scholarly journals STUDI SIMULASI MENGGUNAKAN FUZZY C-MEANS DALAM MENGKLASIFIKASI KONSTRUK TES

2013 ◽  
Vol 15 (1) ◽  
pp. 115-138
Author(s):  
Rukli Rukli
Keyword(s):  
Factor Analysis ◽  
Matlab Simulation ◽  
Simulation Data ◽  
Fuzzy C Means ◽  
Test Items ◽  
Parametric Statistics ◽  
Simulation Results ◽  
Using Data ◽  
Microsoft Office ◽  
Made In

Tulisan ini memperkenalkan metode fuzzy c-means dalam mengklasifikasi konstruk tes. Untuk memverifikasi sifat unidimensional suatu tes biasanya menggunakan analisis faktor sebagai bagian dari statistik parametrik dengan beberapa persyaratan yang ketat sedangkan metode fuzzy c-means termasuk metode heuristik yang tidak memerlukan persyaratan yang ketat. Studi simulasi penelitian ini menggunakan dua metode yakni analisis faktor menggunakan program SPSS dan fuzzy c-means menggunakan program Matlab. Data simulasi menggunakan tipe data dikotomi dan politomi yang dibangkitkan lewat prog-ram Microsoft Office Excel dengan desain 2 kategori, yakni: tiga butir soal dengan banyak peserta tes 10, dan 30 butir soal dengan banyak peserta tes 100. Hasil simulasi menunjukkan bahwa metode fuzzy c-means lebih memberikan gambaran pengelompokan secara deskriptif dan dinamis pada semua desain yang telah dibuat dalam memverifikasi unidimensional pada suatu tes.Kata kunci: fuzzy c-means, analisis faktor, unidimensional_____________________________________________________________ SIMULATION STUDY USING FUZZY C-MEANS FOR CLASIFYING TEST CONSTRUCTIONAbstract This paper introduces the fuzzy c-means method for classifying the test constructs. To verify the unidimensional a test typically uses factor analysis as part of parametric statistics with some strict requirements, while fuzzy c-means methods including method heuristic that do not require strict require-ments. Simulation comparison between the method of factor analysis using SPSS program and fuzzy c-means methods using Matlab. Simulation data using data type dichotomy and politomus generated through Microsoft Office Excel programs each with a number of 3 items using the number of participants 10 tests, while the number of 30 test items using the number as many as 100 participants. The simulation results show that the fuzzy c-means method provides a more descriptive and dyna-mic grouping of all the designs that have been made in verifying the unidimensional as a test.Keywords: fuzzy c-means, factor analysis, unidimensional

Factors of Dementia Caregiver Burden Differentially Contribute to Desire to Institutionalize

2021 ◽  
pp. 089198872110361
Author(s):  
John T. Martin ◽  
Kimberly R. Chapman ◽  
Christopher Was ◽  
Mary Beth Spitznagel
Keyword(s):  
Factor Analysis ◽  
Linear Regression ◽  
Factor Structure ◽  
Caregiver Burden ◽  
Living Arrangements ◽  
Regression Analyses ◽  
Loved One ◽  
Dementia Caregiver ◽  
Future Work ◽  
Made In

The experience of dementia caregiver burden is multidimensional. Little is known about how different aspects of burden contribute to the consideration of moving a loved one to a structured living facility. In the present study, caregiver burden (Zarit Burden Interview; ZBI) and consideration of structured living arrangements (Desire to Institutionalize Scale; DIS) were self-reported by 339 caregivers. Exploratory factor analysis was used to determine the ZBI factor structure; these factors were then examined via hierarchical linear regression for prediction of DIS. Factor analysis indicated a 4-factor ZBI solution: Impact on Life, Guilt, Embarrassment/Frustration, and Escape/Uncertainty. Regression analyses indicated that only Escape/Uncertainty ( p < .001) was associated with DIS. Of the 4 identified factors of caregiver burden, desire to escape the caregiving role was most related to consideration of structured living arrangements. Future work should explore longitudinal contribution of this factor to determine its role in actual changes made in living arrangements.

scholarly journals Heterogeneous Beliefs and Risk-Neutral Skewness

2012 ◽  
Vol 47 (4) ◽  
pp. 851-872 ◽  
Author(s):  
Geoffrey C. Friesen ◽  
Yi Zhang ◽  
Thomas S. Zorn
Keyword(s):  
Factor Analysis ◽  
Latent Variables ◽  
Stock Options ◽  
Systematic Risk ◽  
Heterogeneous Beliefs ◽  
Firm Level ◽  
Cross Sectional ◽  
Skewness Factor ◽  
Risk Neutral ◽  
Using Data

AbstractThis study tests whether belief differences affect the cross-sectional variation of risk-neutral skewness using data on firm-level stock options traded on the Chicago Board Options Exchange from 2003 to 2006. We find that stocks with greater belief differences have more negative skews, even after controlling for systematic risk and other firm-level variables known to affect skewness. Factor analysis identifies latent variables linked to risk and belief differences. The belief factor explains more variation in the risk-neutral skewness than the risk-based factor. Our results suggest that belief differences may be one of the unexplained firm-specific components affecting skewness.

scholarly journals An Efficient Clustering Approach for Automatic Detection of Calcification in Low Dose Chest CT

2019 ◽  
pp. 163-168
Author(s):  
P. Tamijiselvy ◽  
N. Kavitha ◽  
K. M. Keerthana ◽  
D. Menakha
Keyword(s):  
Data Mining ◽  
Low Dose ◽  
Early Stage ◽  
Clustering Algorithms ◽  
Automatic Detection ◽  
Chest Ct ◽  
Data Mining Algorithm ◽  
Fuzzy C Means ◽  
Data Mining Algorithms ◽  
Using Data

The degree of aortic calcification has been appeared to be a risk pointer for vascular occasions including cardiovascular events. The created strategy is fully automated data mining algorithm to segment and measure calcification using Low-dose Chest CT in smokers of age 50 to 70 .The identification of subjects with increased cardiovascular risk can be detected by using data mining algorithms. This paper presents a method for automatic detection of coronary artery calcifications in low-dose chest CT scans using effective clustering algorithms with three phases as Pre-Processing, Segmentation and clustering. Fuzzy C Means algorithm provides accuracy of 80.23% demonstrate that Fuzzy C means detects the Cardio Vascular Disease at early stage.

scholarly journals Portable Generator Thermoelectric Termonitoring IoT sebagai Pembangkit Termal di Daerah 3T (Terdepan, Terluar dan Tertinggal)

Electrician ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 54-57
Author(s):  
Rahmat Bayu Setiawan ◽  
Panji Adhi Pradana ◽  
Muhammad Abdul Fattah ◽  
Khairudin Khairudin
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Electrical Energy ◽  
Thermoelectric Generators ◽  
Simulation Data ◽  
Power Generator ◽  
Testing Data ◽  
Micro Power ◽  
Simulation Results ◽  
The Government

Intisari — Energi terbarukan adalah sumber energi yang dihasilkan secara alamiah dan akan terus berkelanjutan jika dikelola dengan baik. Indonesia adalah negara yang terkenal dengan potensi alam yang sangat melimpah. Banyak sumber daya alam yang perlu perhatian dari pemerintah untuk dikembangkan. Pengaplikasian alat yang dapat dikembangkan yaitu di antaranya yaitu melalui termoelektrik yang dipantau melalui IoT secara portable sehingga dapat menjangkau daerah 3T (Tertinggal, Terdepan dan Terluar). Prototipe penghasil energi terbarukan dan ramah lingkungan dalam sistem pembangkit mikro, yang dalam hal ini portable generator termoelektrik termonitoring IoT sebagai pembangkit termal dapat dikembangkan untuk mengatasi pemerataan dan ketersediaan energi listrik di daerah 3T (terdepan, terluar dan tertinggal) berbasis kearifan lokal dapat didesain menggunakan 3-D INVENTOR dan hasil simulasi dari sisi material menggunakan ANSYS serta hasil simulasi dari output yang dihasilkan menggunakan MATLAB. Pembuatan prototipe sesuai dengan konsep dan desain yang telah didapatkan sebelumnya dengan menggunakan softwareMicroroft Visio, software INVENTOR dan evaluasi hasil simulasi dengan menggunakan software MATLAB. Hasil dari pembuatan prototipe akan dilakukan pengujian tingkat gradien suhu terbaik untuk menghasilkan energi optimal, sehingga didapatkan data optimal dalam menyimulasikan micro power plant tersebut. Berdasarkan simulasi yang dilakukan didapatkan data dengan daya minimum sebesar 6,215 W selama 2 menit dan daya maksimum sebesar 19,932 W selama 8 menit Kata kunci — Energi, IoT, Portable Generator ThermoelectricAbstract — Renewable energy is a source of energy that is generated naturally and will be sustainable if managed properly. Indonesia is a country known for its abundant natural potential. There are many natural resources that need attention from the government to be developed. The development of this power generator tool really requires an understanding of the design of the tools used to get optimal results. The application of tools that can be developed is through thermoelectricity which is monitored via IoT in a portable manner so that it can reach 3T areas (Disadvantaged, Frontier and Outermost). Prototypes for producing renewable and environmentally friendly energy in micro-generating systems, in which IoT-monitored portable thermoelectric generators as thermal generators can be developed to address the distribution and data of electrical energy in 3T (frontier, outermost and disadvantaged) areas based on local wisdom can be designed using 3 -D INVENTOR and simulation of materials using ANSYS and simulation of the output generated from MATLAB. Making prototypes in accordance with the concepts and designs that have been obtained previously using Microroft Visio software, INVENTOR software and evaluation of simulation results using MATLAB software. The results of the prototyping will be tested for the best temperature gradient level to produce optimal energy, so that optimal data can be obtained in simulating the micro power plant. Testing data that has been done, and used as evaluation material in the simulation that is carried out. Based on the simulation, data obtained with a minimum power of 6,215 W for 2 minutes and a maximum power of 19,932 W for 8 minutes.Keywords— Energy, IoT, Portable generator thermoelectric

scholarly journals Item Analysis of Final Test for the 9th Grade Students of SMPN 44 Surabaya in the Academic Year of 2019/2020

2020 ◽  
Vol 2 (1) ◽  
pp. 34-46
Author(s):  
Siti Fatimah ◽  
Achmad Bernhardo Elzamzami ◽  
Joko Slamet
Keyword(s):  
Test Scores ◽  
Item Difficulty ◽  
Statistical Tests ◽  
Item Analysis ◽  
Discrimination Power ◽  
Test Items ◽  
9Th Grade ◽  
Research Findings ◽  
Microsoft Office ◽  
Academic Year

This research was conducted by focusing on the formulated question regarding the test scores validity, reliability and item analysis involving the discrimination power and index difficulty in order to provide detail information leading to the improvement of test items construction. The quality of each particular item was analyzed in terms of item difficulty, item discrimination and distractor analysis. The statistical tests were used to compute the reliability of the test by applying The Kuder-Richardson Formula (KR20). The analysis of 50 test items was computed using Microsoft Office Excel. A descriptive method was applied to describe and examined the data. The research findings showed the test fulfilled the criteria of having content validity which was categorized as a low validity. Meanwhile, the reliability value of the test scores was 0.521010831 (0.52) categorized as lower reliability and revision of test. Through the 50 items examined, there were 21 items that were in need of improvement which were classified into “easy” for the index difficulty and “poor” category for the discriminability by the total 26 items (52%). It means more than 50% of the test items need to be revised as the items do not meet the criteria. It is suggested that in order to measure students’ performance effectively, essential improvement need to be evaluated where items with “poor” discrimination index should be reviewed.    

scholarly journals Gestation at completion of prenatal questionnaires in ALSPAC

2020 ◽  
Vol 5 ◽  
pp. 100
Author(s):  
Yasmin Iles-Caven ◽  
Kate Northstone ◽  
Jean Golding
Keyword(s):  
Data Collection ◽  
Pregnant Women ◽  
First Trimester ◽  
Environmental Data ◽  
Parents And Children ◽  
Using Data ◽  
Time Critical ◽  
Avon Longitudinal Study ◽  
In Pregnancy ◽  
Made In

Enrolling a cohort in pregnancy can be methodologically difficult in terms of structuring data collection. For example, some exposures of interest may be time-critical while other (often retrospective) data can be collected at any point during pregnancy.  The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prime example of a cohort where certain data were collected at specific time points and others at variable times depending on the gestation at contact.  ALSPAC aimed to enrol as many pregnant women as possible in a geographically defined area with an expected date of delivery between April 1991 and December 1992. The ideal was to enrol women as early in pregnancy as possible, and to collect information, when possible, at two fixed gestational periods (18 and 32 weeks). A variety of methods were used to enrol participants.   Approximately 80% of eligible women resident in the study area were enrolled. Gestation at enrolment ranged from 4-41 (median = 14) weeks of pregnancy. Given this variation in gestation we describe the various decisions that were made in regard to the timing of questionnaires to ensure that appropriate data were obtained from the pregnant women.  45% of women provided data during the first trimester, this is less than ideal but reflects the fact that many women do not acknowledge their pregnancy until the first trimester is safely completed. Data collection from women at specific gestations (18 and 32 weeks) was much more successful (80-85%). Unfortunately, it was difficult to obtain environmental data during the first trimester. Given the time critical nature of exposures during this trimester, researchers must take the gestational age at which environmental data was collected into account. This is particularly important for data collected using the questionnaire named ‘Your Environment’ (using data known as the A files).

scholarly journals EVALUASI PELAPORAN KAMSELTIBCAR LANTAS DALAM MENDUKUNG PELAPORAN DEKADE AKSI KESELAMATAN JALAN

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Nunung Nuring Hayati ◽  
Ni Nyoman Suartini ◽  
Achmad Wicaksono ◽  
Ike Fibriani ◽  
Mirtha Firmansyah ◽  
...  
Keyword(s):  
Data Mining ◽  
Road Safety ◽  
Road Transport ◽  
Public Knowledge ◽  
Traffic Law ◽  
Using Data ◽  
Two Parameters ◽  
Self Protection ◽  
The Relationship ◽  
Made In

Kamsebtibcar Lantas or secure, safety, orderliness, and fluency of traffic are made in support of road safety actions reporting on traffic due to the lack of public knowledge about the importance of using self-protection tools that have been determined in traffic law number 22 of 2009 concerning traffic and road transport. By using this program, you can find out the relationship between the factors that cause accidents. From those collected from various regions in East Java, taken from 2016 to 2018. The data obtained can be processed using data mining techniques. This technique works by using a pattern that is a reference for decision making. By using the Fp-Growth algorithm that works with the data tree system to find out the patterns of reporting activities that are happening, this pattern is determined by two parameters, namely support (support value) and confidence (certainty value). With this system, it can help the parties concerned to improve facilities in various Kamseltibcar Lantas reporting activities. Kamsebtibcar lantas atau keamanan, keselamatan, ketertiban, dan kelancaran lalu lintas dibuat dalampedalam mendukung pelaporan aksi keselamatan jalan pada lalu lintas yang dikarenakan minimnya pengetahuan masyarakat tentang pentingnya penggunaan alat perlindungan diri yang telah ditentukan pada undang-undang nomor 22 tahun 2009 tentang lalu lintas dan angkutan jalan. Dengan menggunakan program ini dapat mengetahui hubungan antara faktor-faktor penyebab kecelakaan. Data yang dikumpulkan dari berbagai daerah yang ada di wilayah Jawa Timur diambil pada tahun 2016 sampai dengan 2018. Data yang telah didapat dapat diolah menggunakan teknik data mining. Teknik ini berfungsi dengan menggunakan pola yang menjadi acuan untuk penentuan keputusan. Dengan menggunakan algoritma Fp-Growth yang bekerja dengan sistem data tree untuk mengetahui pola kegiatan pelaporan kamsebticar lalu lintas yang sedang terjadi, pola ini ditentukan dengan dua parameter, yaitu support (nilai penunjang) dan confidence (nilai kepastian). Dengan sistem ini dapat membantu pihak yang berkaitan untuk meningkatkan fasilitas dalam berbagai kegiatan pelaporan Kamseltibcar Lantas.

scholarly journals Density Variations during Solidification of Grey Cast Iron

2018 ◽  
Vol 925 ◽  
pp. 155-162 ◽  
Author(s):  
Kristina Hellström ◽  
Péter Svidró ◽  
Lucian Vasile Diaconu ◽  
Attila Diószegi
Keyword(s):  
Complex Geometry ◽  
Control Volume ◽  
Solidification Process ◽  
Simulation Software ◽  
Volume Changes ◽  
Silicon Alloys ◽  
Know How ◽  
Grey Cast ◽  
Using Data ◽  
Made In

As part of moving towards a sustainable production of diesel engines for heavy vehicle applications, the ability to predict casting defects has become ever so important. In order to model the solidification process for cast components correctly, it is of essence to know how the material will actually behave. To produce sound castings, often of complex geometry, the industry relies on various simulation software for the prediction and avoidance of defects. Thermophysical properties, such as density, play an important part in these simulations.Previous measurements of how the volume of liquid grey iron changes with temperature has been made with a conventional dilatometer. Measurements have also been made in the austenitic range, then on iron-carbon-silicon alloys with a carbon content lower than 1.5 wt%. Based on these measurements the density variations during solidification were calculated. The scope for this paper is to model the volume changes during solidification with the control volume finite difference method, using data from the density measurements.

scholarly journals Is valuing happiness associated with lower well-being? A factor-level analysis using the valuing happiness scale

2016 ◽  
Author(s):  
Maike Luhmann ◽  
Elizabeth A. Necka ◽  
Felix D. Schönbrodt ◽  
Louise Hawkley
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Theoretical Foundation ◽  
Well Being ◽  
The Other ◽  
Factor Level ◽  
Confirmatory Factor ◽  
Positive Correlations ◽  
Using Data ◽  
Level Analysis

Recent studies suggest that valuing happiness is negatively associated with well-being. Most of these studies used the Valuing Happiness Scale (Mauss, Tamir, et al., 2011). In the present paper, we examined the factor structure of this scale using data pooled from six independent samples (Ntotal = 938). Exploratory and confirmatory factor analysis showed that the Valuing Happiness Scale is not unidimensional and that only one of its three factors correlates negatively with various indicators of well-being, whereas non-significant or positive correlations were found for the other factors. These findings indicate that valuing happiness may not necessarily be bad for one’s well-being, and call for a better definition, theoretical foundation, and operationalization of this construct.

Verification of modeling of convective events based on radar reflectivity

2021 ◽  
Author(s):  
Ekaterina Svechnikova ◽  
Nikolay Ilin ◽  
Evgeny Mareev
Keyword(s):  
General Pattern ◽  
Measurement Data ◽  
Quantitative Agreement ◽  
Convective Event ◽  
Simulation Results ◽  
Verification Process ◽  
Using Data ◽  
Wrf Modeling ◽  
Probabilistic Nature

&lt;p&gt;The use of numerical modeling for atmospheric research is complicated by the problem of verification by a limited set of measurement data. Comparison with radar measurements is widely used for assessing the quality of the simulation. The probabilistic nature of the development of convective phenomena determines the complexity of the verification process: the reproduction of the pattern of the convective event is prior to the quantitative agreement of the values at a particular point at a particular moment.&lt;/p&gt;&lt;p&gt;We propose a method for verifying the simulation results based on comparing areas with the same reflectivity. The method is applied for verification of WRF-modeling of convective events in the Aragats highland massif in Armenia. It is shown that numerical simulation demonstrates approximately the same form of distribution of areas of equal reflectivity as for radar-measured reflectivity. In this case, the model tends to overestimate on average reflectivity, while enabling us to obtain the qualitatively correct description of the convective phenomenon.&lt;/p&gt;&lt;p&gt;The proposed technique can be used to verify the simulation results using data on reflectivity obtained by a satellite or a meteoradar. The technique allows one to avoid subjectivity in the interpretation of simulation results and estimate the quality of reproducing the &amp;#8220;general pattern&amp;#8221; of the convective event.&lt;/p&gt;

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