Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika最新文献_第2页

Topic Modeling LDA and SVM in Sentiment Analysis of Hotel Reviews 酒店评论情感分析中的主题建模 LDA 和 SVM

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2023-07-20 DOI: 10.33751/komputasi.v20i2.7604

Erniyati Erniyati, P. Harsani, M. Mulyati, Lutfi Dani Fahriza

引用次数: 0

Identification of Significant Proteins in Hypertension Using The Clustering Molecular Complex Detection (MCODE) Method 利用聚类分子复合物检测（MCODE）方法识别高血压中的重要蛋白质

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2023-07-17 DOI: 10.33751/komputasi.v20i2.7905

Lusi Agus Setiani, W. Kusuma, Silvia Alviani Zulkarnaen

引用次数: 0

Dwiguna Life Insurance Zilmer Reserves With The Cox-Ingersoll-Ross (CIR) Interest Rate Dwiguna Life Insurance Zilmer准备金Cox-Ingersoll-Ross (CIR)利率

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v1i1.6229

Hasriati Hasriati

引用次数: 0

Analysis and Design of Production Monitoring Information Systems on Label Shoe Manufacturing Companies 标签制鞋企业生产监控信息系统的分析与设计

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6075

Jansen Wiratama

{"title":"Analysis and Design of Production Monitoring Information Systems on Label Shoe Manufacturing Companies","authors":"Jansen Wiratama","doi":"10.33751/komputasi.v20i1.6075","DOIUrl":"https://doi.org/10.33751/komputasi.v20i1.6075","url":null,"abstract":"Digital technology can be used to solve problems that arise from business activity. One company that has not optimally used digital technology is PT Tiga Tapak Mutiara, which is engaged in manufacturing shoe labels. In its business process, each related division collects data, and the data collection results will be reported to the manager to unify work activities. The production data collection process has not been carried out optimally by the relevant divisions because the conventional recording is still carried out using a spreadsheet application which can slow down the reporting process to be monitored by the leadership. As a result, a slow process can impact not completing production on time. In addition to the problem of data collection, another problem is that the completion of orders received earlier is not compared to the orders received last. The aim and contribution of this research are to integrate business processes to overcome these problems in data collection, monitoring, and order completion activities. It is necessary to design a web-based monitoring information system with the Rapid Application Development (RAD) method and the application of the First In, First Out (FIFO) method so that the ordering process can run according to the time of order. The result of this research is a web-based information system that is useful for integrating business processes to monitor and optimize production activities to be completed on time. This web-based information system has also passed the functionality test using black box testing and is following the company's needs.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114537295","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}

引用次数: 1

Analysis of Regency and City Pneumonia Clusters in West Java 2020 2020年西爪哇县和城市肺炎聚集性分析

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6412

Yusma Yanti

引用次数: 0

Application of Naive Bayes Algorithm to Analysis of Free Fatty Acid (FFA) Production Based on Fruit Freshness Level 朴素贝叶斯算法在基于水果新鲜度的游离脂肪酸产量分析中的应用

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6293

Wahyu Supriyatin

{"title":"Application of Naive Bayes Algorithm to Analysis of Free Fatty Acid (FFA) Production Based on Fruit Freshness Level","authors":"Wahyu Supriyatin","doi":"10.33751/komputasi.v20i1.6293","DOIUrl":"https://doi.org/10.33751/komputasi.v20i1.6293","url":null,"abstract":"Cooking oil is a basic need for everyone who is used to process food ingredients. The use of cooking oil repeatedly and continuously by heating at high temperatures can increase the free fatty acid levels in the oil. The more the oil is reused, the higher the free fatty acid content. Testing the levels of FFA in oil can be done using the FFA test, because FFA can affect the selling price of CPO when it is marketed. In addition, FFA affects the levels of free fatty acids of CPO. This study aims to determine the analysis of FFA production in palm oil products based on the level of freshness of the fruit. The research was conducted by classifying data mining using the NaÃ¯ve Bayes Algorithm. The NaÃ¯ve Bayes algorithm was used to determine whether FFA production had an effect on fruit freshness, fruit quality and fruit soiling. The research was conducted using RapidMiner Studio 9.10 tools. The results of the research from the distribution table show that the value of the FFA attribute obtained 2 conditions, namely super conditions and normal conditions. Where each of these attributes is influenced by the variables of fruit freshness and fruit quality. Probability accuracy results from 60 training data and 40 testing data used are 92.50% for super FFA conditions.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132815585","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}

引用次数: 1

Sentiment Analysis of Opinions on the Use of Devices in Students Using the Support Vector Machine (SVM) Method 基于支持向量机(SVM)方法的学生设备使用意见情感分析

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6558

M. Zuhri

{"title":"Sentiment Analysis of Opinions on the Use of Devices in Students Using the Support Vector Machine (SVM) Method","authors":"M. Zuhri","doi":"10.33751/komputasi.v20i1.6558","DOIUrl":"https://doi.org/10.33751/komputasi.v20i1.6558","url":null,"abstract":"Sentiment Analysis is a field of science in analyzing a sentiment or opinion on a particular object or problem and the opinion can be divided into several purposes (classes) that lead to negative, neutral or positive opinions. Gadgets (gadgets) are human aids in many fields including work, entertainment, communication and information, the use of gadgets themselves encompasses all ages including school students who use gadgets excessively that affect the mental, physical and attitudes of users. Twitter social media is one of the social media that is used by the public in making opinions about the influence of gadgets, especially parents, these opinions are useful for other users in determining the granting of access rights and direction for children, especially students in using gadgets. Opinion classification is needed in making it easier for other users to see whether opinions from the influence of gadgets fall into the negative, neutral or positive classes. The method used in the classification of opinion is Support Vector Machine (SVM). The data used in this study amounted to 1354 taken in 2019 using web scraping techniques on the Twitter site which are then pre-processed so that it can be processed into the program and classified into 3 classes of sentiments, namely negative, neutral and positive sentiments. In finding the average value of accuracy in the distribution of training data and test data using k-fold cross validation of 10-fold produces an average value of 85.3%. Then testing is done to measure the performance of the SVM method using confusion matrix in the percentage of training data and different test data and produces the highest accuracy value of 83.3%.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124300169","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}

引用次数: 2

Distribution Analysis Active Small and Medium Industries Bogor City Using K-means Clustering 基于k均值聚类的茂物市活跃中小产业分布分析

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6559

Siska Andriani

{"title":"Distribution Analysis Active Small and Medium Industries Bogor City Using K-means Clustering","authors":"Siska Andriani","doi":"10.33751/komputasi.v20i1.6559","DOIUrl":"https://doi.org/10.33751/komputasi.v20i1.6559","url":null,"abstract":"Small and Medium Industries (IKM) is one sector that contributes to driving economic growth, one of which is in West Java province, Bogor city. The number of active IKM in the city of Bogor in 2021 based on the survey results was 1,189, while in 2022 the number of small and medium industries (IKM) active in the city of Bogor based on the survey results was 1,766. The purpose of this study was conducted to determine the distribution of active small and medium industries (IKM) in Bogor city. So, this research can provide solutions related to the government or agencies to assist in building and developing IKM. In this research, the method used is the Knowledge Discovery in Database method, Where the stages are data selection, pre-processing, transformation, data mining and evaluation. Determination of the number of clusters is done using the elbow method. After determining with Elbow, the data will be represented using K-means clustering. The results of the K-means clustering algorithm yield 3 clusters, with each cluster 0 criterion being the distribution of low IKM with a total of 45 sub-districts. Cluster 1 is the distribution of medium IKM with the number of sub-districts is 14, and cluster 2 is the distribution of high IKM with the number of sub-districts totaling 9. The evaluation in this study used the silhouette coefficient method, from the data used it produced a cluster value of 0.56 which means that it is included in the clustering criteria with a good structure.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115101423","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}

引用次数: 0

Identification of Biometrics Using Fingerprint Minutiae Extraction Based on Crossing Number Method 基于交叉数法的指纹特征提取生物特征识别

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v20i1.6814

B. H. Situmorang

{"title":"Identification of Biometrics Using Fingerprint Minutiae Extraction Based on Crossing Number Method","authors":"B. H. Situmorang","doi":"10.33751/komputasi.v20i1.6814","DOIUrl":"https://doi.org/10.33751/komputasi.v20i1.6814","url":null,"abstract":"Biometrics based on fingerprint images is a self-recognition technique using fingerprint to represent a person's identity. Fingerprint is characteristic of someone's identity precisely and safely because there are no similarities and cannot be falsified. The purpose of this research is to develop a biometrics identification system based on fingerprint images by utilizing a cell phone camera for the acquisition of fingerprint images. This is based on its simplicity because almost everyone has a cell phone so that a person's identification system based on fingerprint can be used anytime and anywhere. The research was conducted using images generated from cell phone cameras with camera specifications of 2, 5 and 8 mega pixels. The method used in image processing consists of the minutiae crossing number method for the feature extraction process and the minutiae based matching method for the similarity measurement process. The results of the research concluded that cell phone cameras with specifications of 5 and 8 mega pixels can be used for the process of image acquisition in biometrics systems based on fingerprint. The feature extraction process of image results using the minutiae crossing number method and the match measurement process using the minutiae based matching method resulted in an accuracy value of 92.8% on a 5 mega pixel camera and 95.3% on an 8 mega pixel camera. The accuracy value depends on the results of the image acquisition stage, pre-processing, the threshold value in the identification process, and the number of images used in the training data in the database.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124586921","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}

引用次数: 0

The Sustainability of The Netflix's Business Processes With Knowledge Risk Management Approach 基于知识风险管理方法的Netflix业务流程的可持续性

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2022-12-02 DOI: 10.33751/komputasi.v1i1.5935

Gustian Rama Putra

引用次数: 1