Data Collection Steps Research Articles

Rancang Bangun Mesin Penggiling Sekam Padi Menjadi Bahan Pakan Ternak (Dedak)

In the development of technology and industry, a lot of tools are made to make it easier to do work. In the farming sector, a lot of tools are needed to facilitate development in the farming sector. One of the tools needed is a machine to make animal feed. One of the ingredients for making animal feed is bran, bran produced from the process of milling rice husks. To produce bran, a tool that can crush rice husks into the form of flour is designed to make animal feed suitable, as well as make the shape of a portable grinding machine. In this design, data collection steps were carried out with literature studies and after that carried out experiments on the manufacture of rice husk grinding machines. In conducting the experiment, the concept of design, design, calculation, manufacture and testing of grinding machines was also carried out. The result of this design is the design of a grinding machine and a grinding machine that can smooth rice husks into flour and portable forms. The specifications of the rice husk grinding machine are a frame with a length of 580 mm, a width of 380 mm and a height of 995 mm. Drive source 7 HP petrol motor with belt pulley transmission. The speed of the grinding blade shaft can be changed by replacing the pulley on the driving motor so that it can determine the fineness of the bran and the speed of the grinding. As well as the filter on the milling section can be replaced in order to adjust to the required level of fineness.

The development of the spatial visual-oriented geometry test to measure the creative thinking skills of elementary students

This research is a qualitative descriptive research by using 4D development consisting of the Define, Design, Develop, and Disseminate stages. The research was carried out to develop a spatial visual-oriented geometric test to measure elementary students’ creative thinking skills. The creative thinking level of each student has different categories based on the fluency, flexibility, and novelty. The subjects of this research consisted of 5 students from 30 fifth grade students from elementary school which were selected based on the van Hiele’s level ability category of each student. Operationally, the steps of this research included the preliminary step of research, data collection, and data analysis. The data of this research was obtained by using tests, observation, and interview. The data of the students was obtained by conducting a learning outcome test. The results has showed that 5 students who met the category of students’ creative thinking had a variation on the percentage of the creative thinking level by using a spatial test, namely 40%, 20%, 20%, 20%, 20%, which were respectively categorized as very creative (level 4), creative (level 3), quite creative (level 2), less creative (level 1). There were 2 of 5 students who were at the same level, namely as very creative (level 4) but had differences in answering.

Development of a Basic Educational Kit for Robotic System with Deep Neural Networks.

In many robotics studies, deep neural networks (DNNs) are being actively studied due to their good performance. However, existing robotic techniques and DNNs have not been systematically integrated, and packages for beginners are yet to be developed. In this study, we proposed a basic educational kit for robotic system development with DNNs. Our goal was to educate beginners in both robotics and machine learning, especially the use of DNNs. Initially, we required the kit to (1) be easy to understand, (2) employ experience-based learning, and (3) be applicable in many areas. To clarify the learning objectives and important parts of the basic educational kit, we analyzed the research and development (R&D) of DNNs and divided the process into three steps of data collection (DC), machine learning (ML), and task execution (TE). These steps were configured under a hierarchical system flow with the ability to be executed individually at the development stage. To evaluate the practicality of the proposed system flow, we implemented it for a physical robotic grasping system using robotics middleware. We also demonstrated that the proposed system can be effectively applied to other hardware, sensor inputs, and robot tasks.

Customer experience and brand loyalty in the full-service hotel sector: the role of brand affect

PurposeThis study aims to propose a comprehensive causal model to examine the relationships between customer experience and four key factors in brand building, i.e., brand loyalty, brand trust, brand affect and brand involvement. The dimensionality of customer experience in full-service hotel is also particularly examined in relation to brand building.Design/methodology/approachThree steps of data collection were used: interviews of 50 customers on their experiences of staying full-service hotels, a small survey of 176 hotel guests to establish the measurement scale of customer experience and a major survey of 732 hotel customers in ten major Chinese cities to test the model of brand loyalty.FindingsCustomers’ experiences with full-service hotels are proposed to be categorized into functional, affective and social. There is a chain effect from customer experience to brand trust and to brand affect and then to brand loyalty. The brand involvement does moderate relationships between customer experience and brand trust and brand affect but not brand loyalty.Practical implicationsFor full-service hotels, social and functional experiences are critical in building brand loyalty, and therefore, they need to be the focal points in the enhancement of customer experience. Also, hoteliers are advised to develop emotional connections between the customers and the hotel brand – an effective way of building trust and affection.Originality/valueAccording to the authors’ knowledge, this paper is one of the first few studies to link customer experience to brand loyalty with comprehensive causal effect analysis. This study also contributes to the knowledge of customer experience in the context of the full-service hotel sector.

Kemampuan Gerak Dasar Renang Gaya Dada Pada Siswa Menengah Pertama

This study discusses breaststroke. This type of research is descriptive qualitative. The informants in this study were 6 informants consisting of 5 students of class VII 4 and 1 informant of the sixth grade health care teacher 4 SMP Negeri 5 Kuta Selatan. Qualitative data with written words and data sources used in this study are primary and secondary data sources. Primary data sources used in this study are direct observation and calculation, secondary data used are interview data and questionnaires. Data collection techniques using triangulation are observation, interviews, and questionnaires. The analysis of the data used is the analysis of Miles and Huberman namely the analysis of interactive model data which is done through the steps of data collection, data reduction, data presentation, and conclusions concatenation. The results of this study indicate that students have sufficient ability to perform basic breaststroke movements with (good) categories. With a percentage of the results of observations as many as 18 students (60%) are in the good category and as many as 12 students (40%) are in the sufficient category. The results of the interview data are already maximal. Because a little inhibiting factor. The results of the questionnaire data showed as many as 18 students (60%) in the good category and as many as 12 students (40%) were in the sufficient category. From the three data, get the maximum data results with the category (good).
 
 Keywords: Ability, Basic Motion, Chest Style Swimming.

Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning

This paper studies decision-making in two-player scenarios where the type (e.g. adversary, neutral, or teammate) of the other agent (opponent) is uncertain to the decision-making agent (protagonist), which is an abstraction of security-domain applications. In these settings, the reward for the protagonist agent depends on the type of the opponent, but this is private information known only to the opponent itself, and thus hidden from the protagonist. In contrast, as is often the case, the type of the protagonist agent is assumed to be known to the opponent, and this information-asymmetry significantly complicates the protagonist's decision-making. In particular, to determine the best actions to take, the protagonist agent must infer the opponent type from the observations and agent modeling. To address this problem, this paper presents an opponent-type deduction module based on Bayes' rule. This inference module takes as input the imagined opponent's decision-making rule (opponent model) as well as the observed opponent's history of actions and states, and outputs a belief over the opponent's hidden type. A multiagent reinforcement learning approach is used to develop this game-theoretic opponent model through self-play, which avoids the expensive data collection step that requires interaction with a real opponent. Besides, this multiagent approach also captures the strategy interaction and reasoning between agents. In addition, we apply ensemble training to avoid over-fitting to a single opponent model during the training. As a result, the learned protagonist policy is also effective against unseen opponents. Experimental results show that the proposed game-theoretic modeling, explicit opponent type inference and the ensemble training significantly improves the decision-making performance over baseline approaches, and generalizes well against adversaries that have not been seen during the training.

Nilai Moral dalam Pembelajaran Sastra Anak Melalui Cerita Rakyat Nusantara

The study aims to determine the moral values and social values in a collection of short stories by Ahmad Tohari as learning material in class X SMAN 5 Pandeglang. The aim of this study to 1) Provide knowledge about the values contained in short story, 2) Growing motivation in reading short story literature, 3) Increasing interest in appreciating short stories, 4) Able to analyze the values contained in short story literature, 5) Instill the positive values of short stories in everyday life. The method used in this research is descriptive analysis method. Descriptive method is the method used to make broader conclusions. Research data collection techniques were carried out using literature studies or documentation studies on Ahmad Tohari’s short stories. The steps in this descriptive study are, 1) Identify significant problems that can be solved through the descritive method, 2) Formulate the problem clearly, 3) Determine the purpose and benefits of research, 4) Conduct literature studies related to problems, and 5) Collect and analyze data qualitatively. The steps of data collection are reading Ahmad Tohari’s short stories carefully, recording the appropriate data, identifying and classifying data and making data education. The results of the study indicate that the collection of short stories by Ahmad Tohari contains many values, especially moral values and social values.

Транснационализм в режиме онлайн: миграционные исследования в условиях искусственной социальности

Миграция в Россию из стран СНГ — явление, которое ставит перед социальными учеными многочисленные исследовательские проблемы. Разнообразие миграционных потоков и трудности в доступе к «полю» приводят к тому, что различные фрагменты общей картины лишь в той или иной степени согласуются друг с другом. Статья посвящена осмыслению и сравнению нескольких таких фрагментов, полученных в ходе изучения «следов» активности транснациональных мигрантов в интернете. Авторы стремятся ответить на два вопроса: какие стороны миграционных процессов проявляются в собранных данных, а какие — ускользают от исследователей; как полученные результаты и их ограничения соотносятся со свойствами онлайн-среды, организованной деятельностью поисковых, классифицирующих и сортирующих алгоритмов? Эмпирический материал представлен двумя типами онлайн-данных, характеризующих миграцию в Россию из пяти стран (Азербайджана, Казахстана, Кыргызстана, Таджикистана и Узбекистана). Это группы "ВКонтакте" и сайты, найденные с помощью поисковика Google. Данные были собраны на шести языках: русском и стран исхода. В качестве методов выступают сетевой анализ, контент-анализ, а также онлайн-наблюдение. Охарактеризованы процессы сбора и анализа данных и основные результаты исследования для каждого из методов. Результаты соотнесены друг с другом, сделаны выводы о содержательных характеристиках миграционных процессов и о возможностях и ограничениях исследования миграции в онлайн-среде. Авторы описывают «разделение труда» между людьми и алгоритмами на каждом из этапов исследования, выделяют три типа алгоритмов согласно их роли в исследовательском процессе, а также размышляют над тем, как принятые методологические решения повлияли на полученные результаты. Благодарность. Исследование выполнено при поддержке Российского научного фонда, грант № 18-78-10049.

From a Point Cloud to a Simulation Model-Bayesian Segmentation and Entropy Based Uncertainty Estimation for 3D Modelling.

The 3D modelling of indoor environments and the generation of process simulations play an important role in factory and assembly planning. In brownfield planning cases, existing data are often outdated and incomplete especially for older plants, which were mostly planned in 2D. Thus, current environment models cannot be generated directly on the basis of existing data and a holistic approach on how to build such a factory model in a highly automated fashion is mostly non-existent. Major steps in generating an environment model of a production plant include data collection, data pre-processing and object identification as well as pose estimation. In this work, we elaborate on a methodical modelling approach, which starts with the digitalization of large-scale indoor environments and ends with the generation of a static environment or simulation model. The object identification step is realized using a Bayesian neural network capable of point cloud segmentation. We elaborate on the impact of the uncertainty information estimated by a Bayesian segmentation framework on the accuracy of the generated environment model. The steps of data collection and point cloud segmentation as well as the resulting model accuracy are evaluated on a real-world data set collected at the assembly line of a large-scale automotive production plant. The Bayesian segmentation network clearly surpasses the performance of the frequentist baseline and allows us to considerably increase the accuracy of the model placement in a simulation scene.

KEANEKARAGAMAN BINTANG LAUT (Asteroidea) DI PANTAI LAMALAKA KECAMATAN ILE BOLENG KABUPATEN FLORES TIMUR

Sea star is an invertebrate animal that is included in the phylum Echinoderms from the Asteroidea class. Radial symmetry is shaped and generally has five or more arms and does not have a frame that helps movement. This study aims to determine the diversity of sea star (Asteroidea) in Lamalaka Beach, Ile Boleng District, East Flores Regency.This research will be conducted in July-August 2019, the location of the study is on the Lamalaka coast, Ile Boleng District, East Flores Regency.The method used is a survey method, based on the presence of Asteroidea species that are considered to represent the area. The steps in data collection are field survey, observation, identifying species in each plot, observing and recording their marphological characteristics.Sampling uses the technique of determining the location of sampling using Area sampling. To identify based on Human and Deloach identification guidelines, 2010. Analysis of the data used in this research is quantitative descriptive and the composition of Asteroidea species can be stated based on visual observations calculating species density, relative density, and dominance index, diversity.Based on the results of the study, found 4 species of Asteroidea, namely Protoreaster nodulosus, Linckia laevigata, Echinaster luzonicus, Astropecten polyacanthus. The highest species density calculation results were found in P. nodulosus species with a value of 0.78 ind / m2. while the lowest species density was found in L.laevigata species with a value of 0.63 ind / m2. The highest relative density was found in P. nodulosus species with a value of 27.64%, and the lowest relative density found in L.laevigata species with a value of 22.35 %. The index of starfish species dominance in Lamalaka Beach, obtained a value of D <0.5, indicates that there are no species that dominate in Lamalaka Beach. The existence of starfish in Lamalaka Beach, Ile Boleng District, East Flores Regency needs to be preserved. One form of effort to preserve it is to conduct monitoring with routine monitoring to monitor the condition of the sea star population in these waters. Besides that, it is also necessary to increase the utilization of sea stars as one of the natural tourism objects and as an Ecoedutourism tourism object. Thus, the presence of starfish will be felt by the wider community so that awareness to maintain the existence of starfish will be increased.

A Learning Analytics Framework to Analyze Corporal Postures in Students Presentations.

Communicating in social and public environments are considered professional skills that can strongly influence career development. Therefore, it is important to proper train and evaluate students in this kind of abilities so that they can better interact in their professional relationships, during the resolution of problems, negotiations and conflict management. This is a complex problem as it involves corporal analysis and the assessment of aspects that until recently were almost impossible to quantitatively measure. Nowadays, a number of new technologies and sensors have being developed for the capture of different kinds of contextual and personal information, but these technologies were not yet fully integrated inside learning settings. In this context, this paper presents a framework to facilitate the analysis and detection of patterns of students in oral presentations. Four steps are proposed for the given framework: Data collection, Statistical Analysis, Clustering, and Sequential Pattern Mining. Data Collection step is responsible for the collection of students interactions during presentations and the arrangement of data for further analysis. Statistical Analysis provides a general understanding of the data collected by showing the differences and similarities of the presentations along the semester. The Clustering stage segments students into groups according to well-defined attributes helping to observe different corporal patterns of the students. Finally, Sequential Pattern Mining step complements the previous stages allowing the identification of sequential patterns of postures in the different groups. The framework was tested in a case study with data collected from 222 freshman students of Computer Engineering (CE) course at three different times during two different years. The analysis made it possible to segment the presenters into three distinct groups according to their corporal postures. The statistical analysis helped to assess how the postures of the students evolved throughout each year. The sequential pattern mining provided a complementary perspective for data evaluation and helped to observe the most frequent postural sequences of the students. Results show the framework could be used as a guidance to provide students automated feedback throughout their presentations and can serve as background information for future comparisons of students presentations from different undergraduate courses.

Transformation of entrepreneur education programs (EEPS) of Indonesia’s higher education

The Entrepreneurship Education Program (EEPs) of Indonesia’s higher education has not been effective. The study aims to identify the extent to which EEPs in Indonesia was developed and propose several alternative schemes. The research uses the methodology of traditional narrative literature review and interviews with young entrepreneurs as the output of the EEPs higher education program in Indonesia. The analysis technique is done with an interactive model with steps of data collection, data reduction, data presentation, verification, and conclusions. The literature study is intended for the latest research information that evaluates the effect of EEPs on the formation of EM and the formation of new entrepreneurs. Furthermore, the information is verified by the results of the interview data processing. Entrepreneurship education for multidisciplinary students, business incubators, funding provision, and program sustainability studies is the result of research as a proposal for the development of higher education EEPs. This program is part of a long-term solution to addressing labor problems in Indonesia.

SPORT CENTER UNIVERSITAS TANJUNGPURA

Sports are activity carried out with the aim of getting physical and spiritual health. People of Pontianak, especially academic’s civitas at Tanjungpura University, often do sports activities. There are various ways to develop sports activities, one of which is providing a container that can accommodate sports activities, such as the "Sport Center of Tanjungpura University" with the aim of being a place for matches and training. By applying with a modern architectural approach can generate buildings that emphasize function, relations with the surrounding environment, honesty in the use of materials and simplicity. The planning method used in this report is by collecting data through descriptive methods. This method describes systematically, explains factually and accurately about the facts, nature and relationship of design requirements and design provisions to planning and design. Based on the terms and conditions of the design, which will be searched for the required data. The data collected will be analyzed in order to get clear conclusions and limitations regarding the planning and design of the Tanjungpura University Sport Center area in stages from general problems to detailed problems. The method of discussion will be carried out with the idea step, the problem identification step, the data collection step, the data analysis step, the synthesis step, and the design step. The result of the design of the author's final project is a sports building which consists of 2 floors with the building mass divided into 2 parts, namely the training building and the competition building. The building is designed using a minipile as the foundation, reinforced concrete frame as the column and beam structure, and steel as the roof frame material.

Comparative analysis between theoretical and simulatory learning methods by data science methodology approach

Data Science is the most trending interdisciplinary science that integrates the steps of data collection, preprocessing data, transforming data, storing data, data visualization, and hence extracting the insights from the data to serve stakeholder’s purposes. Python is commonly used and, along with being a versatile and open-source language, is a favorite tool in Data science studies. The vast libraries are being used to manipulate data and are very simple for even a beginner data scientist to understand. In the present work, we intend to apply the data science methodology to decision making and predictive analysis using the python programming language. We consider the problem of selecting the better mode of study concerning some of the impractical phenomena from physics for the exact understanding of the process. Data collection has been from an educational institute and the comparison has been made between theoretical learning and simulatory learning for selected topics from the vast fields like mechanics, thermodynamics, fluid dynamics, and radioactivity. The steps of data science methodology are germinated to achieve the insights into the data procured and the results are wangled concerning the teaching methodology that could be employed. In the present work, we undertake a comparative study between the theoretical and simulatory modes of teaching by exploring the modes individually through evaluating the responses imparted by a class of high school students. The analysis reported the more inclination of the student’s responses towards the simulatory methods when compared to the theoretical method of learning.

Process improvement using value stream mapping and lean methodology: a case study application in batch chemical process industry

Intensifying competition in the global chemicals market is increasing the pressure on companies to adopt lean manufacturing and improve their operational efficiency to remain competitive. Companies operating in emerging economies are no exception. This study looks at the application of value stream mapping (VSM) in the production process of a batch chemical manufacturing company based in Indonesia. The application of value stream method is a multistep approach. A value stream scope is determined in the beginning, followed by a data collection step to construct a current state map. The current state is analysed to gain a deep understanding of how things currently operate and provides the foundation for the ideal future state of the production process. The production process is then redesigned following lean manufacturing principles, and the future state map is drawn. Analysis is then conducted to estimate the potential cost reduction from implementing the proposed future state. The results indicate a more efficient production system as shown by decreased production lead time and reduced production costs.

A novel framework for rapid diagnosis of COVID-19 on computed tomography scans

Since the emergence of COVID-19, thousands of people undergo chest X-ray and computed tomography scan for its screening on everyday basis. This has increased the workload on radiologists, and a number of cases are in backlog. This is not only the case for COVID-19, but for the other abnormalities needing radiological diagnosis as well. In this work, we present an automated technique for rapid diagnosis of COVID-19 on computed tomography images. The proposed technique consists of four primary steps: (1) data collection and normalization, (2) extraction of the relevant features, (3) selection of the most optimal features and (4) feature classification. In the data collection step, we collect data for several patients from a public domain website, and perform preprocessing, which includes image resizing. In the successive step, we apply discrete wavelet transform and extended segmentation-based fractal texture analysis methods for extracting the relevant features. This is followed by application of an entropy controlled genetic algorithm for selection of the best features from each feature type, which are combined using a serial approach. In the final phase, the best features are subjected to various classifiers for the diagnosis. The proposed framework, when augmented with the Naive Bayes classifier, yields the best accuracy of 92.6%. The simulation results are supported by a detailed statistical analysis as a proof of concept.

Efektifitas Pengembangan Buku Ajar Berbasis Nilai-Nilai Karakter Multikultural Terhadap Keterampilan Berpikir Kritis Siswa

This study aims to describe the effectiveness of multicultural-based learning to improve students' critical thinking skills in elementary schools. This is a Research and Development (R & D), with the steps of potential problems analysis, data collection, product design, design validation, design revisions, product trials, and product revisions. This research was conducted in grade IV in SD 1 Tritis and SD 1 Karangnongko, combined as the experimental group, while SD 1 Daren and SD 3 Nalumsari as a control group, all in Nalumsari District, Jepara Regency. The results showed the t-test results found that t arithmetic> T table is 8.994> 1699, the value data were analyzed with a significance level of 0.05. So, as the basis for decision making, it can be concluded that Ho was rejected and Ha was accepted. Thus, it can be concluded that multicultural-based learning is effective in improving the critical thinking skills of fourth grade students of elementary schools.

Appeal of cartoon characters in instructional media through animation in early childhood education in Surakarta

Animated learning media using cartoon characters is an appropriate means of supporting learning methods in Early Childhood Education in the Surakarta area, Central Java, Indonesia. This research method includes data collection, data analysis, and presentation of data analysis. This research method uses a qualitative descriptive approach through data sources that include learning materials, animated cartoon characters, literature study through the stages of analysis obtained from various sources of information in interactive references. The investigation stages from multiple sources of information, both literature reviews and interviews, were carried out using an interactive model, where each research component includes the steps of data collection, data reduction, presentation, and conclusion drawing. The use of cartoon characters in animation learning media is beneficial for students who are very interesting and able to receive material and participate in learning activities. Also, animated audiovisual media are needed by students and teachers by using cartoon characters in it.

Nothing About us Without us: Research Methods Enabling Participation for Aged Care Residents Who Have Dementia

The voices of people living with dementia are rarely included in primary data collection due to cognitive challenges and the concerns of researchers and others about limitations associated with informed consent. This article presents a successfully implemented, step-by-step process enabling effective participation of aged care residents with dementia using a case study approach. Three methodological and critical steps in data collection were identified that led to the successful participation of residents with dementia in research. The process corresponds with, yet is uniquely different from the common elements in the qualitative research process. These are active participation during data collection, researcher familiarization with participants, and their set interval and time-lapse considerations (timeline). The process of involvement of people with dementia in research should proceed at a pace that is guided by the participants. It is important to consider participant interview pace, pattern, and the conversation time points when interruptions occur, to restart the whole interview process. Researchers need to facilitate active engagement by building and maintaining authentic relationships with the participants.

Smart Internet of Vehicles Architecture based on Deep Learning for Occlusion Detection

In our days, the cyber world is developing due to the revolution of smart cities and machine learning technologies. The internet of Things constitutes the essential background of cyber technology. As a case study, the Internet of Vehicles is one of the leading applications which is developed quickly. Studies are focused on resolving issues related to real-time problems and privacy leakage. Uploading data from the cloud during the data collection step is the origin of delay issues. This process decreases the level of privacy. The objective of the present paper is to ensure a high level of privacy and accelerated data collection. During this study, we propose an advanced Internet of Vehicle architecture to conduct the data collection step. An occlusion detection application based on a deep learning technique is performed to evaluate the IoV architecture. Training data at Distributed Intelligent layer ensures not only the privacy of data but also reduces the delay.