Jurnal Ilmu Komputer dan Informasi最新文献_第3页

UML Transformation to Java-based Software Product Lines UML到基于java的软件产品线的转换

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1070

Falah Prasetyo Waluyo, M. R. Setyautami, A. Azurat

引用次数: 0

Gender Prediction of Indonesian Twitter Users Using Tweet and Profile Features 印尼Twitter用户性别预测研究

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1079

Rahmad Mahendra, Hadi Syah Putra, Douglas Raevan Faisal, Fadzil Rizki

引用次数: 0

SGCF: Inductive Movie Recommendation System with Strongly Connected Neighborhood Sampling 基于强连通邻域采样的电影推荐系统

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1066

Jatmiko Budi Baskoro, E. Yulianti

引用次数: 0

A Systematic Literature Review on SOTA Machine learning-supported Computer Vision Approaches to Image Enhancement 基于SOTA机器学习的计算机视觉图像增强方法的系统文献综述

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1017

Marco Klaiber, Jonas Klopfer

引用次数: 0

Sentiment Analysis of COVID-19 Vaccines in Indonesia on Twitter Using Pre-Trained and Self-Training Word Embeddings 使用预训练和自训练词嵌入对印度尼西亚Twitter上COVID-19疫苗的情绪分析

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1044

Kartikasari Kusuma Agustiningsih, Ema Utami, Muhammad Altoumi Alsyaibani

{"title":"Sentiment Analysis of COVID-19 Vaccines in Indonesia on Twitter Using Pre-Trained and Self-Training Word Embeddings","authors":"Kartikasari Kusuma Agustiningsih, Ema Utami, Muhammad Altoumi Alsyaibani","doi":"10.21609/jiki.v15i1.1044","DOIUrl":"https://doi.org/10.21609/jiki.v15i1.1044","url":null,"abstract":"Sentiment analysis regarding the COVID-19 vaccine can be obtained from social media because users usually express their opinions through social media. One of the social media that is most often used by Indonesian people to express their opinion is Twitter. The method used in this research is Bidirectional LSTM which will be combined with word embedding. In this study, fastText and GloVe were tested as word embedding. We created 8 test scenarios to inspect performance of the word embeddings, using both pre-trained and self-trained word embedding vectors. Dataset gathered from Twitter was prepared as stemmed dataset and unstemmed dataset. The highest accuracy from GloVe scenario group was generated by model which used self-trained GloVe and trained on unstemmed dataset. The accuracy reached 92.5%. On the other hand, the highest accuracy from fastText scenario group generated by model which used self-trained fastText and trained on stemmed dataset. The accuracy reached 92.3%. In other scenarios that used pre-trained embedding vector, the accuracy was quite lower than scenarios that used self-trained embedding vector, because the pre-trained embedding data was trained using the Wikipedia corpus which contains standard and well-structured language while the dataset used in this study came from Twitter which contains non-standard sentences. Even though the dataset was processed using stemming and slang words dictionary, the pre-trained embedding still can not recognize several words from our dataset.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83236122","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: 6

Wavelet Transformation and Spectral Subtraction Method in Performing Automated Rindik Song Transcription 小波变换与谱减法在Rindik歌曲自动誊写中的应用

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1009

Y. Christian, I. Darmawan

{"title":"Wavelet Transformation and Spectral Subtraction Method in Performing Automated Rindik Song Transcription","authors":"Y. Christian, I. Darmawan","doi":"10.21609/jiki.v15i1.1009","DOIUrl":"https://doi.org/10.21609/jiki.v15i1.1009","url":null,"abstract":"Rindik is Balinese traditional music consisting of bamboo rods arranged horizontally and played by hitting the rods with a mallet-like tool called \"panggul\". In this study, the transcription of Rindik's music songs was carried out automatically using the Wavelet transformation method and spectral subtraction. Spectral subtraction method is used with iterative estimation and separation approaches. While the Wavelet transformation method is used by matching the segment Wavelet results with the Wavelet result references in the dataset. The results of the transcription were also synthesized again using the concatenative synthesis method. The data used is the hit of 1 Rindik rod and a combination of 2 Rindik rods that are hit simultaneously, and for testing the system, 4 Rindik songs are used. Each data was recorded 3 times. Several parameters are used for the Wavelet transformation method and spectral subtraction, which are the length of the frame for the Wavelet transformation method and the tolerance interval for frequency difference in spectral subtraction method. The test is done by measuring the accuracy of the transcription from the system within all Rindik song data. As a result, the Wavelet transformation method produces an average accuracy of 83.42% and the spectral subtraction method produces an average accuracy of 78.51% in transcription of Rindik songs.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"84 10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75410515","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

Predicting Analysis of User’s Interest from Web Log Data in e-Commerce using Classification Algorithms 基于分类算法的电子商务用户兴趣预测分析

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1024

S. Diwandari, A. T. Hidayat

{"title":"Predicting Analysis of User’s Interest from Web Log Data in e-Commerce using Classification Algorithms","authors":"S. Diwandari, A. T. Hidayat","doi":"10.21609/jiki.v15i1.1024","DOIUrl":"https://doi.org/10.21609/jiki.v15i1.1024","url":null,"abstract":"The accelerated development of e-commerce has been a concern for business people. Business people should be able to gain customer interest in a variety of ways so that their companies can compete with others. Analyzing click-flow data will help organizations or firms assess customer loyalty, provide advertising privileges, and develop marketing strategies through user interests. By understanding consumer preferences, clickstream data analysis may be used to determine who is participating, assist companies in evaluating customer contentment, boost productivity, and design marketing strategies. This research was performed by defining experimental user interests using Dynamic Mining and Page Interest Estimation methods. The findings of this analysis, using three algorithms at the pattern discovery page, demonstrated that the Decision Tree method excelled in both methods. It indicated that the operational performance of the Decision Tree performed well in the assessment of user interests with two different approaches. The findings of this experiment can be used as a proposal for researching the field of web usage mining, collaborating with other approaches to achieve higher accuracy values.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90631743","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

Epidemic Data Analysis of Three Variants of COVID-19 Spread in Indonesia 三种COVID-19变体在印度尼西亚传播的流行数据分析

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.1055

Inna Syafarina, T. Wirahman, S. Iryanto, A. Latifah

{"title":"Epidemic Data Analysis of Three Variants of COVID-19 Spread in Indonesia","authors":"Inna Syafarina, T. Wirahman, S. Iryanto, A. Latifah","doi":"10.21609/jiki.v15i1.1055","DOIUrl":"https://doi.org/10.21609/jiki.v15i1.1055","url":null,"abstract":"Three variants of COVID-19 had been found in Indonesia. A control strategy may rely on the transmission rate of the variant. This study aims to investigate how the variants spread in Indonesia by computing a basic and effective reproduction number on the national and province scale. The basic reproduction number shows the indicator of initial transmission rate of alpha variant computed by an exponential growth rate model. The effective reproduction number describes the dynamic of the transmission rate estimated based on a Bayesian approach. This study revealed that each variant shows different characteristics. The alpha variant of COVID-19 in Indonesia was mainly initiated from big cities, then it spread to all provinces quickly because the control strategies were not established well at the beginning. A rapid increase of the effective reproduction number about July 2021 showed a novel delta variant, but it could be managed quite well by a large number of testing and stronger restrictions. Before the end of 2021, a novel variant omicron was also shown by the steeper change of the effective reproduction number. Thus, the variant spread rate can be estimated by how steep the effective reproduction number change is.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83075301","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

Analysis of Livestock Meat Production in Indonesia Using Fuzzy C-Means Clustering 用模糊c均值聚类分析印度尼西亚畜禽肉类生产

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-02-27 DOI: 10.21609/jiki.v15i1.993

Chalawatul Ais, Abdulloh Hamid, D. C. R. Novitasari

引用次数: 3

Increasing The Capacity of Headstega Based on Bitwise Operation 基于位运算的Headstega容量提升

Jurnal Ilmu Komputer dan Informasi Pub Date : 2021-07-04 DOI: 10.21609/jiki.v14i2.957

H. Hasmawati, A. Barmawi

引用次数: 0