Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

Xplore: Journal of Statistics

xplore
Website

Published by Institut Pertanian Bogor

ISSN : 23025751 EISSN : 26552744 DOI : https://doi.org/10.29244/xplore

Core Subject : Science, Education, Engineering,

Decision Sciences, Operations Research & Management Engineering Mathematics

Xplore: Journal of Statistics diterbitkan berkala 3 (tiga) kali dalam setahun yang memuat tulisan ilmiah yang berhubungan dengan bidang statistika. Artikel yang dimuat berupa hasil penelitian atau kajian pustaka dalam bidang statistika dan atau penerapannya. ISSN: 2302-5751 Mulai Desember 2018, Xplore: Journal of Statistics mendapatkan ISSN baru untuk media online (eISSN:2655-2744) sesuai dengan SK no. 0005.26552744/JI.3.1/SK.ISSN/2018.12 - 13 Desember 2018. Maka sesuai ketentuan pada SK tersebut, edisi Xplore: Journal of Statistics mulai Desember 2018 akan dimulai menjadi Volume 7 dan No 3. eISSN: 2655-2744

Arjuna Subject : Matematika - Statistik dan Probabilitas

Articles 8 Documents

Search results for , issue "Vol. 10 No. 2 (2021)" : 8 Documents clear

Penerapan Regresi Logistik Biner Multilevel terhadap Ketepatan Waktu Lulus Mahasiswa Program Magister Sekolah Pascasarjana IPB Zana Aprillia; Farit Mochamad Afendi; Akbar Rizki
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

The study length of alumnus is one of the study achievement indicator of the university. Study length for Master Program can be divided into two categories which is pass on time (study length â‰¤24 months) and pass not on time (study length >24 months). In the classical regression analysis, each student are assumed to be independent. But in reality, each student are grouped into a different study programs so that the individuals who are in the same study program tend to have a similar characteristics. Multilevel regression is one of the analysis that accomodates the problem. The level used in this study are level 1 (individual student) and level 2 (study programs). The best multilevel regression model obtained is a model with random intercept and the variance is produced from study program is 0.6636. Factors that give an effect to the graduationâ€™s timeliness are age, married status, and the source of the S2 education cost.

Penanganan Pencilan pada Peramalan Data Deret Waktu Menggunakan Metode Pemulusan Holt dan Robust Holt Septanti Kusuma Dwi Arini; Farit Mochamad Afendi; Pika Silvianti
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

The time series data used is time series data following the LLTM (local linear trend model) model with four different error conditions. These conditions are Clean Data (CD), Symmetric Outliers (SO), Asymmetric Outliers (AO) and Fat-tailed data (FT). The time series data contains symmetric and asymmetric outliers that can affect forecasting. The forecasting method used for the trend data pattern is the Holt smoothing method. The forecasting of the data series when it is spinning using the Holt smoothing method is not good enough so that it requires a handler with the smoothing method of Holt robustness. The Holt robustness smoothing method that is carried out on time series simulation data is better used for the condition of scattered data compared to the Holt smoothing method. This is indicated by the value of evaluating the goodness of the method, namely the value of MAD (Mean Absolute Deviation) produced. The smaller MAD value for CD condition training data is the Holt smoothing method, while the data testing method for Holt and robust Holt smoothing is almost comparable. SO's condition for training data and data testing for smaller MAD values is the smoothing method of robust Holt. The condition of AO for training data and data testing for smaller MAD values is the smoothing method of robust Holt. In addition, the MAD value in FT conditions for training data and data testing found almost comparable results between the two methods.

METODE CART UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR YANG MEMENGARUHI WAKTU PEMBELIAN KENDARAAN KEDUA Eka Setiawaty; Farit Mochamad Afendi; Cici Suhaeni
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Increased competition between personal vehicle dealers make them need strategies to hold their customers and increase their sales. One of the strategies they could apply is prospecting their customers at the right time. We could predict the right time by identifying the relationship between the length of their purchase time and its factors based on the transaction data of Z Company from year 2002 to 2015 using Classification and Regression Trees (CART). Data analysis is separated between groups of customers who made the second purchase maximum of 10 years after the first purchase (group A) and more than 10 years after the first purchase (group B). Group Aâ€™s regression tree produces 8 terminal nodes with MAD value 1.84 years. The independent variables that plays a role are tenor, job, age, and brand. Group Bâ€™s regression tree produces 4 terminal nodes. Authorized service and job come out as independent variables which affect the splitting process. MAD value for Group Bâ€™s regression tree is 0.56 years.

Penerapan Synthetic Minority Oversampling Technique pada Pemodelan Regresi Logistik Biner terhadap Keberhasilan Studi Mahasiswa Program Magister IPB Mega Pradita Pangestika; I Made Sumertajaya; Akbar Rizki
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

The Postgraduate School of IPB has academic standards as well as high competitiveness of graduates who have spread both at home and abroad. In this study Binary Logistic Regression method was used to determine the factors that influence the success of the study of Postgraduate students of Bogor Agricultural University (Graduate School-IPB). The data used are data from IPB Graduate School students who graduated from 2011 to 2015. The response variable used is the success status of student studies namely graduating and not passing and using 9 explanatory variables namely gender, marital status, admission status when entering S2, college status S1 level, the source of S2 education costs, group of agencies working, S2 study program groups, age when entering S2 and S1 GPA. The data obtained is not balanced with the percentage of students who graduate is greater than those who did not pass, so the imbalance of data is handled with SMOTE if it is not handled it will cause a misclassification. Comparison of classification results seen in testing data. The results in the model before SMOTE have an area under the curve or AUC of 0.6760, an accuracy value of 88.77%, a sensitivity value of 99.09% and a specificity of 4.63%. The model after 600% oversampling SMOTE has an AUC value of 0.6642, an accuracy value of 78.36%, a sensitivity value of 83.65%, and a specificity value of 35.18%. Although the accuracy of the model and sensitivity value before SMOTE was higher than the model after SMOTE, the specificity in the model after SMOTE was higher, which meant that the model after SMOTE was better at predicting minority classes (not graduating).

Evaluasi Produk Multivitamin Baru Berdasarkan Penilaian Responden Noer Endah Islami; Utami Dyah Syafitri; Cici Suhaeni
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

In order to lead in the market, companies should have an innovation product. Before the innovation product lauch to the market, the marketing research should be done. The goal of the reasearch is to determine whether the new product is accepted or rejected in the market. This study was to identify the characteristics of the new product based on organoleptic point of view and performance the three type of new multivitamin products based on location and social economic classes (SEC) of respondents. MANOVA and biplot analysis were used in this research. Based on MANOVA, there were differences on the organoleptic point of view of respondents among three type of new multivitamin products. The three products had differences on the assessment of aroma, sour taste, and sour after taste. In addtion with biplot analysis, it was concluded that each product had different location for sale and the target of respondents based on sosial economic classes. According to respondents, product A was too sweet taste and too sour after taste in the mouth compared to others. This product was preferred by respondents who reside in South Jakarta with social economic classes (SEC) A2 and C1. Unlike product A, product B was too hard with a bit of bitter after taste in the mouth. This product was relatively preferred by respondents in various residential with social economic classes (SEC) B. Product C was strong aroma with smooth texture and more bitter taste than others. This product was preferred by respondents who reside in North Jakarta and Depok with social economic classes (SEC) A1. Overall, product B was preferred by respondents compared to other products.

Analisis Korelasi Kanonik pada Parameter Kualitas Fisik dan Parameter Kualitas Kimia Air Sungai Ciliwung Nadya Amelia Dewi Suryana; Itasia Dina Sulvianti; Muhammad Nur Aidi
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Water is an important factor in fulfilling the needs of living things, therefore the water that is used must be free from bacterias and do not contain any toxic substances. The most common water source comes from the river. Ciliwung River as one of the main rivers used for drinking, household needs, industrial needs, and transportation must have good water quality. Therefore, the Ciliwung River water quality needed to be known. The water quality is measured based on the parameters such as the physical water quality and the chemical water quality. The measurement of those parameters are classified to be complicated as it measured by laboratorium research, so that the identification of the chemical water quality parameter could be done through the physical water quality that is easier and simpler to be measured. This study aims to determine the variable of the physical water parameters that can be used to identify the chemical water quality parameters, so that the water quality of the Ciliwung River can be known in a simpler way. Statistical method that can be used to see the relationship between the two variable groups is the canonical correlation analysis. Canonical correlation analysis is a method in multiple variable analysis used to investigate the relationship of two groups of variables using the linear combination principle of the two variables. Based on the results of the canonical correlation analysis, it can be concluded that there is a relationship between the physical quality of water and the chemical quality of water. The correlation exists between the variables of physical quality of water, which are the water temperature and the content of suspended substances in water, with the variables of chemical quality of water, namely groups of metals (manganese levels in water and iron content in water) and groups of acid (the level of deep phosphate in water, the level of sulfate in water, the level of nitrite in water, and the level of nitrate in water). The relationship between the physical quality of water is positive between the temperature of water and the chemical quality of water whereas negative between the levels of suspended substances in water and the chemical quality of water.

Penggerombolan Daerah 3T di Indonesia Berdasarkan Rasio Tenaga Kesehatan dengan Metode Penggerombolan Berhierarki dan Cluster Ensemble Kesuma Millati; Cici Suhaeni; Budi Susetyo
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Health is a major factor in community development. Inequality on health is most felt by people living in disadvantaged, outermost, and leading areas (3T) because of the difficulty of access to transportation and communication. Effective efforts are needed to achieve the optimal distribution of health services, one of which is by clustering 3T areas based on the ratio of health workers to see which areas are experiencing shortage of health workers and know the adequacy of the number of health workers spread in 3T areas. The object used in this research is 27 provinces 3T region in Indonesia and the applied statistical method is various hierarchical methods and Cluster Ensemble. Based on the results of this study, 3T area is divided into four clusters. The first cluster consists of 22 provinces and has good characteristics because all categories of the variables are in the medium category. The second and the third cluster consists of two provinces. The characteristics of the second cluster are good enough. The characteristics of the third cluster are not been good enough because there is one variable in the low category. The fourth cluster consists of one province and has characteristics that are not been good enough because there are several categories of the variables are in the low category.

Metode SVM untuk Klasifikasi Enam Tumbuhan Zingiberaceae Menggunakan Variabel Terpilih Hasil Algoritma Genetika Triyani Oktaria; Utami Dyah Syafitri; Mohamad Rafi; Farit M Afendi
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Ginger, red ginger, emprit ginger, elephant ginger, red galangal and white galangal are known to have similar shapes and uses, especially those that are packaged in powder form. In this study, UV-Vis spectrum 200nm-700nm were used as a source of data from chemical compound contain in those plants for classification of the six plants. In this research, the support vector machine (SVM) classification method was used to classify the six plants. Another goal of this study was to identify the wavelengths which give more information about the chemical compound of the plants. The preprocessing procedure was implemented by construction of a genetic algorithm. There were four parameters in the genetic algorithm were set namely population size, crossover probability, mutation, and generation probability. The mutation and the population size influenced significantly the results of SVM. The best result was given by probability of mutation was 10 and population size was 30. The SVM model was better than the SVM model without preprocessing procedure.

Page 1 of 1 | Total Record : 8

Filter by Year

2021 2021

Filter By Issues

All Issue Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023) Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022) Vol. 11 No. 2 (2022): Vol. 11 No. 1 (2022) Vol. 10 No. 3 (2021) Vol. 10 No. 2 (2021) Vol. 10 No. 1 (2021) Vol. 9 No. 1 (2020) Vol. 8 No. 1 (2019): 30 April 2019 Vol. 7 No. 3 (2018): 31 Desember 2018 Vol. 2 No. 2 (2018): 31 Agustus 2018 Vol. 2 No. 1 (2018): 30 Juni 2018 Vol. 1 No. 1 (2013) More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Akbar Rizki

Contact Email
akbar.ritzki@apps.ipb.ac.id

Phone
+628111144470

Journal Mail Official
akbar.ritzki@apps.ipb.ac.id

Editorial Address
Departemen Statistika, IPB Jl. Meranti Kampus IPB Darmaga Wing 22, Level 4 Bogor 16680

Location
Kota bogor,

Jawa barat

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Akbar Rizki

Contact Email akbar.ritzki@apps.ipb.ac.id

Phone +628111144470

Journal Mail Official akbar.ritzki@apps.ipb.ac.id

Editorial Address Departemen Statistika, IPB Jl. Meranti Kampus IPB Darmaga Wing 22, Level 4 Bogor 16680

Location Kota bogor, Jawa barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Akbar Rizki

Contact Email
akbar.ritzki@apps.ipb.ac.id

Phone
+628111144470

Journal Mail Official
akbar.ritzki@apps.ipb.ac.id

Editorial Address
Departemen Statistika, IPB Jl. Meranti Kampus IPB Darmaga Wing 22, Level 4 Bogor 16680

Location
Kota bogor,

Jawa barat

INDONESIA