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Akbar Rizki
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Xplore: Journal of Statistics
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 106 Documents
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Perbandingan Quadratic Discriminant Analysis dan Support Vector Machine untuk Klasifikasi Tutupan Lahan di DKI Jakarta Kamaluddin Junianto Dimas; Rahma Anisa; Itasia Dina Sulvianti
Xplore: Journal of Statistics Vol. 9 No. 1 (2020)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (577.474 KB) | DOI: 10.29244/xplore.v9i1.236

Abstract

DKI Jakarta is a center of government as well as economy and business of Indonesia, thus development projects in Jakarta continue every year. Therefore, monitoring for land use has to be improved in accordance to DKI Jakarta Spatial Planning. The attempt needs to be supported by continuous data availability regarding land cover condition in Jakarta. The aforementioned data collecting process become easier due to remote sensing technology development. Remote sensing technology can be utilized for analyzing the size of land use area by using classification analysis. It has been found that the level of accuracy depends on the type of classification method and number of training data. This research evaluated the level of overall accuracy, sensitivity, and specificity of Quadratic Discriminant Analysis (QDA) and Support Vector Machine (SVM) along with number of data training used in classifying Jakarta land cover in 2017. The results showed that in both methods, the variance of all the aforementioned criteria were getting smaller along with the increasing number of training data. QDA and SVM had similar performance based on overall accuracy and specificity. However, SVM was better than QDA on sensitivity.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (789.92 KB) | DOI: 10.29244/xplore.v10i2.237

Abstract

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 A’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 B’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 B’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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.99 KB) | DOI: 10.29244/xplore.v10i2.238

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (807.521 KB) | DOI: 10.29244/xplore.v10i2.244

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.154 KB) | DOI: 10.29244/xplore.v10i2.245

Abstract

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.
Analisis Kepuasan Terhadap Green Transportation Salvina Salvina; Akbar Rizki; Indahwati Indahwati
Xplore: Journal of Statistics Vol. 9 No. 1 (2020)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (243.654 KB) | DOI: 10.29244/xplore.v9i1.251

Abstract

ABSTRACT SALVINA. Analysis of Satisfaction against Green Transportation. Supervised by AKBAR RIZKI and INDAHWATI. One of the stages of the Green Campus 2020 program as an effort of IPB towards World Class University (WCU) is to carry out the Green Transportation (GT) movement. Buses, electric cars, bicycles and electric motorcycle taxis are the GT transportation modes in IPB. The purpose of this study was to determine the level of satisfaction of GT users and identify attributes that are important and need to be improved so that the GT service system can be improved. This study uses survey data conducted by researchers on undergraduate students who use GT transportation mode in the past week. The sampling method used is random layered sampling with layers in the form of faculties. The analytical methods used are Importance Performance Analysis (IPA), Customer Satisfaction Index (CSI), biplot analysis, and simple correspondence analysis. The CSI value obtained is 2.96 (1-4 scale) with a CSI percentage of 74% in other words the user is satisfied with the service he receives. The aspects that need to be improved are aspects of empathy and reliability on electric cars and assurance on bicycles, while other aspects have been considered good. Biplot analysis shows the diversity of satisfaction obtained from aspects (reliability, empathy, tangibles, assurance, and responsiveness) is the same. Simple correspondence analysis shows students of the Faculty of Veterinary Medicine (FKH), Faculty of Animal Husbandry (FAPET), Faculty of Forestry (FAHUTAN), and General Competency Education Program (PPKU) often use electric cars. Faculties that often use buses are Faculty of Agriculture (FAPERTA), Faculty of Agricultural Technology (FATETA), Faculty of Fisheries and Marine Sciences (FPIK) and Faculty of Mathematics and Natural Sciences (FMIPA). The mode of bicycle transportation cannot be characterized in any faculty because at least the respondents use it. Keywords: biplot, green transportation, IPA-CSI, simple correspondence
Penerapan Two Step Cluster untuk Mengklasifikasikan Desa di Kabupaten Madiun Berdasarkan Data Potensi Desa Alif Supandi; Asep Saefuddin; Itasia Dina Sulvianti
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.04 KB) | DOI: 10.29244/xplore.v10i1.272

Abstract

Village development is a fundamental part of national development. Developing villages requires information on society necessities. This research aims at clustering villages in Kabupaten Madiun which has similar characteristics among each other and identify characteristics of the built clusters. Therefore, specific problems in the clusters of villages may become the foundation to implement development. The method that used for grouping objects with combined variables is two-step cluster. This analysis was used 14 variables consist of six categorical variables and eight numerical variables. The clustering analysis produces four clusters. The clusters that need more attention to be developed was Cluster 2 which had minimum facilities and resources. The average Silhouette coefficient for the clusters built was 0.3 which can be considered as fair category.
Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square Khairunnisa Khairunnisa; Rizka Pitri; Victor P Butar-Butar; Agus M Soleh
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.275

Abstract

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.
Metode Alternatif dalam Pencarian Peringkat E-Commerce di Indonesia Berdasarkan Rating Pelanggan Azira Irawan; Aam Alamudi; Septian Rahardiantoro
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (641.744 KB) | DOI: 10.29244/xplore.v10i1.280

Abstract

The existence of the internet raises an online trading system using applications. The rise of online trading systems has triggered the emergence of various e-commerce in Indonesia that provide various kinds of customer needs. This also causes problems for customers, namely the difficulty in choosing quality e-commerce. The effort to overcome this problem is to rank e-commerce in Indonesia based on customer ratings. The method commonly used for ranking is the analytical hierarchy process (AHP) method, but in practice there are several variables that are not found in e-commerce so the AHP method cannot be used. The alternative method chosen is the ant colony optimization (ACO) method. The feasibility test of the ACO method in searching rankings for e-commerce data needs to be done because not all variables are in e-commerce. Simulations for ranking search are carried out using 2 generated data scenario with analytical hierarchy process (AHP) and ant colony optimization (ACO) method. The simulation results show that the ACO method is feasible to be used for ranking with blank data, then the application of the ACO method for e-commerce data in Indonesia. The best taboo results are based on the highest opportunity value and the highest correlation coefficient, namely in the second taboo, with three major ratings, namely JD, SP, and TP
Pemodelan Pola Produktivitas Cabai Rawit di Kabupaten Magelang Yohanes Purnama; Farit M Affendi; Agus M Soleh
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (282.296 KB) | DOI: 10.29244/xplore.v10i1.358

Abstract

The objective of this study was to determine the best model that describe the pattern of cayenne pepper productivity in Magelang Regency. This study uses primary data which was obtained from the results of a survey of cayenne pepper production by the General Director of Horticulture on several sample plots in Magelang District, Central Java Province in 2018. The process of data analysis was divided into two parts: grouping the sample plots based on the similarity in productivity pattern and then fitting models in each group. The models used to fit data were Logistic Growth Model, Monomolecular Growth Model, Exponential Growth Model, Polynomial Model and Linear B-Spline Model. The best model was determined based on R2 and MAPE. The results showed that the pattern of cayenne pepper productivity in Magelang District had eight different characteristics. Characteristics of each groups were illustrated by the similarity of their productivity pattern. The best model in each group was B-Spline Linear Model.

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