了这个应用程序，管理员和会员就可以更容易地获取正在进行的贷款和付款信息，从而不再需要进行总账重述，因为总账重述有可能在计算利息或累计会员账单金额时出现错误。
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Pub Date : 2024-01-31DOI: 10.47709/cnahpc.v6i1.3487
Gregorius Airlangga
This study investigates the performance of machine learning classifiers in the domain of speaker identification, a pivotal component of modern digital security systems. With the burgeoning integration of voice-activated interfaces in technology, the demand for accurate and reliable speaker identification is paramount. This research provides a comprehensive comparison of four widely used classifiers: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), and Decision Tree (DT). Utilizing the LibriSpeech dataset, known for its diversity of speakers and recording conditions, we extracted Mel-frequency cepstral coefficients (MFCCs) to serve as features for training and evaluating the classifiers. Each model's performance was assessed based on precision, recall, F1-score, and accuracy. The results revealed that RF outperformed all other classifiers, achieving near-perfect metrics, indicative of its robustness and generalizability for speaker identification tasks. KNN also demonstrated high performance, suggesting its suitability for applications where rapid execution and interpretability are critical. Conversely, SVM and DT, while yielding moderate and lower performances respectively, highlighted the necessity for further optimization. These findings underscore the effectiveness of ensemble and distance-based classifiers in handling complex patterns for speaker differentiation. The study not only guides the selection of appropriate classifiers for speaker identification but also sets the stage for future research, which could explore hybrid models and the impact of dataset variability on performance. The insights from this analysis contribute significantly to the field, providing a benchmark for developing advanced speaker identification systems
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