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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Application of the local antimagic total labeling of graphs to optimise scheduling system for an expatriate assignment 3

Application of the local antimagic total labeling of graphs ...

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3rd International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2019

作者： Utami, W. Wijaya, K. Slamin Department of Management Universitas Jember Indonesia Study Program of Informatics Universitas Jember Indonesia

An expatriate assignment at the branch company in other country must be optimised due to the short term duty. Accuracy calculation is needed to optimise the expatriate assignment including its scheduling system. There are many ways and methods to optimise the scheduling system. One of the methods is making use of graph theory instruments such as local antimagic total labeling. The local antimagic total labeling of a graph is a map from the set of vertices and edges of the graph to the set of positive integers from 1 to the number of vertices and edges such that the weight of two adjacent vertices are different. The vertex weight is calculated by adding the labels of the vertex and all edges incident to it. In this paper, this labeling is applied to optimise the scheduling system for the expatriate assignment. This system can be modelled by a graph where the assignments are represented by vertices and connection between the assignments are represented by edges. The represented graph is then labelled by the local antimagic total labeling in order to obtain the minimum number of different vertex weights. The such number is equivalent to the optimal time allocated for the expatriate assignment. © Published under licence by IOP Publishing Ltd.

关键词： Scheduling

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Influence of blended learning on learning result of algorithm and programming 3

Influence of blended learning on learning result of algorith...

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3rd International Conference on informatics and Computing, ICIC 2018

作者： Anggrawan, Anthony Ibrahim, Nurdin Suyitno, M. Satria, Christofer Informatics Engineering Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Visual Communication Design Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia

ISBN: (纸本)9781538669204

The advancement of today's learning technology makes the learning process no longer fully bases on face to face learning, but can achieve by online learning. Online learning is not only useful in overcoming deficiencies in conventional classroom learning, but also a means to meet the learning styles of students who are less fond of and/or dislike face-to-face learning. On the other hand, the main disadvantage of online learning is the lack of face-to-face interaction, while the strength of face-to-face learning is the intensity of student interaction with teachers, the ease of cooperative learning and the clarity of learning materials. In turn, the superiorities on face-to-face learning and online self-learning can be acquired by blended learning. However, blended learning is a learning solution by taking the best advantage of face-to-face classroom learning and online learning. Blended learning has been a learning solution of today's learning. In this study, two blended learning that has different learning content portions between the portion of face-to-face learning materials and online self-learning was conducted to find out which blended learning results produce better pedagogy between two blended learning, and how well the learning outcomes of blended learning are, especially for Algorithm and programming subject. The research results showed the blended learning with 60% face-to-face learning content and 40% online self-learning content delivers learning cognitive competency outcomes worse than 40% face-to-face learning content and 60% online self-learning content. The learning outcome of both blended learning is good, that is greater than 60% from the ideal number. © 2018 IEEE.

关键词： Students

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The Improvement of Personal Service in the MSMEs Marketplace Using a Rank-Based Collaborative Filtering Approach

The Improvement of Personal Service in the MSMEs Marketplace...

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2022 International Conference on Electrical and Information Technology, IEIT 2022

作者： Lestari, Sri Yulmaini Aswin Sulyono Nul Fikri, Ruki Rizal Pratama, Yan Aditiya Informatics Engineering Study Program Faculty of Computer Science Lampung Bandar Indonesia Management Study Program Faculty of Business Economics Lampung Bandar Indonesia

ISBN: (数字)9781665453035

ISBN: (纸本)9781665453035

Indonesian MSMEs in 2022 will begin to enter the transformational recovery phase. Various preparations must be made in order to adapt. One that has been done is to increase the number of MSMEs entering the digital ecosystem, such as the MSME marketplace. The MSME Marketplace is used for marketing various MSME products online. The MSME Marketplace must be supported by methods that are able to provide good and fast personal services, considering the types and variety of products offered are increasing in number and varying from time to time. Therefore, this study proposes the Porat_Rank method to produce product recommendations that match user interests quickly so that users are served well. The experimental results show that the Porat_Rank method is superior to the Copelan Score method both in producing recommendations and in processing speed. © 2022 IEEE.

关键词： Collaborative filtering

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The Recommendation System for Increasing the Independence of Micro, Small and Medium Enterprises (MSMEs) Using the Normalized Rating Frequency (NRF) Method 4

The Recommendation System for Increasing the Independence of...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Lestari, Sri Yulmaini Aswin Kurniawan, Rio Sulyono Pratama, Yan Aditiya Faculty of Computer Science Informatics Engineering Study Program Bandar Lampung Indonesia Faculty of Business Economics Management Study Program Bandar Lampung Indonesia

ISBN: (纸本)9781665433945

Micro, Small, and Medium Enterprises (MSMEs) have an important role in improving the economy of small communities and the stability of the Indonesian economy. However, they still face various problems such as capital, raw materials, distribution, licensing, and others. This study developed a special treatment recommendation system to increase the independence of MSMEs by adopting a ranking-based method to produce recommendations related to problem-solving steps from MSMEs. The ranking method used Normalized Rating Frequency (NRF). This method performed an aggregation process of the ratings given by MSMEs in looking at the priority level of problem-solving based on previous experience. The result of the experiment showed that an average NDCG value was 0.7916. This explained that the quality of the ranking was good so that it was feasible to be recommended in solving problems in the form of special treatment to acquire to the independence of MSMEs. © 2021 IEEE

关键词： Recommender systems

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Artificial Intelligence-Based System 'SiMoniK' for MSMEs 9

Artificial Intelligence-Based System 'SiMoniK' for MSMEs

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9th IEEE Information Technology International Seminar, ITIS 2023

作者： Lestari, Sri Yulmaini Aswin Sulyono Nul Fikri, Ruki Rizal Informatics Engineering Study Program Faculty of Computer Science Bandar Lampung Indonesia Management Study Program Faculty of Economics Business Bandar Lampung Indonesia

ISBN: (纸本)9798350306835

Artificial intelligence was recently implemented in various fields. One of these applied artificial intelligence systems was the Performance Monitoring System "SiMoniK"for MSMEs. This system was designed through the C4.5 algorithm and the Porat-Rank method. The C4.5 algorithm was applied to classify the MSMEs into three classifications, e.g. the micro enterprise classification, the small enterprise classification, and the medium enterprise classification. Moreover, the Porat-Rank method was also applied to distribute the solving-problem recommendations and to improve the independence of MSMEs. The result of this study was that the C4.5 algorithm could classify the MSME data correctly in the form of an accuracy value of 99.2%. Besides, the Porat-Rank method could also provide recommendations in the form of outstanding quality with an NDCG mean value of 0.87. © 2023 IEEE.

关键词： Artificial intelligence

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Analysis of Perceptron Quantum Artificial Neural Networks to Classify the Feasibility of Prospective Debtors 1

Analysis of Perceptron Quantum Artificial Neural Networks to...

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

作者： Pujiastuti, Lise Wahyudi, Mochamad Solikhun STMIK Antar Bangsa Information System Study Program Banten Indonesia Universitas Bina Sarana Informatika Faculty of Technical and Informatics Information Technology Study Program DKI Jakarta Indonesia AMIK Tunas Bangsa Pematangsiantar Informatics Management Study Program North Sumatra Indonesia

Bank is a business entity whose activities are collecting funds from the public in the form ofdeposits and channeling them to the public in the form of loans or other forms to improve the livesof many people. This study aims to classify the feasibility data of prospective borrowers with the perceptron algorithm using quantum computing to facilitate the bank in determining the prospective debtor. The results of this study are an analysis of the feasibility of prospective borrowers usingthe perceptron algorithm with quantum computing. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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Ann : Predicting of State Retail Sukuk Based on Region in Indonesia 3

Ann : Predicting of State Retail Sukuk Based on Region in In...

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3rd International Conference on Computational Science and Information management, ICoCSIM 2019

作者： Solikhun Pujiastuti, Lise Wahyudi, Mochamad AMIK Tunas Bangsa Pematangsiantar Informatics Management Study Program North Sumatra Indonesia STMIK Antar Bangsa Information System Study Program Banten Indonesia Universitas Bina Sarana Informatika Faculty of Technical and Informatics Information Technology Study Program DKI Jakarta Indonesia

Retail Sukuk is a product of State Sharia Securities (Sukuk) issued by the Government of the Republic of Indonesia in this case the Ministry of Finance and sold to individuals or individuals of Indonesian Citizens through Selling Agents in the domestic Primary Market. This research contributes to the government and the Bank to be able to do the maximum promotion for the next sukuk issuance. The data used is data from the Ministry of Finance. These data are sukuk sales data with series 002-010 based on regional groups. The algorithm used in this study is Artificial Neural Network with Backpropogation method. Variabel masukan yang digunakan adalah kelompok wilayah bagian barat selain Jakarta (X1), kelompok Jakarta (X2), kelompok Indonesia Bagian Tengah(X3), dan kelompok Indonesia Bagian Timur (X4) dengan model arsitektur pelatihan dan pengujian sebanyak 4 arsitektur yakni 4-2-1, 4-3-1, 4-2-3-1 dan 4-3-2-1. The best architectural model is 4-3-1 with epoch 266, MSE 0.009918 and 100% accuracy rate. From this model, predictions of retail country sukuk will be made by region. © Published under licence by IOP Publishing Ltd.

关键词： Sales

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Understanding group signature methods in making digital signatures to maintain the validity of messages 2

Understanding group signature methods in making digital sign...

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2nd International Conference on Mechanical, Electronics, Computer, and Industrial Technology, MECnIT 2018

作者： Siregar, Saut Dohot Banjarnahor, Jepri Dharshinni, N.P. Tamba, Saut Parsaoran Robin Faculty of Technology and Computer Science Universitas Prima Indonesia Indonesia Informatics Management Study Program STMIK Mikroskil Indonesia

In this millennial era, a large amount of digital data traffic going through communication media on digital technology every day. Most of the data are documents and other essential information. The existing rapid development of technology nowadays, information can be easily faked. To make sure the validity of a digital document, a digital signature is required to verify the originality of the document. The purpose of this research is to design software which implemented the group signature algorithm to apply and verify digital signatures. The Signature Group algorithm used in this research is the Tseng-Jan scheme. The Tseng-Jan scheme consists of 5 stages: setup, join, sign, verify, and open. After applying the algorithm using 2 digits key and 3 digits key on the samples, 80% of the verification experiment on 2 digits key was succeeded 70% of the verification experiment on 3 digits key was succeeded. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Authentication

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Optimization of hyper parameter bandwidth on naïve Bayes kernel density estimation for the breast cancer classification 2

Optimization of hyper parameter bandwidth on naïve Bayes ke...

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2nd International Conference on Information and Communications Technology, ICOIACT 2019

作者： Sasongko, Theopilus Bayu Arifin, Oki Al Fatta, Hanif Information Technology Department Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Management of Informatics Study Program Economy and Business Departement Politeknik Negeri Lampung Lampung Indonesia

ISBN: (纸本)9781728116556

Cancer is viewed as the most harmful disease in the world. One of the most deadly cancer diseases attacking the women is breast cancer. In this paper, used Naïve Bayes classifier Kernel Density Estimation in breast cancer Wisconsin dataset take from UCI data repository. Naïve Bayes with Kernel Density Estimation was used as it could enable the Naïve Bayes to process the quantitative data. However, the performance of KDE (kernel density estimation) highly depends upon the size of the bandwidth parameter used to control the curve. The problem an accurate choice of parameter bandwidth (h) using trial and error technique requires a long process. A large bandwidth (h) will over-smooth the density and mask the structure in the data, a small bandwidth (h) will yield a density estimate that is spiky and very hard to interpret. The aim of this research is to compare the optimization of grid search parameter with the genetic algorithm to determine the bandwidth parameter (h) on the Naïve Bayes Kernel Density Estimator algorithm. The parameters used to compare the two optimization methods included accuracy, AUC (Area under Curve), and computation time. The experiment results on the test of the significance value on the comparison of grid search and algorithm in determination of the bandwidth parameter (h) naïve Bayes kernel density used Mann-Whitney Test. The result of the significance ranking showed that mean rank of the genetic algorithm accuracy was 489.95 better than the mean value of the rank of grid search accuracy at only 189.05, mean rank of AUC genetic algorithm was 491.82 better than mean rank of AUC grid search only at 187.18. The mean rank of computation time grid search was 243.37 faster than mean rank of computation time genetic algorithm at 435.63. © 2019 IEEE

关键词： Classification (of information)

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