Jusikom : Jurnal Sistem Informasi Ilmu Komputer最新文献

{"title":"COMPARATIVE ANALYSIS OF STROKE CLASSIFICATION USING THE K-NEAREST NEIGHBOR DECISION TREE, AND MULTILAYER PERCEPTRON METHODS","authors":"Ertina Sabarita Barus, Jenny Evans Halim, Sally Yessica","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4083","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4083","url":null,"abstract":"Stroke has become a serious health problem; the main cause of stroke is usually a blood clot in the arteries that supply blood to the brain. Strokes can also be caused by bleeding when blood vessels burst and blood leaks into the brain. In one year, about 12.2 million people will have their first stroke, and 6.5 million people will die from a stroke. More than 110 million people worldwide have had a stroke. Handling that is done quickly can minimize the level of brain damage and the potential adverse effects. Therefore, it is very important to predict whether a patient has the potential to experience a stroke. The K-Nearest Neighbor, Decision Tree, and Multilayer Perceptron algorithms are applied as a classification method to identify symptoms in patients and achieve an optimal accuracy level. The results of making the three algorithms are quite good, where K-Nearest Neighbor (K-NN) has an accuracy value of 93.84%, Decision Tree is 93.97%, and Multilayer Perceptron (MLP) is 93.91%. The best accuracy value is the Decision Tree algorithm with an accuracy difference of no more than 0.10% with the two algorithms used.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"1 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":"135619799","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}

{"title":"IMPLEMENTATION OF DATA MINING TO PREDICT THE VALUE OF INDONESIAN OIL AND NON-OIL AND GAS IMPORT EXPORTS USING THE LINEAR REGRESSION METHOD","authors":"Elvis Sastra Ompusunggu, Wilson Sinaga, Mikael Siahaan, Jaspin Winata","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4081","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4081","url":null,"abstract":"Indonesia's export-import activities in recent years, the value of Indonesia's exports and imports has decreased due to global conditions. The problems that occur are the uncertainty and complexity in estimating the value of international trade in the oil and gas and non-oil and gas sectors, dependence on just one or a few markets, and the problem of unfair competition, unfair competition between business actors can reduce export-import prices. The value of oil and gas and non-oil and gas exports and imports is influenced by several external factors that are difficult to predict, such as fluctuations in oil and gas prices, changes in trade policies, and global economic factors. The prediction results are obtained every month from the export value data using the rapid miner application. From the export data, the value of non-oil and gas exports obtains a very high value compared to the export data of oil and gas values. Then the results from rapid miner using the linear regression algorithm are obtained. The predicted import value of oil and gas and non-oil and gas value data in June is 209,162,268, and the predicted export value of oil and gas and non-oil and gas value data in June is 349,285,781 and non-oil and gas which more are predicted to have the highest value compared to the value of oil and gas in each month.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"51 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":"135619802","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}

{"title":"EXPLORATORY DATA ANALYSIS OF CLINICAL HEART FAILURE USING A SUPPORT VECTOR MACHINE","authors":"Putri tua Sinaga, Salda Sari Purba, David Wiranto, Okta Jaya Maharja, Evta Indra","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4100","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4100","url":null,"abstract":"This study aims to explore the clinical data of patients diagnosed with heart failure using the Support Vector Machine (SVM) algorithm as a classification method. Clinical data from verified patients has been collected and analyzed to identify patterns, associations, and risk factors contributing to heart failure risk. The exploratory data analysis results reveal essential clinical data characteristics and provide initial insight into patient profiles and clinical variables that can influence heart failure risk. The SVM model was built to predict the risk of heart failure based on clinical data. This model is evaluated using classification metrics such as F1-Score and accuracy. Evaluation results show good performance with an F1-Score reaching 0.83, which indicates a reasonable degree of accuracy and balance in predicting the risk of heart failure. The conclusion of this study shows the potential of the classification model as a tool in managing heart failure patients. This model can help medical personnel identify high-risk patients and provide appropriate treatment to prevent disease progression and improve prognosis. However, these results need further verification with more in-depth analysis and validation using broader data. This model can help medical personnel identify high-risk patients and provide appropriate treatment to prevent disease progression and improve prognosis. However, these results need further verification with more in-depth analysis and validation using broader data. This model can help medical personnel identify high-risk patients and provide appropriate treatment to prevent disease progression and improve prognosis. However, these results need further verification with more in-depth analysis and validation using broader data. Keywords: Exploratory Data Analysis, Heart Failure, Classification, Python, Support Vector Machine","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135716409","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}

{"title":"ANALYSIS OF CLASSIFICATION OF LUNG CANCER USING THE DECISION TREE CLASSIFIER METHOD","authors":"Wendy Setiawan, Jepri Banjarnahor, Muhammad Faja Shandika, Amalia -, Muhammad Radhi","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4136","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4136","url":null,"abstract":"The International Agency for Research on Cancer (IARC) revealed staggering figures, with 19.3 million global cancer cases and 10 million related deaths in that year. Cancer, characterized by abnormal cell growth, can potentially be dangerous with the ability to metastasize. Notably, lung cancer is often detected in an advanced stage due to a lack of awareness and comprehensive medical assessment. Lung cancer usually presents with a late-stage diagnosis. From 60% to 85% of individuals diagnosed with lung cancer show a lack of awareness about their condition. Early diagnosis using an accurate classification method can significantly increase the success of lung cancer diagnosis. To improve predictions, Decision Tree Classifier method was used in lung cancer classification, resulting in a significant increase in accuracy. This study achieved a good level of accuracy, with an accuracy value of 95.16% at a max_depth model depth of 15, and tested in 40 experimental iterations. These results are expected to provide hope for progress in the classification of lung cancer. Keywords: Lung, Cancer, Classification, Decision Tree","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135876572","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}

{"title":"LIVER DISEASE CLASSIFICATION ANALYSIS USING THE XGBOOST METHOD","authors":"Yadi Sitinjak, Muhaymin -, Marlince Nababan","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4130","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4130","url":null,"abstract":"Liver disease is a severe pathological condition that can cause liver inflammation due to viral infection, toxic agents, or bacterial invasion, interfering with normal liver function. The death rate from this disease reaches 1.2 million people annually in Southeast Asia and Africa. Liver disease can cause damage to the liver and negatively affect overall body function. To reduce disease progression, it is critical to facilitate early diagnosis, thereby enabling rapid initiation of treatment for affected individuals. Classification methods are widely used to make decisions based on new information from previous data processing through calculation algorithms. This study uses the XGBoost classification method to build a predictive model for liver disease. The results of this study confirm that the XGBoost model is a robust and efficient choice for liver disease classification based on patient data. The use of the XGBoost approach has proven its success in the category of liver disease with an accuracy of up to 95% and an accuracy balance of 95%, demonstrating the effectiveness and efficiency of this method in overcoming class imbalances in liver disease classification data.   Keywords: Xgboost, Liver, Classification, Disease","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135876258","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}

{"title":"OBJECT-ORIENTED PARTS INVENTORY INFORMATION SYSTEM MODELING USING UNIFIED MODELING LANGUAGE","authors":"Fauzan Asrin","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4147","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4147","url":null,"abstract":"The availability of spare parts in a vehicle service workshop needs to be correctly recorded and recorded, making it easier for workshop owners to ensure the complete availability of vehicle spare parts. From the results of the author's observations, the Rizki Prima workshop has several obstacles in recording the availability of spare parts where the business processes being carried out are still a hassle for the employees working in the workshop. The problem often occurs when recording is the incompleteness of data related to incoming and outgoing goods. So the recording made in the ledger needs to be more accurate and requires a relatively long time to search one by one in the register if the workshop owner needs it. As a result of poor recording of goods, it is difficult for the owner to order goods again, worried that duplicating data will record incoming goods. The above problems are the basis for the authors to conduct research by utilizing information systems and modeling with an object-oriented approach using a unified modeling language to design a spare parts inventory information system according to user needs. To provide an overview of the Rizki Prima workshop transforming from conventional spare parts data recording to digital spare parts recording. The above problems are the basis for the authors to conduct research by utilizing information systems and modeling with an object-oriented approach using a unified modeling language to design a spare parts inventory information system according to user needs. To provide an overview of the Rizki Prima workshop transforming from conventional spare parts data recording to digital spare parts recording. The above problems are the basis for the authors to conduct research by utilizing information systems and modeling with an object-oriented approach using a unified modeling language to design a spare parts inventory information system according to user needs. To provide an overview of the Rizki Prima workshop transforming from conventional spare parts data recording to digital spare parts recording. KEYWORDS: Modeling, Information Systems, Spare Parts Inventory, Availability, Unified Modeling Language","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136064917","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}

{"title":"DECISION SUPPORT SYSTEM FOR TEACHER PERFORMANCE APPRAISAL WITH SIMPLE ADDITIVE WEIGHTING METHOD","authors":"Jijon Raphita Sagala, Penda Sudarto Hasugian","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4122","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4122","url":null,"abstract":"Teachers are the most influential component in creating quality educational processes and outcomes. Therefore, improvement efforts are made to improve the quality of education. Schools will not make a significant contribution without the support of professional and qualified teachers. Teachers are really required to have high performance. To improve the quality of teacher performance, the 064022 State Elementary School conducts teacher performance appraisals every 3 months but the mechanism is less effective due to lack of transparency. Research on teacher performance appraisal using the system is applied for efficiency and transparency. The system was developed using the Simple Additive Weighting method. The Simple Additive Weighting method is part of the Decision Support System (DSS) used to help determine decisions based on alternative data and criteria data.
 
 Keywords: Decision Support System, Teacher Performance, Simple Addictive Weighting.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135023054","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}

{"title":"IMPLEMENTATION OF THE ELECTRE METHOD IN DETERMINING THE DIRECTOR OF THE SUMATERA BLIND FOUNDATION","authors":"Murni Marbun, Oktavia Tumangger, Arta Putri Simalango","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4025","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4025","url":null,"abstract":"A director is a position held by someone in an agency or institution. The head of an institution engaged in special education, namely the Extraordinary School, is responsible for managing the school, so many criteria must be met and selected. Determination of the director requires a method to be more efficient, and the results are more valid. This study aims to implement the ELECTRE method to elect administrators at blind education schools at the Sumatra Blind Education Foundation. The ELECTRE method can be used when alternatives that do not fit the criteria are removed and the appropriate alternative is selected. The criteria for being a director are having ability in visual impairment, ability as a leader, psychological test results, ability to speak English and the results of interviews with HBM Germany. Implementing the ELECTRE method provides a sequence of choices for each alternative; if the number of ecl = 1 is more significant, the alternative is better. The results showed that of the four alternatives as director candidates, alternative A1 was the better choice, while alternatives A2, A3 and A4 were eliminated.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135022798","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}

{"title":"APPLICATION OF DATA MINING USING THE NAÏVE BAYES CLASSIFIER METHOD TO ANALYZE THE LEVEL OF CUSTOMER SATISFACTION IN ICE CREAM MIXUE","authors":"Anita Anita, Deslin Fitri Y. Lumban Gaol, Meta Doner Septia Sipayung","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4035","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4035","url":null,"abstract":"Ice Cream Mixue is a company engaged in the production of beverages and food. They provide a wide range of ice cream flavors with premium quality and natural ingredients, attracting many customers' attention. This study uses a quantitative method because the data sources are apparent. The research method is a scientific way to obtain data with specific purposes and uses. The technique used is the Naïve Bayes Classifier Algorithm with rapidminer results. 356 customers answered the questionnaire results satisfied, 64 customers who answered the questionnaire results were neutral, and 80 customers responded to the questionnaire results and were not happy. In this case, the Naïve Bayes Classifier Method can predict the level of customer satisfaction for ice cream mixes using the Rapidminer Application with Satisfied Words. This analysis obtained Class Precision satisfaction results of 94.72%, pred. neutral 2.0%, and pred. They are dissatisfied by 4%.","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135492246","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}

{"title":"USER SATISFACTION ANALYSIS OF DANA APPLICATION USING END USER COMPUTING SATISFACTION METHOD","authors":"Sudarsono Aritonang, Dedy Agung Prabowo, Cepi Ramdani","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3947","DOIUrl":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3947","url":null,"abstract":"The XYZ e-wallet application provides convenience in non-cash transactions with various features. Even though it allows for comfort in commerce, there are deficiencies in the XYZ e-wallet application that make users feel uncomfortable and dissatisfied. Weaknesses in the XYZ e-wallet application, namely there are problems updating the XYZ e-wallet to Premium, it is difficult to make payments to merchants who work with the XYZ e-wallet application, and there are problems with e-wallet application services on the service menu reporting problems response the customer service of the XYZ e-wallet application is old and ineffective. The results of the pre-research questionnaire on 59 answers found that 54.2% of respondents needed help making transactions. As many as 61% of users are dissatisfied with the services provided by the XYZ e-wallet application. This research analyzed user satisfaction with the XYZ e-wallet application using the EUCS method. This method measures five variables: Content, Accuracy, Format, Ease of Use, and Timelines. Each variable is measured with four questions. The results showed that the variables Content, Format, and Ease of Use were satisfied with Very Satisfied criteria, while the Accuracy and Timeliness variables had Satisfied criteria. The smallest calculated value is in the Accuracy and Timeliness variables which discuss the accuracy of errors when making transfers, upgrading the XYZ e-wallet account to Premium, and timeliness in handling problem reports. This research analyzed user satisfaction with the XYZ e-wallet application using the EUCS method. This method measures five variables: Content, Accuracy, Format, Ease of Use, and Timelines. Each variable is measured with four questions. The results showed that the variables Content, Format, and Ease of Use were satisfied with Very Satisfied criteria, while the Accuracy and Timeliness variables had Satisfied criteria. The smallest calculated value is in the Accuracy and Timeliness variables which discuss the accuracy of errors when making transfers, upgrading the XYZ e-wallet account to Premium, and timeliness in handling problem reports. This research analyzed user satisfaction with the XYZ e-wallet application using the EUCS method. This method measures five variables: Content, Accuracy, Format, Ease of Use, and Timelines. Each variable is measured with four questions. The results showed that the variables Content, Format, and Ease of Use were satisfied with Very Satisfied criteria, while the Accuracy and Timeliness variables had Satisfied criteria. The smallest calculated value is in the Accuracy and Timeliness variables which discuss the accuracy of errors when making transfers, upgrading the XYZ e-wallet account to Premium, and timeliness in handling problem reports. Each variable is measured with four questions. The results showed that the variables Content, Format, and Ease of Use were satisfied with Very Satisfied criteria, while the Accuracy and Timeliness varia","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135598084","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}