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All Journal FORUM STATISTIKA DAN KOMPUTASI Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Sosioinforma Journal of Mathematical and Fundamental Sciences JOIN (Jurnal Online Informatika) BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Socioeconomics and Development Andragogi: Jurnal Diklat Teknis Pendidikan dan Keagamaan Jurnal Jamu Indonesia Jurnal Penelitian Kebijakan Pendidikan Indonesian Journal of Educational Assesment Jurnal Pendidikan dan Kebudayaan Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Bulletin of Computer Science Research Jurnal Penelitian Kebijakan Pendidikan Aceh International Journal of Science and Technology Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Xplore: Journal of Statistics Indonesian Journal of Jamu Jurnal Pendidikan Progresif Indonesian Journal of Statistics and Its Applications Integra: Journal of Integrated Mathematics and Computer Science Limits: Journal of Mathematics and Its Applications
Budi Susetyo
Departemen Statistika, IPB University
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Journal : FORUM STATISTIKA DAN KOMPUTASI

 1 
Metode AMMI pada Model Campuran . Suwardi; Ahmad Ansori Mattjik; Budi Susetyo
FORUM STATISTIKA DAN KOMPUTASI Vol. 6 No. 1 (2001)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Metode AMMI (Additive Main Effects and Multiplicative Interaction) adalah suatu metode analisis yang menggabungkan pengaruh utama aditif pada analisis ragam dengan penguraian bilinear pengaruh interaksi ganda. Dalam berbagai penelitian agronomi metode ini mampu menjelaskan lebih efektif pengaruh dan pola struktur interaksi antara genotip dengan lingkungan. Metode AMMI dapat diterapkan pada model campuran jika pengaruh acak pada faktor interaksi dipandang sebagai pengaruh tetap. Sebagai ilustrasi penerapan, penelitian ini menggunakan data produksi padi gogo (ton per hektar) dari hasil percobaan multi lingkungan.
METODE KLASIFIKASI BERSTRUKTUR POHON DENGAN ALGORITMA CRUISE, QUEST, DAN CHAID Yasmin Erika Faridhan; Budi Susetyo; Alamudi Aam
FORUM STATISTIKA DAN KOMPUTASI Vol. 11 No. 1 (2006)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Metode klasifikasi berstruktur pohon mulai banyak digunakan di berbagai bidang terutama karena hasilnya yang mudah diinterpretasikan. Tulisan ini mengangkat CRUISE sebagai metode pohon klasifikasi yang relatif baru, serta membandingkannya dengan dua metode serupa yang telah dikenal sebelumnya, yaitu CHAID dan QUEST. Data jamur tingkat tinggi (mushroom) genus Agaricus dan Lepiota digunakan untuk penerapan empat metode (CRUISE 1D, CRUISE 2D, QUEST, dan CHAID). Analisis keempat metode tersebut menunjukkan bahwa peubah-peubah yang palingberkaitan dengan klasifikasi jamur yang ‘dapat dimakan’ atau ‘beracun’ adalah aroma dan warna sporanya. Untuk kasus ini, tampaknya CRUISE merupakan metode yang paling baik, dengan salah klasifikasi 0.0000 dan menghasilkan pohonterkecil. Berdasarkan metode ini, jamur yang dapat dimakan adalah jamur beraroma almond, adas, atau tidak beraroma, memiliki warna spora selain hijau, serta tidak ditemui secara bergerombol. Identifikasi jamur demikian cukup mendapat dukungan dari segi mikologi. QUEST dan CHAID masing-masing menghasilkan salah klasifikasi 0.0014 dan 0.0028. Dari segi kecepatan proses, CRUISE 1D adalah yang tercepat. QUEST sedikit lebih lambat daripada CRUISE 1D untuk data berukuran besar dan peubah kategorik yang banyak, sedangkan CRUISE 2D memerlukan waktu pemrosesan (CPU time) paling lama. Dengan salah klasifikasi yang relatif kecil dan pohon yang pendek, CRUISE dapat menjadi alternatif yang baik bagi metode klasifikasi lainnya.
EBLUP METHOD OF TIME SERIES AND CROSS-SECTION DATA FOR ESTIMATING EDUCATION INDEX IN DISTRICT PURWAKARTA Febriyani Eka Supriatin; Budi Susetyo; Kusman Sadik
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Since decentralisation was implemented in Indonesia, more detailed information about the condition of an area becomes very necessary to know as an evaluation of development that the government has done. the success development of a region can be seen through the Human Development Index (HDI). HDI consists of three basic dimensions, knowledge as one of that three basic measured by the index of education. This index is measured by the Adult Literacy Rate and Mean Years of Schooling. Education is one of the important factors in improving human development. The enhancement of education index results in increasing the HDI of an area. Purwakarta has a vision that is made as a district that excels in education in West Java, but until now Purwakarta’s education index is still below the West Java province. One step that can be done is to seek information on the education index each district in Purwakarta, with the aim to provide the right policy in each region. Direct estimation of the components forming the HDI for districts is not feasible because these estimates will generate a great value of variance, This is due to the size of the sample used is too small. This study proposes a statistical method by performing the estimation using small area estimation. These estimates using information from surrounding areas that can improve the effectiveness of the sample size and the lower the standard error. Some surveys are conducted regularly every year, in conducting indirect estimation in the survey such as this, efficiency of estimating education index for district level can be improved by including the random effect of the area as well as the random effect of time (Sadik and Notodipuro, 2006). So in this study will be used Empirical Best Linear Unbiased Prediction (EBLUP) by combining the time series and cross-section data for estimating the education index at the level of districts in Purwakarta. The direct estimation of education index produce a larger variance than our methode, it shown by comparing mean square error (MSE) of direct method and indirect method, direct method have the largest MSE.Key words : Indirect Estimation, Small Area Estimator, EBLUP, Time Series and Cross-Section, HDI, Education Index.
SMALL AREA ESTIMATION OF LITERACY RATES ON SUB-DISTRICT LEVEL IN DISTRICT OF DONGGALA WITH HIERARCHICAL BAYES METHOD Rifki Hamdani; Budi Susetyo; _ Indahwati
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Literacy Rate (LR) is defined as percentage of population aged over 15 with ability to read and write. LR, as one of people welfare indicators, is a measurement of educational development. The indicator, as a measurement of government performance on education, can be measured if all variables related is available. Statistics Indonesia (BPS) each year calculated LR based on National Socio-Economic Survey (SUSENAS) with estimation available only on provincial level and district level. Along with establishment of autonomous regional policy, where regional government had greater power to manage its own region, availability of LR on lower levels to monitor educational development is necessary. Due to sampling design of SUSENAS, accommodated only estimation on district level, will give high variance if used to estimate on lower sub-district level, although still unbiased. Modelling LR was done with Logit-Normal approach, because LR data followed Binomial Distribution. Good estimators from inadequate sample size can be obtained with method of Small Area Estimation (SAE). Hierarchical Bayes (HB) method is one of SAE methods which are proven to give good estimate on binomial distributed data as LR. Estimation on sub-district level in District of Donggala with HB method gave better result compared to the direct estimation with lower Mean Square Error (MSE).Key words : Small Area Estimation, Literacy Rate, Hierarchical Bayes, Logit-Normal Model
Co-Authors Aam Alamudi Aceng Komarudin Mutaqin Aditya Ramadhan adwendi, satria june Ahmad Ansori Mattjik Aji Hamim Wigena Akbar Rizki Amir, Sulfikar Anak Agung Istri Sri Wiadnyani Anang Kurnia Andina Fahriya Anis Sulistiyowati Anisa, Rahma ASEP SAEFUDDIN Aulia Dwi Oktavia Aunuddin Aunuddin Bagus Sartono Bambang H. Trisasongko Bambang Juanda Brian G. Lees Cici Suhaeni Cut N. Ummu Athiyah DAMAYANTI BUCHORI Darfiana Nur Dewi Jasmina Dewi Jasmina, Dewi Dhea Dewanti Dian Kurniasari Dito, Gerry Alfa Dyah R. Panuju Endah Febrianti Erfiani Erfiani Fadjrian Imran Fahriya, Andina Faisal Arkan Farit Mochamad Afendi Fitrianto, Anwar H Karwono Hafidz Muksin Hamid, Assyifa Lala Pratiwi Hari Wijayanto Herlina Herlina Hermawati, Neni Hiola, Yani Prihantini I Made Sumertajaya Inayatul Izzati Diana Yusuf Indahwati Indahwati Indahwati Indahwati, NFN Intan Juliana Panjaitan Iswan Achlan Setiawan Izzati Rahmi HG Jap Ee Jia Jia, Jap Ee Karwono, H Kesuma Millati Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Kristuisno Martsuyanto Kapiluka Kriswan, Suliana Kusman Sadik Kusni Rohani Rumahorbo La Ode Abdul Rahman La Ode Abdul Rahman La Ode Abdul Rahman M Nur Aidi M Nur Aidi, M Nur Mahmud A. Raimadoya Mohammad Masjkur Muh Nur Fiqri Adham Muhammad Amirullah Yusuf Albasia Muhammad Nur Aidi Muhammad Sayuti Mustofa Usman Nurfadilah, Khalilah Nurfajrin, Tria Ermina Nurul Qomariasih Pannu, Abdullah Pika Silvianti Pika Silvianti Putri, Mega Ramatika Qalbi, Asyifah Qomariasih, Nurul Rachman, Nurul Aulia Rahma Anisa Rahmawat, NFN Rahmawati, nFN Ratnasari, Andika Putri Rifannisa Bahar Rifki Hamdani Rizki, Akbar Robert, Zahira Rahvenia Safitri, Wa Ode Rahmalia Sanusi, Ratna Nur Mustika Satriyo Wibowo Sembiring, Febryna Sri Ningsih Desi Afriany Sulandra, Ardelia Maharani Sulfikar Amir Suliana Kriswan Supriatin, Febriyani Eka Syahrir, Nur Hilal A. Syahrir, Nur Hilal A. Sylvia P. Soetantyo Syukri, Nabila Tina Aris Perhati Tiya Wulandari Ulfa Afilia Shofa Utami Dyah Syafitri Wan Muhamad, Wan Zuki Azman Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Warsono Wulan Andriyani Pangestu Yasmin Erika Faridhan Zahira Rahvenia Robert Zainal A Koemadji