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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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Journal : FORUM STATISTIKA DAN KOMPUTASI

 1 
Multi-locations trials play an important role in plant breeding and agronomic research. Study concerning genotype-environment interaction is needed in the selection of genotype to be released. AMMI (Additive Main Effect and Multiplicative Interaction) is one of the statistical techniques used to analyze data from multi-locations trials. The analysis of AMMI is a combination of analysis between additive main effect and principal component analysis. Multi-location sampling data which were collecte Pika Silvianti; Khairil Anwar Notodiputro; I Made Sumertajaya
FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 1 (2010)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Multi-locations trials play an important role in plant breeding and agronomic research. Study concerning genotype-environment interaction is needed in the selection of genotype to be released. AMMI (Additive Main Effect and Multiplicative Interaction) is one of the statistical techniques used to analyze data from multi-locations trials. The analysis of AMMI is a combination of analysis between additive main effect and principal component analysis. Multi-location sampling data which were collected several years on several planting season used these analyzed separately. To obtain more comprehensive information of multi-location sampling data, an analysis which combines all of the information through out the years are needed. One of the alternatives is the Bayesian approach. This method utilizes initial information on the estimated parameters and information from samples. The simulation states that prediction with Bayesian methods will produce a better estimator, because the MSE of the Bayesian estimator is smaller than the MSE estimator generated using least squares method.
Additive Main Effects Multiplicative Interaction (AMMI) is a widely known analysis used in understanding genotype and environment interaction (GEI) in plant breeding research. The interpretation of AMMI based on biplot visualizes the first two component of principle components analysis. Biplot of AMMI is only an exploration analysis and it does not provide the hypothesis testing, so it can conduct  different  interpretation by plant breeding researchers. The aim of this research is to find a sys Pepi Novianti; Ahmad Ansori Mattjik; I Made Sumertajaya
FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 1 (2010)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Additive Main Effects Multiplicative Interaction (AMMI) is a widely known analysis used in understanding genotype and environment interaction (GEI) in plant breeding research. The interpretation of AMMI based on biplot visualizes the first two component of principle components analysis. Biplot of AMMI is only an exploration analysis and it does not provide the hypothesis testing, so it can conduct  different  interpretation by plant breeding researchers. The aim of this research is to find a systematic approach through bootstrap resampling method. Bootstrap resampling method in AMMI model produces confidence region of the first two interaction principle component ( and ) for genotype and environment respectively. Bootstrap confidence region of  and  estimated the stability of genotype, thus making AMMI analysis more precise and realiable for characterization and selection of  genetic  environment.
PENGARUH PEMILIHAN ARAH ACUAN 00 DAN ARAH ROTASI PADA ANALISIS KORELASI DAN REGRESI LINIER-SIRKULAR (STUDI KASUS: PETA KAWASAN RAWAN BENCANA LETUSAN GUNUNG Abdul Aziz Nurussadad; I Made Sumertajaya; Ahmad Ansori Mattjik
FORUM STATISTIKA DAN KOMPUTASI Vol. 16 No. 1 (2011)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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The measurement results doesn't only consist of data with linear attributes, but also data with circular attributes. The circular data has a uniqueness that is not owned by the linear data, circular data is independent of the choice of 0o reference and rotation direction. The uniqueness of circular data analysis is tested in linear circular correlation and linear circular regression. The results of correlation analysis proved that the selection of the reference direction 0o can be done subjectively because the linear circular correlation results show the same value 0.899 for all possible selection of 0o reference and rotation direction. For linear circular regression, the model constructed has a same coefficient of determination that is 0.808 and the same b0, which is 5.231 for all possible selection of 0o reference and rotation direction. Similarly, statistics from the error of linear circular regression analysis have the same value, minimum = -2.693, quartile 1 = -0.835, median = -0.171, quartile 3 = 0.548, maximum = 8.421. Alleged circular linear regression parameters, namely b1 and b2, forming a cycle that each has in common b1 = -1.226 E-07-2.728 cos (α) - 2.655 sin (α) and b2 = 3.061 E-07-2.655 cos (α ) + 2.728 sin (α) where α is the position of the 0o reference direction in degrees on each model.   Keywords :  Directional Statistics, Circular Statistics, Linear-Circular Regression, Linear Circular Correlation
ANALISIS KONJOIN: METODE FULL PROFILE DAN CBC UNTUK MENELAAH PERSEPSI MAHASISWA TERHADAP PILIHAN PEKERJAAN I Made Sumertajaya; Erfiani Erfiani; Windi D.Y Putri
FORUM STATISTIKA DAN KOMPUTASI Vol. 12 No. 1 (2007)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Penggerombolan adalah proses mengelompokkan objek ke dalam kelompok-kelompok yang memiliki kemiripan. Beberapa masalah yang sering dijumpai dalam analisis gerombol yaitu skala pengukuran peubah tidak sama dan jumlah objek besar serta jumlah gerombol tidak diketahui. Salah satu pendekatan untuk menangani masalah ini tanpa mentransformasi peubah-peubah tersebut adalah dengan menggunakan metode Two Step Cluster. Penelitian ini bertujuan sebagai penerapan metode Two Step Cluster dengan menggerombolkan desa/kelurahan yang berada di Jawa Barat. Hasil penggerombolan dengan metode TwoStep Cluster, gerombol awal yang dihasilkan pada tahap pertama adalah sebanyak delapan gerombol, sedangkan gerombol optimal yang dihasilkan pada tahap dua adalah sebanyak tiga gerombol. Gerombol satu tidak dapat dikatakan sebagai suatu gerombol, karena anggota-anggota didalamnya merupakan objek-objek yang memencil ekstrim dan tidak dapat dimasukkan ke dalam gerombol lainnya. Desa/kelurahan yang termasuk gerombol dua memiliki karakteristik pedesaan. Desa/kelurahan tersebut memiliki lahan terluas, jumlah rumah tangga pertanian terbanyak, namun belum berkembang dalam bidang industri serta komunikasi dan informasi. Sehingga untuk meningkatkan potensi desa pada gerombol ini, yang harus diperhatikan adalah peubah-peubah yang tingkat perkembangannya masih rendah. Gerombol tiga memiliki karakteristik desa yang berstatus perkotaan. Desa/kelurahan pada gerombol ini memiliki jarak terdekat ke pusat kota, cukup maju dalam bidang industri, komunikasi dan informasi, namun memiliki angka pengangguran tertinggi.
KLASIFIKASI GENOTIPE PADA DATA TIDAK LENGKAP DENGAN PENDEKATAN MODEL AMMI Ahmad Anshori Mattjik; I Made Sumertajaya; Pika Silvianti
FORUM STATISTIKA DAN KOMPUTASI Vol. 12 No. 1 (2007)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Percobaan multilokasi mempunyai peranan penting dalam perkembangbiakan tanaman dan penelitian agronomi. Kajian mengenai interaksi antara genotipe dan lingkungan diperlukan dalam penyeleksian genotipe yang akan dilepas. Metode statistika yang biasa digunakan untuk mengolah data hasil percobaan multilokasi salah satunya adalah AMMI (Additive Main effect and Multiplicative Interaction).  Metode ini menggabungkan analisis ragam  aditif bagi pengaruh utama perlakuan dengan analisis komponen utama pada pengaruh interaksinya. Pendekatan AMMI juga sangat baik digunakan untuk uji multilokasi tanpa ulangan. AMMI adalah analisis yang membutuhkan data yang lengkap. Jika ada data yang hilang, maka harus dilakukan pendugaan terhadap data tersebut. Pada kasus data tidak lengkap, diperlukan suatu metode pendugaan data untuk mempermudah analisis. Metode yang dapat  digunakan antara lain connected data dan algoritma EM-AMMI untuk menduga data yang tak lengkap.
SURVIVAL ANALYSIS OF CUSTOMER IN POSTPAID TELECOMMUNICATION INDUSTRY Doni Suhartono; Asep Saefuddin; I Made Sumertajaya
FORUM STATISTIKA DAN KOMPUTASI Vol. 18 No. 1 (2013)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Currently, the business competition in mobile telecommunication industry among providers in Indonesia is tighter and it has given rise to a phenomenon of customer defection which has serious consequences for the business performance. In the current circumstances, customers are faced numerous options to be selected that probably cause them at risk to get churn. Therefore, it becomes one of the challenges encountered by Division of Loyalty and Retention to makes the efforts of decreasing customer defection. So that it is important conducting a model of churn practically applied to predict tendency of customer churn and also recognizing the prognostic factors influence customer churn. Survival analysis modelling, such as Cox’s proportional hazard model, was very successful in previous research, which investigatedthe relationship between survival time and possible prognostic factors. Based on the research, Cox’s proportional hazard model of customer lifetime is effective to distinguish relative risk between churn customers and others, and also between which loyal customers and with other short time customers with their significant prognostic factors. Afterwards the simulation of the survival probability estimated over time with particular possible combination of the most significant characteristics affecting tendency of churn, are able to predict such information of lifetime to churn event and compare the survival performance of one another. Finally, the results of this research is able to yield simple, helpful and applicable results as the principle of taking decission for optimizing their customer retention and/or treatment resources in their customer retention efforts for the company.Key words : Churn, Cox’s proportional hazard model, customer retention, survival analysis and telecommunication industry.
PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP BAGI ARAH RATA-RATA DATA SIRKULAR (Bootstrap Confidence Interval Estimation of Mean Direction for Circular Data) Cici Suhaeni; I Made Sumertajaya; Anik Djuraidah
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 2 (2012)
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Abstract

The confidence interval is an estimator based on the sampling distribution. When the sampling distribution can not be derived from population distribution, the bootstrap method can be used to estimate it. Three methods used to estimate the bootstrap confidence interval for circular data were equal-tailed arc (ETA), symmetric arc (SYMA), and likelihood-based arc (LBA). In this study, three methods were evaluated through simulation study. The most important criterion to evaluate them were true coverage and interval width. The simulation results indicated in all methods, the interval width shortened when the concentration parameter increased. True coverage approached confidence level when the concentration parameter were one or more. For small concentration parameter, all three methods appeared unstable. Based on the true coverage, SYMA was the best, while in terms the interval width, LBA was the best one. For both criterion could be summarized that ETA is the best result. ETA applicated for estimate the period of Dengue Fever outbreaks in Bengkulu. The estimation showed that Dengue Fever outbreaks in 2009 were October through January. In 2010, it were January through March, and in 2011, it were June through September.Keywords : Circular, Bootstrap confidence interval, Equal-tailed arc, Symmetric arc, Likelihood-based arc.
MODELLING OF FORECASTING MONTHLY INFLATION BY USING VARIMA AND GSTARIMA MODELS Andi Setiawan; Muhammad Nur Aidi; I Made Sumertajaya
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

The model parameters could be different form the well to the factors of time and location. A general model of GSTAR can be used to establish model the inflation in some locations by using GSTARIMA model if time series data is self-contained autoregressive, differentiation, and moving averages. This study examines whether the effect of such locations on the GSTARIMA model is better than the VARIMA model that regardless of the location influences. The aim of this study is to establish two models of inflation six provincial capitals in Java using VARIMA model and GSTARIMA model with inverse distance weighting. Dummy variables have been used to overcome normality and white noise problems. The best forecasting of monthly inflation in provincial captitals in Java Island is GSTAR(1;1) with inverse distance weighting. It has smallest RMSE value of 0.9199.Key words : GSTARIMA, Inverse Distance, RMSE, VARIMA
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 Azagi, Ilham Alifa 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 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 Yenni Angraini Zulkarnain, Rizky