Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)最新文献_第9页

Ontology-based Conversational Recommender System for Recommending Camera 基于本体的相机推荐会话系统

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4852

Restu Aditya Rachman, Z. Baizal

{"title":"Ontology-based Conversational Recommender System for Recommending Camera","authors":"Restu Aditya Rachman, Z. Baizal","doi":"10.29207/resti.v7i3.4852","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4852","url":null,"abstract":"The camera is a product that has developed very quickly in terms of specifications and functions. In addition, the cameras available on the market are becoming increasingly varied, so customers need more time to find a camera that suits their needs. Currently, many recommender systems have been developed to assist users in finding suitable products, especially the conversational recommender system (CRS). CRS is a recommender system that recommends products through conversations between the user and the system. However, many developed CRS still forces users to have knowledge of the product's technical characteristics. In the real world, many people are not familiar with the technical features of products, especially cameras. People interact more easily with CRS by stating the camera function they want. In this study, we call that statement functional requirements. Therefore, we proposed a CRS for recommending cameras that interact with users using functional requirements. This CRS uses semantic reasoning techniques on ontologies. To evaluate system performance, we use two parameters, i.e., user satisfaction and recommendation accuracy. The evaluation results show that the accuracy of the recommendations is at a value of 82.35%, and the level of user satisfaction reaches 0.66. With these results, the system can provide recommendations accurately and satisfy users. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134276057","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

Logistic Regression Using Hyperparameter Optimization on COVID-19 Patients’ Vital Status 基于超参数优化的新冠肺炎患者生命状态Logistic回归

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4868

Vinna Rahmayanti Setyaning Nastiti, Yufis Azhar, Riska Septiana Putri

{"title":"Logistic Regression Using Hyperparameter Optimization on COVID-19 Patients’ Vital Status","authors":"Vinna Rahmayanti Setyaning Nastiti, Yufis Azhar, Riska Septiana Putri","doi":"10.29207/resti.v7i3.4868","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4868","url":null,"abstract":"This study aims to classify COVID-19 patients based on the results of their hematology tests. Hematology test results have been shown to be useful in identifying the severity and risk of COVID-19 patients. Specifically, this study focuses on classifying COVID-19 patients based on their vital status, namely Deceased and Alive. The dataset used in this study contains four variables: white blood cells (WBC), neutrophils (NEU), lymphocytes (LYM), and Neutrophil Lymphocyte Ratio (NLR). Logistic Regression algorithm was used to solve the problem, and hyperparameter optimization was implemented to obtain the best model performance. The objective of this study was to build the best parameter in classifying the patients’ vital status. The proposed model achieved an accuracy score of 78%, which is the best performance among the tested models. The results of this study provide a key component for decision making in hospitals, as it provides a way to quickly and accurately identify the vital status of COVID-19 patients. This study has important implications for managing the COVID-19 pandemic and should be of interest to researchers and practitioners in the field. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117281414","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

Modified Q-Learning Algorithm for Mobile Robot Real-Time Path Planning using Reduced States 基于状态简化的移动机器人实时路径规划改进q -学习算法

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4949

Hidayat, A. Buono, K. Priandana, S. Wahjuni

{"title":"Modified Q-Learning Algorithm for Mobile Robot Real-Time Path Planning using Reduced States","authors":"Hidayat, A. Buono, K. Priandana, S. Wahjuni","doi":"10.29207/resti.v7i3.4949","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4949","url":null,"abstract":"Path planning is an essential algorithm in any autonomous mobile robot, including agricultural robots. One of the reinforcement learning methods that can be used for mobile robot path planning is the Q-Learning algorithm. However, the conventional Q-learning method explores all possible robot states in order to find the most optimum path. Thus, this method requires extensive computational cost especially when there are considerable grids to be computed. This study modified the original Q-Learning algorithm by removing the impassable area, so that these areas are not considered as grids to be computed. This modified Q-Learning method was simulated as path finding algorithm for autonomous mobile robot operated at the Agribusiness and Technology Park (ATP), IPB University. Two simulations were conducted to compare the original Q-Learning method and the modified Q-Learning method. The simulation results showed that the state reductions in the modified Q-Learning method can lower the computation cost to 50.71% from the computation cost of the original Q-Learning method, that is, an average computation time of 25.74s as compared to 50.75s, respectively. Both methods produce similar number of states as the robot’s optimal path, i.e. 56 states, based on the reward obtained by the robot while selecting the path. However, the modified Q-Learning algorithm is capable of finding the path to the destination point with a minimum learning rate parameter value of 0.2 when the discount factor value is 0.9.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130777467","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

Implementation of n-gram Methodology to Analyze Sentiment Reviews for Indonesian Chips Purchases in Shopee E-Marketplace 用n-gram方法分析Shopee电子商城印尼芯片购买的情绪评论

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4726

M. E. Purbaya, Diovianto Putra, Maliana Puspa Arum, LU Zian, Nasifah

{"title":"Implementation of n-gram Methodology to Analyze Sentiment Reviews for Indonesian Chips Purchases in Shopee E-Marketplace","authors":"M. E. Purbaya, Diovianto Putra, Maliana Puspa Arum, LU Zian, Nasifah","doi":"10.29207/resti.v7i3.4726","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4726","url":null,"abstract":"Chips are a well-known product among Small and Medium Enterprises (SMEs). In order to enhance the quality of chips as an SME product, sentiment analysis is a crucial step. In this research, sentiment analysis of chip purchases on the Shopee E-marketplace was conducted using the Natural Language Processing (NLP) method, utilizing the N-Gram Model and Term Frequent-Inverse Document Frequency (TF-IDF) as feature extraction techniques, and the Support Vector Machine (SVM) algorithm for sentiment classification. The objective of this research is to identify the most suitable feature extraction model and optimal SVM kernel type from the options of Linear, Polynomial degree, Gaussian RBF, and Sigmoid kernels. Results from the experiments indicate that the TF-IDF and unigram feature extraction techniques offer the best performance for SVM classification when utilizing the Linear kernel. By labeling the dataset, it was observed that using a lexicon-based approach for sentiment classification resulted in 84.31% of the total reviews being positive. The words \"price\", \"cheap\" and \"quality\" in unigram have the highest weights above 0.040. In the unigram model, linear kernel accuracy and precision performance values are 88.4% and 87.3%. At the same time, the recall performance values is 88.4%. The results of the F1-Score assessment matrix from Unigram were 86.9%, Bigram was 78.5% and Trigram was 77.4%. Ultimately, the unigram model combined with a linear kernel in the SVM algorithm demonstrates strong potential for application in the development of various systems focused on detecting user reviews in the Indonesian language on the Shopee E-Marketplace. ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122734985","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

Triangular fuzzy numbers-based MADM for selecting pregnant mothers at risk of stunting 基于三角模糊数的MADM选择有发育迟缓风险的孕妇

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4966

W. Hadikurniawati, Kristoko Dwi Hartomo, I. Sembiring, Hindriyanto Dwi Purnomo, Ade Iriani

{"title":"Triangular fuzzy numbers-based MADM for selecting pregnant mothers at risk of stunting","authors":"W. Hadikurniawati, Kristoko Dwi Hartomo, I. Sembiring, Hindriyanto Dwi Purnomo, Ade Iriani","doi":"10.29207/resti.v7i3.4966","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4966","url":null,"abstract":"Stunting is caused by a lack of proper nutrition before and after birth. This research paper identifies and measures the risk of stunting during pregnancy and make recommendations for ranking pregnant women at risk. These aims to provide appropriate treatment and action to reduce mothers giving birth to children at risk of stunting. To make the optimal choice, the selection procedure for pregnant women at risk of giving birth to stunted children considers a variety of factors, including maternal age, maternal nutrition, arms circumference, hemoglobin, parity, birth interval, height, baby weight, and body mass index (BMI). Decision-maker’s expectation to reduce uncertainty and imprecision are represented linguistically by triangular fuzzy numbers. The triangular fuzzy numbers arithmetic approach is used to determine the selection process output. The ranking is determined from the alternative with the most parameter values to the alternative with the fewest parameters. Based on the results of the calculation, it was determined that PM (Pregnant Mother) had the highest score and was ranked first. That pregnant mother was declared as pregnant mother who had the lowest risk of giving birth to stunted baby \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124464669","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

Aspect Based Sentiment Analysis Marketplace Product Reviews Using BERT, LSTM, and CNN 基于方面的情感分析使用BERT, LSTM和CNN的市场产品评论

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4751

Syaiful Imron, Esther Irawati Setiawan, Joan Santoso, Mauridhi Hery Purnomo

{"title":"Aspect Based Sentiment Analysis Marketplace Product Reviews Using BERT, LSTM, and CNN","authors":"Syaiful Imron, Esther Irawati Setiawan, Joan Santoso, Mauridhi Hery Purnomo","doi":"10.29207/resti.v7i3.4751","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4751","url":null,"abstract":"Bukalapak is one of the largest marketplaces in Indonesia. Reviews on Bukalapak are only in the form of text, images, videos, and stars without any special filters. Reading and analyzing manually makes it difficult for potential buyers. To help with this, we can extract this review by using aspect-based sentiment analysis because an entity cannot be represented by just one sentiment. Several previous research stated that using LSTM-CNN got better results than using LSTM or CNN. In addition, using BERT as word embedding gets better results than using word2vec or glove. For this reason, this study aims to classify aspect-based sentiment analysis from the Bukalapak marketplace with BERT as word embedding and using the LSTM-CNN method, where LSTM is for aspect extraction and CNN for sentiment extraction. Based on testing the LSTM-CNN method, it gets better results than LSTM or CNN. The LSTM-CNN model gets an accuracy of 93.91%. Unbalanced dataset distribution can affect model performance. With the increasing number of datasets used, the accuracy of a model will increase. Classification without using stemming on datasets can increase accuracy by 2.04%. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128438692","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

Secure Cybersecurity Information Sharing for Sectoral Organizations Using Ethereum Blockchain and IPFS 使用以太坊区块链和IPFS的部门组织安全网络安全信息共享

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-02 DOI: 10.29207/resti.v7i3.4956

Tony Haryanto, K. Ramli

{"title":"Secure Cybersecurity Information Sharing for Sectoral Organizations Using Ethereum Blockchain and IPFS","authors":"Tony Haryanto, K. Ramli","doi":"10.29207/resti.v7i3.4956","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4956","url":null,"abstract":"The COVID-19 pandemic has resulted in increased cross-sector cyber-attacks. Passive and reactive cybersecurity techniques relying solely on technology are insufficient to combat sophisticated attacks, necessitating proactive and collaborative security measures to minimize attacks. Cybersecurity Information Sharing (CIS) enhances security via proactive and collaborative cybersecurity information exchange, but its implementation via cloud services faces threats from man in the middle (MITM) and distributed denial of service (DDoS) attacks, as well as a vulnerability in cloud storage involving centralized data control. These threats and vulnerabilities result in a lack of user confidence in the confidentiality, integrity, and availability of information. This paper proposes Secure Cybersecurity Information Sharing (SCIS) to secure Cybersecurity Information in sectoral organizations using the private interplanetary file system (IPFS) network and the private Ethereum Blockchain network. Private Ethereum Blockchain enables secure and transparent transaction logging, while Private IPFS network provides decentralized storage, addressing vulnerabilities in centralized storage systems. The outcomes of the tests reveal that the suggested SCIS system offers cybersecurity information availability, confidentiality, and integrity. SCIS provides a high level of security to protect cybersecurity information exchanged between sectoral organizations using the Private Ethereum Blockchain network and the Private IPFS network so that organizations can safely share and utilize information. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"428 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115931952","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

Sentiment Analysis on Social Media with Glove Using Combination CNN and RoBERTa 结合CNN和RoBERTa对戴手套的社交媒体情感分析

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-01 DOI: 10.29207/resti.v7i3.4892

Diaz Tiyasya Putra, Erwin Budi Setiawan

{"title":"Sentiment Analysis on Social Media with Glove Using Combination CNN and RoBERTa","authors":"Diaz Tiyasya Putra, Erwin Budi Setiawan","doi":"10.29207/resti.v7i3.4892","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4892","url":null,"abstract":"Twitter is a popular social media platform that allows users to share short message’s opinion and engage in real-time conversations on a wide range of topics known as tweet. However, tweets often have a complicated and unclear context, which makes it difficult to determine the actual emotion. Therefore, sentiment analysis is required to see the tendency of an opinion, whether the opinion tends to be positive, negative, or neutral. Researchers or institutions can find out how the response and emotions of an issue are happening and make good decisions. With the large user of Twitter social media in Indonesia, sentiment analysis will be carried out using deep learning Convolutional Neural Network (CNN), Term Frequency-Inverse Document Frequency (TF-IDF), Robustly Optimized BERT Pretraining Approach (RoBERTa), Synthetic Minority Over-sampling Technique (SMOTE), and Global Vector (Glove). In this research, the dataset used is trending topics with hashtags related to government policies on Twitter social media and obtained through crawling. By using 30.811 data, the result shows the highest accuracy of 95.56% using CNN with a split ratio of 90:10, baseline unigram, RoBERTa, SMOTE, and Top10 corpus tweet with an increase 10.1%.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222399","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: 3

Implementation of Self Driving Car System with HSV Filter Method Based on Raspberry & Arduino Serial Communication 基于Raspberry和Arduino串行通信的HSV滤波方法实现自动驾驶汽车系统

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-01 DOI: 10.29207/resti.v7i3.4579

Kelvin Kristian Roestamadji, F. B. Setiawan, L. Pratomo, Slamet Riyadi

{"title":"Implementation of Self Driving Car System with HSV Filter Method Based on Raspberry & Arduino Serial Communication","authors":"Kelvin Kristian Roestamadji, F. B. Setiawan, L. Pratomo, Slamet Riyadi","doi":"10.29207/resti.v7i3.4579","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4579","url":null,"abstract":"The development of technology in the transportation sector at this time is increasingly crucial. So the company innovates to create a car that can run itself with a high level of security. In this study, we designed an autonomous drive system for a 1:10 scale RC car using the main components in the form of a Raspberry Pi 4 and a Raspberry Pi camera as image processing for automatic control of an self driving car. Then the Arduino Nano, BTS7960, and Driver L298N components are used to regulate the movement of the DC motor. In this article, the control strategy of this self-driving car will be shown which will be implemented to detect lanes as a guide to walk autonomously. This study uses the HSV color filer method with morphology techniques to detect the path to be passed. This study resulted in a path detection that was very accurate and operated in real-time when compared to the CNN method using sampling paths to be passed that had previously been researched. After the path is detected, the interconnection between the mini computer and the microcontroller will work to synchronize the path detection and motor movement. In trials and hardware implementations carried out in the self-driving car laboratory with artificial intelligence, it can work according to the algorithm created with a success rate of 90%. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133792406","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

Sentiment Analysis of Cryptocurrency Trading Platform Service Quality on Playstore Data: A Case of Indodax 基于Playstore数据的加密货币交易平台服务质量情绪分析——以印度指数为例

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-06-01 DOI: 10.29207/resti.v7i3.4769

Kamrozi, A. Hidayanto, Krishna Yudhakusuma, Muhammad Alviazra Virgananda, Ryan Randy Suryono

{"title":"Sentiment Analysis of Cryptocurrency Trading Platform Service Quality on Playstore Data: A Case of Indodax","authors":"Kamrozi, A. Hidayanto, Krishna Yudhakusuma, Muhammad Alviazra Virgananda, Ryan Randy Suryono","doi":"10.29207/resti.v7i3.4769","DOIUrl":"https://doi.org/10.29207/resti.v7i3.4769","url":null,"abstract":"Indodax is one of the cryptocurrency trading platforms in Indonesia that has the highest sentiment for the quality they provide, good quality on a platform is an important factor in obtaining user satisfaction and will have an impact on the long-term success of a company. The importance of user satisfaction on cryptocurrency online trading platforms is a significant factor in increasing user loyalty in today's competition. This research was conducted to analyze the quality of existing cryptocurrency trading platform services so that they can be input for cryptocurrency trading service providers to improve the quality of their services, this information can also be considered by prospective platform users in choosing a trading platform that has the best quality of service to minimize losses that may be caused by the platform. In this study, sentiment analysis was used for indodax play store platform users and then processed using the lexicon classification method to produce sentiment analysis for each significant factor of service quality. From the results of the classification carried out in this study, the results of the analysis show that most users are satisfied and give positive sentiments related to security, namely 87.63%, positive sentiments related to the interface design 88.46%, positive sentiments related to service & convenience by 83%, but some users also gave a slightly positive sentiment related to administrative costs, namely 39%, and their negative sentiment was mostly related to the error & failure system, which received more than 80% sentiment. While the recall value is 38.07%, the precision is 56.69% and the f1-score is 45.55%. The results of this study can be concluded that there are still many important points that must be improved in quality by the indodax platform service providers so that they can be more attractive and used by everyone. \u0000 ","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131698095","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