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All Journal FORUM STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Desimal: Jurnal Matematika Xplore: Journal of Statistics Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications

Aam Alamudi

Department Of Statistics, Bogor Agricultural University (IPB)

Author-ID : 3379300

Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Mathematics Social Sciences Other

Published : 23 Documents Claim Missing Document

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Segmentasi Mahasiswa S1 IPB terhadap Sistem Peminjaman Sepeda Tania Amalia Darsono; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

IPB is the one campus that realize the Green Campus program. One of the elements in Green Campus is Green Transportation. In realizing this Green Transportation, IPB has several programs that include the Green Bike program. There are rules in implementation the Green Bike program related to the borrowing system. Because of the borrowing system, it is necessary to make the segmentation of S1 IPB students on bicycle borrowing system. Segmentation of respondent's characteristic used two step clustering method and the result is 3 optimal clusters. Then segmentation on respondent's preference to bicycle borrowing system used k-means method and the result is 2 optimal clusters. Segmentation of bicycle borrowing system based on respondent's characteristic and respondent's preference is 6 combinations of cluster using cross tabulation.

Penerapan Metode Two Step Cluster pada Data Survei Angkatan Kerja Nasional (Sakernas) Maya Deanti; Farit Mochamad Afendi; Aam Alamudi
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

MAYA DEANTI. Implementation of Two Step Cluster Method on National Labor Force Survey Data (Sakernas) 2017 Bogor Regency. Supervised by FARIT MOCHAMAD AFENDI and AAM ALAMUDI. Five labor issues in Indonesia that have not been resolved by 2017 are termination of employment due to digitalization or automation, labor informalization, BPJS, high accident and occupational safety (K3), and outsourcing. In addition, the increasing number of Foreign Workers (TKA) in Indonesia can affect the decrease in local employment opportunities. Therefore, in this study will be carried out clustering to the labor force data to determine the condition of employment in Indonesia, especially Bogor regency. However, this labor force data has considerable observation with mixed data types, namely numerical and categorical. Regular cluster analysis can not be applied directly to the condition of the data, so that to be used in this research is a Two Step Cluster analysis which is a modification of existing cluster analysis. This Two Step Cluster analysis produces 3 clusters, with the characteristics of each cluster that is cluster 1 consisting of resident households or unemployed, cluster 2 consists of self-employed residents, and cluster 3 with the majority of the population working as laborers or employees. This clustering is based on work aspect only because the demography and education aspect of Bogor Regency is quite uniform. Keywords: cluster analysis, cluster, Two Step Cluster, uniform

Pendugaan Produktivitas Bagan Perahu dengan Regresi Gulud, LASSO dan Elastic-net Resty Fanny; Anik Djuraidah; Aam Alamudi
Xplore: Journal of Statistics Vol. 2 No. 2 (2018): 31 Agustus 2018
Publisher : Department of Statistics, IPB

Regression analysis is a statistical technique to examine and model the relationship between dependent variable and independent variable. Multiple linear regression includes more than one independent variable. Multicollinearity in multiple linear regression occurs when the independent variables has correlations. Multicolinearity causes the estimator by ordinary least square to be unstable and produce a large variety. Multicollinearity can be overcome by the addition of penalized regression coefficient. The purpose of this research is modeling ridge regression, LASSO, and elastic-net. Data which is data of fisherman catch at Carocok Beach of Tarusan Sumatera Barat as dependent variable and amount of labor, amount of fuel, volume of fishing/waring boat, number of catches, ship size, number of boat wattage, sea experience, education and age of fisher as independent variables. The best model provided by LASSO that has a RMSEP value of validated regression model is minimum than ridge regression and elastic-net. LASSO shrinked amount of labor, amount of fuel and number of wattage equal zero. There can be influence (productivity change) that is volume of fishing/waring boat and boat size that used by fisher.

Segmentasi Mahasiswa S1 IPB terhadap Sistem Peminjaman Sepeda Tania Amalia Darsono; Utami Dyah Syafitri; Aam Alamudi
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

Green Campus is one program of IPB. One element of Green Campus is Green Transportation. There are programs in Green Transportation, one of the programs is Green Bike. There are rules in Green Bike program which were related to the system of borrowing. Based on the rules, so it was required to make segmentation of undergraduate students IPB on bicycle borrowing system. This research used data of undergraduate students IPB on bicycle borrowing systemâ€™s preferences and characteristics of respondents. Segmentation on characteristics of respondents using two step cluster method. The distance that was used in two step cluster is log-likelihood and to determinate the optimal clusters using BIC. There are 3 optimal clusters formed and quality of clustering is fair (coefficient Silhouette = 0.3). Then segmentation on bicycle borrowing systemâ€™s preferences using kmeans method. The distance that was used in k-means is euclid and there are 2 optimal clusters formed (based on the Pseudo-F value). Based on segmentation on bicycle borrowing system by combining characteristics and preferences of respondents, there are 6 cluters formed.

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

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.

Faktor-Faktor yang Berpengaruh dalam Mendapatkan Pekerjaan bagi Lulusan Statistika IPB dengan Menggunakan Metode CHAID Aulia Dwi Oktavia; Aam Alamudi; Budi Susetyo
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.v8i1.156

Unemployment is one of the economic problems in Indonesia. Judging from the level of education that was completed there were unemployment from the level of college graduates. This encourages the level of competition in getting jobs to be more stringent, so that college graduates (bachelor of Statistics in IPB) must have the preparation of various factors to maintain the quality of their graduates. The quality of college graduates can be seen from the length of time waiting to get a job. This study aims to determine the influential factors in getting a job for graduates of the IPB Statistics degree, so that the CHAID method can be used in this study. The results of CHAID's analysis in this study in the form of tree diagrams using Î± = 10% explained that the factors influencing the waiting period variables were sex, internship, and the ability to master statistical software, where the accuracy value generated by the classification model was 79.3 %.

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

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

Penggerombolan Sekolah pada Penerimaan Mahasiswa Baru Jalur SNMPTN di IPB Menggunakan Metode Two-Step Cluster Ni Kadek Manik Dewantari; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

New student admissions are opened in three pathways including SNMPTN, SBMPTN, and Seleksi Mandiri. In order to improve the SNMPTN selection system at IPB, a study was conducted on the quality of SMA/MA which registered to IPB through school clustering. In general, cluster analysis cannot handle large and mixed-type data, so this school clustering used the Two-Step Cluster method with two alternatives, namely without handling outliers and handling 5 percent outliers. Both of these alternatives produced an average Silhouette coefficient value of 0.2 and 0.3 respectively, which was still under the good category. However, clustering without handling outliers resulted in more detailed cluster criteria with 4 optimal clusters. The criteria for these four clusters include, Cluster 1 is a category of Low Commitment, Low Quality, and Low Consistency schools, Cluster 2 and 3 are categories of schools that have special criteria in certain categories, and Cluster 4 is a category of High Commitment, High Quality, and High Consistency.

Analisis Unggahan Media Sosial pada Instagram Rachel Vennya Menggunakan Metode Importance Performance Else Virdiani; Aam Alamudi; Yenni Angraini
Xplore: Journal of Statistics Vol. 11 No. 1 (2022)
Publisher : Department of Statistics, IPB

Instagram is one of the social media applications that can publish photos or videos for its users. Rachel Vennya is a well-known Instagram user who has more than five million followers. This research was conducted to see the expected posts by Rachel Vennya's followers on Instagram. Through the importance-performance analysis (IPA) it will be known the types of posts that are interesting and need to be increased in publication. This study's two IPA approaches, namely expected performance analysis (EPA) and importance-performance matrix analysis (IPMA). The results of each analysis are then mapped into a Cartesian diagram so that it is known that several posts increase follower loyalty and posts that need to be increased or decreased. After comparing the two Cartesian diagrams, it is known that there is no difference in the placement of variables between the two analyzes. Posts that deserve to be maintained include Motivation, Cooking, Family, and posts considered excessive in the publication are Business and Endorsements. Furthermore, customer satisfaction index (CSI) analysis was carried out to see follower satisfaction. The CSI value obtained is 72.69, which indicates the follower satisfaction index belongs to the satisfied criteria.

Kajian Metode Pohon Model Logistik (Logistic Model Tree) dengan Penanganan Ketakseimbangan Data Akmala Firdausi; Aam Alamudi; Kusman Sadik
Xplore: Journal of Statistics Vol. 11 No. 2 (2022):
Publisher : Department of Statistics, IPB

Logistic model tree is a nonparametric modelling method that combines decision tree with linear logistic regression. Logistic model tree handles multicollinearity well, but is not immune to problems that arise due to data imbalance. This study was carried to compare the performance of undersampling, SMOTE, and ROSE in handling imbalanced data when used in tandem with logistic model tree. The data used in the simulation was obtained by generating random numbers following the Bernoulli distribution as the response variable and the Bivariate Normal distribution as the explanatory variables, based on five different imbalance levels. Comparisons done on the AUC value showed that logistic model trees built with methods to handle imbalanced data performed better than logistic model trees built without applying any such method on every level of tested data imbalance in classifying objects. Among those, logistic model trees built with ROSE performed better than logistic model trees built with other methods. On datasets with low level of imbalance, the performance of logistic model trees built with ROSE and undersampling do not significantly differ.

Co-Authors . Aunuddin Agus M Soleh Agus M Soleh Agus Soleh Akmala Firdausi Anik Djuraidah Aulia Dwi Oktavia Ayoe Indria Winuri Azira Irawan Bagus Sartono Budi Susetyo Dhika Firmansyah Dian Kusumaningrum Else Virdiani Eria, Raisa Nida Erlinda Widya Widjanarko Farit Mochamad Afendi Fitrianto, Anwar Hanifatun Nufusia Hiola, Yani Prihantini Indahwati Indonesian Journal of Statistics and Its Applications IJSA Iqbal Hanif Itasia Dina Sulvianti Kusman Sadik Mahdiyah Riaesnianda Maya Deanti Mega Maulina Muhammad Farhan Zahid Nadhif Nursyahban Ni Kadek Manik Dewantari Nisa Nur Aisyah Pika Silvianti Pika Silvianti Putri, Oktaviani Aisyah Rahardiantoro, Septian Rahma Anisa Rahma Anisa Resty Fanny Riansyah, Boy Silmi Annisa Rizki Manaf Tania Amalia Darsono Utami Dyah Syafitri Yasmin Erika Faridhan Yenni Angraini

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Journal : Xplore: Journal of Statistics