bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning algorithm to identifies fraud emails with feature selection
Authors: Sinaga Anita Sindar , Munandar Musthafa Haris , Sitio Arjon Samuel 
Published: February 2021

Abstract
One percent of the emails that come in each day are fraudulent. Promotion emails tend to offer products. The recipient’s email is recorded by a company or organization. Not all promotional emails are considered spam or hoaxes. When observed, incoming promotional emails provide the information that is needed. How to identify promotional emails including hoaxes or shipping with machine learning, known as algorithms, Support Vector Machines, Naïve Bayes, Decision Tree, Logistic Regression, Stochastic Gradient Descent, and Neural Network (MLP). Decision trees are effective tracing using a data structure consisting of vertices & edges. A node (root, branch, leaf) can categorize incoming e-mail, including hoax or e-mail shipping. Previously, it was necessary to categorize the characteristics of the email. After searching the email, the promotional email grouping is continued. In Feature Extraction, the calculation of Gain and Entropy is used to determine the selection of features in the classification of promotional emails, fraudulent emails or hoaxes.
Improving cybersecurity awareness using phishing attack simulation
Authors: Chatchalermpun Surachai , Daengsi Therdpong 
Published: February 2021

Abstract
This paper aims to present a case study of the cybersecurity awareness level of the workers in a financial institution in Thailand. In this study, there were 2 phases of cyber drills using a spear-phishing email. The first phase was conducted with more than 20,300 workers. It was found that there were 23.25% of potential victims. However, the second phase was conducted four months later with more than 20,200 workers after performing knowledge transfer. The number of workers who opened phishing emails in the second phase decreased to 6.76% only. Therefore, it can be indicated that an appropriate cybersecurity knowledge transfer can reduce a large number of potential victims and cyber threats that may occur in such organizations.
Developing web apps based on multi-criteria decision making and user preferences
Authors: Effendy Faried 
Published: February 2021

Abstract
There are different perspectives on the ideal place for dining, including the taste, parking lot, service, price, and other support facilities. Therefore, accommodating tourist preferences is essential to produce appropriate recommendations since tourists are very subjective and diverse when defining their favorite culinary places. Culinary support systems may help the community to obtain a culinary location recommendation as they please. This study aims to develop a web-based system that provides an appropriate recommendation for gastronomic tourists using the VIKOR method as a ranking advisor. The results showed that the algorithm ensures optimal decision - making based on user and expert assessments.
Determination of the relationship pattern of association topic on Al-Qur’an using FP-Growth Algorithms
Authors: Novita Rice , Mustakim  , Salisah Febi Nur 
Published: February 2021

Abstract
The Qur’an is an Islam holy book used as life guidance. Since its function as human life guidance, some strategies and ways are necessary in learning al Qur’an. Many strategies are usable in learning Qur’an, one of them is by learning munasabah science and the relationship between the topic and verses of Qur’an. The development of Data Mining that is expanded with text mining makes it easy to divide and find out the relationship of the topic of Qur’an especially in its translation. FP – Growth Algorithm is one of algorithm with many excellences in obtaining association pattern, in this case by determining topic relationship on Qur’an. The experiment in this research was carried out with 4 models where the best parameter is at minimum support 80% and its minimum confidence is 40%. Rule that is produced by algorithm is 159 with lift ratio 1.203. The best rule is implemented on android programming language as Qur’an learning media.
Design and Application Data Collection for integrated evaluation and monitoring
Authors: Hidayatullah Muhammad , Wahyudi Agus Teguh , Esabella Shinta , Andriani Titi , Gunawan G 
Published: February 2021

Abstract
The process of data collection of tax subjects and objects at the Regional Revenue Agency (BAPENDA) of Sumbawa Regency is still manual, where the subject and tax object data are still managed in the form of records on bookkeeping media and office application office media applications such as Microsoft Excel. The need for an application design as a form of digitizing a manual process in the governance system to improve the effectiveness and efficiency of the agency. The research aims to develop Tax Object Subject Data Collection Applications. The application is built with Web-based programming, using the PHP Programming Language and Sublime Text as Tools Editor and MySQL as a data storage medium. The application built can present data collection features related to tax object subject data such as companies, restaurants, hotels, parking and ground water data and can display reports in the form of data related to tax object and object data collection to facilitate the monitoring process in BAPENDA Sumbawa Regency.
Implementation of ELECTRE Method for Decision Support System
Authors: Siregar Victor Marudut Mulia , Sihombing Volvo , Siahaan Nimrot , Indra Kumalasari M , Siregar Muhammad Yusuf , Sagala Elviana , Toni  
Published: February 2021

Abstract
This study aims to design a decision support system to determine users’ priority of office inventory items at PT. INL. Deciding the priority of users of office inventory items aims to determine the most appropriate employees to use office inventory items in their daily work so that each employee’s performance can be more optimal. Deciding office inventory users’ priority is done using the ELECTRE (Elimination Et Choix Traduisant La Realite) method. The result of this research is a decision scavenger system that can help and facilitate companies in selecting and prioritizing users of office inventory items at the company. Employees who are prioritized as inventory users in the Electre method are the alternative that has the most value of 1, which outperforms other alternatives.
Application of SEM: an analysis of Depok City’s website
Authors: Prastya Imam Yudhi , Meilinda Selvi Diana , Sulistiowati Rahayu , Alfiandri Alfiandri , Yudiatmaja Wayu Eko 
Published: February 2021

Abstract
Electronic government is one of the strategies to create a more effective government. Many governments around the globe have applied electronic government, including Indonesia. Although there is various research on the electronic government in Indonesia, only a few studies have focused on analyzing the intention to use government websites, particularly the local government’s website. To address the research gap, this paper intends to statistically examine the intention to use Depok City’s website based on the user’s perspective by applying structural equation modelling. This study was carried out using a survey approach. Data were collected using an online questionnaire on the Depok’s citizens. One hundred twenty-five respondents participated in this study. Data were analyzed using covariance-based structural equation modelling. The key findings of this research confirm all developed hypotheses in which system quality, information quality, and service quality influence website intention to use. The results demonstrated in this work provide theoretical and practical implications further elaborated in the light of this paper.
Optimization of the CNN model for smart agriculture
Authors: Gunawan  , Zarlis M , Sihombing P , Sutarman  
Published: February 2021

Abstract
Artificial intelligence is a branch of computer science that has advanced quite rapidly and is very useful in helping to alleviate human tasks. One of the models or algorithms part of artificial intelligence is the Convolutional Neural Network (CNN). This model is proven to be very accurate in image data processing. CNN has been used for facial recognition and image data detection systems. In this study, researchers will optimize CNN to obtain a faster and more accurate model for processing plant disease image data in this study using oil palm plant sample data. With the Research and Development method and FGD (Focus Group Discussion) with various experts, this research is expected to produce a CNN model that is faster and more accurate.
Election model classifications of problem-based learning using a machine learning technique
Authors: Rohmat Cep Lukman , Anwar Saeful , Dikananda Arif Rinaldi , Ali Irfan , Rizki Ade Rinaldi 
Published: February 2021

Abstract
Strategy learning based problem involve all college students to active in working class and find the solution of problems being discussed. The active involvement of all students in learning and the capability of think critically students hoped would improve learning outcomes especially cognitive students study results. This study aims to choose model classification and evaluate how much of accuracy and precision from the learning problem learning based using a technique machine learning. Classification problems based learning treatment based on student learning outcomes and creativity. Optimize parameters applied at an election algorithms applied with both operators select sub proses. By applying some algorithms so operator select sub proses will vote in the best automatic algorithms. The algorithms Decision Tree, Naïve Bayes, and Random Forest are acquired automatic algorithms Naive Bayes have the accuracy of 75 % of the kappa 2,3%.
Classification of human development index using particle swarm optimization based on support vector machine algorithm
Authors: Mulyawan  , Dwilestari Gifthera , Bahtiar Agus , Basysyar Fadhil Muhammad , Suarna Nana 
Published: February 2021

Abstract
Human Development Index (HDI) is the comparative of life expectancy, education and standard of living to all countries. Human Development Index used as an indicator to assess the quality of the construction. Human Development Index may also be used to classify the city or state whether a country of developed countries, developing countries, or the state of underdeveloped and as well as to gauge the effects of economic policy on the quality of life. In the study is done capability of classifications Human Development Index in Indonesia. Methods Used to know Classifications of Human Development Index this is using Support Vector Machines algorithms base Particle Swarm Optimization. Support Vector Machine algorithms based Particle Swarm Optimization is a-method that has the capacity for the Classification of Human Development Index data. In research was built model of Support Vector Machines algorithms based Particle Swarm Optimization. Results from the human development index is in the country or province 24 96 data not be in class, very high with human development index is at the high is 952, data while in the medium is 2018 data and there are at the level of low 201 data with an accuracy to 96.26 %, weighted mean recall 97.74 %, weighted mean precision 99.09.
Comparison K-Medoids Algorithm and K-Means Algorithm for Clustering Fish Cooking Menu from Fish Dataset
Authors: Suarna Nana , Wijaya Yudhistira Arie , Mulyawan  , Hartati Tuti , Suprapti Tati 
Published: February 2021

Abstract
The production of fish-based food processing has become a commodity for restaurants, restaurants, catering and home consumption, but there are still many people who don’t know how fish can be processed in various dishes for their daily needs. To find out how to make fish-based dishes, the researchers provide a solution to cooking any kind of food, starting from the grouping of types of dishes, the basic ingredients that must be prepared, how to cook them, to the address of the cooking link with ingredients from fish. This study aims so that people can cook various menus whose basic ingredients come from fish. This research uses clustering algorithm, k-means and k-medoids. The stages of this research consisted of data collection, data selection, modeling, data training, data testing and evaluation. The object in the study of menu data for various processed fish dishes consisted of 978 datasets of processed fish dishes. The data used for data relating to fish food ingredients with fish food attributes and the number of likes via the website, the fish dataset is sourced from https://ipm.bps.go.id/data/dataset/ikan. From the two algorithms, the best accuracy results are -1.777 for the k-means algorithm, while -1.535 results are obtained for the accuracy of the k-medoids algorithm.
Development application of a quality assurance management information system for Paulus Indonesia Christian University
Authors: Sudianto Lande , Simon Petrus 
Published: February 2021

Abstract
University of Christian Indonesia Paulus (UKI Paulus) currently already has the standard documents, policies and quality documents. Yet the implementation is not supported by an information system, so the socialization process for standards, policies and quality documents is ineffective and causes limited access for those who need it. Furthermore, the implementation of monitoring and evaluation quality audits is also inefficient and brings obstacles to the implementation of the quality assurance system. The Unified Modeling Language (UML) is used for the information and communication technology (ICT) based quality assurance management information system. The development of the UKI Paulus Quality Assurance Management Information System (SIM-MUTU UKI Paulus) uses a System Development Life Cycle (SDLC) paradigm approach which consists of 5 stages: (1) identification of system requirements; (2) analysis and modeling system; (3) the system creation; (4) the system testing and restoration; and (5) implementation. The SIM-MUTU UKI Paulus which was developed is a web-based information system that provides convenience in managing the quality assurance at the university level. Various features developed in this system include: accreditation features, internal academic quality audit features and library features. System testing is carried out using white box testing and black box testing methods. 5 aspects usability testing questioners were given to 30 respondents, they are: (a) learnability, (b) efficiency, (c) memorability, (d) errors, (e) satisfaction and the result were 86.5%, 78, 2%, 75.0%, 72.5%, and 75.2% for each aspect. Based on the ISO 9241-11 indicator, the average level of usability is 77.5%. The results of this test indicated that the system run optimally, has a high level of usability with a feasibility rate of 86%. Higher education quality assurance management information system based on information and communication technology able to facilitate auditing and provide information with complete documentation related to the quality management business process in Higher Education. The utilization of technology in the form of implementing an information system support the quality assurance management process to be more automated without eliminating the business processes that have been running so far. This Information system also increase the value of an organization’s competitive advantage and facilitate the users in the decision-making processes.
E-Commerce Application based on cloud computing in SMEs
Authors: Panggalo Wendyanto , Arrang Hermin 
Published: February 2021

Abstract
Small-medium enterprises (SMEs) have an essential role in national economic development. The impact of Covid-19 affects income on SMEs in Indonesia. SMEs in the North Toraja district is one of the business sectors affected by Covid 19. This pandemic has caused a decline in the demand side’s performance, namely consumption and purchasing power, which then disrupted the production and trade processes. Therefore, SMEs need an innovative online business transaction that can affect the development of business activities in North Toraja. E-commerce is an application that can distribute products from SMEs. This study aims to design and implement cloud computing-based e-commerce that can be used by all SMEs in the North Toraja district. The system design uses the visual modeling method with the testing system using the black box testing method. The resulting E-Commerce application can help all SMEs in the North Toraja district to expand marketing, simplify product and transaction processing, and facilitate product ordering
Monitoring of the Virtual Learning Process during the Covid-19 pandemic
Authors: Batara Chris 
Published: February 2021

Abstract
The COVID-19 pandemic that is currently sweeping the world is forcing the world of education to close classrooms and avoid physical gatherings. This situation forces the education system to redesign or re-engineer an education and training system that is not limited by time and space, with a virtual learning system (e-learning) that utilizes information and communication technology, the use of digital devices for various purposes in the world of formal education. and non-formal. Virtual Learning System (e-learning) is a learning system by providing an online environment based on information and communication technology. This system can overcome problems that arise due to Covid-19 not to come together to carry out the learning process, but must learn from their respective places. In the virtual learning process, there is a need for a system that can be used to monitor and ensure the learning process goes well and the quality is maintained. Monitoring and evaluation which is part of the governance system developed to maintain and ensure that education is carried out according to educational standards listed in Permenristek Dikti no 44 of 2015 concerning National Higher Education Standards (SN-Dikti). Realizing this, education managers need to make various efforts to ensure good management of learning, starting from the planning stage, implementation to the evaluation process. Based on the foregoing, it is necessary to formulate guidelines for monitoring and evaluation of learning as a reference to ensure the implementation of SN-Dikti. The monitoring carried out in this study was the activeness of lecturers and students in virtual learning.
Additional Security using Three-Pass Protocol and Pohlig-Hellman
Authors: Rahim Robbi , Zahri Nik Adilah Hanin , Warip Mohd Nazri Bin Mohd 
Published: February 2021

Abstract
Data and information protection is usually done by encrypting sensitive data and information using cipher keys or symmetric algorithms. This includes using what is known as “cipher keys,” which are used in systems that require two parts, a sender’s and receiver’s part, which is a special system that needs to be assembled, and a location where data is sent to or stored. The Three-Pass Protocol and Pohlig Hellman Algorithm solves a key distribution problem in symmetric and asymmetric cryptography, allowing senders and receivers to process encryption and decryption due to lack of key distribution processes.
A reconfigurable IoT-based monitoring and control system for small-scale agriculture
Authors: Hoan Tran Nhut Khai , Qui Nguyen Cao , Truong Nguyen Phuc , Danh Lương Vinh Quốc 
Published: February 2021

Abstract
In this paper, we present the design of a low-cost remote monitoring and control network for household cultivation, in which peripherals connected to each sensor-node can be re-configured remotely from the internet via a master node without any changing on the system firmware. The feasibility of the proposed scheme is evaluated via experiments. Particularly, the experiments set-up consists of one master node communicating wirelessly with some sensor nodes (slaves) to collect sensing data or send commands to them to manage the operating of the system. The sensing data from slaves will be collected and updated periodically to Google Sheets by master node via the internet connection. Additionally, slaves are equipped with versatile ports for connecting with sensors. The port is designed to be compatible with most popular communication standards such as analog, digital, I2C, UART, SPI. The key design of these communication ports is that when plugging/unplugging a sensor into/from a port, the corresponding slave can be re-configured directly on Google Sheets or keypad connected to master node. The research results can be further extended and improved to be applicable to household cultivation as well as application models of smart agriculture.
Analysis of working load of semi-automatic sprayer knapsack operators on spraying at paddy fields
Authors: Ansar  , Murad  , Sukmawaty  , Hatmurizal  
Published: February 2021

Abstract
The use of a knapsack sprayer for pest and disease control is quite exhausting, causing fatigue for operators. This fatigue can cause pain or injury to the muscles. Therefore, this study aimed to determine the operator’s workload based on fatigue and total energy consumption in operating the knapsack sprayer. There are 2 types of knapsack sprayer equipment, namely high-density polyethylene sprayer (HDPS), and stainless steel sprayer (3S). The results show that the operator’s workload is in light of the moderate category as indicated by the average IRHR value for HDPS between 1.063-1,580 and 3S between 1,194-1,687. Calculation of the operator’s workload obtained an average value of total energy consumption for HDPS between 0.034-0.078 kcal/kg, while 3S between 0.046-0.087 kcal/kg. The normalized work energy consumption value of the HDPS operator between 1.367-3.554 kcal/kg, while 3S between 1.954-4.234 kcal/kg. Based on the calculation of the total score of each operator, it is known that the level of muscle complaints using the HDPS or 3S shows did not differ significantly. However, the workload of using HDPS is lower than the 3S at a capacity of 8-14 litters.
Application of an adaptive fuzzy logic controller to optimize the performances of the P&O algorithm
Authors: Chekenbah Hamid , Maataoui Yassir , Lasri Rafik , Choukri Larbi 
Published: February 2021

Abstract
In this work, an Adaptive Fuzzy Logic Controller is studied to optimize the transfer of the power provided by a photovoltaic generator. The adaptation process is carried out online in two tasks: the adaptation of the rules consequences and the self-organization of the internal structure of the Fuzzy Controller. In comparison with two types of traditional controls, the performance of the controller studied is validated. The simulation results show that the controller studied makes it possible to reduce the response time by 3 % compared to the conventional controller, and minimizes the steady-state error by eliminating the phenomenon of oscillation around the PPM and that the proposed controller exhibits good behavior with a wide range of power.
The Regression Estimation Model of Post-empowerment Household with Consumption Function Theory
Authors: Rahim Abd. , Malik Abdul , Hastuti Diah Retno Dwi , Syam Ulfah , Marhawati  
Published: February 2021

Abstract
The existence of an empowerment program for fisherwomen in household-scale capture fish processing aims to improve the family economy so that it will impact changes in household consumption expenditure after the empowerment of small-scale fishermen’s wives. The research method used qualitative independent variable regression estimation with the consumption function theory. The results showed that post-empowerment household consumption expenditures on small-scale fishermen’s wives were influenced by household income and household members’ numbers. On the other hand, the wife’s education and regional differences did not have a significant effect. The increase in household consumption of small-scale fishermen’s can be realized if there is an increase in household income from the catch and processing of fisheries products from fishermen’s wives in a sustainable manner during the fishing season.