scholarly journals Implementasi Algoritma Clustering Partitioning Around Medoid (PAM) dalam Clustering Virus MERS-Cov

2020 ◽  
Vol 5 (1) ◽  
pp. 70
Author(s):  
Septian Wulandari ◽  
Nurfidah Dwitiyanti
Keyword(s):  
Dna Sequences ◽  
Direct Contact ◽  
Clustering Algorithm ◽  
Deoxyribonucleic Acid ◽  
Literature Study ◽  
Silhouette Coefficient ◽  
The Common ◽  
Quantitative Descriptive ◽  
Respiratory Coronavirus ◽  
Cluster 2

<p><em>Th</em><em>e Middle East Respiratory Coronavirus (MERS-CoV) is a disease caused by a coronavirus. This virus is contagious, but its transmission is not as easy as the common cold, MERS-CoV virus is better susceptible to transmitting through direct contact, for example in people who care about the MERS-CoV virus without the need for virus protection. To determine the characteristics, the MERS-CoV disease virus can be identified by identifying DNA (deoxyribonucleic acid). One technique in understanding the characteristics of life is by grouping. Grouping can be done by grouping DNA into groups that have attributes and functions. The Clustering algorithm used in this study is Partitioning Around Medoid (PAM). This algorithm has the advantage that the results of the grouping process are not by following the order of entering the dataset and overcome sensitivity to noise and outliers. The purpose of this study is to implement the Partitioning Around Medoid (PAM) clustering algorithm in clustering the MERS-CoV virus. This research was conducted through a quantitative descriptive literature study. The implementation of the PAM algorithm on the MERS-CoV DNA sequence obtained 2 clusters with the highest silhouette coefficient value on the number of clusters 2, namely 0.61534. The number of members in Cluster 1 is 84 MERS-CoV DNA sequences and the number of members in Cluster 2 is 16 MERS-CoV DNA sequences.</em></p>

Scaled Fuzzy Graph for Cluster Analysis in DNA Sequence of Olfactory Receptors

2013 ◽  
Vol 8 (1) ◽  
pp. 57-70
Author(s):  
Satya Ranjan Dash ◽  
Satchidananda Dehuri ◽  
Uma Kant Sahoo
Keyword(s):  
Cluster Analysis ◽  
Dna Sequence ◽  
Simulation Study ◽  
Dna Sequences ◽  
Clustering Algorithm ◽  
Deoxyribonucleic Acid ◽  
Graph Model ◽  
Olfactory Receptors ◽  
Fuzzy Graph ◽  
Before And After

Olfactory receptors (ORs) are responsible for recognition of odor molecules. The deoxyribonucleic acid (DNA) sequences of these receptors are severely affected by local mutations. Therefore, to study the changes among affected and non-affected ORs, the authors attempted to use unsupervised learning (clustering) algorithm. In this paper, they have used a scaled fuzzy graph model for clustering to study the changes before and after the local mutation on DNA sequences of ORs. Their simulation study at the fractional dimensional level confirms its accuracy.

PERANCANGAN SISTEM INFORMASI INFENTARIS SPAREPART HANDPHONE BERBASIS PHP DAN MYSQL DI PLANET PHONE

2019 ◽  
Vol 3 (1) ◽  
pp. 49-61
Author(s):  
Fitriani Dwi Ratna Sari ◽  
Amin Suryana
Keyword(s):  
Information System ◽  
Data Collection ◽  
Data Processing ◽  
Inventory Data ◽  
Literature Study ◽  
Know How ◽  
Internet Connection ◽  
To Come ◽  
Quantitative Descriptive ◽  
Descriptive Method

Research that the author did aim to know how to design inventory system on Planet Phone.The method used is quantitative descriptive method. Data collection techniques used are literature study, observation, and interviews. From the research conducted found that there is a problem on inventory data processing. The process of inventory data processing only by writing using a general ledger. So this causes inaccuracies and delays in reports. Therefore the authors make the information system by using PHP and MySQL database. This system consists of inputting inventory data, inventory reports, sales reports and income reports. As for some suggestions given to tackle the problem is by connecting the system with internet connection, for employees more quickly and effectively in penginputan inventory data and owner can also know the sales reports and income reports more quickly without having to come directly to the store.

ANALISIS RETURN ON INVESTMENT (ROI) UNTUK MENILAI KINERJA KEUANGAN PADA PT. MITRA INVESTINDO, Tbk.

2021 ◽  
Vol 3 (1) ◽  
pp. 35-43
Author(s):  
Dedy Hardiansyah ◽  
Nurhayati Nurhayati
Keyword(s):  
Financial Performance ◽  
Return On Investment ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Literature Study ◽  
Descriptive Research ◽  
Analysis Technique ◽  
Research Population ◽  
Quantitative Descriptive

The purpose of this study is to find out how much Return On Investment (ROI) is to assess the financial performance of PT Mitra Investindo, Tbk. This type of quantitative descriptive research uses secondary data. Data collection techniques are documentation and literature study. Research population for 22 years from the start of listing on the Indonesia Stock Exchange 1997-2019. Then a sample of 10 years from 2010-2019 with purposive sampling technique. The data analysis technique used statistical analysis with a one-sample t-test. The results showed that the Return On Investment (ROI) to assess the financial performance of      PT Mitra Investindo, Tbk was in a bad condition because it was less than 30% of the expected.

Percutaneous Coronary Intervention Operator Profiles and Associations With In-Hospital Mortality

2021 ◽  
Author(s):  
Jacob A. Doll ◽  
Adam J. Nelson ◽  
Lisa A. Kaltenbach ◽  
Daniel Wojdyla ◽  
Stephen W. Waldo ◽  
...  
Keyword(s):  
Percutaneous Coronary Intervention ◽  
Hospital Mortality ◽  
Patient Outcomes ◽  
Clustering Algorithm ◽  
Practice Patterns ◽  
Coronary Intervention ◽  
Case Mix ◽  
Case Volume ◽  
Percutaneous Coronary ◽  
Cluster 2

Background: Percutaneous coronary intervention is performed by operators with differing experience, technique, and case mix. It is unknown if operator practice patterns impact patient outcomes. We sought to determine if a cluster algorithm can identify distinct profiles of percutaneous coronary intervention operators and if these profiles are associated with patient outcomes. Methods: Operators performing at least 25 annual procedures between 2014 and 2018 were clustered using an agglomerative hierarchical clustering algorithm. Risk-adjusted in-hospital mortality was compared between clusters. Results: We identified 4 practice profiles among 7706 operators performing 2 937 419 procedures. Cluster 1 (n=3345) demonstrated case mix and practice patterns similar to the national median. Cluster 2 (n=1993) treated patients with lower clinical acuity and were less likely to use intracoronary diagnostics, atherectomy, and radial access. Cluster 3 (n=1513) had the lowest case volume, were more likely to work at rural hospitals, and cared for a higher proportion of patients with ST-segment–elevation myocardial infarction and cardiogenic shock. Cluster 4 (n=855) had the highest case volume, were most likely to treat patients with high anatomic complexity and use atherectomy, intracoronary diagnostics, and mechanical support. Compared with cluster 1, adjusted in-hospital mortality was similar for cluster 2 (estimated difference, −0.03 [95% CI, −0.10 to 0.04]), higher for cluster 3 (0.14 [0.07–0.22]), and lower for cluster 4 (−0.15 [−0.24 to −0.06]). Conclusions: Distinct percutaneous coronary intervention operator profiles are differentially associated with patient outcomes. A phenotypic approach to physician assessment may provide actionable feedback for quality improvement.

No, I’m not… Chaucer? The Arabic motif in Troilus and Criseyde and Pushkin’s ‘The Prophet’ [‘Prorok’]

2021 ◽  
pp. 140-153
Author(s):  
A. A. Shapovalova
Keyword(s):  
Direct Contact ◽  
Common Source ◽  
Long Poem ◽  
Troilus And Criseyde ◽  
Potential Influence ◽  
Religious Texts ◽  
Common Motif ◽  
Courtly Romance ◽  
Genetic Source ◽  
The Common

The article discusses two works of literature: Troilus and Criseyde, a long poem written in the genre of courtly romance (1382–1386/1387) by G. Chaucer, and ‘The Prophet’ [‘Prorok’] (1826), a poem by A. Pushkin. The two works are compared due to a common motif: the opening of the chest and swapping of the heart as a sign of the person’s spiritual regeneration. In her comparative analysis of the two poems, the author attempts to identify their common source or the likelihood of direct contact — whether Pushkin had come across Chaucer’s work and borrowed the motif directly. As for the heart being replaced, it seems both poets may have been inspired by several biblical stories. Further analysis of the motif of the chest being opened suggests that the research should focus on the Arabic tradition alone and take into account the potential influence of Islamic religious texts on Pushkin as well as Chaucer. Relying on the available data about Russian and European relations with the Arabic world, the article hypothesises about the ways in which the motif in question could have reached each of the poets. The author names the Quran as the common genetic source of the two poems.

scholarly journals SISTEM APLIKASI BERBASIS OPTIMASI METODE ELBOW UNTUK PENENTUAN CLUSTERING PELANGGAN

JOUTICA ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 117 ◽  
Author(s):  
Elly Muningsih ◽  
Sri Kiswati
Keyword(s):  
Data Center ◽  
Clustering Algorithm ◽  
Visual Basic ◽  
Customer Management ◽  
Number Of Clusters ◽  
Transaction Data ◽  
Development Method ◽  
Popular Method ◽  
Or Groups ◽  
Cluster 2

Customer is a very important asset for the company. Having customers who are loyal to the company is an absolute and important for the progress of the company. This study aims to help companies, especially in the online shop to create a better customer management by identifying and grouping customers into several clusters or groups to know the characteristics of their loyalty to the company. The method used in this research is K-Means method which is one of the best and most popular method in clustering algorithm. To overcome the weakness of the K-Means method in determining the number of clusters, we use the Elbow method where this method gets the comparison of the number of clusters added by calculating the SSE (Sum of Square Error) of each cluster value. This research starts from collecting the necessary data and will be processed. From total transaction data 478 then done cleaning of data and result 73 data. Then the data processed with RapidMiner software from Cluster 2 up to 10 to search the data center of each cluster. From the calculated SSE value found that the best number of clusters is 3. The end result of the research is a Visual Basic based application program that is expected to provide ease in grouping or clustering customers. Software development method using Waterfall method.

scholarly journals The Effectiveness of Implementing Law Number 23 of 2004 on Elimination of Violence in Household: Case Study in Makassar City

2020 ◽  
Vol 2 (3) ◽  
pp. 1-11
Author(s):  
A. Dewi Vitasari ◽  
Hambali Thalib ◽  
Sufirman Rahman
Keyword(s):  
Data Analysis ◽  
Law Enforcement ◽  
Environmental Factors ◽  
Literature Study ◽  
Factors Affecting ◽  
Analysis Techniques ◽  
Analysis Technique ◽  
Quantitative Data Analysis ◽  
Quantitative Descriptive

This study aims to determine the effectiveness of implementing Law Number 23 of 2004 on Elimination of Violence in Household, as well as the factors that influence its enforcement. This type of research is empirical legal research with a quantitative descriptive in nature. This research was conducted in Makassar City to be precise at the Makassar City Police. The data collection techniques used in this study were questionnaires, documentation, and literature study. The data analysis technique used is quantitative data analysis techniques. The results showed that the implementation of Law No. 23 of 2004 in Makassar City is still considered less effective. Factors affecting the effectiveness of the implementation of Law No. 23 of 2004 in Makassar City consists of several factors, namely: legal factors; law enforcement factors; supporting facility factors; environmental factors; and cultural factors. in addition, environmental factors are the biggest factor affecting the effectiveness of the implementation of Law No. 23 of 2004. It is hoped that the police will further strengthen environmental factors in order to increase the effectiveness of the implementation of Law No. 23 of 2004 in the future.

scholarly journals Clustering Students' Interest Determination in School Selection Using the K-Means Clustering Algorithm Method

2020 ◽  
pp. 68-75
Author(s):  
Suhefi Oktarian ◽  
Sarjon Defit ◽  
Sumijan
Keyword(s):  
Clustering Algorithm ◽  
School Selection ◽  
Cluster 2

Pendidikan merupakan satu diantara fokus utama program kerja Pemerintah Kabupaten Indragiri Hilir. Berdasarkan data Badan Pusat Statistik Daerah kabupaten Indragiri tahun 2019 memaparkan, tingginya tingkat minat siswa dalam mengenyam bangku sekolah adalah pada jenjang SD dan SMP. K-means Clustering merupakan salah satu Teknik pengeolompokan data dengan cara membagi data yang ada ke dalam bentuk satu atau lebih cluster. Pengelompokan sekolah berdasarkan minat siswa merupakan hal penting dikarenakan pada tingkat SMA minat siswa dalam mengenyam pendidikan sudah berkurang sehingga di perlukan informasi sekolah mana yang sangat diminati, cukup diminati dan kurang diminati oleh siswa pada tingkat SMP ketika setelah selesai dari pendidikan SD. Penelitian ini bertujuan membantu pihak Dinas Pendidikan dalam proses pengambilan keputusan untuk menentukan sekolah mana yang paling banyak diminati oleh siswa guna sebagai acuan dalam pembangunan baik dari segi kualitas maupun kuantitas. Data yang digunakan dalam penelitian ini adalah data Dapodikdasmen tahun 2019. pengolahan data dalam penelitian ini menggunakan metode K-means Clustering dengan jumlah 3 cluster yaitu cluster 0 (C0) kurang diminati, Cluster 1 (C1) cukup diminati, cluster 2 (c2) sangat diminati siswa dalam memilih sekolah. Hasil dari proses clustering dengan 2 kali iterasi menyatakan bahwa untuk cluster 0 berjumlah 6 data sekolah, untuk cluster 1 berjumlah 3 data sekolah cluster 2 berjumlah 1 data sekolah.

scholarly journals Modified HuffBit Compress Algorithm – An Application of R

2018 ◽  
Vol 15 (3) ◽  
Author(s):  
Nahida Habib ◽  
Kawsar Ahmed ◽  
Iffat Jabin ◽  
Mohammad Motiur Rahman
Keyword(s):  
Dna Sequences ◽  
Binary Tree ◽  
Deoxyribonucleic Acid ◽  
Repetitive Sequences ◽  
Huffman Codes ◽  
R Language ◽  
Living Organisms ◽  
Encoding Method ◽  
Dna Sequence Compression ◽  
Sequence Compression

Abstract The databases of genomic sequences are growing at an explicative rate because of the increasing growth of living organisms. Compressing deoxyribonucleic acid (DNA) sequences is a momentous task as the databases are getting closest to its threshold. Various compression algorithms are developed for DNA sequence compression. An efficient DNA compression algorithm that works on both repetitive and non-repetitive sequences known as “HuffBit Compress” is based on the concept of Extended Binary Tree. In this paper, here is proposed and developed a modified version of “HuffBit Compress” algorithm to compress and decompress DNA sequences using the R language which will always give the Best Case of the compression ratio but it uses extra 6 bits to compress than best case of “HuffBit Compress” algorithm and can be named as the “Modified HuffBit Compress Algorithm”. The algorithm makes an extended binary tree based on the Huffman Codes and the maximum occurring bases (A, C, G, T). Experimenting with 6 sequences the proposed algorithm gives approximately 16.18 % improvement in compression ration over the “HuffBit Compress” algorithm and 11.12 % improvement in compression ration over the “2-Bits Encoding Method”.

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