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Journal : Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika

ANALISIS CLUSTER UNTUK MENGELOMPOKKAN PENGGUNAAN KARTU PERDANA SELULER DI UNIVERSITAS BINA BANGSA : Survei Mahasiswa Jurusan Pendidikan Matematika Ajeng Afifah Muhartini; Tanti Febriati; Sri Sukmawati
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 2 No. 1 (2022): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (259.433 KB) | DOI: 10.46306/bay.v2i1.25

Abstract

The development of technology and communication has led to increasing competition, especially in the field of marketing, one of which is in the cellular phone cards business. There are several companies that innovate in issuing cellular card products with their respective advantages to attract consumers' interest, be it the phone cards, postpaid cards or internet quota cards. In marketing segmentation, the decision to purchase starter packs by customers or buyers based on the benefits or benefits obtained is certainly different. The purpose of this study was to classify the types of starter packs used by students of the Mathematics Education Department at Bina Bangsa University based on their marketing. This research is a quantitative research with survey method with Cluster Analysis. Cluster analysis used is the Hierarchy Method using agglomerative grouping procedures. The results obtained in the calculation of the euclidean distance between Telkomsel Cards and Axis Cards is 542.76 while the euclidean distance between Telkomsel Cards and XL Cards is 486.34, for the euclidean distance between Telkomsel Cards and Three Cards is 671.31 while the euclidean distance between Telkomsel Cards and Indosat Cards is 809.13. The conclusion is that there are 2 clusters where the grouping of starter packs into 2 clusters has the composition or number of groups of each cluster. The minimum is cluster 1 which consists of only 1 starter card and the most is cluster 2 which consists of 5 starter cards
ANALISIS PENGARUH JENIS KELAMIN, TINGKAT SEMESTER DAN MEDIA SOSIAL TERHADAP IPK MAHASISWA DENGAN PENDEKATAN BINARY LOGISTIC REGRESSION: Studi kasus mahasiswa Universitas Bina Bangsa Sri Sukmawati; Isnaini Mahuda; Ernawati Ernawati; Tubagus Bakhrul Alam
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 3 No. 1 (2023): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (234.537 KB) | DOI: 10.46306/bay.v3i1.46

Abstract

Student Grade Point Average (GPA) is a number that shows the achievement or progress of student learning cumulatively from the beginning of the semester to the end. Many things can affect a student's GPA score. This study aims to see the relationship between gender, semester level and student time in using social media on the GPA obtained. The method used is binary logistic analysis (Binary Logistic Regression / BLR) with 1 response variable and 3 predictor variables. The Y categorical data is the GPA of students who are categorized and . Another categorical variability is gender. The conclusions show that student GPA can be explained by variables in the study or student GPA is influenced by gender, semester level and student time in using social media
IMPLEMENTATION OF ARIMA METHOD TO FORECAST CPI FOR COICOP OF FOOD, BEVERAGE AND TOBACCO IN NEW NORMAL PERIOD Mahuda, Isnaini; Rahmawati, Septi Dwi; Sukmawati, Sri; Abdullah, Syarif
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 2 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i2.87

Abstract

CPI is one of the economic indicators that can provide information on development of prices for goods and services paid by consumers or the society, especially urban societies. CPI is usually used to measure price changes, but not to measure the price level. In addition, the CPI also can be used as a benchmark to determine inflation or deflation in a certain area. CPI value after the COVID-19 pandemic is the object to be predicted. There are 11 category in the CPI. This category is named COICOP which one of it is food, beverage and tobacco. The purpose of this research was to determine the ARIMA model to forecast the CPI value in the COICOP of food, beverage and tobacco in Banten Province. The data used is CPI data of COICOP for food, beverage and tobacco in Banten period January 2019 to April 2022. Based on these data obtained several prospective ARIMA models that passed the model diagnostic stage. The Models are ARIMA (0.3,1), ARIMA (1,3,0) and ARIMA (2,3,0) with MSE 1.1294, 1.9496 and 1.2484. The ARIMA (0.3.1) model was chosen because it has the smallest MSE value of 1.1294. Forecasting using the ARIMA (0.3.1) model obtained a significant increase in the CPI value from May to December 2022