Pub Date : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8761
Tundo Tundo, Panji Wijonarko
XYZ University has a scholarship program intended for outstanding students. Determination of recipients of outstanding scholarships is still constrained by the unclear system for determining scholarship recipients. This can affect the fairness of receiving scholarships. Students who really deserve to get a scholarship do not receive the scholarship. The solution to overcome this problem, the researcher came up with an idea in the form of a Multi-Objective Optimization by Ratio Analysis (MOORA) Decision Support System method, with the aim of being able to solve the problem of selecting an objective scholarship acceptance process. The MOORA method was chosen because it can solve the problem with a fairly effective method. After conducting research, it was found that 5 (five) candidates were eligible to receive scholarships for outstanding students, namely Alt7, Alt10, Alt37, Alt49, and Alt35. Furthermore, from the results of this study, it was concluded that students who get achievement scholarships are students with the highest scores from the results of the MOORA method, there is no element of subjectivity.
{"title":"Penyeleksian Beasiswa Berprestasi pada Universitas XYZ Menggunakan Metode MOORA","authors":"Tundo Tundo, Panji Wijonarko","doi":"10.36499/jinrpl.v5i2.8761","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8761","url":null,"abstract":"XYZ University has a scholarship program intended for outstanding students. Determination of recipients of outstanding scholarships is still constrained by the unclear system for determining scholarship recipients. This can affect the fairness of receiving scholarships. Students who really deserve to get a scholarship do not receive the scholarship. The solution to overcome this problem, the researcher came up with an idea in the form of a Multi-Objective Optimization by Ratio Analysis (MOORA) Decision Support System method, with the aim of being able to solve the problem of selecting an objective scholarship acceptance process. The MOORA method was chosen because it can solve the problem with a fairly effective method. After conducting research, it was found that 5 (five) candidates were eligible to receive scholarships for outstanding students, namely Alt7, Alt10, Alt37, Alt49, and Alt35. Furthermore, from the results of this study, it was concluded that students who get achievement scholarships are students with the highest scores from the results of the MOORA method, there is no element of subjectivity.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321653","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8818
Hilya Anbiyani Fitri Muhyidin, Liptia Venica
Cyber-crime is becoming more massive as online activities increase. Cybercrime is a criminal act that exploits digital technology to damage, harm, and destroy property. Therefore, it is crucial for internet users to have knowledge of cybersecurity and the world of technology and the internet in order to avoid falling victim to cybercrime. The aim of this study is to develop a chatbot system as a centralized information medium on cybersecurity, technology, and the internet for internet users. The development of this chatbot aims to reduce the risks of cybercrimes and help enhance internet users' awareness of cybercrime. This research employs the AI Project Cycle method in chatbot development and utilizes the Long Short-Term Memory (LSTM) deep learning model algorithm to develop a model that achieves high accuracy. The training results of the LSTM model achieved an accuracy score of 100% and a loss of 3.09% with 400 epochs. Consequently, it can be concluded that the LSTM algorithm is highly effective for training and developing a chatbot model.
{"title":"Pengembangan Chatbot untuk Meningkatkan Pengetahuan dan Kesadaran Keamanan Siber Menggunakan Long Short-Term Memory","authors":"Hilya Anbiyani Fitri Muhyidin, Liptia Venica","doi":"10.36499/jinrpl.v5i2.8818","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8818","url":null,"abstract":"Cyber-crime is becoming more massive as online activities increase. Cybercrime is a criminal act that exploits digital technology to damage, harm, and destroy property. Therefore, it is crucial for internet users to have knowledge of cybersecurity and the world of technology and the internet in order to avoid falling victim to cybercrime. The aim of this study is to develop a chatbot system as a centralized information medium on cybersecurity, technology, and the internet for internet users. The development of this chatbot aims to reduce the risks of cybercrimes and help enhance internet users' awareness of cybercrime. This research employs the AI Project Cycle method in chatbot development and utilizes the Long Short-Term Memory (LSTM) deep learning model algorithm to develop a model that achieves high accuracy. The training results of the LSTM model achieved an accuracy score of 100% and a loss of 3.09% with 400 epochs. Consequently, it can be concluded that the LSTM algorithm is highly effective for training and developing a chatbot model.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321675","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8913
Putu Ary Indra Pratama, Nengah Widya Utami, Putu Trisna Hady Permana S
This study aims to evaluate usability on the user's M-Pise LPD Digital application page in Jembrana Regency by using the usability testing method with Performance Measurement and RTA (Retrospective Think Aloud) techniques. The usability aspects reviewed are effectiveness, efficiency, and user satisfaction. In this study there were 20 respondents who were involved consisting of a group of advanced respondents and a group of novice respondents. The results showed that (1) the M-Pise LPD Digital application was still not effective when viewed from errors (errors) when the respondent was doing the task, (2) the M-Pise LPD Digital application in terms of efficiency has proven to be efficient seen from statistical testing Mann Whiteney showed that there was no difference in time between the beginner and advanced groups of respondents so that it could be said to be efficient, (3) User satisfaction was still unsatisfied as seen from the SUS questionnaire score of 64. Thus the M-Pise application page did not have good usability. Thus the recommendations for improvement given are based on the results of performance measurements, namely errors. Recommendations for improvement will focus on improving menu components and features. Meanwhile, based on the results of the problems and suggestions for the results of the RTA, namely simplification of features and improvements as well as clarity of the layout of letters, numbers and icons.
{"title":"Evaluasi Usability Pada Aplikasi M-Pise LPD Digital Di Kabupaten Jembrana dengan Metode Usability Testing","authors":"Putu Ary Indra Pratama, Nengah Widya Utami, Putu Trisna Hady Permana S","doi":"10.36499/jinrpl.v5i2.8913","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8913","url":null,"abstract":"This study aims to evaluate usability on the user's M-Pise LPD Digital application page in Jembrana Regency by using the usability testing method with Performance Measurement and RTA (Retrospective Think Aloud) techniques. The usability aspects reviewed are effectiveness, efficiency, and user satisfaction. In this study there were 20 respondents who were involved consisting of a group of advanced respondents and a group of novice respondents. The results showed that (1) the M-Pise LPD Digital application was still not effective when viewed from errors (errors) when the respondent was doing the task, (2) the M-Pise LPD Digital application in terms of efficiency has proven to be efficient seen from statistical testing Mann Whiteney showed that there was no difference in time between the beginner and advanced groups of respondents so that it could be said to be efficient, (3) User satisfaction was still unsatisfied as seen from the SUS questionnaire score of 64. Thus the M-Pise application page did not have good usability. Thus the recommendations for improvement given are based on the results of performance measurements, namely errors. Recommendations for improvement will focus on improving menu components and features. Meanwhile, based on the results of the problems and suggestions for the results of the RTA, namely simplification of features and improvements as well as clarity of the layout of letters, numbers and icons.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"241 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321712","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8562
Luh Ketut Kartika Candra Dewi, I. G. A. P. Dwi Putri, Linda Yupita
The rapid development of Information Technology (IT) is currently creating new habits and facilitating life activities from all aspects which is a challenge for various parties, including non-bank financial companies, to be prepared to face business competition through the application of information technology. One of the companies investing in information technology is the Nirmala Cooperative by presenting Nirmala Hadir e-commerce to support its business units and prioritize convenience for its members. When developing digital technology, companies need a large capital investment with an uncertain percentage of return and the measurement is quite difficult to do so an analysis of the benefits of technology investment is needed to ensure that the benefits obtained are higher than the negative impacts that arise. The method applied in this research is a qualitative descriptive approach which in its analysis uses the Ranti's Generic IS/IT Business Value and Cost Benefit Analysis (CBA) methods. The results of research with Ranti's Generic IS/IT obtained 7 categories and 9 sub-categories of benefits and CBA calculations obtained an ROI value of 7.93%, NPV of IDR 11,731,529, Payback Period of 0.929 (339 days) and BCR of 9.87 which indicates that the technology investment made by the Nirmala Cooperative has a good profitability value with a payback period of less than one year.
{"title":"Analisis Manfaat Investasi Teknologi Informasi Nirmala Hadir pada Koperasi Nirmala","authors":"Luh Ketut Kartika Candra Dewi, I. G. A. P. Dwi Putri, Linda Yupita","doi":"10.36499/jinrpl.v5i2.8562","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8562","url":null,"abstract":"The rapid development of Information Technology (IT) is currently creating new habits and facilitating life activities from all aspects which is a challenge for various parties, including non-bank financial companies, to be prepared to face business competition through the application of information technology. One of the companies investing in information technology is the Nirmala Cooperative by presenting Nirmala Hadir e-commerce to support its business units and prioritize convenience for its members. When developing digital technology, companies need a large capital investment with an uncertain percentage of return and the measurement is quite difficult to do so an analysis of the benefits of technology investment is needed to ensure that the benefits obtained are higher than the negative impacts that arise. The method applied in this research is a qualitative descriptive approach which in its analysis uses the Ranti's Generic IS/IT Business Value and Cost Benefit Analysis (CBA) methods. The results of research with Ranti's Generic IS/IT obtained 7 categories and 9 sub-categories of benefits and CBA calculations obtained an ROI value of 7.93%, NPV of IDR 11,731,529, Payback Period of 0.929 (339 days) and BCR of 9.87 which indicates that the technology investment made by the Nirmala Cooperative has a good profitability value with a payback period of less than one year.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321716","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}
Curriculum changes are needed to adapt education to the times. Since the covid-19 pandemic, face-to-face learning has been suspended. Online learning is an alternative used during a pandemic. This has an impact on learning loss so that the quality of learning decreases. Recovery of learning during the pandemic and post-pandemic Covid-19 is important to reduce the impact of learning loss on students. After the pandemic, the independent curriculum was launched which was a refinement of the 2013 curriculum which had only been implemented in several schools. The subject structure of the Merdeka curriculum for SMA level in Fese E or grade 10, all students get the same subjects. While in Phase F (grades 11 and 12), the subject structure is divided into 2 main groups, namely general subjects and elective subjects. Based on the provisions of the SMKA 2021-2022 curriculum structure, SMA Negeri 1 Kebumen prepares elective subjects (MPP) which are made up of 7 MPP packages. This study uses a clustering technique of student scores using the K-Means algorithm to obtain MPP package recommendations that suit student abilities. For each MPP package, clustering is carried out into 2 clusters with features in the form of predetermined subject scores. The result of this clustering is that each student gets a "yes" or "no" recommendation for each MPP package.
{"title":"Rekomendasi Paket Mata Pelajaran Pilihan (MPP) pada SMA Negeri 1 Kebumen Menggunakan Algoritma K-means","authors":"Gustina Alfa Trisnapradika, Wildanil Ghozi, Yuminah Yuminah","doi":"10.36499/jinrpl.v5i2.8514","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8514","url":null,"abstract":"Curriculum changes are needed to adapt education to the times. Since the covid-19 pandemic, face-to-face learning has been suspended. Online learning is an alternative used during a pandemic. This has an impact on learning loss so that the quality of learning decreases. Recovery of learning during the pandemic and post-pandemic Covid-19 is important to reduce the impact of learning loss on students. After the pandemic, the independent curriculum was launched which was a refinement of the 2013 curriculum which had only been implemented in several schools. The subject structure of the Merdeka curriculum for SMA level in Fese E or grade 10, all students get the same subjects. While in Phase F (grades 11 and 12), the subject structure is divided into 2 main groups, namely general subjects and elective subjects. Based on the provisions of the SMKA 2021-2022 curriculum structure, SMA Negeri 1 Kebumen prepares elective subjects (MPP) which are made up of 7 MPP packages. This study uses a clustering technique of student scores using the K-Means algorithm to obtain MPP package recommendations that suit student abilities. For each MPP package, clustering is carried out into 2 clusters with features in the form of predetermined subject scores. The result of this clustering is that each student gets a \"yes\" or \"no\" recommendation for each MPP package.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"125 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321620","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8750
Fernando Bayu Andika, A. Purnomo
Information and communication technology continues to develop and progress which demonstrated by the presence of gadget technology. Gadgets are smart electronic devices that assist in making it simple for users to accomplish various task. The use of gadget technology in children are unable to be separated. According to the 2020 KPAI survey, approximately 71,3% of school-age children own and have played with gadgets for a longer time. As a result, it is expected that early detection of gadget addiction can be carried out to ensure that mental and emotional disorders in children who use gadgets can be properly addressed. The aim of this research is to create a prototype expert system for early detection of gadget addiction levels in children using the fuzzy tsukamoto. The fuzzy tsukamoto method was used in this study. This study included 74 respondents aged 9 to 12 years old. The DAS (Digital Addiction Scale : For Children) was used as the data collection method in this study. The system’s as performance will be evaluated using 74 respondents data by comparing the result of expert calculations and fuzzy tsukamoto method calculations. Fuzzy Tsukamoto reasoning with 64 rule bases in used to build this expert system. According to evaluation with 74 respondent data, this expert system has a system acurracy rate of 87,83%, which indicates that it proceeds succesfully.
{"title":"Sistem Pakar Deteksi Dini Tingkat Kecanduan Gadget pada Anak Menggunakan Fuzzy Tsukamoto","authors":"Fernando Bayu Andika, A. Purnomo","doi":"10.36499/jinrpl.v5i2.8750","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8750","url":null,"abstract":"Information and communication technology continues to develop and progress which demonstrated by the presence of gadget technology. Gadgets are smart electronic devices that assist in making it simple for users to accomplish various task. The use of gadget technology in children are unable to be separated. According to the 2020 KPAI survey, approximately 71,3% of school-age children own and have played with gadgets for a longer time. As a result, it is expected that early detection of gadget addiction can be carried out to ensure that mental and emotional disorders in children who use gadgets can be properly addressed. The aim of this research is to create a prototype expert system for early detection of gadget addiction levels in children using the fuzzy tsukamoto. The fuzzy tsukamoto method was used in this study. This study included 74 respondents aged 9 to 12 years old. The DAS (Digital Addiction Scale : For Children) was used as the data collection method in this study. The system’s as performance will be evaluated using 74 respondents data by comparing the result of expert calculations and fuzzy tsukamoto method calculations. Fuzzy Tsukamoto reasoning with 64 rule bases in used to build this expert system. According to evaluation with 74 respondent data, this expert system has a system acurracy rate of 87,83%, which indicates that it proceeds succesfully.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321451","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8047
Ihsanulfu’ad Suwandi
Measurement of temperature and humidity generally uses a tool that can determine the value of two physical quantities of a material or system (thermometer or hygrometer). When it comes to hatchery incubators, success and protection are priorities. The microcontroller is a small computer in the form of a chip, DHT22 temperature and humidity sensor with a range of (-40)-80°C. Formulation of the problem, (1) How to get digital data of hatching incubator room temperature using a microcontroller? (2) How is the application of the system to hatching incubators?. Methods of research, analysis, implementation, and simulation (a) Analysis, the lowest ideal temperature for hatching eggs shows a figure of approximately 38°C and the highest is 38.5–39°C. (b) Implementation, starting with the use of DHT22 giving a temperature signal according to whether or not when the condition of the incandescent lamp as a heater will turn on or off, the display will be displayed on the LCD. (c) Simulation, the first stage is the DHT22 schematic to Arduino, the second stage is the relay schematic to Arduino, the third is I2C LCD to Arduino, the fourth is relay to lights and indicators. Based on the analysis, implementation and simulation, conclusions are drawn (1) Digital data related to temperature from the DHT22 sensor displayed on the LCD can be applied to help monitor the hatching process of chicken eggs using an incubator. (2) Arduino board-based microcontrollers can be applied as controllers related to system flow in chicken egg hatching incubators.
{"title":"Sistem Informasi Suhu dan Kelembaban Inkubator Telur Ayam Menggunakan Sensor Dht22 Berbasis Mikrokontroler","authors":"Ihsanulfu’ad Suwandi","doi":"10.36499/jinrpl.v5i2.8047","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8047","url":null,"abstract":"Measurement of temperature and humidity generally uses a tool that can determine the value of two physical quantities of a material or system (thermometer or hygrometer). When it comes to hatchery incubators, success and protection are priorities. The microcontroller is a small computer in the form of a chip, DHT22 temperature and humidity sensor with a range of (-40)-80°C. Formulation of the problem, (1) How to get digital data of hatching incubator room temperature using a microcontroller? (2) How is the application of the system to hatching incubators?. Methods of research, analysis, implementation, and simulation (a) Analysis, the lowest ideal temperature for hatching eggs shows a figure of approximately 38°C and the highest is 38.5–39°C. (b) Implementation, starting with the use of DHT22 giving a temperature signal according to whether or not when the condition of the incandescent lamp as a heater will turn on or off, the display will be displayed on the LCD. (c) Simulation, the first stage is the DHT22 schematic to Arduino, the second stage is the relay schematic to Arduino, the third is I2C LCD to Arduino, the fourth is relay to lights and indicators. Based on the analysis, implementation and simulation, conclusions are drawn (1) Digital data related to temperature from the DHT22 sensor displayed on the LCD can be applied to help monitor the hatching process of chicken eggs using an incubator. (2) Arduino board-based microcontrollers can be applied as controllers related to system flow in chicken egg hatching incubators.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"103 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321487","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}
Based on the results of previous studies, research on machine learning for predicting ICU patients is crucial as it can aid doctors in identifying high-risk individuals. A high accuracy in machine learning models is necessary for assisting doctors in making informed decisions. In this study, machine learning models were developed using two models, namely Random Forest and Artificial Neural Network (ANN), to predict patient mortality in the ICU. Patient data was obtained from The Global Open Source Severity of Illness Score (GOSSIS) and underwent preprocessing to address issues of missing values and imbalanced data. The data was then divided into training, validation, and testing sets for model training and evaluation. The results of the study indicate that the Random Forest model performs better with an accuracy of 93% on the testing data compared to the ANN which only achieved an accuracy of 86% on the testing data. Consequently, the Random Forest model can be utilized as a solution for predicting patient mortality in the ICU.
根据以往的研究结果，对机器学习预测重症监护病房病人的研究至关重要，因为它可以帮助医生识别高危人群。机器学习模型的高准确性对于协助医生做出明智的决定非常必要。本研究使用随机森林和人工神经网络（ANN）两种模型开发了机器学习模型，用于预测重症监护室患者的死亡率。患者数据来自全球开放源疾病严重程度评分（GOSSIS），并经过预处理以解决缺失值和不平衡数据问题。然后将数据分为训练集、验证集和测试集，用于模型训练和评估。研究结果表明，随机森林模型在测试数据上的准确率为 93%，而 ANN 在测试数据上的准确率仅为 86%，两者相比，随机森林模型的表现更好。因此，随机森林模型可用作预测重症监护室病人死亡率的解决方案。
{"title":"Classification Model Analysis of ICU Mortality Level using Random Forest and Neural Network","authors":"Lymin Lymin, Alvin Alvin, Bodhi Lhoardi, Darwis Darwis, Joseph Siahaan, Abdi Dharma","doi":"10.36499/jinrpl.v5i2.8749","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8749","url":null,"abstract":"Based on the results of previous studies, research on machine learning for predicting ICU patients is crucial as it can aid doctors in identifying high-risk individuals. A high accuracy in machine learning models is necessary for assisting doctors in making informed decisions. In this study, machine learning models were developed using two models, namely Random Forest and Artificial Neural Network (ANN), to predict patient mortality in the ICU. Patient data was obtained from The Global Open Source Severity of Illness Score (GOSSIS) and underwent preprocessing to address issues of missing values and imbalanced data. The data was then divided into training, validation, and testing sets for model training and evaluation. The results of the study indicate that the Random Forest model performs better with an accuracy of 93% on the testing data compared to the ANN which only achieved an accuracy of 86% on the testing data. Consequently, the Random Forest model can be utilized as a solution for predicting patient mortality in the ICU.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"50 6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321408","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 : 2023-10-09DOI: 10.36499/jinrpl.v5i2.8632
S. Winardi, Mohammad Diqi, Arum Kurnia Sulistyowati, Jelina Imlabla
This study explores the application of the Transformer model in sentiment analysis of tweets generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled as "Good", "Bad", and "Neutral". The Transformer model demonstrated high accuracy (90%) in classifying sentiments, particularly predicting "Bad" tweets. However, it showed slightly lower performance for the "Good" and "Neutral" categories, indicating areas for future research and model refinement. Our findings contribute to the growing body of evidence supporting deep learning methods in sentiment analysis and underscore the potential of AI models like Transformers in handling complex natural language processing tasks. This study broadens the scope for AI applications in social media sentiment analysis.
{"title":"Sentiment Analysis of ChatGPT Tweets Using Transformer Algorithms","authors":"S. Winardi, Mohammad Diqi, Arum Kurnia Sulistyowati, Jelina Imlabla","doi":"10.36499/jinrpl.v5i2.8632","DOIUrl":"https://doi.org/10.36499/jinrpl.v5i2.8632","url":null,"abstract":"This study explores the application of the Transformer model in sentiment analysis of tweets generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled as \"Good\", \"Bad\", and \"Neutral\". The Transformer model demonstrated high accuracy (90%) in classifying sentiments, particularly predicting \"Bad\" tweets. However, it showed slightly lower performance for the \"Good\" and \"Neutral\" categories, indicating areas for future research and model refinement. Our findings contribute to the growing body of evidence supporting deep learning methods in sentiment analysis and underscore the potential of AI models like Transformers in handling complex natural language processing tasks. This study broadens the scope for AI applications in social media sentiment analysis.","PeriodicalId":33961,"journal":{"name":"Jurnal Informatika dan Rekayasa Perangkat Lunak","volume":"214 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139321423","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 : 2023-10-01DOI: 10.36499/jinrpl.v5i2.7988
Muhammad Afnan Wicaksana, Akhmad Pandhu Wijaya
Sistem informasi merupakan salah satu faktor yang penting bagi perusahaan dalam kegiatan operasional perusahaan yang digunakan untuk mengumpulkan, mengolah, dan menyediakan informasi. Untuk itu perusahaan sudah mulai menggunakan sistem informasi dalam melakukan pekerjaan. Gudang Sakti merupakan tempat usaha yang masih menggunakan cara manual untuk pengolahan dan penyimpanan data produk, barang masuk, barang keluar beserta masing-masing laporan yang ada. Hasil dari penelitian ini berupa sistem informasi penyimpanan barang berbasis web untuk Gudang Sakti. Metode pembangunan perangkat lunak yang digunakan adalah model air terjun atau yang biasa disebut dengan Waterfall. Sistem penyimpanan barang berbasis web dapat mengelola data barang, data pembelian, data penjualan, data supplier, profil admin, profil perusahaan, dan data transaksi pembayaran. menghasilkan laporan data pembelian, data penjualan, data keuntungan, dan data transaksi sehingga mempermudah bagi admin gudang.
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