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Determining the Eligibility of Providing Motorized Vehicle Loans by Using the Logistic Regression, Naive Bayes and Decission Tree (C4.5) 1

Determining the Eligibility of Providing Motorized Vehicle L...

引用

1st International Conference on Advanced Information Scientific Development, ICAISD 2020

作者： Rianto, Harsih Amrin Rudianto Pahlevi, Omar Kusumawardhani, Paramita Hadi, Seno Sudarmono Program Studi Sistem Informasi Fakultas Teknik Dan Informatika Universitas Bina Sarana Informatika Jl. Kramat Raya No. 98 Jakarta Indonesia

Evaluating in determining the eligibility of giving credit is very important. Errors in providing credit worthiness assessments can result a bad credit risk. The problem that often occurs is not the application of the system by financial parties but more on HR when making predictions about the determination of consumer credit worthiness. Research in the field of computers has been done toreduce credit risk resulting in losses to the company. In this research a comparison of Logistic Regression (LR), Naïve Bayes (NB) and Decision Tree (C4.5) algorithms is performed to predict the feasibility of granting credit. In order to produce a prediction of the feasibility of granting credit to new consumers, credit data used by the company is used. The data used in this study consists of 481 consumer records that have been classified as consumers with current credit and bad credit. After testing using the same dataset on the three algorithms by comparing the AUC and Confusion Matrix values, it was found that the appropriate algorithm to be applied to the credit worthiness dataset was Logistic Regression with an Area Under Curve (AUC) value of 0.972 and Accuracy or Confusion Matrix of 93.14%. As for the Decision Tree Algorithm (C4.5) from the test results, the AUC value is 0.926 and the Accuracy is 90.85% and the Algortima Naïve Bayes AUC value is 0.905 and the Accuracy is 82.75%. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Decision trees

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Enhancing Larval Classification Accuracy Through Hyperparameter Optimization in ResNet50 with Three Different Optimizers

Enhancing Larval Classification Accuracy Through Hyperparame...

引用

2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Rujito Muhathir Khairina, Nurul Ilhadi, Veri Ula, Mutammimul Sahputra, Ilham Fakultas Teknik Program Studi Teknik Informatika Universitas Medan Area Medan Indonesia Universitas Medan Area Fakultas Teknik Prodi Teknik Informatika Medan Indonesia Universitas Malikussaleh Fakultas Teknik Program Studi Sistem Informasi Aceh Indonesia

ISBN: (纸本)9798350369359

Recent research has explored the application of deep learning models in the classification of Zophobas Morio and Tenebrio Molitor larvae, focusing on optimizing the choice of optimizer. This study aimed to investigate and compare the performance of the ResNet50 model using three different optimizers (Adam, Nadam, and Adagrad) for accurate classification of these larvae. We conducted an experimental study, training and evaluating the R model on a dataset of Zophobas Morio and Tenebrio Molitor larvae images using the mentioned optimizers. This study followed a quantitative approach to assess model performance. Our findings indicated that the Adam optimizer yielded the highest accuracy (approximately 97.1%), outperforming Nadam and Adagrad. However, recognizing Tenebrio Molitor still presented challenges, highlighting room for improvement. The results suggest that the choice of optimizer significantly influences the model's performance in larva classification. While Adam showed promising results, further enhancements are needed for accurate Tenebrio Molitor recognition. Future research should explore different deep learning architectures and larger datasets for improved classification outcomes. © 2023 IEEE.

关键词： Classification (of information)

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The Analysis of Digital Provider Sentiment of 'by.u' on Google Play Which Uses the Support Vector Machine (SVM) Method 1

The Analysis of Digital Provider Sentiment of 'by.u' on Goog...

引用

1st International Conference on Advanced Information Scientific Development, ICAISD 2020

作者： Ardiansyah, Angga Aji, Sopian Pratmanto, Dany Kuryanti, Sandra Jamu Putra, Octa Pratama Adiwihardja, Cep Program Studi Sistem Informasi STMIK Nusa Mandiri Jakarta Universitas Bina Sarana Informatika Indonesia

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 © 2020 Published under licence by IOP Publishing Ltd.

关键词： Support vector machines

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Electricity Smart Meter Payment System Through Payment Gateway and User Interface Design 15

Electricity Smart Meter Payment System Through Payment Gatew...

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15th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2021

作者： Adiono, Trio Daud, Alija Rasyidi Institut Teknologi Bandung Program Studi Teknik Elektro Sekolah Teknik Elektro Dan Informatika Bandung Indonesia

ISBN: (纸本)9781665428927

The electricity smart meter is an Internet-of- Things (IoT) based intelligent electricity metering device. This device has a two-way data communication system connected to the internet using LoRA® technology so that electrical data can be accessed digitally. One of the main features of a digital electricity meter is the addition of electricity credits and payment through a payment gateway, so that users can top-up through payments at supermarkets, internet banking, or digital wallets. In addition, data on electricity meter usage can be accessed through an interface system by both operators and customers. In this system, a data communication system architecture on a digital electricity meter is made, which includes a database, protocol, server, so that it allows customers to access payments through payment gateways. Customers can also access electricity meter data, electricity meter control, notifications, through the provided interface. The results of the implementation of the payment gateway feature and data access through the interface went well as expected. © 2021 IEEE.

关键词： User interfaces

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Analyzing the Effectiveness of VGG Deep Learning Architecture for Mushroom Type Classification 7

Analyzing the Effectiveness of VGG Deep Learning Architectur...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Syuhada, Rahmad Muhathir Khairina, Nurul Muliono, Rizki Susilawati Sembiring, Zulfikar Fakultas Teknik Program Studi Teknik Informatika Universitas Medan Area Medan Indonesia Fakultas Teknik Prodi Teknik Informatika Universitas Medan Area Medan Indonesia

ISBN: (纸本)9798350360752

Indonesia is a center of biodiversity, one of the diversity of plant species is mushrooms. Fungi are very simple plants, have nuclei, spores, without chlorophyll, in the form of cells or branching filaments with walls of cellulose or chitin or both. Identification of mushrooms is still difficult due to the large number of types of mushrooms, lack of knowledge about mushrooms, and lack of experts in the mushroom field. Additionally, most mushrooms have a high degree of similarity in certain characteristics, making it difficult for unskilled humans to visually identify the type of mushroom. Therefore, it is important to be able to classify the types of mushrooms so that the public will better understand the types of each mushroom. This research uses a transfer learning approach with the VGG-19 architecture to provide an accurate method for classifying fungal species. There are 4 model scenarios that are trained and the best model performance is obtained using hyperparameter number of epochs 50, batch size 64, and the SGD optimizer gets an accuracy of 77.3% in the training process. After testing using data testing and evaluating using a confusion matrix and classification report, an accuracy score of 70% was obtained © 2023 IEEE.

关键词： Biodiversity

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An android-based application to predict student with extraordinary academic achievement 1

An android-based application to predict student with extraor...

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1st International Conference on Innovation in Research, ICIIR 2018

作者： Sudipa, I.G.I. Wijaya, I.N.S.W. Radhitya, M.L. Mahawan, I.M.A. Arsana, I.N.A. Program Studi Teknik Informatika STMIK STIKOM Indonesia Jl. Tukad Pakerisan No.97 Bali Indonesia

The study period of students who pass the time limit and high numbers of dropout in a college can affect the value of campus accreditation. The anticipation of that possibility, the college must make predictions about potential students don't graduate on time. This study aims to build a system capable of predicting students who have the potential. If students with unpredictable graduation risks can be identified in the early stages, then the indication of dropout rates may be reduced by providing special appeals to students at risk. Prediction analysis applies the K-Nearest Neighbors method to dig up the trace data stack and look for the proximity of the data with the new data. The test data used student class of 2011 with 100 students as sample data. This method of classification is based on several attributes, namely the evaluation of the 1st semester to semester 6th, the number of GPA, credits that have been taken each semester, number of credits passed, and the number of credits that didn't pass. The result of classification becomes the output of the system which is then entered into the testing phase. This stage compares the output with the original data with 70, 73% accuration result. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Students

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Classification of Mango Leaf Diseases Using XGBoost Method and HoG Feature Extraction

Classification of Mango Leaf Diseases Using XGBoost Method a...

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2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Suprayoga, Rizky Zega, Suparsianto Muhathir Mardiana, Siti Universitas Medan Area Fakultas Teknik Program Studi Teknik Informatika Medan Indonesia Universitas Medan Area Fakultas Sains Dan Teknologi Program Studi Biologi Medan Indonesia

ISBN: (纸本)9798350369359

Mango (Mangifera indica L.;Anacardiaceae) is a globally significant tropical fruit, renowned for its unique flavor and rich nutritional value. With over 90 countries engaged in mango cultivation, Asia stands out as the primary producer, contributing approximately 75% to the world's mango production. However, mango cultivation faces substantial threats from fungal diseases, affecting fruit quality and yield, particularly in countries heavily reliant on agriculture, like Indonesia. This study aims to classify mango leaf diseases through the analysis of leaf images using the XGBoost method. Additionally, we evaluate the XGBoost-based classification approach with the assistance of HoG feature extraction. The study contributes to the identification of mango leaf diseases by analyzing relevant leaf image features. We conducted a quantitative study, utilizing image processing and computer vision techniques for disease identification. The XGBoost algorithm was employed for classification, with feature extraction carried out using the Histogram of Oriented Gradients (HoG) technique. The research resulted in a successful classification of mango leaf diseases, demonstrating the effectiveness of the XGBoost algorithm when combined with HoG feature extraction. The study achieved a significant level of accuracy in disease classification. The findings indicate the potential of the XGBoost algorithm combined with HoG feature extraction for mango leaf disease classification. While the study achieved its primary objectives, further research can explore the optimization of this method and its application in practical agricultural settings to enhance disease management and mango production. © 2023 IEEE.

关键词： Feature extraction

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The use of User-centered Design Canvas for Rapid Prototyping 1

The use of User-centered Design Canvas for Rapid Prototyping

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1st Paris Van Java International Seminar on Computer, Science, Engineering, and Technology, PVJ ISComSET 2020

作者： Kautsar, Irwan Alnarus Ruslianor Maika, M. Program Studi Informatika Fakultas Sains Dan Teknologi Universitas Muhammadiyah Sidoarjo Indonesia Program Studi Perbankan Syariah Fakultas Agama Islam Universitas Muhammadiyah Sidoarjo Indonesia

This paper presents the use of User-Centered Design Canvas to help students design the user experience (UX) on the designated Collaborative Projects. The Collaborative Project itself has been conducted by students with multi-discipline backgrounds. The User-Centered design itself was widely used as an approach to software development in order to achieve better alignment between the user experience and the business goal. Adopting Business Model Canvas, the User-Centered Design Canvas was introduced as an acceleration tool for rapid prototyping and ensures the effectiveness and efficient manner for the sake of user satisfaction. As the results from the questionnaire, more than 78% of users express the benefits of the current adaptation of User-Centered Design Canvas. Also from the Log Metric Analysis, users2 have completed a designated task under 5 minutes with minimum repetition. This indicates that the use of proposed adaptation is easy to use and shows the effectiveness of the User-Centered Design Canvas for rapid prototyping. © Published under licence by IOP Publishing Ltd.

关键词： User centered design

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Selection of Prospective Employees Using Analytical Hierarchy Process (AHP) and ISO 9126 1

Selection of Prospective Employees Using Analytical Hierarch...

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1st International Conference on Applied Information Technology and Innovation, ICAITI 2018

作者： Mujito Prasetyo, Basuki Hari Subandi Anubhakti, Dian Widjaja, Ady Program Studi Teknik Informatika Fakultas Teknologi Informasi Jakarta Selatan DKI Universitas Budi Luhur Jakarta Indonesia

ISBN: (纸本)9781538667262

Resources Management is one of the important aspects to determine the success of work at company. To get qualified human resources, the company applies a tight selection of employee acceptance to job applicants to fit the company's needs for checking and selection process is done manually by looking at one by one file submitted by applicants. This is of course in addition to very inconvenient also inefficient and takes a long time, not to mention the possibility of human error and subjective assessment so that the candidate is not the best candidate. By utilizing a Decision Support System that uses Analytical Hierarchy Process (AHP) Algorithm to help employee acceptance selection problem, Analytical Hierarchy Process (AHP) is a decision-making process using Pairwise Comparisons to explain the evaluation factor and weight factor under conditions multi factor. ISO 9126 is an international standard issued by ISO for software quality evaluation and Capability Testing of Employee Selection Model Using Analytical Hierarchy Process (AHP) adopted on ISO 9126 test model with Functionality, Reliability, Usability and Efficiency criteria. So, the result of this research is an application or decision support system that generates the output of a ranking of each prospective employee, so that the management decision makers can see the ability of each prospective employee based on the ranking. © 2018 IEEE.

关键词： Decision support systems

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Build sorghum database for developing SEU digital network on sorghum website of Wijaya Kusuma Surabaya University 3

Build sorghum database for developing SEU digital network on...

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3rd Annual Applied Science and Engineering Conference, AASEC 2018

作者： Widiartin, T. Noerhartati, E. Fakultas Teknik Program Studi Teknik Informatika Universitas Wijaya Kusuma Surabaya Indonesia Fakultas Teknik Program Studi Teknologi Ilmu Pertanian Universitas Wijaya Kusuma Surabaya Indonesia

As the center of the sorghum entrepreneur, Wijaya Kusuma Surabaya University has many units of sorghum entrepreneurs is named SEU (Shorgum Enterpreneurship Unit). Each SEU has a variety of activities. The production of processed sorghum is unique. Therefore, need to build an SEU network. This research will be build a digital SEU network. In order that as a center of entrepreneur sorghum, Wijaya Kusuma University Surabaya is able to monitor and evaluate activity and sorghum products of SEU. There are 7 stages done in this research. First, activity for analysis of data needs, process needs, and information needs analysis in conducting monitoring and evaluation activities in SEU. Second, data flow analysis activities that occur in the process of monitoring and evaluation of activities in the SEU. Third, activity of storage analysis to store the data and information. Fourth, design of the entity relationship diagram of the database. Fifth, transformation activity on Entity Relationship Diagram to generate Entity Relationship Schema for the database. Sixth, create the Database Sorghum Script using Structured Query Language. Seventh, testing of database engine using MySQL. © Published under licence by IOP Publishing Ltd.

关键词： Data flow analysis

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