Pub Date : 2023-09-01DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4125
Samuel Valentino Hutagalung, Yennimar Yennimar, Erikson Roni Rumapea, Michael Justin Gesitera Hia, Terkelin Sembiring, Dhanny Rukmana Manday
This research was conducted to test how the Support Vector Regression and Random Forest Regression algorithms predict gold futures prices. The data used in this research was taken from the Investing.com website which will later be processed into a prediction model by comparing the SVR and RVR algorithms. The Support Vector Regression and Random Forest Regression algorithms will be tested to see the performance of each prediction model. The test results show that the Support Vector Regression model is superior in terms of accuracy with a value of 83%. However, the Random Forest Regression algorithm is superior with a smaller error rate, namely with an MSE value of 270.85 and an MAE value of 12.53. Keyword: Comparison, Prediction, Support Vector Regression, Random Forest Regression.
{"title":"COMPARISON OF SUPPORT VECTOR REGRESSION AND RANDOM FOREST REGRESSION ALGORITHMS ON GOLD PRICE PREDICTIONS","authors":"Samuel Valentino Hutagalung, Yennimar Yennimar, Erikson Roni Rumapea, Michael Justin Gesitera Hia, Terkelin Sembiring, Dhanny Rukmana Manday","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4125","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4125","url":null,"abstract":"This research was conducted to test how the Support Vector Regression and Random Forest Regression algorithms predict gold futures prices. The data used in this research was taken from the Investing.com website which will later be processed into a prediction model by comparing the SVR and RVR algorithms. The Support Vector Regression and Random Forest Regression algorithms will be tested to see the performance of each prediction model. The test results show that the Support Vector Regression model is superior in terms of accuracy with a value of 83%. However, the Random Forest Regression algorithm is superior with a smaller error rate, namely with an MSE value of 270.85 and an MAE value of 12.53. Keyword: Comparison, Prediction, Support Vector Regression, Random Forest Regression.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134961978","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}
Success in learning and learning activities at SMA Asy-Syafiiyah Medan, is not only influenced by teachers, but also by student aspects such as attendance, parental income, activity participation, achievement scores, and discipline. To obtain optimal results, the authors designed an application using the Weighted Aggregated Sum Product Assessment (WASPAS) method that can determine students who receive BOS funds. After calculating 5 times with predetermined criteria, Rizki Ridho Silalahi's final result was 0.9197. The system designed for receiving BOS Fund assistance at SMA Asy-Syafiiyah Medan has been tested by inputting criteria data and carrying out the calculation process using the WASPAS method.
{"title":"DECISION SUPPORT SYSTEM IMPLEMENTATION IN DETERMINING STUDENTS TO RECEIVE BOS FUNDING USING THE WASPAS METHOD","authors":"Napisah Napisah, Rizki Muliono, Nurul Khairina, Muhathir -","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4046","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4046","url":null,"abstract":"Success in learning and learning activities at SMA Asy-Syafiiyah Medan, is not only influenced by teachers, but also by student aspects such as attendance, parental income, activity participation, achievement scores, and discipline. To obtain optimal results, the authors designed an application using the Weighted Aggregated Sum Product Assessment (WASPAS) method that can determine students who receive BOS funds. After calculating 5 times with predetermined criteria, Rizki Ridho Silalahi's final result was 0.9197. The system designed for receiving BOS Fund assistance at SMA Asy-Syafiiyah Medan has been tested by inputting criteria data and carrying out the calculation process using the WASPAS method.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135992395","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 : 2023-08-30DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3869
Paul Erikson, Bobby Rahman Angkat, Eliza Christovel Yosua, Mutiara Sembiring, Marlince Nababan
Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large. Key Word: Performance Appraisal, Data Mining, K-Means
{"title":"APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE","authors":"Paul Erikson, Bobby Rahman Angkat, Eliza Christovel Yosua, Mutiara Sembiring, Marlince Nababan","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3869","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3869","url":null,"abstract":"Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large. Key Word: Performance Appraisal, Data Mining, K-Means","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136241201","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 : 2023-08-26DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4029
Insidini Fawwaz, Erwin Conery Firtan, Steven -, Helbert Yawin
The main problem Indonesia faces, especially in education in the era of globalization, is the low quality of human resources. One of the efforts to improve the quality of human resources is to increase interest in reading and the habit of reading. From this fact, the library is expected to be the center of activities to develop interest in reading and reading habits. Libraries have a great responsibility to increase and generate interest in reading. Library data management is one of the essential activities in running a library. Librarians must be able to process and manage book data efficiently and effectively to avoid losing library property. This study uses PHP to create a website design to assist librarians in processing and storing data about existing books. This study designs a library data processing system that contains library book loans, such as recording books, transactions, and student data collection in the library. The results of this website design can facilitate library staff in organizing and tracking library management quickly and efficiently. Keywords: Digital Library, Library Website, Electronic Journal
{"title":"WEBSITE-BASED LIBRARY DATA PROCESSING DESIGN","authors":"Insidini Fawwaz, Erwin Conery Firtan, Steven -, Helbert Yawin","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4029","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4029","url":null,"abstract":"The main problem Indonesia faces, especially in education in the era of globalization, is the low quality of human resources. One of the efforts to improve the quality of human resources is to increase interest in reading and the habit of reading. From this fact, the library is expected to be the center of activities to develop interest in reading and reading habits. Libraries have a great responsibility to increase and generate interest in reading. Library data management is one of the essential activities in running a library. Librarians must be able to process and manage book data efficiently and effectively to avoid losing library property. This study uses PHP to create a website design to assist librarians in processing and storing data about existing books. This study designs a library data processing system that contains library book loans, such as recording books, transactions, and student data collection in the library. The results of this website design can facilitate library staff in organizing and tracking library management quickly and efficiently. Keywords: Digital Library, Library Website, Electronic Journal","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135236624","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 : 2023-08-25DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3968
Sri Wahyuni Tarigan
This study aims to determine differences in chemistry learning outcomes taught using computer-based media compared to conventional teaching on the Subject of Electrolyte and Non-Electrolyte Solutions. The research was conducted at Prima Indonesia University for the 2021/2022 Academic Year. The population of this study were all first- semester students consisting of two classes. A sample of 60 students, consisting of an experimental style and a control class, was given a different treatment, namely multimedia computer-based teaching with conventional media on the same subject. Based on data collection, the results obtained are that the experimental class has higher learning outcomes than the control class. Keywords: Computers, Electrolyte Solutions, Non-Electrolytes
{"title":"USE OF COMPUTER-BASED EDUCATIONAL MEDIA TO IMPROVE THE LEARNING ABILITY OF INDUSTRIAL ENGINEERING STUDENTS IN CHEMISTRY","authors":"Sri Wahyuni Tarigan","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3968","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3968","url":null,"abstract":"This study aims to determine differences in chemistry learning outcomes taught using computer-based media compared to conventional teaching on the Subject of Electrolyte and Non-Electrolyte Solutions. The research was conducted at Prima Indonesia University for the 2021/2022 Academic Year. The population of this study were all first- semester students consisting of two classes. A sample of 60 students, consisting of an experimental style and a control class, was given a different treatment, namely multimedia computer-based teaching with conventional media on the same subject. Based on data collection, the results obtained are that the experimental class has higher learning outcomes than the control class. Keywords: Computers, Electrolyte Solutions, Non-Electrolytes","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134930764","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 : 2023-08-24DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4047
Mohammad Didit Sriardi, Tukino -, Fitria Nurapriani
Major changes in the job search have occurred with the development of the digital age. Therefore, user experience enhancement (UserExperience, UX) and user interface (UserInterface, UI) in job search applications is becoming an urgent need. This study aims to explore the application of the methoddesign thinkingin designing the UI/UX of a job search application namedCareer Hunt.Design thinking, a user-centric approach, enabling developers to understand deeply the needs, challenges and expectations of users, and create innovative and effective solutions. There are five stages used in this study: empathy, definition, ideation,prototype, and testing / test. In this study, interviews and contextual observations were conducted to gain a deeper understanding of user behavior and needs. Based on these findings, the main issues need to be solved, and then facilitate the sessionbrainstormingto generate a variety of potential solutions. Then, developprototypebased on those ideas and do user testing.feedbackreceived is used for literacy and further improvement. As a result, useDesign Thinkingin designUI/UXThis job search application has succeeded in increasing user satisfaction levels as well as job search efficiency. Keywords:Job Search,Career Hunt, Design Thinking, UI/UX
{"title":"IMPLEMENTATION OF DESIGN THINKING METHODS IN UI/UX DESIGNING JOB SEARCHING APPLICATIONS","authors":"Mohammad Didit Sriardi, Tukino -, Fitria Nurapriani","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4047","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4047","url":null,"abstract":"Major changes in the job search have occurred with the development of the digital age. Therefore, user experience enhancement (UserExperience, UX) and user interface (UserInterface, UI) in job search applications is becoming an urgent need. This study aims to explore the application of the methoddesign thinkingin designing the UI/UX of a job search application namedCareer Hunt.Design thinking, a user-centric approach, enabling developers to understand deeply the needs, challenges and expectations of users, and create innovative and effective solutions. There are five stages used in this study: empathy, definition, ideation,prototype, and testing / test. In this study, interviews and contextual observations were conducted to gain a deeper understanding of user behavior and needs. Based on these findings, the main issues need to be solved, and then facilitate the sessionbrainstormingto generate a variety of potential solutions. Then, developprototypebased on those ideas and do user testing.feedbackreceived is used for literacy and further improvement. As a result, useDesign Thinkingin designUI/UXThis job search application has succeeded in increasing user satisfaction levels as well as job search efficiency. Keywords:Job Search,Career Hunt, Design Thinking, UI/UX","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135471560","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 : 2023-08-24DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4056
Donni Nasution, Aldi Hermanto Sinaga, Indra Samudera, Iman Paskalis Hulu
The rapid growth of private universities and higher education institutions has led to increased competition among faculties to meet their set quotas, resulting in uneven student distribution. Universities and faculties must consistently strive to improve quality in various areas to achieve their set quotas. In measuring student satisfaction, a questionnaire was distributed to students. Out of the 369 questionnaires filled out, only 235 were deemed valid and analyzed. The analysis was conducted using two calculation methods, the first being the Customer Satisfaction Index (IPA), which resulted in a 75.42% satisfaction rate, and the Importance Performance Analysis (IPA), which identified 10 indicators in quadrant 1. It can be said that both methods resulted in a fairly satisfactory service quality.
{"title":"ANALYSIS OF CUSTOMER SATISFACTION INDEX METHOD ON THE PERCEPTION OF UNIVERSITAS PRIMA INDONESIA'S NEW BUILDING BY ITS STUDENTS","authors":"Donni Nasution, Aldi Hermanto Sinaga, Indra Samudera, Iman Paskalis Hulu","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4056","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4056","url":null,"abstract":"The rapid growth of private universities and higher education institutions has led to increased competition among faculties to meet their set quotas, resulting in uneven student distribution. Universities and faculties must consistently strive to improve quality in various areas to achieve their set quotas. In measuring student satisfaction, a questionnaire was distributed to students. Out of the 369 questionnaires filled out, only 235 were deemed valid and analyzed. The analysis was conducted using two calculation methods, the first being the Customer Satisfaction Index (IPA), which resulted in a 75.42% satisfaction rate, and the Importance Performance Analysis (IPA), which identified 10 indicators in quadrant 1. It can be said that both methods resulted in a fairly satisfactory service quality.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135471270","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}
Diabetes is a significant public health problem and affects millions of people worldwide. This study will perform a comparative analysis of three ensemble learning algorithms (Random Forest, AdaBoost, and XGBoost) in classifying diabetes diagnoses. Based on the research that has been carried out, it is concluded that the model with the highest accuracy is Random Forest with a value of 0.86, XGBoost with a value of 0.85, and AdaBoost with a value of 0.82. It can also be concluded that the three models perform well and can be used to classify diabetes. Based on the visualization of the results of Feature Importance that has been made, it can be concluded that the Random Forest and XGBoost algorithms have in common the 3 most important features, namely Glucose, BMI and Age. As for AdaBoost, the 3 most important features are DPF, BMI and Glucose.
{"title":"COMPARISON OF ENSEMBLE LEARNING ALGORITHM IN CLASSIFYING EARLY DIAGNOSTIC OF DIABETES","authors":"Okta Jaya Harmaja, Irvan Prasetia, Yosi Victor Hutagalung, Hendra Ardanis Sirait","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4054","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4054","url":null,"abstract":"Diabetes is a significant public health problem and affects millions of people worldwide. This study will perform a comparative analysis of three ensemble learning algorithms (Random Forest, AdaBoost, and XGBoost) in classifying diabetes diagnoses. Based on the research that has been carried out, it is concluded that the model with the highest accuracy is Random Forest with a value of 0.86, XGBoost with a value of 0.85, and AdaBoost with a value of 0.82. It can also be concluded that the three models perform well and can be used to classify diabetes. Based on the visualization of the results of Feature Importance that has been made, it can be concluded that the Random Forest and XGBoost algorithms have in common the 3 most important features, namely Glucose, BMI and Age. As for AdaBoost, the 3 most important features are DPF, BMI and Glucose.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135471268","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 : 2023-08-24DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4075
Dadan Suhamdani, Daniel Christian, Frans Aditya Bangun, Ahmad Rifai, Evta Indra
The Indonesian hospitality industry has grown rapidly over the past decades and is one of the most important sectors of the national economy. The focus is on determining the number of rooms sold using the Sugeno method's fuzzy logic. This study optimizes room sales by developing a fuzzy logic-based system that can effectively determine the number of rooms sold considering availability, best available rates, and revenue target. The Sugeno method is a type of fuzzy inference system that determines the relationship between input variables (room availability, best available rate, revenue target) and output variables (number of rooms sold). Modeled by using linguistic variables and fuzzy rules, the Sugeno method can provide a quantitative output based on specified input conditions. To evaluate the accuracy of the proposed fuzzy logic model, the mean absolute percentage error (MAPE) is used as a performance measure. Target data 175,000,000 to 245,000,000, BAR standard room 225,000 to 335,000, BAR superior room 285,000 to 425,000, available standard room 68 rooms/day, superior room 10 rooms/day, model accuracy measurement result is 1,80% very accurate interpreted. As such, the proposed system is useful for decision-making related to optimizing room sales in the hospitality industry.
{"title":"FUZZY LOGIC FOR OPTIMIZING ROOM SALES: SUGENO METHOD AND MAPE EVALUATION","authors":"Dadan Suhamdani, Daniel Christian, Frans Aditya Bangun, Ahmad Rifai, Evta Indra","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4075","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4075","url":null,"abstract":"The Indonesian hospitality industry has grown rapidly over the past decades and is one of the most important sectors of the national economy. The focus is on determining the number of rooms sold using the Sugeno method's fuzzy logic. This study optimizes room sales by developing a fuzzy logic-based system that can effectively determine the number of rooms sold considering availability, best available rates, and revenue target. The Sugeno method is a type of fuzzy inference system that determines the relationship between input variables (room availability, best available rate, revenue target) and output variables (number of rooms sold). Modeled by using linguistic variables and fuzzy rules, the Sugeno method can provide a quantitative output based on specified input conditions. To evaluate the accuracy of the proposed fuzzy logic model, the mean absolute percentage error (MAPE) is used as a performance measure. Target data 175,000,000 to 245,000,000, BAR standard room 225,000 to 335,000, BAR superior room 285,000 to 425,000, available standard room 68 rooms/day, superior room 10 rooms/day, model accuracy measurement result is 1,80% very accurate interpreted. As such, the proposed system is useful for decision-making related to optimizing room sales in the hospitality industry.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135471554","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 : 2023-08-23DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4078
Ongki Sopie Simbolon, Murni Esterlita Manullang, Stevin Alvarez, Lolo Frans M. Brutu, Evta Indra
In line with the needs of the community and the progress of the times in the advanced field of fintech, cash payments are currently considered insecure as well as ineffective and efficient. To run a non-cash or cashless transaction program currently run by the government, PT. Pertamina invites the public to use E-Payment from the My Pertamina application in collaboration with LinkAja. In this study, the sentiments of MyPertamina application users will be analyzed based on reviews on the Google Play Store. Review data will be analyzed to determine whether the review has positive, negative, or neutral sentiments. The data analysis stage is text preprocessing to change uppercase to lowercase, clearing text, separating text, taking important words, changing essential words, and labeling data into positive, negative, and neutral classes. As well as the classification and evaluation of results. This study used the Support Vector Machine (SVM) and Naïve Bayes classification methods. To evaluate the results, the confusion matrix was used to test the accuracy, precision, recall, and F1 score value. The classification results obtained the highest accuracy value for the Support Vector Machine (SVM) method, which had accuracy (68.50%), precision (70.00%), recall (69.70%), and F1 score (68.46%). Meanwhile, the Naïve Bayes method has performance with accuracy (63.00%), precision (63.90%), recall (61.34%), and F1 score (59.55%).
{"title":"SENTIMENT ANALYSIS OF MYPERTAMINA APPLICATION USING SUPPORT VECTOR MACHINE AND NAÏVE BAYES ALGORITHMS","authors":"Ongki Sopie Simbolon, Murni Esterlita Manullang, Stevin Alvarez, Lolo Frans M. Brutu, Evta Indra","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4078","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4078","url":null,"abstract":"In line with the needs of the community and the progress of the times in the advanced field of fintech, cash payments are currently considered insecure as well as ineffective and efficient. To run a non-cash or cashless transaction program currently run by the government, PT. Pertamina invites the public to use E-Payment from the My Pertamina application in collaboration with LinkAja. In this study, the sentiments of MyPertamina application users will be analyzed based on reviews on the Google Play Store. Review data will be analyzed to determine whether the review has positive, negative, or neutral sentiments. The data analysis stage is text preprocessing to change uppercase to lowercase, clearing text, separating text, taking important words, changing essential words, and labeling data into positive, negative, and neutral classes. As well as the classification and evaluation of results. This study used the Support Vector Machine (SVM) and Naïve Bayes classification methods. To evaluate the results, the confusion matrix was used to test the accuracy, precision, recall, and F1 score value. The classification results obtained the highest accuracy value for the Support Vector Machine (SVM) method, which had accuracy (68.50%), precision (70.00%), recall (69.70%), and F1 score (68.46%). Meanwhile, the Naïve Bayes method has performance with accuracy (63.00%), precision (63.90%), recall (61.34%), and F1 score (59.55%).","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135619803","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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