2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)最新文献_第2页

Deep Learning-based Approach on sgRNA off-target Prediction in CRISPR/Cas9 基于深度学习的CRISPR/Cas9中sgRNA脱靶预测方法

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127682

Alyssa Imani, Jonathan Valiant, Alexander Agung Santoso Gunawan

引用次数: 0

Instagram vs TikTok: Which Engage Best for Consumer Brand Engagement for Social Commerce and Purchase Intention? Instagram vs TikTok:哪个最适合社交商务和购买意愿的消费者品牌参与?

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127760

Jovan Tandy, Jesselin, Natalie, Ratna Sari

{"title":"Instagram vs TikTok: Which Engage Best for Consumer Brand Engagement for Social Commerce and Purchase Intention?","authors":"Jovan Tandy, Jesselin, Natalie, Ratna Sari","doi":"10.1109/ICCoSITE57641.2023.10127760","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127760","url":null,"abstract":"Restrictions from the government during the Covid-19 pandemic have made people spend more of their time online, browsing social media and encouraging them to shop online to fulfill their needs. The two social media with the most number of users are Instagram and TikTok. This popularity makes consumers interact more actively with other people on social media, which can increase product evaluation and make better purchasing decisions through product comments and reviews. This factor marks the beginning of the \"social commerce\" phenomenon. The purpose of this research is to compare the two social commerce, Instagram and TikTok, which platform engage best for consumer brand engagement and purchase intention, and how they relate to each other.This research uses a quantitative method with a SEM-based Partial Least Square (PLS) model using the Smart PLS 4 application. The result of this research are as follows, the selection of social media network platforms does not have a significant effect on consumer brand engagement and social commerce purchase intention. Instead, social commerce purchase intention is significantly influenced by the engagement between users. In turn, this consumer brand engagement is affected by the users’ habits when using social media.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114084488","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

Multivariate time series with Prophet Facebook and LSTM algorithm to predict the energy consumption

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127735

Sasmitoh Rahmad Riady, Rika Apriani

{"title":"Multivariate time series with Prophet Facebook and LSTM algorithm to predict the energy consumption","authors":"Sasmitoh Rahmad Riady, Rika Apriani","doi":"10.1109/ICCoSITE57641.2023.10127735","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127735","url":null,"abstract":"Energy is one of the most important factors in a country growth, both in the industrial and household fields. Among these fields, the industrial sector that needs the most in supporting the development of a company, energy saving is an important target for every company. Therefore, an accurate prediction is needed to determine future energy consumption. Many researchers have proposed research on the prediction of energy consumption using either machine learning or deep learning. One of the challenging factors in predicting energy consumption is data using a multivariate time series model with several uses in the area. In this project, researchers will conduct research on energy consumption predictions in manufacturing companies engaged in the food sector. This company has several areas as well as several predictable energies such as electricity, water, and diesel fuel, the data studied are multivariate time series modeled data. For the case of a data model like this, we use two algorithms, namely prophet and LSTM, because this algorithm can predict time series data. From the results of our research, it shows that Prophet Facebook which has the best results in predicting the energy consumption of electricity, water, and diesel fuel, a very significant difference in error rate is obtained by the LSTM algorithm for predicting time series models.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124389697","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

Performance of Known Ratings-Based Multi-Criteria Recommender System for Housing Selection 基于已知评级的多标准住房选择推荐系统的性能

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127720

Yunifa Miftachul Arif, Muhammad Farid Muhtarom, Hani Nurhayati

{"title":"Performance of Known Ratings-Based Multi-Criteria Recommender System for Housing Selection","authors":"Yunifa Miftachul Arif, Muhammad Farid Muhtarom, Hani Nurhayati","doi":"10.1109/ICCoSITE57641.2023.10127720","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127720","url":null,"abstract":"Housing developments are increasingly massive, and the lack of available information makes prospective customers experience difficulties in choosing a housing. These conditions resulted in the need for a recommendation system to assist consumers in choosing a place to live. In this study, we propose using the Multi-Criteria Recommender System (MCRS) to produce the most recommended housing selection recommendations in a case study of five housing complexes in Malang Raya. The system generates recommendations based on known user rating of 14 criteria and an overall rating (R0) stored in the database. In the experimental stage, the MCRS system in this study used four different methods: cosine, adjust cosine, Pearson correlation, and spearman rank-order correlation coefficient. The test results show that the recommendation system with each similarity method can produce housing recommendations by displaying the three most relevant housing recommendations to the user. Next, we use a confusion matrix to analyze the accuracy of the recommendations generated by the four similarity methods. The results of the confusion matrix calculation show that the average accuracy value for cosine-based similarity is 63.8%, the adjusted-cosine similarity is 70.4%, the Pearson correlation is 88.7%, and the Spearman rank-order correlation coefficient is 75.57%.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124453929","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

Salary Classification & Prediction based on Job Field and Location using Ensemble Methods 基于工作领域和工作地点的薪酬分类与预测

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127828

Jocelyn Verna Siswanto, Laurentia Alyssa Castilani, Natasha Hartanti Winata, Nathania Christy Nugraha, Noviyanti T M Sagala

{"title":"Salary Classification & Prediction based on Job Field and Location using Ensemble Methods","authors":"Jocelyn Verna Siswanto, Laurentia Alyssa Castilani, Natasha Hartanti Winata, Nathania Christy Nugraha, Noviyanti T M Sagala","doi":"10.1109/ICCoSITE57641.2023.10127828","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127828","url":null,"abstract":"The economy is one of the determinants of how a person can live their life. In this current economic situation, inflation occurs everywhere, causing the prices of necessities to rise. In order to have a decent life, people must find a job with the highest possible salary to fulfill their needs. Various job industries have their salary range. Obtaining the information of salary level for the respective job is helpful for employers and employees to estimate the expected salary. This work aims to classify the salary level of jobs available in Indonesia and determine whether those salaries are decent enough. The learning methods are logistic regression, decision tree, k-nearest neighbor, support vector machine, voting classifier, bagging classifier, random forest, and boosting classifier. Random Forest achieved the best result with an accuracy rate of 72%. Based on the analysis result, factors such as job field, educational background, working experience, working hours, and job location influence salary.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"5 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134256509","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

Object Size Recognition as Intra-class Variations using Transfer Learning 用迁移学习识别类内变化的对象大小

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127785

Rissa Rahmania, H. L. Hendric Spits Warnars, B. Soewito, F. Gaol

{"title":"Object Size Recognition as Intra-class Variations using Transfer Learning","authors":"Rissa Rahmania, H. L. Hendric Spits Warnars, B. Soewito, F. Gaol","doi":"10.1109/ICCoSITE57641.2023.10127785","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127785","url":null,"abstract":"The ability to differentiate various products in the retail store plays an essential role to provide effectiveness to customers and reduce or even eliminate long queues. However, traditional machine learning algorithms are incapable of recognizing many subordinate categories in various retail product. This paper aims to recognize the retail product recognition algorithm based on the YOLOv7 model in terms of intra-class variations, with the sub-categories of brand and size. We used two schemes of the dataset to compare recognition performance between them. Firstly, the YOLOv7 is applied in the two schemes of the dataset that is annotated with the subordinate category to detect the brand as meta category. Secondly, the proposed method is applied by adding the object size classification into the YOLOv7 model where the square area of the bounding box was calculated to classify the product according to size. Confidence score and square area are used to verify the object and to obtain the product size, which represents sub-category of the product. The experimental results show that our proposed method achieves higher recall compared to baseline object detection.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134436134","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

Role of E-Business Enabled Smartphones in Creating Smart Travelers 电子商务智能手机在打造智能旅行者中的作用

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127688

Sanjeev Kadam, Sujoy Sen

引用次数: 0

Fix-It: Design and Implementation of a Public Complaint Management System 解决问题:公众投诉管理系统的设计与实施

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127715

Faris Abdulrahman Alenezy, Muhammad Akhlaq

{"title":"Fix-It: Design and Implementation of a Public Complaint Management System","authors":"Faris Abdulrahman Alenezy, Muhammad Akhlaq","doi":"10.1109/ICCoSITE57641.2023.10127715","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127715","url":null,"abstract":"An effective complaint management system is essential to providing quality public services to the residents of a smart city. The complaints or feedback from residents can help identify a problem and hence provide an opportunity to improve the quality of a service by the service providers. We propose a public complaint management system, called Fix-It, to provide a link between a service provider and the users of that service. The system uses an Android app, online database, Google maps, and a web interface. The Android app allows a user to quickly report an incident with its location and other details. The web interface allows a service provider to receive and read the complaints, and then provide feedback to the complainant after taking any corrective actions. Fix-It is a simple, lightweight, effective and easy to maintain system for communication between the provider and users of a public service. The proposed system can be easily extended to other uses such as managing customer complaints in a business, reporting incidents on the streets, reporting the progress of a public project, etc. The testing of proposed system in a municipality department shows that the system is highly effective in reducing the time and procedures for complaint reporting, tracking the progress or status of the complaint, and providing the feedback to the complainant.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128941236","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

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127711

Larissa Navia Rani, Y. Yuhandri

{"title":"Similarity Measurement on Logo Image Using CBIR (Content Base Image Retrieval) and CNN ResNet-18 Architecture","authors":"Larissa Navia Rani, Y. Yuhandri","doi":"10.1109/ICCoSITE57641.2023.10127711","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127711","url":null,"abstract":"In this study aimed to measure the level of similarity between two logos, both those that look different and those that look the same. This can be realized by forming a logo image database that is stored in a logo image database derived from various existing logo image data. This research uses 4 logo images as data testing and 210 image data for the database as data training. All of the logo images used come from the Ministry of Law and Human Rights of the Republic of Indonesia (Kemenkumham RI) West Sumatra Regional Office. The size images are color images with a pixel size of 320 x 320 pixels, the purpose of which is for the process of dimensional uniformity of the images to be studied. This research uses Content Base Image Retrieval (CBIR) method to search for images from a large image database than using Convolutional Neural Network (CNN) type Residual Network (ResNet-18) Architecture to get the similarity score accurately. The result of this implementation is the formation of an automatic distribution of training images and validation images with 147 training image data values (70%) and 63 validation images (30%) of the 210 existing images. The result of this research is producing the algorithm to implement the method and the tool software application to measure the similarity of logo images. The accuracy of this tool is 93.65% with a total of 84 iterations.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131009289","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

Determining The Delivery Of Goods Using The K-Nearest Neighbor Algorithm And The Saving Matrix Method To Obtain The Optimal Route And Save Costs 利用k近邻算法和节省矩阵法确定货物的交付，以获得最优路线并节省成本

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) Pub Date : 2023-02-16 DOI: 10.1109/ICCoSITE57641.2023.10127714

Lidiawati, H. Setiawan, Adhitya Ilham Ramdhani, Satria, Sulistyowati, K. Mukiman

{"title":"Determining The Delivery Of Goods Using The K-Nearest Neighbor Algorithm And The Saving Matrix Method To Obtain The Optimal Route And Save Costs","authors":"Lidiawati, H. Setiawan, Adhitya Ilham Ramdhani, Satria, Sulistyowati, K. Mukiman","doi":"10.1109/ICCoSITE57641.2023.10127714","DOIUrl":"https://doi.org/10.1109/ICCoSITE57641.2023.10127714","url":null,"abstract":"Delivery of goods is a transaction or agreement between the seller and the buyer that produces an item to be transported and sent to the buyer. This study found problems with the late delivery of goods, namely limited vehicle capacity which resulted in delays in delivery of goods by sellers, delays in receiving goods by customers, and expensive transportation costs as a result where customers became dissatisfied with delivery services, decreased number of purchases, decreased delivery of goods and losses incurred suffered by the company or the seller in terms of costs or profits. The k-nearest neighbor algorithm is a classification technique by choosing a distance based on the size of the shortest distance and a saving matrix method that will form a delivery route taking into account vehicle capacity and saving on transportation costs. And later it will be formed into several new routes that aim to facilitate the delivery of goods with the advantage of providing satisfaction to customers and being able to save on transportation costs. So this research was developed for the route of delivery of goods by taking into account the capacity and number of vehicles which in previous studies regarding delivery routes. The results of this study solve the problem quite optimally at 12.67% or Rp. 757,356 cost savings while the delivery of goods resulted in 6 shipping lines instead of 11 shipping lines which cut 5 shipping lines or 11.11% for a total of 1532.15 Km.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131312561","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