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All Journal POSITIF Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Ilmu Pendidikan: Jurnal Kajian Teori dan Praktik Kependidikan Jurnal Pilar Nusa Mandiri Indonesian Journal of Applied Statistics Desimal: Jurnal Matematika MUST: Journal of Mathematics Education, Science and Technology Adi Widya : Jurnal Pengabdian Masyarakat Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Jurnal Ilmiah Sinus Jurnal Karinov Jurnal PAUD: Kajian Teori dan Praktik Pendidikan Anak Usia Dini Square : Journal of Mathematics and Mathematics Education Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Journal of Mathematics Education and Science Indonesian Journal of Mathematics and Natural Science Education International Journal of English Linguistics, Literature, and Education (IJELLE) Jurnal Pengabdian Masyarakat IPTEK Postulat : Jurnal Inovasi Pendidikan Matematika Journal of Practical Computer Science (JPCS) prosiding seminar nasional Abdi Makarti Euclid International Journal of Trends in Mathematics Education Research (IJTMER) Journal of Technology, Mathematics and Social Science (J'THOMS) Jurnal Pengabdian Masyarakat Ilmu Komputer Indonesian Journal of Mathematics and Natural Science Education Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) International Journal of Computing Science and Applied Mathematics-IJCSAM
Retno Tri Vulandari
STMIK Sinar Nusantara
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Journal : Indonesian Journal of Applied Statistics

 1 
Classification of Human Development Index Using K-Means Retno Tri Vulandari; Sri Siswanti; Andriani Kusumaningrum Kusumawijaya; Kumaratih Sandradewi
Indonesian Journal of Applied Statistics Vol 2, No 1 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i1.28566

Abstract

Human development progress in Central Java. It is characterized by a continued rise in the human development index (HDI) of Central Java. HDI is an important indicator for measuring success in the effort to build the quality of human life. HDI explains how residents can access the development results in obtaining a long and healthy life, knowledge, education, decent standard of living and so on. HDI is affected by four factors, namely life expectancy, expected years of schooling, means years of schooling, and expenditure per capita. Currently the Central bureau of statistics do grouping HDI, using calculation formula then known how the value HDI each regency or city in Central Java. In this research we classified the regency or city in Central Java based on the HDI be high, middle, and under estimate area. We used cluster analysis. Cluster analysis is a multivariate technique which has the main purpose to classify objects based on their characteristics. Cluster analysis classifies the object, so that each object that has similar characteristics to be clumped into a single cluster (group). One of the cluster analysis method is k-means. The result of this research, there are three groups, high estimate area, middle estimate area, and under estimate area. The first group or the under estimate area contained 12 regencies, namely Cilacap, Purbalingga, Purworejo, Wonosobo, Grobogan, Blora, Rembang, Pati, Jepara, Demak, Pekalongan, and Brebes. The second group or the middle estimate area contained 8 regencies, namely Banjarnegara, Kebumen, Magelang, Temanggung, Wonogiri, Batang, Pemalang, and Tegal. The third group or the high estimate area contained 11 regencies, namely Banyumas, Kudus, Boyolali, Klaten, Sukoharjo, Karanganyar, Sragen, Semarang, Kendal, Surakarta, and Salatiga.Keywords : cluster analysis, k-means, the human development index.
Application of Analytic Hierarchy Process and Weighted Product Methods in Determining the Best Employees Sri Harjanto; Setiyowati Setiyowati; Retno Tri Vulandari
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.44059

Abstract

Abstract. Employees are one of the company's assets that must be managed properly. Therefore the selection of the best employees is now needed. The problem faced in determining the best and qualified employees is that there are still no standards in assessing only one person subjectively in determining the best employee, which consequently lacks appropriate or objective results. To provide rewards for the best employees, we need a system to support the decisions of the best employees who deserve to receive rewards to be on target. The purpose of this research is to design and build a decision support system application in determining the best employees using the analytic hierarchy process and weighted product methods. Stages of software development of the Software Development Life Cycle (SDLC) uses a waterfall, that is data analysis, system design, construction, coding, testing and implementation. The results of this process are in the form of calculation applications that have been obtained from the analytic hierarchy process and weighted product methods in determining the best employee. The result gives an accuracy rate of 82.3%.Keywords: analytic hierarchy process, weighted product, decision support system, employees
Application of K-Means Clustering in Mapping of Central Java Crime Area Retno Tri Vulandari; Wawan Laksito Yuly Saptomo; Danar Wijaya Aditama
Indonesian Journal of Applied Statistics Vol 3, No 1 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i1.40984

Abstract

Crimes occur in many places and cause complex problems that have widespread impacts on all levels of society. Crime is related to several factors including crime index, the ratio of the number of police to the population, population density and poverty rates. In this study trying to develop an information system that is able to display and map crime-prone areas in Central Java. Based on these factors, it is used to classify regions in Central Java, namely the category of safe, quite vulnerable, vulnerable and very vulnerable. K-Means clustering method, is very suitable to be used in predicting and grouping which areas are included in the 4 categories. The formulation of the problem is to find out areas prone to crime in Central Java. Based on the results, there are 11 regions with safe categories, 4 areas with quite vulnerable categories, 13 regions with vulnerable categories and 6 regions with very vulnerable categories.Keywords : K-Means clustering, mapping, Central Java,  criminality, crime area.
Co-Authors Afan Lathofy Ahmad Samawi Al Fiyan Nizaela F Andriani Kusumaningrum Bayu Tristanto Bebas Widada Bentar Putra Pamungkas Danar Wijaya Aditama Dhian Dwi Hermawan Dhian Dwi Hermawan Didik Nugroho Dorestin, Nacita Agnes Dwi Handoko Dwi Handoko Dwi Rema wati Dwi Remawati Dwi Tri Laksono Eny Nur Aisyah Erinsyah Aditya Nugroho Putro Fadel Thoriq Nur Muhammad FADILA, FATIN Febriyanti, Renita Hakam Febtadianrano Putro Hendro Wijayanto Hendro Wijayanto Heri Setyawan Hermawan, Dhian Dwi I Made Seken Intan Rofiah Kumaratih Sandradewi Kustanto, Kustanto Kusumaningrum, Andriani Kusumawijaya, Andriani Kusumaningrum Lathofy, Afan Lestari, Zannuba Anugrah Indah Mita Purwati MUHAMMAD HASBI Muhammad Hasbi Muhammad Yusuf Mujirahayu Meyliana, Nirma Nacita Agnes Dorestin Nacita Agnes Dorestin Nugraheni, Ria Pertiwi Nugroho, Zulkifly Setyo Nur Fitrina Parwitasari, Tika Andarasni paulus harsadi Pravitasari, Suryanti Galuh Putri Pertiwi, Ina Raden Arie Febrianto Ragil Prasojo Raharja, Bayu Dwi Rahmatika Restu Utami, Widya Ria Pertiwi Nugraheni Rimawati, Elistya Sakti, Dicky Cahyono Saptomo, Wawan Laksito Yuly Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Sri Hariyati Fitriasih Sri Harjanto Sri Harjanto Sri Harjanto Sri Siswanti Sulistiyowati, Amin Sumanto Suryadi Suryadi Sutanto Sutrima Sutrima Teguh Susyanto Teguh Susyanto Tika Andarasni Parwitasari Tri Irawati, Tri Tristanto, Bayu Usep Kustiawan W, Yustina Retno Waskitho, Anggit Widhi wati, Dwi Rema Wawan Laksito YS Wawan Laksito Yuly Saptomo Widada, Bebas Wijayanto, Hendro Wuri Astuti Yehoshua Yehoshua Yustina Retno W Yustina Retno Wahyu Utami