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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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Klasifikasi Keberhasilan Melanjutkan Pendidikan Tingkat SMA Provinsi Banten Menggunakan CART dan Random Forest Muhammad Amirullah Yusuf Albasia; Budi Susetyo; I. Made Sumertajaya
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dropout rate in Indonesia has a higher percentage as education levels grow. The percentage of continuing education to senior high school in Indonesia is at 77.50%. Banten is one of the provinces that has a higher dropout percentage when the education level is also higher. Beside that, Banten is the second lowest province in Indonesia in the percentage of continuing education to senior high school that is 68.92%. The study examines importance variables and performance classification that is generated by classification tree and random forest. The results showed that importance variables that is generated by both methods were same, that is per capita expenditure (X8) and proportion of household members who are less educated than senior high school (X10). Then, based on the AUC value that obtained by 10-fold cross validation showed that random forest is better than classification tree. Experiments with values ​​of accuracy, sensitivity, and specificity at some cuts off values ​​also show that random forest can provide more optimum prediction performance than classification tree.
Pembentukan Selang Kepercayaan Bootstrap Kebutuhan Hidup Mahasiswa FMIPA IPB (Studi Kasus Mahasiswa FMIPA angkatan 2015 dan 2016) Dhika Firmansyah; Aam Alamudi; Agus M Soleh
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.119

Abstract

Kebutuhan hidup menjadi aspek penting dalam menunjang kebutuhan mahasiswa selama kuliah sesuai dengan keuangan yang dimiliki tiap mahasiswa. Biaya yang dikeluarkan tiap mahasiswa bergantung dengan kebutuhan dan keuangan yang dimiliki tiap mahasiswa. Biaya yang dikeluarkan oleh mahasiswa FMIPA IPB tiap bulannya memiliki sebaran yang tidak normal sehingga dilakukan analisis dengan metode yang sesuai. Statistika deskriptif dan selang kepercayaan persentil dengan metode bootstrap digunakan untuk memperkirakan besaran pengeluaran tiap bulan selama kuliah di kampus IPB. Ulangan yang digunakan dalam penelitian ini adalah 500, 1000 dan 2000 dengan masing-masing ulangan memiliki ukuran contoh yang terambil sebesar 30, 50, 100, 150, dan 200. Rata-rata pengeluaran mahasiswa FMIPA per bulan yaitu sebesar Rp1166129 dengan nilai minimum sebesar Rp250000 dan maksimum sebesar Rp3700000. Selang kepercayaan 90% dengan metode persentil dengan ulangan lima ratus dan ukuran contoh dua ratus menghasilkan lebar selang kepercayaan yang lebih presisi dan galat baku terkecil dibandingkan dengan kombinasi ulangan dan ukuran contoh lainnya. Selang kepercayaan tersebut memiliki batas bawah 1108159, batas atas 1218434 dan galat baku 32713. Selang kepercayaan kuartil untuk menduga parameter median dengan ulangan lima ratus dan ukuran contoh dua ratus memiliki selang kepercayaan yang lebih presisi dengan batas bawah sebesar 1015000, dan batas atas 1065250.
Dekomposisi Ensemble untuk Peramalan Harga Bawang Merah DKI Jakarta Febie Tri Lestari; Farit Mochamad Afendi; Mohammad Masjkur; Budi Waryanto
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.v8i1.120

Abstract

Onions are one of the vegetable commodities that are not distributed and included as seasonal crops. Onions are commonly used as cooking spices and traditional medicine. At the time of the religious holidays or non-harvest season, the stock of onions is not able to meet the demand, hence the government has to import them, but that increase the fluctuations of onion prices on the market. Actually, by utilizing the price fluctuation, information about the factors, will be obtained by reviewing the price movement and precise forecasting of the price of onions. Ensamble Empirical Mode Decomposition (EEMD) method can be applied to examine that. EEMD is a decomposition method that can be used to convert a series of time functions from a data signal into several sub-signals resulting from flattening, otherwise known as Intrinsic Mode Function (IMF) and IMF remaining. In this research, this concept applied to data on weekly onion prices in DKI Jakarta from July 2008 to April 2018 as many as 521 data. Based on the results of data processing, as many as 7 IMF and IMF remaining were used as IMF forecasting and the IMF remaining in the future. The forecast was performed by choosing the best model of each IMF component and IMF remaining, used ARIMA. In the end, the weekly price forecast for onion in Jakarta from May - July 2018 ranged from Rp34295.67, - to Rp36133.36, - with average forecasting prices for May-July 2018 amounting to Rp34482.39 - Rp 35207.12 and Rp 36024.88 with a MAPE value of 1.85%.
ANALISIS KEPUASAN DAN PREFERENSI KONSUMEN TERHADAP TEMPAT MAKAN AYAM GEPREK Rachmat Wildan
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.123

Abstract

The culinary business is one of businessess that believed to be an economic business has better prospects. One of culinary business in Dramaga, Bogor, West Java which has very rapid development is ayam geprek, this is evidenced by the increasing number of similar culinary businesses are increasingly penetrated in the area. Based on the condition, one of the places to eat ayam geprek in Dramaga is Ayam Geprek Pejuang (AGP) assess is very important to know the level of interest and consumer satisfaction AGP and consumer preferences of ayam geprek. The method required to explain this case was conjoint method, Importance Performance Analysis (IPA) and Customer Statisfaction Index (CSI). The data was primary data by evaluating the combination of levels and attributes by rating. Based on the level of satisfaction and interest of respondents AGP was very satisfied with the attributes associated with AGP.
Analisis Tingkat Kesenjangan Pendapatan antar Provinsi di Indonesia Menggunakan Regresi Data Panel Model Pengaruh Tetap Thooriq Ghaith; Hari Wijayanto; Anang Kurnia
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.125

Abstract

THOORIQ GHAITH. Analysis of Income Disparity Rates among Provinces in Indonesia Using Panel Data Regression. Supervised by HARI WIJAYANTO and ANANG KURNIA. Income disparities in Indonesia generally and in each province particularly is a serious problem from year to year. It is necessary to find out the factors that affect the income disparity rates (Gini ratio) to be taken into consideration in determining the economic policy. By using data of 33 provinces from 2007 until 2016, panel data regression with provincial fixed effect model approach was used to determine factors that affect Gini ratios in Indonesia and to capture the differences of Gini ratio characteristics of each province in form of intercept. Modeling was done for whole Indonesia and for five regions as well to find out what factors that affect the Gini ratio of provinces in Indonesia generally and what factors affect Gini ratios of provinces in each region particularly. The percentage of poor people is a significant factor to Gini ratio in the model throughout Indonesia and in the model of each region, except in Sumatera. Beside the percentage of the poor people, other explanatory variables affecting Gini ratios are GDP growth rates in Kalimantan, open unemployment rates in Sulawesi, and provincial minimum wage in Nusa Tenggara, Maluku and Papua. All of the predicted models are good enough because they produce MAPE values below 10%.
The Impact of Oil Price Shocks on Stock Market Returns in Each Regime using Vector Autoregressive Method Wahida Ainun Mumtaza; Asep Saefuddin; Bagus Sartono
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.v8i1.126

Abstract

World oil prices affect the stock market in developed and developing countries, including Indonesia. Therefore, development of the Indonesian economy is affected by the shocks of world oil prices and the stock market. This study characterized the impact and causal relationship between oil price shocks and stock market in Indonesia from 1996 to 2016. In this research, there are nine sectors of the stock market, there are sector agriculture, basic, consumer, finance, infrastructure, mining, miscellaneous industry, property, and trade. To analyze the impact of oil price shocks to Indonesia stock market, we employed an autoregressive vector model (VAR) methodology involving different lags for each regime. We examined that the dynamic relationship between changes in oil prices and stock market in Indonesia in each regime varied which was indicated by impulse response and variance decomposition value. The Granger Causality test found that there were one-way relationship between oil variable with infrastructure sector variable, oil variable with agricultural sector variable and oil variable with basic sector variable in Regime 2, Regime 3 there was one way relationship significantly between oil variable with infrastructure sector variable and Regime 4 also there were one-way relationship. One-way relationship significantly between oil variable with property sector variable, but not significant in Regime 1.
Perbandingan Metode Koreksi Pencaran pada Data Hasil Alat Pemantau Kadar Glukosa Darah Non-Invasif Siti Raudlah; Mohammad Masjkur; Kusman Sadik; . Erfiani
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.127

Abstract

Scatter correction is one of the methods in data preprocessing that aim at eliminating the physical properties of the spectrum and reducing the variance between samples. The most commonly methods of scatter correction used are the Multiplicative Scatter Correction (MSC) and Standard Normal Variate (SNV) methods. The MSC method corrects the spectrum by utilizing the results of simple linear regression parameter estimation. The SNV method performs spectral correction with the median and standard deviation. Another alternative method of scatter correction is the Orthogonal Scatter Correction (OSC) applying the principle of orthogonality. The methods used in this research were MSC, SNV, and OSC methods in order to correct the result data of non-invasive blood glucose measuring instrument. The result of this research showed that the time domain spectrum data and intensity had different amount so that the summarized data was needed. Furthermore, this research found that the OSC method with the five series of statistics gained a good correction result compared to the other methods. The OSC method produced a smaller average value of the variance than the other methods.
Identifikasi Cepat Segmentasi Konsumen Susu Cair dalam Kemasan Fadhila Hijryani; Bagus Sartono; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.128

Abstract

Consumer segmentation is the process of grouping customers into some segments based on some shared similar characteristics. Consumer segmentation allows companies to understand the customer's characteristics in each segment, thus make them easier to establish suitable marketing strategies for each segment's characteristics.Companies tend to use marketing strategies with demographical and consumer behavioural based scheme of consumer segmentation therefore make them easier to identify customer as the characteristics are easily measured. This research uses k-means method for segmenting 419 customers of packaged liquid milk. The life style pattern of the customers are used as the basis of the segmentation. Furthermore, this research uses decision tree algorithm to classify characteristics of the new customer. According to Hartigan index alteration (26.2433), ideal number of segments is 4. After tree pruning step, classification modelling with CART method yielded 54.61% accuracy.
Penerapan Regresi Peubah Ganda untuk Menentukan SNP yang Berpengaruh terhadap Prestasi Akademik SMA/MA Wulan Andriyani Pangestu; Budi Susetyo; Rahma Anisa
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.130

Abstract

The evaluation step in school accreditation process includes eight components of national education standard (SNP). The result of accreditation from the evaluation is believed to explicate the academic achievement of student, in this case is National Examination (UN). Thus, it is necessary to further observe the relation between the accreditation results and the score of national examination. One of the analysis that can be used is regression analysis, it is used to observe the relation between the accreditation result and the sroce of national examination also to identify the SNP components that affect the national examination score. However, since the study was conducted at senior high school level where the national examination score for this level covers six subjects, the analysis used is no longer a simple regression but a multiple variable regression. It is because of the relationship between the score of the national examination that characterizes an academic achievement. The application result of multiple variable regression method shows that there is a relation between SNP and national examination score.
Two Step Method for Clustering Mixed Data untuk Menggerombolkan Toko Mainan Anak Digital Muhammad Shalih; Cici Suhaeni; Septian Rahardiantoro
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.131

Abstract

The development of digital trading system today, triggering the proliferation of shops that sell various needs in various marketplace. This is supported by the large number of internet users in Indonesia that facilitate the store with commercial-based digital to reach market share. One of the growing categories in a marketplace is the stores that sell toys. However, not all toy stores have a good reputation. Clustering based on store reputation indicators can be done to find out how the condition of toy stores in a marketplace. The store reputation indicators used are categorical and numerical scale variables. This study uses A Two-Step Method for Mixed Categorical and Numerical Data (TMCM), which is a clustering method that can cluster mixed numerical and categorical data that using a co-occurence concept. The result of this clustering found that the optimal number of cluster is five cluster based on the maximum value of Pseudo-F and the minimum value of ratio (R ).

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