scholarly journals PERSEBARAN LOKASI PRAKTEK BIDAN MELALUI PENERAPAN SISTEM INFORMASI GEOGRAFIS MENGGUNAKAN METODE CLUSTERING

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Andi Setiawan ◽  
Sri Nining ◽  
Tri Ginanjar Laksana
Keyword(s):  
Quality Of Service ◽  
Pregnant Women ◽  
Data Clustering ◽  
Measurement Data ◽  
Clustering Methods ◽  
Clustering Method ◽  
Service Clustering ◽  
Segment Data ◽  
Vast Area

Distribution of midwife practice pomegranate (quality of service) in Cirebon is difficult to know where the location of the practice because of the vast area of Cirebon. Then, the number of pregnant women who are less get help quickly (giving birth without medical assistance) because of ignorance location midwife practice pomegranate (quality of service) nearby. And the number of midwives pomegranate (quality of service) has not cooperated with the insurance BPJS to perform payment transactions. This study uses a clustering method, which can segment data clustering method, which is used to facilitate information retrieval midwife pomegranate (quality of service). Clustering methods have representation stage pattern, the selection traits or characteristics, pattern proximity, distance measurement, data obtained from IBI (Indonesian Midwives Association) and the tools used: phpMyAdmin, notepad ++, xampp, GoogleMapApi, Dreamwaver. This system can be expected to map the location of the practice of midwives pomegranate (quality of service) in the district of Cirebon, can find the nearest location midwife pomegranate (quality of service), can find pomegranate midwives who work with BPJS to perform payment transactions. Then, hopefully it can help people in handling pregnant women rapidly. And, is expected to reduce maternal and child mortality.

scholarly journals KOMPARASI METODE CLUSTERING K-MEANS DAN K-MEDOIDS DENGAN MODEL FUZZY RFM UNTUK PENGELOMPOKAN PELANGGAN

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Elly Muningsih - AMIK BSI Yogyakarta
Keyword(s):  
Data Clustering ◽  
Small Data ◽  
Clustering Methods ◽  
Monetary Model ◽  
Clustering Method ◽  
Online Sales ◽  
Rfm Model ◽  
Potential Customers ◽  
Cluster 2 ◽  
Better Than

Abstract ~ The K-Means method is one of the clustering methods that is widely used in data clustering research. While the K-Medoids method is an efficient method used for processing small data. This study aims to compare two clustering methods by grouping customers into 3 clusters according to their characteristics, namely very potential (loyal) customers, potential customers and non potential customers. The method used in this study is the K-Means clustering method and the K-Medoids method. The data used is online sales transaction. The clustering method testing is done by using a Fuzzy RFM (Recency, Frequenty and Monetary) model where the average (mean) of the third value is taken. From the data testing is known that the K-Means method is better than the K-Medoids method with an accuracy value of 90.47%. Whereas from the data processing carried out is known that cluster 1 has 16 members (customers), cluster 2 has 11 members and cluster 3 has 15 members. Keywords : clustering, K-Means method, K-Medoids method, customer, Fuzzy RFM model. Abstrak ~ Metode K-Means merupakan salah satu metode clustering yang banyak digunakan dalam penelitian pengelompokan data. Sedangkan metode K-Medoids merupakan metode yang efisien digunakan untuk pengolahan data yang kecil. Penelitian ini bertujuan untuk membandingkan atau mengkomparasi dua metode clustering dengan cara mengelompokkan pelanggan menjadi 3 cluster sesuai dengan karakteristiknya, yaitu pelanggan sangat potensial (loyal), pelanggan potensial dan pelanggan kurang (tidak) potensial. Metode yang digunakan dalam penelitian ini adalah metode clustering K-Means dan metode K-Medoids. Data yang digunakan adalah data transaksi penjualan online. Pengujian metode clustering yang dilakukan adalah dengan menggunakan model Fuzzy RFM (Recency, Frequenty dan Monetary) dimana diambil rata-rata (mean) dari nilai ketiga tersebut. Dari pengujian data diketahui bahwa metode K-Means lebih baik dari metode K-Medoids dengan nilai akurasi 90,47%. Sedangkan dari pengolahan data yang dilakukan diketahui bahwa cluster 1 memiliki 16 anggota (pelanggan), cluster 2 memiliki 11 anggota dan cluster 3 memiliki 15 anggota. Kata kunci : clustering, metode K-Means, metode K-Medoids, pelanggan, model Fuzzy RFM.

On Fuzzy Non-Metric Model for Data with Tolerance and its Application to Incomplete Data Clustering

2016 ◽  
Vol 20 (4) ◽  
pp. 571-579 ◽  
Author(s):  
Yasunori Endo ◽  
◽  
Tomoyuki Suzuki ◽  
Naohiko Kinoshita ◽  
Yukihiro Hamasuna ◽  
...  
Keyword(s):  
Data Clustering ◽  
Incomplete Data ◽  
Clustering Algorithm ◽  
Uncertain Data ◽  
Data Sets ◽  
Membership Degree ◽  
Clustering Methods ◽  
Clustering Method ◽  
Numerical Examples ◽  
Metric Model

The fuzzy non-metric model (FNM) is a representative non-hierarchical clustering method, which is very useful because the belongingness or the membership degree of each datum to each cluster can be calculated directly from the dissimilarities between data and the cluster centers are not used. However, the original FNM cannot handle data with uncertainty. In this study, we refer to the data with uncertainty as “uncertain data,” e.g., incomplete data or data that have errors. Previously, a methods was proposed based on the concept of a tolerance vector for handling uncertain data and some clustering methods were constructed according to this concept, e.g. fuzzyc-means for data with tolerance. These methods can handle uncertain data in the framework of optimization. Thus, in the present study, we apply the concept to FNM. First, we propose a new clustering algorithm based on FNM using the concept of tolerance, which we refer to as the fuzzy non-metric model for data with tolerance. Second, we show that the proposed algorithm can handle incomplete data sets. Third, we verify the effectiveness of the proposed algorithm based on comparisons with conventional methods for incomplete data sets in some numerical examples.

scholarly journals A review on data clustering using spiking neural network (SNN) models

2019 ◽  
Vol 15 (3) ◽  
pp. 1392
Author(s):  
Siti Aisyah Mohamed ◽  
Muhaini Othman ◽  
Mohd Hafizul Afifi
Keyword(s):  
Neural Network ◽  
Data Clustering ◽  
Network Clustering ◽  
Complex Data ◽  
Spiking Neural Network ◽  
Clustering Methods ◽  
Clustering Method ◽  
Static Data ◽  
Clustering Approach ◽  
Clustering Problems

The evolution of Artificial Neural Network recently gives researchers an interest to explore deep learning evolved by Spiking Neural Network clustering methods. Spiking Neural Network (SNN) models captured neuronal behaviour more precisely than a traditional neural network as it contains the theory of time into their functioning model [1]. The aim of this paper is to reviewed studies that are related to clustering problems employing Spiking Neural Networks models. Even though there are many algorithms used to solve clustering problems, most of the methods are only suitable for static data and fixed windows of time series. Hence, there is a need to analyse complex data type, the potential for improvement is encouraged. Therefore, this paper summarized the significant result obtains by implying SNN models in different clustering approach. Thus, the findings of this paper could demonstrate the purpose of clustering method using SNN for the fellow researchers from various disciplines to discover and understand complex data.

scholarly journals Teleconsultation demand classification and service analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenjia Chen ◽  
Jinlin Li
Keyword(s):  
Hierarchical Clustering ◽  
Cosine Similarity ◽  
Graph Representation ◽  
Clustering Methods ◽  
Clustering Method ◽  
Network Graph ◽  
Before And After ◽  
Hierarchical Clustering Methods ◽  
Demand Classification

Abstract Background To enhance teleconsultation management, demands can be classified into different patterns, and the service of each pattern demand can be improved. Methods For the effective teleconsultation classification, a novel ensemble hierarchical clustering method is proposed in this study. In the proposed method, individual clustering results are first obtained by different hierarchical clustering methods, and then ensembled by one-hot encoding, the calculation and division of cosine similarity, and network graph representation. In the built network graph about the high cosine similarity, the connected demand series can be categorized into one pattern. For verification, 43 teleconsultation demand series are used as sample data, and the efficiency and quality of teleconsultation services are respectively analyzed before and after the demand classification. Results The teleconsultation demands are classified into three categories, erratic, lumpy, and slow. Under the fixed strategies, the service analysis after demand classification reveals the deficiencies of teleconsultation services, but analysis before demand classification can’t. Conclusion The proposed ensemble hierarchical clustering method can effectively category teleconsultation demands, and the effective demand categorization can enhance teleconsultation management.

scholarly journals PANTSA Influence in grouping Mixed and Incomplete Data

2019 ◽  
Vol 9 (2) ◽  
pp. 579-583
Keyword(s):  
Experimental Evidence ◽  
Data Clustering ◽  
Incomplete Data ◽  
Clustering Algorithms ◽  
Numerical Data ◽  
Clustering Methods ◽  
High Quality ◽  
Before And After

Obtaining high quality groups and processing mixed and incomplete data (DMI) are still problems in the data clustering. Recently a method was proposed that improves the results obtained by clustering algorithms, the PAntSA; but this was only designed and tested for numerical data. For this reason, this paper analyzes the influence of applying the PAntSA in the performance of DMI restricted clustering algorithms. For this, the results of different algorithms are compared before and after applying the PAntSA. The comparisons made provide experimental evidence that the PAntSA algorithm improves the quality of the groups obtained by traditional DMI clustering methods.

scholarly journals CLG clustering for dropout prediction using log-data clustering method

2021 ◽  
Vol 10 (3) ◽  
pp. 764
Author(s):  
Agung Triayudi ◽  
Wahyu Oktri Widyarto ◽  
Lia Kamelia ◽  
Iksal Iksal ◽  
Sumiati Sumiati
Keyword(s):  
Data Mining ◽  
Data Clustering ◽  
Statistical Data ◽  
Source Code ◽  
Educational Data Mining ◽  
Mining Machine ◽  
Clustering Methods ◽  
Clustering Method ◽  
Log Data ◽  
Cluster Data

<span lang="EN-US">Implementation of data mining, machine learning, and statistical data from educational department commonly known as educational data mining. Most of school systems require a teacher to teach a number of students at one time. Exam are regularly being use as a method to measure student’s achievement, which is difficult to understand because examination cannot be done easily. The other hand, programming classes makes source code editing and UNIX commands able to easily detect and store automatically as log-data. Hence, rather that estimating the performance of those student based on this log-data, this study being more focused on detecting them who experienced a difficulty or unable to take programming classes. We propose CLG clustering methods that can predict a risk of being dropped out from school using cluster data for outlier detection.</span>

scholarly journals Measurement of clustering effectiveness for document collections

2022 ◽  
Author(s):  
Meng Yuan ◽  
Justin Zobel ◽  
Pauline Lin
Keyword(s):  
Information Retrieval ◽  
Measurement Techniques ◽  
High Dimensionality ◽  
Clustering Methods ◽  
Clustering Method ◽  
Similar Material ◽  
Document Collections ◽  
Clustering Techniques

AbstractClustering of the contents of a document corpus is used to create sub-corpora with the intention that they are expected to consist of documents that are related to each other. However, while clustering is used in a variety of ways in document applications such as information retrieval, and a range of methods have been applied to the task, there has been relatively little exploration of how well it works in practice. Indeed, given the high dimensionality of the data it is possible that clustering may not always produce meaningful outcomes. In this paper we use a well-known clustering method to explore a variety of techniques, existing and novel, to measure clustering effectiveness. Results with our new, extrinsic techniques based on relevance judgements or retrieved documents demonstrate that retrieval-based information can be used to assess the quality of clustering, and also show that clustering can succeed to some extent at gathering together similar material. Further, they show that intrinsic clustering techniques that have been shown to be informative in other domains do not work for information retrieval. Whether clustering is sufficiently effective to have a significant impact on practical retrieval is unclear, but as the results show our measurement techniques can effectively distinguish between clustering methods.

Assessment of patient satisfaction and perception of quality of antenatal care services among pregnant women attending antenatal clinics at a secondary health care facility in Anambra State, Nigeria.

2021 ◽  
Vol 3 (1) ◽  
pp. 025-034
Author(s):  
Chigozie Joseph Ezeoke ◽  
Onyeka Chukwudalu Ekwebene ◽  
Tyotswam Simeone Yanmeer ◽  
Chioma Favour Ekwebene ◽  
Chigbo Chisom God’swill ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Patient Satisfaction ◽  
Child Health ◽  
Antenatal Care ◽  
Pregnant Women ◽  
Rural Areas ◽  
Anambra State ◽  
Care Services ◽  
And Child Health

Introduction: Prenatal care is an important component of maternal care worldwide more so in sub-Saharan Africa. Methodology: This work is a cross-sectional descriptive study carried out among 170 pregnant women attending antenatal clinic in health facilities in Ekwulobia, Anambra state. Convenience sampling technique was used in this study. The study instrument was a semi structured interviewer administered questionnaire which was developed according to the objectives of the study. In this study we evaluated patient waiting time, pregnancy outcome, quality of care, attitude of staff and facility neatness as parameters for measuring patient satisfaction, we also evaluated quality of service, attitude of staff, proximity to ANC centre, waiting time and cost as determinants of ANC use. Result: The study showed a demonstration of good knowledge of ANC and its importance in maternal and child health, 65.6% were aware of first trimester has the most appropriate time for ANC booking. A high level of satisfaction was recorded among the participants, 65.6% rated the ANC services as very good and 30.3% rated the service as good. Conclusion: Pregnant women in rural areas in eastern Nigeria receive quality and accessible antenatal care services and majority of the women are satisfied with the quality of service. Efforts to improve maternal and child health status in Eastern Nigeria is yielding fruit especially in rural areas. It is recommended that similar studies studies be conducted in other parts for the country to discover the conditions of ANC use and i effects and compare the factors that influence ANC use

Analisis Kualitas Pelayanan Dalam Pelaksanaan Tera Dan Tera Ulang Alat Ukur, Timbang, Takar Dan Perlengkapannya (UTTP) Pada Bidang Perdagangan Dinas Koperasi, Perindustrian Dan Perdagangan Kabupaten Pacitan

2016 ◽  
Vol 3 (2) ◽  
pp. 159-173
Author(s):  
Susi Minarsih ◽  
Ary Sutrischastini
Keyword(s):  
Quality Of Service ◽  
Service Quality ◽  
Level Of Service ◽  
Research Use ◽  
Validity And Reliability ◽  
Analysis Instrument ◽  
Service Execution ◽  
Traditional Market ◽  
Convenience Sampling

The aims of this study are to measure the level of service quality and how to improve the quality of service execution in re-measurement tera and tera of UTTP in Commerce On duty Co-Operation, Industrial and Commerce Of Sub-Province of Pacitan. This research’s object is traditional market of Minulyo Pacitan as mains market in Sub-Province of Pacitan with 100 perpetrator people of sample as user/owner of UTTP (ukur,timbang, takar, dan perlengkapannya) with method intake of sampel by Convenience Sampling. The technique of collecting data uses questionnaires and direct interview. This research use qualitative analysis instrument test of validity and reliability to know valid or not and reliabel or not about the questions of questionnaire. Then, this research was done with Servqual method as instrument to do measurement of service quality. The measurement of service quality in Servqual method pursuant to five service dimension that is tangibles, responsiveness, realibility, assurance, and empathy. This research will be measured of gap 5 that is difference among performance and its expectation. Ad for yielded gap from a enumeration of Servqual 5 gap, -146 progressively lower him mount the quality of given service activities. Therefore, its needs the existence of priority repair of service quality, in this case is service of remeasurement tera and tera of UTTP at biggest difference or gap that is at variable of Responsiveness ( Energy Listen carefully) and attribute that has smallest difference that is – 0.44 at dimension question of variable of Tangibles ( Evidence Physical). Keyword: Quality Of Service, Method of Service Quality.

PENGARUH KUALITAS PELAYANAN DAN PROMOSI TERHADAP PERLUASAN PANGSA PASAR PRODUK DANA TALANGAN HAJI DI BANK SYARIAH MANDIRI KCP UJUNGBERUNG DAN KCP RANCAEKEK BANDUNG

2018 ◽  
Vol 2 (1) ◽  
pp. 1-15
Author(s):  
Intan Nurrachmi
Keyword(s):  
Quality Of Service ◽  
Service Quality ◽  
Market Share ◽  
Significant Influence ◽  
Strong Correlation ◽  
T Test ◽  
Market Expansion ◽  
Difference Constraints ◽  
Branch Office

This study departs from the hajj bailout financing facility which is a booming product because of the customer's interest, but in this case there is a difference in the target achievement between Bank Syariah Mandiri (BSM) Ujungberung KCP which is less successful in improving the hajj bailout products while the Rancaekek KCP is very superior in one consolidation Ahmad Yani Branch Office Bandung. This is what is interesting for researchers to carry out this research, the difference constraints include service quality and promotion factors. This phenomenon raises problems that must be examined, namely how the influence of service quality and promotion of market share expansion products hajj bailouts at Bank Syariah Mandiri KCP Ujungberung and KCP Rancaekek Bandung. This study aims academically to contribute in the study of Islamic economics in worksheets, especially the quality of service and promotion of market share expansion and practically expected to be able to provide input to all employees of BSM KCP Ujungberung regarding the quality of service and promotion of market expansion of bailout products. Hajj that has been successfully carried out by BSM KCP Rancaekek.The conclusion of this study is that there is a significant influence of service quality on the expansion of market share by 53.3% with a strong correlation of 0.730 and through t test, where t counts at 8.245 (> t table), then H_0 is rejected and H_i is accepted. Furthermore, there is a significant influence of promotion on the expansion of market share by 30.3% with a moderate / sufficient correlation of 0.550 through t test, where t counts is 4.219 (> t table), then H_ (0) is rejected and H_i is accepted. Then there is a significant influence of service quality and promotion simultaneously to the expansion of market share by 60.6% and a strong correlation of 0.784 and through Test F, where F count is 67.023 (> F table), then 〖H〗 _ ( 0) rejected and H_i accepted.

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