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All Journal Semeton Mathematics Journal IJASDS: Indonesian Journal of Applied Statistics and Data Science
Asri, Adis Tia Juli Agil
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Economics, Econometrics & Finance Environmental Science Mathematics Public Health Social Sciences

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Pengendalian Kualitas Produk Spon Kasur Menggunakan Exponentially Weighted Moving Average (Ewma) pada UD. Celcius Gegutu Timur Lingking, Fransiska Prisilia; Harsyiah, Lisa; Sulistyowati, Emmy Dyah; Asri, Adis Tia Juli Agil
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i1.273

Abstract

Problems that arise at UD. Celsius, one of the manufacturers of sponge mattress products in the East Gegutu area, said that differences in product weight will cause a decrease in product quality. Consequently, here, quality is of primary concern. Because the Exponentially Weighted Moving Average (EWMA) control chart can detect small average changes, this study aims to examine the quality control of mattress sponge products using this chart. The information used relates to the mass of a mattress sponge product measuring 160×120×25 cm, with four variables, namely X_1,X_2,X_3 and X_4, Quality control in this research uses a weighting factor value of  = 0.4. Based on the research results, the assumption that is not fulfilled is the assumption of data randomness, so that the EWMA control chart pattern formed shows that the data is not statistically controlled. However, there is no data that is out of control, so in this study the Average Run Length (ARL) value of 27,204 indicates that there will be data that is first out of control, namely the 27th or 28th data. And the results of the capability analysis of the process show that the production process is not capable because the values of Cp=0.3432 and Cpk=0.3373 where the values of Cp,Cpk<1, this is due to the influencing factors, namely man, machine, material and method factors.
Analisis Cluster Untuk Pengelompokan Provinsi Di Indonesia Berdasarkan Tingkat Kemiskinan Menggunakan Metode Average Linkage Saputra, Dede; Ardania, Azrianti; Putri, Syaftirridho; Asri, Adis Tia Juli Agil; Harsyiah, Lisa
Indonesian Journal of Applied Statistics and Data Science Vol. 1 No. 1 (2024): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v1i1.5446

Abstract

Poverty is a major economic and social issue in Indonesia because it is a serious problem that can affect social welfare. Poverty is influenced by many factors including school enrollment rate, life expectancy, gross regional domestic product, human development index and open unemployment rate. Cluster analysis is a technique in multivariate statistics where objects are grouped based on proximity or similarity of properties so that objects that have close proximity (similar properties) will be in the same group (cluster). The purpose of this study is to cluster provinces in Indonesia based on poverty levels using the average linkage method. The results of this study obtained 5 clusters, where cluster 1 consists of Nanggroe Aceh Darussalam, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung Islands, Central Java, East Java, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, North Kalimantan, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku and West Papua. Cluster 2 consists of Riau Islands, West Java, Banten and North Sulawesi. Cluster 3 consists of DKI Jakarta and East Kalimantan. Cluster 4 consists of DI Yogyakarta and the last cluster consists of Papua.
Co-Authors Ardania, Azrianti Emmy Dyah Sulistyowati, Emmy Dyah Harsyiah, Lisa Lingking, Fransiska Prisilia Putri, Syaftirridho Saputra, Dede