bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Decision Tree with PSO on Sharia Cooperative Customer Funding
Authors: Rahmawati Eka , Agustina Candra 
Published: November 2020

Abstract
Credit is a service for Sharia Cooperatives to provide funding to customers who are paid in installments. The accuracy of the customer paying the payments is a determining factor for the smooth operation of the Sharia Cooperative. In addition to timeliness, the ability of customers to pay installments is also the most critical factor for credit returns. Bad credit is a significant threat for Sharia Cooperatives where customers cannot pay payments according to agreed agreements. That makes the prediction of the smooth operation of Sharia Cooperative customers needed. One way that can be done to make predictions is to apply data mining techniques. To make a prediction, several attributes of the customer are used, such as gender, age, status, residency status, number of dependents owned, education, employment, remittance, ceiling, type of loan, credit period, method of payment and collat- eral used. The research will use the J48 as one of the Decision Tree algorithms with particle swarm optimization techniques to improve algorithm performance. The accuracy of J48 with PSO is lower than without PSO.
Feature Dependent Naïve Bayes For Network Intrusion Detection System
Authors: Rahayuningsih Panny Agustia , Maulana Reza , Irmayani Windi , Saputra Dedi , Purwaningtias Deasy 
Published: November 2020

Abstract
The intrusion detection system is an important component that performs the analysis for. the problem arising from the IDS is a collection of data sets in a computer network. to increase the high level and low false positive level of approach with the learning machine in applied. The data mining algorithm used is Naïve bayes one of the most widely used algorithms in space due to its simplicity, efficiency and effectiveness. NB has high accuracy and speed when applied into the database with large data. However, the NB algorithm assumes independent attributes (free) and is very sensitive to the selection of many features that interfere with the performance or accuracy of the NB to be low but in practice, the possibilities of the feature are interrelated. The Feature Dependent Naïve Bayes (FDNB) method is an effective method used to solve existing problems in NB by computing features as pairs and creating dependencies between each other as well as by applying learning models implemented to cross-validation, Feature Selection and data steps preprocessing that gives better accuracy results. After testing with two models of Naïve bayes and FDNB, the results obtained from the Naïve Bayes algorithm resulted in an accuracy of 84.42%, while for FDNB and oversampling (CFS + GS) the accuracy was 94.58%, FDNB and oversampling (CFS + BFS) the accuracy value of 94.69%, FDNB and SMOTE (CFS + GS) and FDNB and SMOTE (CFS + BFS) has an accuracy value of 93.27%. For the average per attack type DOS attack shows the highest result for its accuracy value of 97.86% and U2R attack produces the best accuracy when classifying U2R with 93.80% accuracy, U-F size of 96.26% U2R can be considered as a very result nice. Because U2R attack is considered very dangerous.
Development of Fuzzy Analytic Hierarchy Process(F-AHP) For The Selection Of Alternative New Product Development Ideas In Coconut Downstream Agroindustry
Authors: Wardah S , Baidawi T 
Published: November 2020

Abstract
Downstream coconut agro-industry can increase added value, strengthen industrial structure, grow industrial population, provide employment, create business opportunities, and improve the national economy. The low level of downstream coconut agro-industry is due to the low development of new products that are key to long-term agro-industry. One important success step in developing new products is making the right decision in choosing a new product development idea. The choice of ideas is important to reduce risk in various uncertainties and market conditions. Based on this, this research aims to develop the Fuzzy Analytic Hierarchy Process (F-AHP) method for selecting the right idea to develop new products so that the downstream coconut agro-industry can develop. To achieve this goal, we use the F-AHP approach with an expert confidence level of 0.5. From this approach, the results are obtained that the critical criteria are product specificity, product superiority, product safety, product demand trends, the number of similar industries at the national level and the number of similar industries at the international level with alternative ideas for new product development are coconut meat, coconut shell coconut water towards the food industry and coconut fiber towards the transportation industry.
Public Acceptance Of Pedulilindungi Application In The Acceleration Of Corona Virus (Covid-19) Handling
Authors: Kurniawati  , Khadapi M , Riana D , Arfian A , Rahmawati E , Heriyanto  
Published: November 2020

Abstract
Coronavirus Disease (COVID 19) is a subject of ongoing scientific discussion in Indonesia and the world, COVID-19 confirmed cases continue to grow in Indonesia, this is influenced by the factor of the lack of more knowledge and awareness that some people have for the disease. Application PeduliLindungi was made by the Ministry of Communication and Information together with several state-owned agencies and Badan Usaha Milik Negara (BUMN) aimed at helping government agencies break the chain of transmission of COVID-19. Sample data from Technology Acceptance Model (TAM) is used to check the acceptance of the use of the application PeduliLindungi from 115 active respondents spread across Indonesia for analysis using SmartPLS. The analysis shows that the ease of use of the PeduliLindungi application greatly influences the usability and attitude in using it. The attitude in the use and usefulness of application PediliLindungi greatly influences the intention to use it. The use of the application PeduliLindungi has very little effect on the attitude to use it. In Conclusion the use of the applaication PeduliLindungi will increase because of the ease of use, it also indicates the level of acceptance of the application
Mobile-Assisted Language Learning (MALL): Students’ Perception and Problems towards Mobile Learning in English Language
Authors: Nuraeni Cicih , Carolina Irmawati , Supriyatna Adi , Widiati Wina , Bahri Syamsul 
Published: November 2020

Abstract
Mobile-Assisted Language Learning (MALL) is the latest learning way in the language education where applications or websites are used to facilitate students learning activities. Mobile phone has been studied years by researchers in its connection with education-related activities. This research will focus on its main purposes, they are: 1) students’ perceptions in using mobile phone in English language learning classroom activities; 2). the problem of using mobile phone to support classroom activities, especially in English language learning. The method of the research was quantitative method which used 70 students as research object. The data were collected through a 5-point Likert Scale questionnaire. The research found; first, the students’ majority had positive perception on the usage of MALL to support classroom activities, especially in learning English language. Second, the problem in internet connectivity is the biggest problems that students faced in terms of using MALL in English language classroom. But, It is hoped that MALL will be used as one of the teaching aids that could assist students in learning English as a Foreign Language (EFL) more effectively.
User Satisfaction Analysis of Pikobar Covid19 Website Using the Webqual Method
Authors: Ismunandar Dinar , Yanto  , Riana Dwiza , Fatmawati  , Hertyana Hylenarti , Triantori Vito 
Published: November 2020

Abstract
The PIKOBAR website is used as a place for public information in the form of data distribution of covid-19 sufferers that occurred in West Java. In this study, the quality of the PIKOBAR website is measured using the Webqual method as a measurement tool for website system development, where there are variables consisting of assessing the quality of usability, information quality, service interaction quality and interface quality. In determining the results of the four variables, SmartPLS is used to determine the effect of these variables on respondent satisfaction. Data obtained in this study were obtained from questionnaire processing as many as 120 respondents. The results obtained in this study include (1) quality of usability does not have a positive and significant effect on website user satisfaction, (2) the quality of information that is positive and significant for website user satisfaction, (3) the quality of service interactions has a positive and significant impact on website user satisfaction, and (4) quality of interface has a positive and significant effect on website user satisfaction. These results indicate that the quality of information, the quality of service interactions and the quality of the interface have a positive influence on PIKOBAR website users.
Teacher Attendance Monitoring System Teaching with QR-Code and Geo Location using Android Platform
Authors: Amirulloh I , Iskandar I d , Apriyani Y , Warnilah A I , Purnia D S , Surahman M 
Published: November 2020

Abstract
The world of education has a good level of reputation if it has a professional educator staff and with high integrity, one of the examples is that educators must be hardened on time and not truant to teach students at school. So that the stigma of students and the community does not give a negative value. The role of the principal is also very important to build high integrity, a principal must always monitor every day the teachers who enter the class. But the limitations and the many teaching hours of teachers that must be monitored make the principal difficult because of limited time and other busyness. So the need to design and build an Android platform-based application that is intended to monitor the schedule, and the presence of teachers in real-time called Teacher Attendance Monitoring System Teaching with QR-Code and Geo-Location. SoftwareThe software is intended to make it easier for principals to monitor teachers who teach in class in realtime. Black box testing results show 100% for functional testing of systems and for testing the application interface has a 100% success rate. Then the software is feasible to use.
Neural network parameters optimization with genetic algorithm to improve liver disease estimation
Authors: Harafani H , Suryani I , Ispandi  , Lutfiyana N 
Published: November 2020

Abstract
Liver disease is an important public health problem. Over the past view decades machine learning has develop rapidly, and it has been introduced for application in medical-related fields. In this study we use neural network method to solve regression task of liver disorder dataset. Genetic algorithm applied for optimize NN parameters to improve the estimation performance value. NN-GA performance results show the most superior value compared to another methods.
The Influence of Pikobar Application in Suppressing the Rate of Coronavirus Spread
Authors: Wicaksono Bagus Dwi , Indrawan Dwin , Riana Dwiza , Taufik Andi , Nuryamin Yamin , Wasesha Dian Ambar 
Published: November 2020

Abstract
Coronavirus has developed massively in Indonesia, in the face of Coronavirus, Indonesian people are required to be able to survive the outbreak, by not interacting directly between people. Pikobar is one of the applications on a smartphone (android), which can provide up-to-date information about the development of the coronavirus in Indonesia (especially in West Java), which allows people to receive that information without having to do physical interaction between communities. To find out the level of customer satisfaction in using the pikobar application, the TAM method is used. the data collected was obtained from the results of a survey of the Indonesian population. The survey results were processed using smartPLS. From the results of the study showed if perceived ease of use of the application greatly influenced the community to use the pikobar application, so that the public could use the application in accordance with the application’s purpose, namely to reduce the rate of coronavirus spread.
Implementation Of The Lab Rotation Model In Blended Learning Based On Student Perspectives
Authors: Adiwisastra Miftah Farid , Mulyani Yani Sri , Alawiyah Tuti , Wibisono Taufik , Iskandar Iqbal Dzulfikar , Purnia Dini Silvi 
Published: November 2020

Abstract
The use of digital technology requires the world of education to transform digital so that students are increasingly in demand. One of them is Islamic Boarding School education which metamorphoses by providing education that is not only oriented towards religious knowledge but broader in the mission of improving the quality of human resources to be able to face a wider real life in accordance with challenges of the times. Various learning methods are applied in order to be able to balance and develop. One of them is the use of the Blended learning method, which is a learning method that combines technology-based learning and information with classroom or face-to-face learning. Combining learning or combining face-to-face, distance learning, and e learning. To implement the method, a study was conducted at the Darul Muta’allimin Islamic Boarding School Middle School to see students’ perceptions. The blended learning model used is the lab rotation model. The results of research students’ perceptions of learning using the blended learning method get a positive response with a value of 65% agree because it provides motivation for students to study hard and is very helpful in learning and the material provided is easy to understand.
Approval of Sharia Cooperative Customer Financing Using PSO-Based SVM Classification Algorithm
Authors: Nurajijah  , Amsury Fachri , Saputra Irwansyah , Frieyadie  , Sulistyowati Daning Nur , Rifai Bakhtiar 
Published: November 2020

Abstract
Credit financing approval is an important task for financial institutions. The accuracy of decision making in accepting or rejecting credit applications must be precise and accurate. Data mining techniques can help credit approval with a smaller risk of error. Previous research has been carried out to classify customer loan history data with the highest accuracy obtained by the Support Vector Machine (SVM) algorithm. This study aims to improve the accuracy of previous research in classifying loan history data based on smooth and stuck credit labels to predict credible prospective customers. The algorithm used in managing the data is Support Vector Machine with Particle Swarm Optimization (PSO). The dataset used was 869 records from January 2015 to September 2018, labeled 291 records and 578 records smoothly. The results of the study proved that the Support Vector Machine algorithm based on Particle Swarm Optimization produced the best performance with an accuracy of 90.91% compared to SVM without PSO of 89.86%.
Measuring The Quality of Website Services covid19.kalbarprov.go.id Using The Webqual 4.0 Method
Authors: Handayani Kartika , Juningsih Eka Herdit , Riana Dwiza , Hadianti Sri , Rifai Achmad , Serli Rosi Kusuma 
Published: November 2020

AbstractWebsite covid19.kalbarprov.go.id is a website that serves as a medium for spreading information about the spread of the coronavirus in West Kalimantan. Currently, the number of covid19.kalbarprov.go.id website users is very large because many people want to know the latest information about the coronavirus in the West Kalimantan region. Therefore it is necessary to measure the level of user satisfaction on the site covid19.kalbarprov.go.id. The purpose of this study is to determine the level of user satisfaction with website services using the Webqual 4.0 method. Webqual is one method of measuring website quality based on the perception of end-users. Webqual variables are usability, information quality, service interaction quality, and user satisfaction. In processing research data using the smartPLS application to determine the level of validity and reliability of the data obtained. The results showed that usability, information quality, and service interaction had a positive effect on User Satisfaction. So it can be concluded that the quality of usability, quality of information, and quality of service interaction affect the satisfaction of website users covid19.kalbarprov.go.id.
Utilization of Information System in Electrical Panel Project Management to Provide Various Facility in Project Implementation
Authors: Soleh Oleh , Rosdiana  , Dewi Meta Amalya , Ningsih Yosi Fitria 
Published: November 2020

Abstract
The development of technology, especially in the field of information and communication from year to year plays an important role in human life. At present many projects specifically deal with work in the field of information technology. Project management is a scientific discipline in terms of planning, organizing, managing, to be able to achieve project objectives. For a small company that is just running a business, a system that can do the processing of a project is needed. Usually the data processing and project control processes still use manual paperwork and result in not requiring a lot of time so that it impacts on the preparation of project reports. The existence of a project management system can make it easier to make reports on the results of ongoing projects. The research method used consisted of; data collection methods, namely: interviews, observation, and literature study. For analysis using the BSC (Balanced Scorecard) analysis method. This system is made using PHP programming language and Mysql database. The system design uses the design of the UML (Unified Modeling Language) model. The testing method used is the Black box Testing method. The results of this study are a project management application system that helps companies in terms of data management, starting from the tender project, material data, until the reports generated.
Identification of Diabetic Retinopathy with Retinal Fundus Imagery Using Probabilistic Neural Network
Authors: Elveny M , Anjulina T , Siregar B , Syah R 
Published: November 2020

Abstract
Diabetic retinopathy is a microvascular complication of diabetes mellitus that attacks blood vessels in the retina. The main characteristics of diabetic retinopathy are microaneurysm, retinal haemorrhages, exudates, and neovascularization. One of the methods used to diagnose diabetic retinopathy is by examining the retinal fundus image. The examination is still done manually by an ophthalmologist. Manual examination requires a high level or concentration and misidentification may occur because some diabetic retinopathy characteristics are difficult to see directly, so it is needed a method that can facilitate the ophthalmologist in making decisions to identify diabetic retinopathy. The method proposed in this research is Probabilistic Neural Network to identify diabetes retinopathy. Before the identification stage is carried out, the retinal image will go through the pre-processing stage in the form of resize, green channel, contrast stretching and feature extraction using the Gray Level Co-Occurrence Matrix. After testing in this research, it was concluded that the proposed method was able to identify diabetes retinopathy with an accuracy of 86.8%.
Classification of Road Surface Quality Based on SVM Method
Authors: Afenika Adhelinia , Gunawan P. H. , Tarwidi D. 
Published: November 2020

Abstract
Damaged and potholes roads can occur due to rain puddles, too many heavy vehicles, poor asphalt quality, or maybe long road life. Damaged roads can hamper activities and endanger the safety of road users. It is necessary to monitor road quality periodically which is conducted by government, so that roads improvement can be done quick as possible. The aim of this study is to build a system that can classify roads surface quality. Support Vector Machine (SVM) classifications method is used to classify roads based on roadworthiness. In this study, 300 road surface data which contains good/smooth and damage quality of road are used. The simulation results show that SVM model can classify road surface data into two classes with average accuracy of 93%. The results can be a recommendation for government to prioritize which roads need to be improved.
A New Framework of Feature Selection Approach for Sentiment Analysis
Authors: Wahyudi Mochmad , Zarlis Muhammad , Mawengkang Herman , Efendi Syahril 
Published: November 2020

Abstract
Undoubtedly that the huge business data could make data analysis becomes more complicated such that the decision-making process would be out of reach. This condition happens. In the fields of consumer buying behavior, A well-known method called sentiment analysis can help in extracting information about the up-to-date trends and is able to increase market value of product through improving its quality. One of the approaches in solving the sentiment analysis is feature selection technique. However, this technique contains a combinatorial behavior and the analysis of the huge data can experience uncertainty parameter. This paper describes a framework for solving the sentiment analysis based on feature selection approach using a stochastic combinatorial programming.
Association Rule Implementation Using Algorithm Apriori To Analize Fishing Pattern In Indonesia
Authors: Kristiana Titin , Putri Sukmawati Anggraeni , Nurmalasari  , Handayani Rani Irma , Merlina Nita , Yunita Norma 
Published: November 2020

Abstract
There are more than 80 species of fish caught by fishermen in the sea of Indonesia. To find out what kinds of fish mostly caught, it is necessary to analyse the data pattern of fish being caught. The activities of searching and associating the data pattern are closely related to data mining technique that being used to discover the rules of association of items. In this associative rule method, there are two process can be used: the process of generating frequent itemset and finding associative rules. The Frequent Itemset Generation is a process to get the connection of the itemset and the value of the association based on the value of support and confidence. The algorithm used to generate the frequent itemset is Apriori Algorithm. The Apriori Algorithm has a weakness in the extraction of the appropriate feature of the used attributes. This condition causes the rules formed in large number. This research applies Apriori Algorithm based on principal component analysis to obtain more optimal rules. After the experiments using the apriori algorithm applied with the magnitude ˚ = 30, minimum Support 80% and Confidence 80%, the result of the rule formed are totally 82 rules.
Implementation of Data Mining in Grouping Percentage of Blind Letters Age 15+ By Province Using K-Means Algorithm
Authors: Saifullah  , Hidayati Nani , Solikhun  
Published: November 2020

Abstract
Data Mining is a method that is often needed in large-scale data processing, so data mining has important access to the fields of life including industry, finance, weather, science and technology. In data mining techniques there are methods that can be used, namely classification, clustering, regression, variable selection, and market basket analysis. Illiteracy is one of the factors that hinder the quality of human resources. One of the fundamental things that must be fulfilled to improve the quality of human resources is the eradication of illiteracy among the community. The purpose of this research is to determine the clustering of illiterate communities. The results of the study are illiterate data clustering according to the age proportion of 15+, namely 1 node of the high group, the low group has 23 nodes, and the medium group of 10 nodes. The results of this study become input for the government to determine illiteracy eradication policies in Indonesia based on provinces