scholarly journals Implementasi Metode K-Means pada Hasil Produksi Daging Jenis Ternak

2021 ◽  
Vol 6 (1) ◽  
pp. 235
Author(s):  
Siti Nurmila Saragih ◽  
M Safii ◽  
Dedi Suhendro
Keyword(s):  
Meat Production ◽  
Microsoft Excel ◽  
Group Data ◽  
Data Clusters ◽  
Calculation Algorithms ◽  
North Sumatra ◽  
Manual Calculation ◽  
Cluster 2 ◽  
Education Standard ◽  
High Cluster

Meat production results should have good quantity and quality. To increase meat production, of course it is necessary to look at healthy types of livestock. Meat continues to increase in line with the increase in population, community income, education, standard of living and awareness of the nutritional value of animal production. The need for livestock meat production is one of the driving factors for the economy in Indonesia. This research can provide and input to the local government which is the leading producer of meat for the type of livestock in North Sumatra province and as a basis for making policies to increase meat production for other provinces. The method used in this research is the K-Means Algorithm. Where K-Means is one of the Algorithms in Data Mining that can be used to group data clusters. So that the data from 33 districts / cities will be divided into 2 clusters where cluster 1 is the high group, while cluster 2 is the low group. The results obtained from the study show that the results of manual calculation Algorithms and Microsoft Excel data have the same value, namely high cluster 1 and low cluster 32, and entering Microsoft Excel calculations into rapidminer has the same value as well

scholarly journals Clustering Fasilitas Kesehatan Berdasarkan Kecamatan Di Karawang Dengan Algoritma K-Means

2021 ◽  
Vol 8 (1) ◽  
pp. 83
Author(s):  
Bagus Muhammad Islami ◽  
Cepy Sukmayadi ◽  
Tesa Nur Padilah
Keyword(s):  
Data Mining ◽  
Developing Countries ◽  
Data Processing ◽  
Health Problems ◽  
Health Facilities ◽  
Microsoft Excel ◽  
Two Factors ◽  
Clustering Data ◽  
Index Value ◽  
Cluster 2

Abstrak: Masalah kesehatan yang ada di dalam masyarakat terutama di negara- negara berkembang seperti Indonesia dipengaruhi oleh dua faktor yaitu aspek fisik dan aspek non fisik. Berdasarkan data yang diperoleh dari karawangkab.bps.go.id data dibagi menjadi 3 cluster yaitu sedikit, sedang dan terbanyak. Algoritma yang digunakan adalah K-Means cluster yang diimplementsikan menggunakan Microsoft Excel dan Rapidminer Studio. Hasil pengolahan data fasilitas kesehatan di karawang menghasilkan 3 cluster dengan cluster 1 yang mempunyai fasilitas kesehatan sedikit sebanyak 23 kecamatan, cluster 2 yang mempunyai fasilitas kesehatan sedang sebanyak 5 kecamatan dan cluster 3 yang mempunyai fasilitas kesehatan terbanyak terdapat 2 kecamatan. Kinerja yang dihasilkan dari algoritma K-means menghasilkan nilai Davies Boildin Index sebesar 0,109.   Kata kunci: clustering, data mining, fasilitas kesehatan, K-Means.   Abstract: Health problems that exist in society, especially in developing countries like Indonesia, are built by two factors, namely physical and non-physical aspects. Based on data obtained from karawangkab.bps.go.id the data is divided into 3 clusters, namely the least, medium and the most. The algorithm used is the K-Means cluster which is implemented using Microsoft Excel and Rapidminer Studio. The results of data processing of health facilities in Karawang produce 3 clusters with cluster 1 which has 23 sub-districts of health facilities, cluster 2 which has medium health facilities as many as 5 districts and cluster 3 which has the most health facilities in 2 districts. The performance resulting from the K-means algorithm results in a Davies Boildin Index value of 0.109.   Keywords: clustering, data mining, health facilities, K-Means.

scholarly journals Sistem Informasi Pengolahan Data Kependudukan Pada Kantor Desa Sampean Berbasis Android

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Muhamad Alda
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Processing ◽  
Population Data ◽  
Distribution Data ◽  
Microsoft Excel ◽  
Time And Energy ◽  
The Village ◽  
North Sumatra

The population data is the data have to be in record in any office the villages around. With the citizens data , the village office can do monitoring inhabitant of which is found in the neighborhood. So far, the village office sampean kecamatan sungai kanan kabupaten labuhan batu selatan, north sumatra still use application desktop in doing processing the population data that is use application microsoft excel .In such a manner as there are still several problems and the obstacles, especially time and energy issued when their distribution data population in parties in need by the village office sampean. The purpose of he did this research is to design and construct information system the population data processing based android. With the information systems that in designed by the writer, is expected to help parties the village office sampean in doing processing the population data and do distribution the population data easily And rapidly through a smartphone android. Information system built by using application kodular and a database airtable

scholarly journals Ukuran Gejala Pusat Data Dikelompokkan pada Penjualan Smartphone Tahun 2019-2020

2021 ◽  
Author(s):  
Samuel Gibson Devonius ◽  
R.Arie Trihartanto ◽  
Theresia Meri Tarigan
Keyword(s):  
Data Processing ◽  
Data Center ◽  
Microsoft Excel ◽  
Work System ◽  
Average Value ◽  
Group Data ◽  
Symptom Measures

Data center symptom measures can represent the data as a whole. Which means that if all the valuescontained in the data are sorted in size and the average value is entered into it and one way to calculate the size of thedata center symptoms is Static Descriptive. The aim is to provide information and data processing, facilitate datapresentation, data processing and analysis, and add insight in analyzing group data in the Smartphone field. Thisstatic description is limited to providing a description of the characteristics of the object under study. In this activity,it is analyzed using Microsoft Excel, and then there is software used, namely SPPS. This software has the advantageof being able to display histograms with a work system that is faster, more efficient, practical, and precise.Descriptive Static can also be numbers, letters or graphics.

scholarly journals PENGARUH INISIASI MENYUSU DINI (IMD) TERHADAP JUMLAH DARAH KALA IV PERSALINAN

2020 ◽  
Vol 2 (2) ◽  
pp. 199-204
Author(s):  
Irma Nurianti ◽  
Tati Murni Karo Karo ◽  
Sri Melda Bangun ◽  
Sri Yana
Keyword(s):  
Maternal Mortality ◽  
Post Partum ◽  
Family Health ◽  
Director General ◽  
Control Group ◽  
Breastfeeding Initiation ◽  
A Value ◽  
Group Data ◽  
North Sumatra ◽  
Static Group

Early Breastfeeding Initiation (EBI) or the onset of early breastfeeding is to give newborns the opportunity to suckle themselves on their mothers in the first hour of birth, Early Breastfeeding Initiation (EBI) is related to the production of the hormone oxytocin, which helps the uterus contract so that it does not can immediately reduce bleeding in the mother. The Early Breastfeeding Initiation (EBI) itself is still low in Indonesia, North Sumatra contributes to the low rate of EBI implementation at 24%, according to the Director General of Family Health of the Ministry of Health Eni Gustina. The biggest cause of maternal mortality in Indonesia during 2010-2013 was bleeding 30.3 %. The purpose of this study was to determine whether there was an effect of early breastfeeding initiation (EBI) on the amount of bleeding period IV in the midwife clinic Suherni Amd. Keb Kec Beringin kab Deli Serdang in 2019. This type of research is pre-experiment with the design of static group comparison, with a population of 28 post partum mothers. Sampling is done by "purposive sampling", the sample size in this study amounted to 20 mothers then divided into 2 groups where 10 mothers as the experimental group and 10 mothers as the control group. Data collection is recorded on the observation sheet, data analysis is done by univariate and bivariate with t-independent test. The results of the analysis showed that there was an effect of Early Breastfeeding Initiation (EBI) on the amount of Bleeding Period IV in the Midwife Clinic Suherni Amd. Keb Kec Beringin Kab Deli Serdang in 2019 with a value of p 0,000. It is expected that the number of mothers who breastfeed in the first minute to one hour of birth can increase, because EBI provides many benefits for babies and mothers. If immediately breastfeeding after giving birth can reduce maternal mortality.

scholarly journals Consumer Assessment of Sustainability Traits in Meat Production. A Choice Experiment Study in Spain

2020 ◽  
Vol 12 (10) ◽  
pp. 4093
Author(s):  
Ali Eldesouky ◽  
Francisco J. Mesias ◽  
Miguel Escribano
Keyword(s):  
Choice Experiment ◽  
Meat Production ◽  
Consumer Decision Making ◽  
Purchasing Decisions ◽  
Production Methods ◽  
Mature Women ◽  
Purchasing Behaviour ◽  
Consumer Assessment ◽  
Cluster 2 ◽  
Beliefs And Attitudes

Consumers are increasingly concerned about the way their food is produced. This is particularly relevant in the case of meat, due to the impacts that its production methods can have on greenhouse gas emissions and its role in climate change. In relation to this issue, the purpose of our research is to obtain more information on the consumer decision-making process for beef, in order to determine the relative importance of sustainability claims and traditional attributes, and identify consumer profiles with similar perceptions and intentions. A choice experiment was used to assess the influence of these attributes on consumers’ purchasing decisions. The results reveal that the best purchase choice for the consumer would be organic beef, produced in Spain, with an animal welfare label and eco-labelled. Later on, a cluster analysis was carried out using consumer beliefs and attitudes towards meat consumption as inputs, together with purchasing behaviour variables. A solution was obtained with three well-defined consumer segments showing different preference patterns: Cluster 1 (Male millennials indifferent towards environment or sustainability), Cluster 2 (Sustainability-concerned mature women) and Cluster 3 (Middle-aged meat eaters with established families). The results of this study are relevant to develop more appropriate strategies that may be adapted to the behaviour and expectations of eco-friendly food consumers.

scholarly journals K-Means Clustering Dalam Penerimaan Karyawan Baru

2020 ◽  
Vol 4 (2) ◽  
pp. 103
Author(s):  
Anggun Setiadi ◽  
Erma Delima Sikumbang
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster ◽  
Test System ◽  
Selection Strategy ◽  
New Employees ◽  
Or Groups ◽  
Data Clusters ◽  
New Employee ◽  
Cluster 2 ◽  
Employee Data

Dalam penerimaan karyawan baru sulitnya bagian SDM PT. Erdikha Elit Sekuritas dalam mengelompokkan data-data karyawan baru dan tidak adanya sistem tes dalam pemilihan karyawan baru. Metode K-Means Clustering adalah salah satu metode cluster analysis non hirarki yang berusaha untuk mengelompokkan data-data yang ada satu atau lebih cluster atau kelompok, oleh karena itu metode ini sangat cocok digunakan untuk mengatasi permasalahan dalam mengelompokkan data-data calon karyawan baru dan mengimplementasikan menggunakan software RapidMiner dengan hasil penelitian 0,125% untuk cluster 1 yang berjumlah 2 data karyawan baru, 0,125% untuk cluster 2 yang berjumlah 2 data karyawan baru, dan 0,750% untuk cluster 3 yang berjumlah 12 data karyawan baru. Strategi pemilihan karyawan baru nantinya akan mengikuti cluster yang terbentuk berdasarkan data yang paling banyak diantara 3 cluster yang ada, yaitu di cluster ke- 3, karena dengan data cluster yang paling banyaklah yang lebih banyak memenuhi kriteria. Kata kunci: K-Means Clustering, Penerimaan Karyawan Baru Abstract: In the case of hiring new employees, the difficulty of the HR department of PT. Erdikha Elit Sekuritas in classifying new employee data and the absence of a test system in the selection of new employees. K-Means Clustering method is a non-hierarchical cluster analysis method that seeks to group existing data into one or more clusters or groups, therefore this method is very suitable to be used to overcome problems in grouping data on prospective new employees and implements using RapidMiner software with research results of 0.125% for cluster 1 which amounts to 2 new employee data, 0.125% for cluster 2 which amounts to 2 new employee data, and 0.750% for cluster 3 which amounts to 12 new employee data. The new employee selection strategy will follow the clusters formed based on the most data among the 3 existing clusters, namely in the 3rd cluster, because with the most data clusters that meet more the required criteria. Keywords: Acceptance of new employees, K-Means Clustering.

scholarly journals Comparison between the commonly used radiographic techniques for intra oral imaging in dentistry-A questionnaire study

2017 ◽  
Vol 5 (2) ◽  
pp. 157
Author(s):  
Ramesh Tatapudi ◽  
Swathi Myla ◽  
Upendra Gurugubelli ◽  
Jyothirmai Koneru ◽  
Meenakshi K ◽  
...  
Keyword(s):  
Patient Comfort ◽  
P Value ◽  
Microsoft Excel ◽  
Chi Square ◽  
Technical Parameters ◽  
Private Practitioners ◽  
The People ◽  
Group Data ◽  
Chi Square Test

Aim:-To compare the opinion regarding usage of bisecting-angle technique and the paralleling techniques among BDS students, post graduate students, private practitioners in and around Bhimavaram town for intra oral imaging in dentistry. Materials and methods: A detailed questionnaire composed of questions regarding technical parameters, exposure parameters, operator and patient comfort and image accuracy in diagnosis. Details of the study were explained to the participants preferred option to be marked according to the question mentioned in the questionnaire. Total 500 individuals participated in the present study, with 100 individuals in each group. Data was collected and entered in Microsoft Excel (2010) and statistically analysed using SPSS 20. Chi-square test was used to evaluate differences in the responses with P-value ≤ 0.05 were considered significant. Results: Results showed that in technical parameters most of the people opted for bisecting angle technique with p value≤ 0.05 and found as significant. In aspect of exposure parameters, results are in favour of paralleling technique and p value is ≤ 0.05. In aspect of the operator and patient comfort there is an equal opinion most of them opted for bisecting angle technique and paralleling technique p value is significant. In aspect of image accuracy p value is significant for paralleling technique. Conclusion: Great work should have to be done to alleviate the quality of radiographs and the understanding and perspective of dental graduates regarding dental and maxillo-facial radiology. The results of present study revealed though there is knowledge about the techniques, but lack of application decreases their ability to get more accurate diagnostic radiograph. Paralleling technique being the most accurate in image accuracy should be emphasized to practice and needed to be modified in conditions where it is not feasible to deal with.

scholarly journals HUBUNGAN PANJANG DAN BERAT, FAKTOR KONDISI , FEKUNDITAS, DAN PERKEMBANGAN TELUR IKAN TENGADAK (Barbonymus schwanenfeldii) DARI SAROLANGUN, JAMBI DAN ANJONGAN, KALIMANTAN BARAT, INDONESIA

2018 ◽  
Vol 17 (2) ◽  
Author(s):  
Irin Iriana Kusmini ◽  
Jojo Subagja ◽  
Fera Permata Putri
Keyword(s):  
Condition Factor ◽  
Regression Coefficient ◽  
Fish Farming ◽  
Growth Patterns ◽  
Gonad Weight ◽  
Microsoft Excel ◽  
West Kalimantan ◽  
Weight Relationship ◽  
Group Data ◽  
Average Factor

Tinfoil barb (Barbonymus schwanenfeldii) is one of the potential local fish to be cultivated as a food or pet fish. The data and information of the growth pattern of species are essential for fish farming success. The observation on the length and weight relationship is an usefull indicator to determine the pattern of growth fish observed. This study aims to determine the growth patterns of tinfoil barb fish based on length and weight relationship, condition factor and fish fecundity of tinfoil barb from Sarolangun, Jambi and Anjongan, West Kalimantan. The 30 samples were taken randomly from each group. Data were analyzed using analysis regression Microsoft Excel. The result showed that the regression coefficient of length and weight relationship was 2.811 for Sarolangun and 2.686 for Anjongan. The regression value indicates that the the growth of tinfoil barb was allometric negative, with an average factor condition ranged from 0.99 to 1.002. Length and weight relationship had determinant value (R2) ranged from 0.79 to 0.96, with the fecundity ranged from 20168 to 232.040 eggs from 9–45.5g of gonad weight. 

scholarly journals Aplikasi Microsoft Excel Dalam Penyelesaian Masalah Rata-rata Data Berkelompok

Matematika ◽  
2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Devy Andriyani ◽  
Erwin Harahap ◽  
Farid Hijri Badruzzaman ◽  
Muhammad Yusuf Fajar ◽  
Deni Darmawan
Keyword(s):  
Smart Device ◽  
Microsoft Excel ◽  
Digital Era ◽  
Data Application ◽  
Group Data ◽  
Average Group ◽  
Complex Calculation ◽  
Short Time

Abstrak. Era digital menuntut segala bentuk aktivitas dikerjakan dengan cepat, efektif, dan efisien, dengan pemanfaatan teknologi yang mutakhir. Pada era reformasi teknologi 4.0 saat ini, berbagai informasi dapat diperoleh dalam waktu yang singkat melalui perangkat pintar dengan aplikasi tertentu, salah satunya adalah aplikasi untuk menghitung nilai rata-rata. Penyelesaian masalah nilai rata-rata pada data berkelompok memerlukan suatu usaha perhitungan yang teliti dan kompleks. Pada artikel ini penulis menguraikan sebuah aplikasi untuk penyelesaian masalah perhitungan nilai rata-rata pada data berkelompok secara efektif, cepat, dan akurat dengan menggunakan software Microsoft Excel. Kata kunci: microsoft excel, rata-rata data berkelompok, aplikasi matematikaAbstract. Digital era can demand all of activity to working with quick, effective, and efficient with utilization a up to date’s technology. In the era of Reformation Technology 4.0, various information was obtained in a short time via smart device with particular application , one of them is application to calculate average. Finishing a average’s problem in group data can make a careful and complex calculation effort. In this article, the author outlines a application for completed a problem of calculate average for group data with effective, quick, and accurate with using a Microsoft ExcelKeywords : Microsoft Excel, average group data, application in mathematics

scholarly journals Analisis K-Medoids Clustering Dalam Pengelompokkan Data Imunisasi Campak Balita di Indonesia

2019 ◽  
Vol 1 ◽  
pp. 687
Author(s):  
Siti Sundari ◽  
Irfan Sudahri Damanik ◽  
Agus Perdana Windarto ◽  
Heru Satria Tambunan ◽  
Jalaluddin Jalaluddin ◽  
...  
Keyword(s):  
Data Processing ◽  
Virus Transmission ◽  
Clustering Method ◽  
Immunization Program ◽  
Data Grouping ◽  
Cluster 2 ◽  
High Cluster ◽  
Central Statistics

Measles is a contagious infections disease that attacks children caused by a virus. Transmission of measles from people through coughing and sneezing. Measles causes disability and death, so further threatment is needed. Measles immunization program that can inhibit the development of measles is one of the efforts in eradicating the disease. In this study the data used were sourced from the Central Statistics Agency National in 2013-2017. This study uses datamining techniques in data processing with K-Medoids algorithm. The K-Medoids method is a clustering method that functions to break datasets into groups. The advantages of this method are the ability to overcome the weaknesses of the K-Means method which is sensitive to outliers. Another advantage of this algorithm is that the results of the clustering process do not depend on the entry sequence of the dataset. The k-medoids clustering method can be applied to the data on the percentage of measles immunization can be identified based on province, so that the grouping of provinces based on these data. From the data grouping three clusters are obtained: low cluster (2 provinces), medium cluster (30 provinces) and high cluster (2 provinces) with the percentage of measles immunization in each of these provinces from data grouping in percentage. It is expected this research can provide information to the govermant about the data on grouping measles immunization for toddlers in Indonesia which has an impact on the distribution of immunization against measles toddlers in Indonesia.

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