bluuebunny/crossref_metadata_2025_split huggingface dataset:
App Review Sentiment Analysis Shopee Application In Google Play Store Using Naive Bayes Algorithm
Authors: Pratmanto Dany , Rousyati Rousyati , Wati Fanny Fatma , Widodo Andrian Eko , Suleman Suleman , Wijianto Ragil 
Published: November 2020

Abstract
An online marketplace site is a shopping place that is currently popular with the community because it offers a variety of convenience and one of the marketplace apps is Shopee. Some people are satisfied with the service provided by the Shopee app. But unisex some people who give complaints about this application. User-provided response to Shopee app in the Comments field of Shopee Google Play Store can be analyzed for negative and positive sentiments. This research aims to assist Shopee’s management of the positive or negative opinions of application users and can provide empirical evidence for related theories so that it can be used as a donation of thought for the development of theories Next. With the number of reviews shown, you need an analysis that can classify these reviews into positive or negative classes. The method used for the sentiment analysis of Shopee app reviews is the Naive Bayes algorithm obtaining an accuracy yield of 96,667%
Employee attendance application using location based service (lbs) method based on android
Authors: Fatkharrofiqi Achmad , Kuswanto Herman , Rahman Taufik , Sumarna  , Handono Felix Wuryo , Nurdin Hafis 
Published: November 2020

Abstract
PT. Brainmatics Cipta Informatika is an IT Training and Consulting company located in Jakarta. The development of a company can not be separated from the role of employees in it. The success assessment of existing human resources apart from the aspect of success in the field of work is also inseparable from the assessment of the conditions including the assessment of attendance. Problems that occur at PT. Cipta Cipta Brainmatics is the process of existing employee attendance, attendance is done by using Odoo’s web based Enterprise Resource Planning system that stores employee data on coming and outgoing hours that can be accessed anywhere without any location or area restrictions, so employees can do attendance at anywhere, even without having to come to the office. Based on these problems, an Android-based attendance application was designed by utilizing the Location Based Service (LBS) feature that can be operated using a smartphone and can be used with a limited area determined for the attendance process. This application was built with the Java programming language using Android Studio, PostgreSQL and Objecbox software as its database. It is expected that the application that is designed can resolve the attendance issues that exist at PT. Brainmatics Cipta Informatika.
The Analysis of Digital Provider Sentiment Of ‘by.u’ On Google Play Which Uses The Support Vector Machine (SVM) Method
Authors: Ardiansyah Angga , Aji Sopian , Pratmanto Dany , Kuryanti Sandra Jamu , Putra Octa Pratama , Adiwihardja Cep 
Published: November 2020

Abstract
The development of technology in the industrial revolution 4.0 is very rapid in various sectors in trade, communication and other sectors; both nationally and internationally. One of the fields, it is the telecommunications sector. Becoming one of the digital based providers of ‘by.u’ from Telkomsel which is the first digital operator in Indonesia. The algorithm testing uses Support Vector Machine (SVM) from 300 user review data applications. The ‘by.u’ review consists of 150 negative reviews; which refers to dislike or bad expressions. Next, 150 positive reviews; which refers the constructive suggestion or support the text in using Indonesian. The resulting model gets the results of testing accuracy by using Support Vector Machine with accuracy value shows that: 87.24
Analysis of Community Satisfaction Level Against the Ministry of Health’s Infection Emerging Websites Using Webqual 4.0
Authors: Said Fadillah , Astoni Khabib , Riana Dwiza , Wahyuni Asri 
Published: November 2020

Abstract
As one form of communication and information media, web sites have a very big role in representing a government institution to interact with the public. A website is designed in such a way as to meet certain service quality standards set by the developer. However, good service quality must also consider perceptions from the point of view of users in this case the wider community. The study purpose is to determine the level of community satisfaction with the quality of the website as an indicator of success by the government in conveying information to the public. The method used in this study is to distribute questionnaires with a Webqual approach which is of three categories, specifically Usability Dimension, Information Quality Dimension, and Service Interaction Dimension. The data were obtained then analyzed using the Structural Equation Model (SEM) Technique with the SmartPLS 3 software. Based on a survey of 104 respondents, it was found that in general users were satisfied with the services on the website.
Villages Status Classification Analysis Involving K-Means Algorithm To Support Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi Work Programs
Authors: Hasugian Paska Marto , Hutahaean Harvei Desmon , Sinaga Bosker , Sriadhi  , Silaban Saranom 
Published: November 2020

Abstract
Data mining is a technique of extracting information that has not been known before in a collection of data in the database. Data mining has been applied in various fields that require extracting information, some of the work that can be generated with data mining is classification, prediction, and data grouping. In this study, an analysis of village data collection was carried out to explore the potential or knowledge of the data that has been presented with the main objective of producing a grouping of village status. To support clustering or grouping activities the K-means algorithm used with the general process is to carry out the modeling process without supervision and is one of the methods for grouping data with a system partition, with the principle of allocating each data to the centroid or the closest average, work steps conducted in support of this research is to collect data related to the analysis of data grouping and proceed with the calculation process in accordance with the work steps of the K-means algorithm, the amount of data used as a test of 303 villages scattered in the old Padang regency. The results of calculations by displaying a new group of Cluster 0 is occupied by 120 villages, cluster 1 with a total data of 123 villages, Cluster 2 with a total of 6 villages, cluster 3 with a total of 33 villages while cluster 4 with a total of 21.
Analysis of Factors Affecting Quality of corona.jatengprov.go.id Website Towards User Satisfaction using Webqual 4.0 Method
Authors: Nugraha Ranu Agastya , Andriyanto Dwi , Riana Dwiza , Khasanah Siti Nur 
Published: November 2020

Abstract
This research focuses on how to measure the quality of a website using the Webqual 4.0 method, what are the factors that influence user satisfaction. The PLS-SEM technique was used to verify questionnaire data from a sample of 155 respondents. The result shows that the quality of service interaction has a significant (positive) effect of 54.2% compared to the aspect of information quality and usability quality that has no significant effect. These results indicate that the corona.jatengprov.go.id site users expect quality of service interaction as a measure of satisfaction from the quality of a website. Users are more likely not to see deficiencies in the aspect of information quality and usability quality according to the assessment of satisfaction given. Therefore, the corona.jatengprov.go.id website manager needs to focus on the quality of service interaction aspects of website as a priority in improving grade.
Swietenia Mahagoni Wood Defects Segmentation Using YIQ Color Space and Thresholding
Authors: Rahayu Sri , Qhomariyah Nurul , Purnama Jajang Jaya , Riana Dwiza , Achyani Yuni Eka , Ariani Fattya 
Published: November 2020

Abstract
The biggest income from Southeast Asian countries came from timber production export activities. The potential for timber exports in Indonesia continued to increase every year. This skyrocketing potential needed to be improved by maintaining quality so that trust and good cooperation continued to be established. The quality of wood has closely related to wood defects, the faster detection of wood defects would be the faster also determines the quality of wood. Current technology has being developing rapidly to help productive human activities, image processing has being a breakthrough to be able to detect wood defects. This study aims to detect wood defects by segmenting Swietenia Mahagoni wood images by using the YIQ color space and Thresholding has resulted in a fairly good segmentation that is successful in segmenting the types of bark grown wood defects on bontos and defects in healthy knot on the body of wood with each percentage of 83.3%.
Assessing E-Commerce Success from a Millennial Perspective in Indonesia
Authors: Mahendra Irfan , Sulistianto SW , Mulyani Astriana , Wiyatno Agus , Rosanto Oki 
Published: November 2020

AbstractThis research was conducted to assess the success of e-commerce from the perspective of the millennial generation in Indonesia. This research was conducted through a case study on the Bukalapak Application, which in recent times has decreased from the perspective of the number of visitors. This study refers to the DeLon and McLean Updated Information System Success Model. The measurement indicators used in this study were modified based on a review of several recent studies. Data collection was carried out using a questionnaire distributed to 291 respondents consisting of Bukalapak Application users who are included in the millennial generation in Indonesia. Based on the research results above, it can be concluded that all hypotheses can be accepted. Where the quality of information and customer satisfaction has a stronger influence on the use of the Bukalapak Application. Whereas service quality and system quality have a stronger influence on customer satisfaction in using the Bukalapak Application. Then user satisfaction has a stronger effect than using the system at a net profit. It is also known that the millennial generation in Indonesia also considers that the Bukalapak Application has good information quality, system quality, and service quality. Millennial also claims to have used the Bukalapak Application and expressed satisfaction with using the Bukalapak Application and stated that the Bukalapak Application was useful.
Prediction of Evaluation Result of E-learning Success Based on Student Activity Logs With Selection of Neural Network Attributes Base on PSO
Authors: Saputra Elin Panca , Supriatiningsih  , Indriyanti  , Sugiono  
Published: November 2020

Abstract
Evaluation of learning systems based on e-learning is very important to determine learning success. The purpose of this study is to obtain predictive results from evaluating students who follow e-learning based learning systems. The data used is the result of logs of student learning activities taken from the LMS. The data used in this study were 641 user logs of student activity. In predicting the evaluation results based on the learning system on e-learning we use a neural network method based on swarm particle optimization. Neural Network has a problem in optimizing very large data so using swarm particle optimization can solve this problem. From the data testing we have done, the results obtained by the Neural Network method get an accuracy value of 95.47%, and the results of the AUC value of 97.90%. The observation of variables C, ∊ and population of Neural Network and particle swarm optimization use the K-Fold Cross Validation method. Then the researchers tested several choices on the attributes used. By using the Neural Network method based on the swarm particle optimization attribute, there are 9 predictor variables so that as many as 6 attributes are used, namely sports, chat, discussion, messages, Quiz exercises and total logs. The results show an accuracy rate higher than 97.50%, and an AUC value of 98.20%. So the accuracy value increased by 2.03% and the AUC increased by 0.3%. With accuracy and AUC values, the Artificial Neural Network algorithm based on particle optimization is very well categorized.
Identification and Detection Odontoglossum ringspot virus on Native Orchids Collection of Nurserys in Java, Indonesia
Authors: Mahfut  
Published: November 2020

Abstract
Nature orchid are one of original floral in Indonesia. Virus infection is one of the limiting factor in the cultivation of orchid. Infection Odontoglossum ringspot virus (ORSV) was reported infets native orchids collection in Indonesia. The purpose of this study was to identification and ORSV that infects native orchid nurserys collection in Java, Indonesia. Symptomatic samples were collected from 5 nurserys collections, i.e. Rumah Bunga Rizal (Bandung), Bali Tanaman Hias (Cianjur), Borobudur Orchids Center (Magelang), Kebun Anggrek Bungarinte (Yogyakarta), and Titi Orchids (Yogyakarta). Detection and identification was conducted by serological test using ORSV specific antisera, RT-PCR and DNA sequencing. The serological test using ORSV antisera showed that 3 of 11 sampels reacted positively against ORSV antiserum i.e Phalaenopsis amabilis (Cianjur.1, Cianjur.2, and Magelang). RT-PCR of the 3 samples using specific primer of ORSV coat protein (CP) gene amplified a DNA with size ± 474 bp. Homology analysis of those 3 Indonesian isolates showed highest index similiarity (IS) was 99.8% with corresponding sequences from 10 other ORSV isolates. Phylogenetic analysis showed that ORSV Cianjur.1 and Cianjur.2 isolates clustered in separated group far from ORSV isolates in other countries.
Comparation of K-Nearest Neighboor (K-NN) and Naive Bayes Algorithm for the Classification of the Poor in Recipients of Social Assistance
Authors: Firasari Elly , Khasanah Nurul , Khultsum Umi , Kholifah Desiana Nur , Komarudin Rachman , Widyastuty Wiwiek 
Published: November 2020

Abstract
Poverty is a problems faced by developing countries, as well as Indonesia. According to data from the Central Statistics Agency in 2018, more than half the distribution of the poor population in Indonesia is in Java, which is 13,340.15 million people. Somokerto village is one of the villages in the district of Magelang, Central Java, which receives government assistance in an effort to reduce poverty. But in the process of classifying citizens who are entitled to receive assistance is still done manually. Manual classification is considered inaccurate in obtaining the results of social assistance recipients. In overcoming this problem, we need a systematic calculation to get accurate results. In this case, the researcher uses data mining classification calculation by comparing 2 calculation methods, namely K-NN and Naïve Bayes. The reseachers use Rapidminer tools. The research stages are identification of problems, data collection, implementation K-NN, Implementation Naive bayes, data testing process to produce accuracy and compare the result. The results obtained are the accuracy of Naïve Bayes higher than K-NN, namely Naïve Bayes 89.04% and K-NN 87.67%. This figure is classified in the category of good classification. From the results of the study it can be concluded the Naïve Bayes algorithm is suitable to be applied in the calculation of recipients of social assistance.
The Influence of “Check The Risk of Contracting Coronavirus” Application Quality from Alodokter on The Benefits Gained by Users, to get COVID-19 Early Detection
Authors: Firizkiansah A , Kriswantara B , Riana D , Widayanto A , Akbar F , Budi E S 
Published: November 2020

Abstract
This research uses the IS Success Model DeLone and McLean approach to finding the relationship that occurs between the quality of the Alodokter application to check the risk of contracting coronavirus. This research also tries to figure out how much benefit users have gained in conducting early detection of COVID-19. This Model uses six interrelated variables, including system quality, information quality, service quality, usage, user satisfaction, and clean benefits. With 200 respondents, data analysis uses the partial least square structural equation model (PLS-SEM) method with SmartPLS 3.0 software. This research gives the results that the better the quality of information and services of the Alodokter application, the more benefits gained by the user. However, the system quality factor from the Alodokter application does not affect how much benefits a user gains while they use the app.
E-Wallet Sentiment Analysis Using Naïve Bayes and Support Vector Machine Algorithm
Authors: Kristiyanti Dinar Ajeng , Putri Dwi Andini , Indrayuni Elly , Nurhadi Acmad , Umam Akhmad Hairul 
Published: November 2020

Abstract
Nowadays most of consumers in urban areas are accustomed to using digital wallets. The habit of transaction in cashless has been widely applied to the transportation system, restaurants and shops in the mall or supermarket. Apart of the ease of conducting transactions, various promotions in the form of points and cashback offered from various digital wallet application developers or e-wallets have become very attractive to users. One of the most widely used e-wallets by the public is OVO and DANA. This phenomena encourages researchers to do a research and make it as an object of study due to both are widely discussed by various groups, especially in the capital of Jakarta lately. As it is used, many customers write product and service reviews based on their experience on the Google Play store. Sentiment analysis is a technique that can find the right solution in creating a system that can automatically analyse these reviews and extract information that is most relevant to users. Researchers collected OVO and DANA review data on the Google Play store with a total of 2000 datasets. In this study, researchers compared the two algorithms namely Naïve Bayes and Support Vector Machine (SVM). The stages carried out in this study are data collection, initial data processing, modelling with the chosen method, experimental & model testing as well as evaluation and validation of result. Evaluation is carried out using 10 Fold Cross Validation. The result showed that OVO is the most popular e-wallet application by the public with an accuracy measurement using the Confusion Matrix reaching 91.00% for the SVM algorithm. The ROC curve showed the best AUC result of 0.986 (Excellent Classification).
The Classification Of Monster And Williams Pear Varieties Using K-Means Clustering And K-Nearest Neighbor (KNN) Algorithm
Authors: Indarti  , Indriyani Novita , Budi Arief Setya , Laraswati Dewi , Yusnaeni Wina , Hidayat Arief 
Published: November 2020

Abstract
Pear is a kind of fruits which has a lot of varieties. One of the way to differ pear varieties is by looking at the color, size and shape. This research is aimed at giving assistance to classify two varieties of pear i.e. Monster Pear and Williams Pear. In order to get the purpose, pear image processing is done to ease the classification process of pear varieties. Research method used consists of RGB Color Room to l*a*b, image segmentation, characteristics extraction with K-Means Clustering. Besides, K-Nearest Neighbor (KNN) is used to know the distribution and the classification. The use of practice data will increase the accuracy of pear varieties classification. The data used here are 88 pear images which cover 44 image practice data of Monster pear and 44 image practice data of Williams pear. Meanwhile, the test data taken are 10 images of each variety. The result of this research shows that the pear classification accuracy level is 95% which is very good.
Implementation Face Recognition Attendance Monitoring System for Lab Surveillance with Hash Encryption
Authors: Hamami F , Dahlan I A , Prakosa S W , Somantri K F 
Published: November 2020

Abstract
Face recognition (FR) is becoming popular to identify people. In fact, using the FR scheme, surveillance tasks can be built by recognizing people from their faces. This paper presents the implementation of face recognition as a biometric method for smart attendance as well as we also proposed the integrated scheme from capturing data from edge devices (CCTVs), streaming data to the dedicated server, then presenting the real-time data through android mobile devices. In this scheme, we proposed to employ deep learning algorithms based on the Convolutional Neural Network (CNN). Through the CCTV data streaming, faces are captured and matched with the database. Therefore, it is considered as their logging attendance. Furthermore, it is marked and stored into the database. This system prototype is developed by big data technology to tackle this complexity of data. The recognized faces can be monitored in real time monitoring. Eventually, real time reports are delivered through the web and android device with API after the data transmission is secured with hash encryption.
Performance Comparison and Optimized Algorithm Classification
Authors: Saputra Dedi , Dharmawan Weishky Steven , Wahyudi Mochamad , Irmayani Windi , Sidauruk Juniato , Martias  
Published: November 2020

Abstract
The current development of technology is quite rapidly not disengaged in a large data processor covering of all areas such as information technology, computer science, medicine, finance and other. This brings a large computing effect in identifying the processing of data. In data analysis for very large data, data processing is very much needed, in this study the authors propose data mining method as a solution to a large data processing problem, data mining is divided into several techniques including classification method techniques that aims to classify large amounts of data to be relevant data information. In this study the authors compared 5 algorithms in the classification method to get better performance in classification problems. Researchers analyze and test 5 Algorithm classifications with 4 different datasets as a tool in the problem of large data classification. The results of this research show the method SVM is much better to be used 4 comparison methods in calculating the value of AUC by using 4 datasets of UCI Repository. The LSVT Dataset shows the highest AUC value with 0973, Ionsphere 0887, Sonar 0897, Heartstatlog 0868.
Sentiment Analysis of Online Transportation Service using the Naïve Bayes Methods
Authors: Tika Adilah M , Supendar Hendra , Ningsih Rahayu , Muryani Sri , Solecha Kusmayanti 
Published: November 2020

Abstract
Sentiment analysis is a computational study of opinions and emotions expressed textually. Sentiment analysis will group text in sentences or documents to find out the opinions expressed in the sentence or document, whether negative or positive. This sentiment analysis research was conducted on the online taxi transportation service. Gojek uses a lot of social media to communicate with its customers, one of the social media used is Instagram. This research takes 1000 comments from the Instagram of the Gojek page which is used to see the public opinion of the online Gojek transportation services. Comments from the page are processed by doing text preprocessing and then classified using the Naive Bayes Classifier (NBC) method to obtain the value of the public value for online transportation services. The results of this study using the Naive Bayes method resulted in an accuracy value of 81.00%, which means that from all the comments on the Instagram page, the subject of the NBC method could be accurately classified by 81.00% whether the comments were negative or positive comments.