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All Journal Jurnal Manajemen dan Organisasi FORUM STATISTIKA DAN KOMPUTASI Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika Jurnal Ilmu Dasar Jurnal Manajemen Teknologi Jurnal Agro Ekonomi JAM : Jurnal Aplikasi Manajemen Indonesian Journal of Business and Entrepreneurship (IJBE) JUITA : Jurnal Informatika Indonesian Journal of Biotechnology Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Manajemen. AL ISHLAH Jurnal Pendidikan International Research Journal of Business Studies (E-Journal) Jurnal Penelitian Pertanian Tanaman Pangan BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ekonomi Integra JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications JURNAL AGRONIDA Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya ComTech: Computer, Mathematics and Engineering Applications Jurnal Manajemen Inferensi Jurnal Agro Ekonomi Journal of Data Science and Its Applications Jurnal Teknik Informatika (JUTIF) Xplore: Journal of Statistics STATISTIKA Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) International Research Journal of Business Studies Indonesian Journal of Statistics and Its Applications Limits: Journal of Mathematics and Its Applications
I Made Sumertajaya
Departemen Statistika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor Kampus Darmaga, Bogor 16680
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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ANALISIS KARAKTERISTIK DAN KESEJAHTERAAN SUBJEKTIF TERHADAP OUTCOME BEKERJA DARI RUMAH Nurlia Eka Damayanti; Anggraini Sukmawati; I Made Sumertajaya
Jurnal Ekonomi Integra Vol 13, No 1 (2023): Jurnal Ekonomi Integra
Publisher : STIE 'INDONESIA' Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51195/iga.v13i1.290

Abstract

Salah satu bentuk pencegahan penularan covid-19 yang dilakukan oleh perusahaan adalah menerapkan kebijakan bekerja dari rumah. Konsep bekerja dari rumah yang telah diterapkan oleh banyak negara adalah pengaturan kerja yang sengaja dirancang sesuai dengan kebutuhan perusahaan dan karyawan. Sementara itu, yang terjadi di Indonesia merupakan dorongan akibat pandemi covid-19. Oleh karena itu, tujuan dari penelitian ini adalah mengidentifikasi faktor yang menguntungkan bagi karyawan dan bagaimana kesejahteraan subjektif karyawan yang menjalankan kebijakan bekerja dari rumah serta menganalisis hubungannya terhadap outcome bekerja dari rumah. Data penelitian diperoleh dari hasil mengisi kuesioner online. Metode pengambilan sampel menggunakan teknik convenience sampling. Pada penelitian ini jumlah sampel yang digunakan sebesar 340 sampel. Hasil penelitian menunjukkan bahwa faktor yang memiliki hubungan kuat dengan outcome bekerja dari rumah adalah kesempatan bekerja pada waktu produktif dan ksesuaian bekerja dari rumah. Kesejahteraan subjektif memiliki hubungan kuat dengan kepuasan secara keseluruhan yang dijelaskan dalam bentuk perasaan positif.
Evaluation of Bicluster Analysis Results in Capture Fisheries Using the BCBimax Algorithm Cynthia Wulandari; I Made Sumertajaya; Muhammad Nur Aidi
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15457

Abstract

Biclustering is a simultaneous clustering technique by finding sub-matrixes that have the same similarity between rows and columns. One of the biclustering algorithms that is relatively fast and can be used as a reference for the comparison of several algorithms is the BCBimax algorithm. The BCBimax algorithm works by finding a sub-matrix containing element 1 of the formed binary data matrix. The selection of thresholds in the binarization process and the minimum combination of rows and columns are essential in finding the optimal bicluster. Capture fisheries have an important role in supporting sustainable growth in Indonesia, so information on the potential of fish species that have similarities in several provinces is needed in optimally mapping the potential. The BCBimax algorithm found 11 optimal biclusters in grouping capture fisheries data. The median of each variable is used as a threshold in the binarization process, and the minimum combination of row 2 and maximum column 2 is chosen to find the optimal bicluster result. The optimal average value of Mean Square Residual bicluster obtained is 0.405403 with the similarity of bicluster results (Liu and Wang index) which is different for each bicluster combination produced. All the bicluster results grouped the provinces and types of fish that had the same potential simultaneously.
Penggerombolan Provinsi di Indonesia Berdasarkan Produktivitas Tanaman Pangan Tahun 2005-2015 Menggunakan Metode K-Error Emeylia Safitri; I Made Sumertajaya; Akbar Rizki
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.475 KB) | DOI: 10.29244/xplore.v2i1.75

Abstract

Clustering analysis is a multivariate analysis that’s aim for gruping the observasion objects to some groups. The clusters have low similarity between the clusters and high similarity in same cluster. Classic grouping analysis have a weakness that doesn’t insert measurement error information that related with data. Clustering analysis with K-Error method is expanded for solusing solving the measurement error data problem in classic grouping analysis. The research is aim for clustering the provinces in Indonesia using K-Error and K-Means method based on crops productivity. K-Error method produces better clusters than KMeans. K-Error method formed 7 clusters. Cluster 5 consist of provinces with highest productivity almost at all crops. Cluster 2 and 3 have low productivity for partial crops.
Pemodelan Harga Beras di Pulau Sumatera dengan Menggunakan Model Generalized Space Time ARIMA Dwi Yulianti; I Made Sumertajaya; Itasia Dina Sulvianti
Xplore: Journal of Statistics Vol. 2 No. 2 (2018): 31 Agustus 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.342 KB) | DOI: 10.29244/xplore.v2i2.105

Abstract

Generalized space time autoregressive integrated moving average (GSTARIMA) model is a time series model of multiple variables with spatial and time linkages (space time). GSTARIMA model is an extension of the space time autoregressive integrated moving average (STARIMA) model with the assumption that each location has unique model parameters, thus GSTARIMA model is more flexible than STARIMA model. The purposes of this research are to determine the best model and predict the time series data of rice price on all provincial capitals of Sumatra island using GSTARIMA model. This research used weekly data of rice price on all provincial capitals of Sumatra island from January 2010 to December 2017. The spatial weights used in this research are the inverse distance and queen contiguity. The modeling result shows that the best model is GSTARIMA (1,1,0) with queen contiguity weighted matrix and has the smallest MAPE value of 1.17817 %.
Aplikasi Structural Equation Modeling-Partial Least Squares dalam Menentukan Faktor yang Mempengaruhi Kinerja Karyawan Amanda Permata Dewi; I Made Sumertajaya; Aji Hamim Wigena
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

Structural Equation Modeling (SEM combines factor and path analysis, so researchers can see the relationship between latent variables and their indicators and the relationship between latent variables. Partial Least Square is a soft modeling approach on SEM that has no assumption of data distribution and minimum number of observations which is often called SEM-PLS. The data used in this study is the performance of 70 constructions company employees. The number of observations is too small and couldn’t fulfill the data normality assumption so the analysis method used is SEM-PLS. This study applies SEM-PLS to identify the factors that influence the performance based on competence data from each of the existing employees. The results of this study indicate that both variables have a significant influence on the performance variables. The model tested in the research is good enough to explain the diversity of the performance variables with the evaluation value of Q2 of 75.24%.
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.
Penerapan Metode VAR-X untuk Pemodelan Data Deret Waktu dengan Calendar effects Ade Gusalinda; I Made Sumertajaya; Septian Rahardiantoro
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.v8i1.147

Abstract

One of the commodities that has quite varied price fluctuations is broiler and carcass chicken. The context of forecasting is quite important considering the policies that can be taken by the producer and even the strategies that can be taken by consumers. This study attempts to modeling broiler and carcass prices together with Vector Autoregressive (VAR) which is one method in time series analysis that utilizes more than one time series variable. In addition, the effect of calendar calendar events is also the topic of discussion in this study which is implemented by the VAR-X method. As a result, the calendar effects variables that affect broiler and carcass prices are February, the first week of Ramadan and Eid-ul-Fitr. Furthermore, forecasting with VAR-X produces a pretty good value than VAR with lower MAPE criteria.
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).
Penerapan Metode CART pada Pengklasifikasian Bekerja dan Pengangguran di Kabupaten Subang Ilma Nabila; I Made Sumertajaya; Mulianto Raharjo
Xplore: Journal of Statistics Vol. 11 No. 2 (2022):
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (562.57 KB) | DOI: 10.29244/xplore.v11i2.890

Abstract

Unemployment is a complex problem faced by developing countries, including Indonesia. The high unemployment rate in Indonesia impacts poverty, so that the government seeks to carry out economic development. Subang is one of the districts that contributed 8,68 percent of the open unemployment rate in 2019 and increased by 9,48 percent in 2020. The incessant growth of industrial estates and smart city program development in Subang is one of the efforts to reduce unemployment. This study used a classification and regression tree (CART) to determine the factors that influenced unemployment status in Subang Regency. The advantage of the CART method is easy to interpret the results of the analysis. However, the accuracy of the classification tree is relatively low due to data imbalance. Therefore, this study used SMOTE method to deal with this problem. The optimal classification tree was formed from 17 terminal nodes and 6 explanatory variables. 7 terminal nodes represent work as work, and 10 terminal nodes represent unemployment as unemployment. The 6 explanatory variables consist of marital status (X3), attending job training (X5), the position in the family (X4), the education level (X2), gender (X1), and age (X6).
SUPPORT VECTOR REGRESSION (SVR) METHOD FOR PADDY GROWTH PHASE MODELING USING SENTINEL-1 IMAGE DATA Hengki Muradi; Asep Saefuddin; I Made Sumertajaya; Agus Mohamad Soleh; Dede Dirgahayu Domiri
MEDIA STATISTIKA Vol 16, No 1 (2023): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.16.1.25-36

Abstract

Support Vector Machines (SVMs) have received extensive attention over the last decade because it is claimed to be able to produce models that are accurate and have good predictions in various situations. This study aims to test the SVR (Support Vector Regression) method for modeling the growth phase of paddy using sentinel-1 image data. This method was compared for its accuracy with the LR (Linear Model) method using RMSE and R2 statistics and model stability using 10 repetitions. The accuracy of the model with the two best predictors is when the NDPI and API Polarization Index are the predictors. The paddy age model from the SVR method is better than the paddy age model from the LR method, where the SVR method produces a model with an average RMSE of 11.13 and an average coefficient of determination of 88.10%. The accuracy of the SVR model with NDPI and API predictors can be improved by adding VH polarization to the model, where the average RMSE statistic decreases to 11.0 and the average coefficient of determination becomes 88.42%. In this scenario, the best model gives a minimum RMSE value of 10.35 and a coefficient of determination of 90.05%.
Co-Authors A Kurnia A. A. Mattjik AA Mattjik Abd. Rasyid Syamsuri Abdu Alifah Abdul Aziz Nurussadad Ade Gusalinda Adelia Putri Pangestika Agus Mohamad Soleh Agustin Faradila Ahmad Anshori Mattjik Ahmad Ansori Matjjik Ahmad Ansori Mattjik Ahmad Ansori Mattjik Aidi, Muhammad N Aji Hamim Wigena Akbar Rizki Alfian Futuhul Hadi Alwani, Nadira Nisa Amanda Permata Dewi Anang Kurnia Andi Setiawan Andrew Donda Munthe Anggraini Sukmawati Anik Djuraidah Arina, Faula Aropah, Vina Da'watul Aropah, Vina Da’watul ASEP SAEFUDDIN Azis, Irfani Bagus Sartono Budi Susetyo Budi Susetyo Choirun Nisa Chrisinta, Debora Cici Suhaeni Cynthia Wulandari Dede Dirgahayu Domiri Dian Kusumaningrum Dian Kusumaningrum Diki Akhwan Mulya Doni Suhartono Dwi Agustin Nuriani Sirodj Dwi Yulianti Embay Rohaeti Emeylia Safitri Erfiani Erfiani Erfiani Erfiani, Erfiani Erwina Erwina Evita Choiriyah Fadilah, Anggita Rizky FAHREZAL ZUBEDI Fahriya, Andina Faqih Udin dan Jono M. Munandar Meivita Amelia Farit M Afendi Farit Mochamad Afendi Fitria Hasanah Fitrianto, Anwar Gusti Tasya Meilania Halimatus Sa'diyah Hari Wijayanto Haryastuti, Rizqi Hengki Muradi Hidayat, Agus Sofian Eka Hilda Zaikarina Huda, Usep Firdaus I Gede Nyoman Mindra Jaya Ilham Alifa Azagi Ilma Nabila Imam Adiyana Indahwati Indonesian Journal of Statistics and Its Applications IJSA Iqbal, Teuku Achmad Irfani Azis Irfani Azis Ismah, Ismah Isti Rochayati Itasia Dina Sulvianti Jamaluddin Rabbani Harahap Jasiulewicz, Anna Jono Mintarto Mundandar Khairil Anwar Notodiputro Kurnia, A Kusdaniyama, Nunung Kusman Sadik Laradea Marifni Lestari P, Merryanty Linda Sakinah M. Syamsul Maarif Ma'mun Sarma Manuel Leonard Sirait Manuel Leonard Sirait Manuel Leonard Sirait Mattjik, AA Maulida, Annisaturrahmah Mega Pradita Pangestika Meilania, Gusti Tasya Merryanty Lestari P Mohamad Rhesa Adisty Muhamad Nur Aidi Muhammad Amirullah Yusuf Albasia Muhammad N Aidi Muhammad Nur Aidi Muhammad Ulinnuha Mulianto Raharjo Newton Newton Nina Valentika Ningsih, Wiwik Andriyani Lestari Noercahyo, Unggul Sentanu Novi Hidayat Pusponegoro Nunung Kusdaniyama Nunung Kusdaniyama Nur Hikmah Nurlia Eka Damayanti Nurus Sabani Pasaribu, Sahat M. Pepi Novianti Pika Silvianti Pratiwi, Windy Ayu Pudji Muljono Purwaningsih, Siti Samsiyah Puspasari, Novia Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rizqi Haryastuti Sahat M. Pasaribu Sarah Fadhlia Sarma, Ma’mun Satria Yudha Herawan SATRIYAS ILYAS Setyono Setyono Setyono Sirait, Manuel Leonard Siti Samsiyah Purwaningsih Sri Surjani Tjahjawati Sunardi Sunardi Sunardi Suruddin, Adzkar Adlu Hasyr Sutomo, Valantino A Syafitri, Utami Syella Sumampouw Tsabitah, Dhiya Ulfah Sulistyowati Utami Dyah Syafitri Valantino A Sutomo Valentika, Nina Wibowo, Dwi Yoga Ari Winda Nurpadilah Windi D.Y Putri Wiwik Andriyani Lestari Ningsih Wiwik Andriyani Lestari Ningsih Yenni Angraini Zulkarnain, Rizky