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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Ilmu Pertanian Indonesia Jurnal Penyuluhan MEDIA KONSERVASI Jurnal Manajemen dan Agribisnis FORUM STATISTIKA DAN KOMPUTASI Forum Pasca Sarjana Media Gizi dan Keluarga Buletin Peternakan Media Statistika Statistika Jurnal Manajemen Teknologi IPTEK The Journal for Technology and Science CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ilmu Komunikasi Sains Tanah Journal The Winners Journal of Economics, Business, & Accountancy Ventura Gadjah Mada International Journal of Business JAM : Jurnal Aplikasi Manajemen Journal of the Indonesian Mathematical Society Jurnal RISET Geologi dan Pertambangan Journal of Regional and City Planning JUITA : Jurnal Informatika Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Binus Business Review JURNAL HAMA DAN PENYAKIT TUMBUHAN TROPIKA Journal of Economic Education Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal SEPA (Social Economic and Agribusiness Journal) Informatika Pertanian BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Agrisocionomics: Jurnal Sosial Ekonomi Pertanian Jurnal Kebijakan Sosial Ekonomi Kelautan dan Perikanan KEK (Kajian Ekonomi dan Keuangan) STI Policy and Management Journal JURNAL PANGAN FIBONACCI: Jurnal Pendidikan Matematika dan Matematika InPrime: Indonesian Journal Of Pure And Applied Mathematics ESTIMASI: Journal of Statistics and Its Application Jurnal Statistika dan Matematika (Statmat) MEANS (Media Informasi Analisa dan Sistem) Jurnal Risalah Kebijakan Pertanian dan Lingkungan BISNIS & BIROKRASI: Jurnal Ilmu Administrasi dan Organisasi JURNAL ILMIAH GLOBAL EDUCATION Malcom: Indonesian Journal of Machine Learning and Computer Science Xplore: Journal of Statistics STATISTIKA Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) Society Media Penelitian dan Pengembangan Kesehatan Indonesian Journal of Statistics and Its Applications Journal on Mathematics Education eJEBA

ASEP SAEFUDDIN

Departemen Statistika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogorm, Kampus IPB Darmaga, Bogor 16688

Author-ID : 234691

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Veterinary Other

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INVESTMENT AND RESILIENCE OF THE AGRICULTURAL SECTOR FACING THE COVID 19 CRISIS Arman Arman; Asep Saefuddin; Fathia Anggriani Pradina; Sri Yusnita Burhan
Agrisocionomics: Jurnal Sosial Ekonomi Pertanian Vol 7, No 1 (2023): March 2023
Publisher : Faculty of Animal and Agricultural Science, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/agrisocionomics.v7i1.15126

The Covid 19 pandemic appeared suddenly and caused a global crisis that threatens the food security of various countries. The economy was paralyzed, but this did not happen to the agricultural sector in Indonesia. This study aims to (1) examine the role of the agricultural sector during the Covid-19 pandemic crisis, (2) analyze the level of investment efficiency in the growth of the agricultural sector before and during the Covid 19 pandemic crisis, and (3) formulate a policy solution for the agricultural sector facing the crisis. The research method uses Incremental Capital Output Ratio (ICOR) and descriptive methods. We are of the view that the agricultural sector has the resilience to face the Covid 19 crisis marked by positive growth, the second largest employment absorption, increased farmer exchange rates and exports. The performance of the agricultural sector was still efficient in the 2012-2019 range even though the ICOR value relatively rose and growth tended to decline. The agricultural sector faces food supply chain constraints, food loss and loss of added value. The triggers are long distribution chains, technology, high input costs, road and transportation infrastructure. The government and industry must support the provision of supporting infrastructure, namely technology, infrastructure, human resources and institutional strengthening. Diversification of food, industry 4.0, high-quality seeds and food supply chain as part of mitigation and adaptation needs to be supported by technology, human resources and strong institutions. The agricultural sector has proven to play a vital role in economic resilience.

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

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.

Penetapan Ekstrakurikuler Wajib untuk Siswa Sekolah Menengah Atas Berdasarkan Kecerdasan Majemuk Muggy David Cristian Ginzel; Asep Saefuddin; Erfiani Erfiani
Xplore: Journal of Statistics Vol. 9 No. 1 (2020)
Publisher : Department of Statistics, IPB

Senior high school in Indonesia is divided into two groups, namely Natural science and Social science. Those grouping of majors is allegedly not appropriate enough the potential of students yet because of the multiple intelligence of each student is different. This study aims to establish an extracurricular program for everyone grouped by multiple intelligences carried out by each student. The method used in this study are the non-hierarchical clustering k-Means and hierarchical clustering Ward method. The k-Means method used to determine the effective number of groups, while Ward method used to identify the member of each cluster and the recommendation of extracurricular in the cluster obtained. Based on the results of the clustering analysis, there are five clusters obtained, Language and Fine Arts; Communication; Leadership; Nature Lovers; and also Design and Photography.

Penerapan Two Step Cluster untuk Mengklasifikasikan Desa di Kabupaten Madiun Berdasarkan Data Potensi Desa Alif Supandi; Asep Saefuddin; Itasia Dina Sulvianti
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Village development is a fundamental part of national development. Developing villages requires information on society necessities. This research aims at clustering villages in Kabupaten Madiun which has similar characteristics among each other and identify characteristics of the built clusters. Therefore, specific problems in the clusters of villages may become the foundation to implement development. The method that used for grouping objects with combined variables is two-step cluster. This analysis was used 14 variables consist of six categorical variables and eight numerical variables. The clustering analysis produces four clusters. The clusters that need more attention to be developed was Cluster 2 which had minimum facilities and resources. The average Silhouette coefficient for the clusters built was 0.3 which can be considered as fair category.

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

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%.

Klasifikasi Varietas Unggul Padi Menggunakan Metode Bagging, Boosting, dan Extremely Randomized Trees Lukmanul Hakim; Asep Saefuddin; Sausan Nisrina
Statistika Vol. 22 No. 2 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i2.1455

Rice is one of the agricultural products which is the main commodity in Indonesia. Supporting factors that play a very important role in efforts to increase rice production are superior varieties. Superior rice varieties have characteristics that are similar to one another. Thus, farmers must choose the varieties used through a classification process to determine the appropriate type of rice. At this stage, three methods are used: bagging, boosting, and extremely randomized trees. From the analysis results, the overall method of extremely randomized trees has more optimal capabilities compared to the bagging and boosting methods. This is indicated by the three parameters, sensitivity, specificity, and accuracy, which have the highest values.

Analisis Data Produk Domestik Regional Bruto Pulau Jawa Menggunakan Pendekatan Regresi Kuantil Spasial Lismayani Usman; Asep Saefuddin; Anik Djuraidah
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 2, Juli, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v4i2.27573

Gross Regional Domestic Product (GRDP) often shows spatial patterns. In a spatial perspective, spatial effects consist of of spatial dependence and spatial heterogeneity. To address the problems, this study uses spatial autoregressive quantile regression/SARQR model. SARQR is a method that combines Spatial Autoregressive (SAR) modeling with quantile regression. There are two methods that can be used to estimate the parameters of the SARQR model, namely Two Stage Quantile Regression (2SQR) and Instrumental Variable Quantile Regression (IVQR). The simulation results showed that IVQR method is better than 2SQR method. IVQR provides a smaller value and variance of bias. Furthermore, IVQR method is applied to Java’s GRDP data on 2019. The results showed that the number of workers significantly influences Java’s GRDP. The highest quantile verification skill score (QVSS) value is 0.713 when τ =0.75. It means that in the 75% quantile modeling, the model can describe the GRDP diversity of 71.3%.

Mixed Models of Non-Proportional Hazard and Application in The Open Distance Education Students Retention Data Dewi Juliah Ratnaningsih; Anang Kurnia; Asep Saefuddin; I Wayan Mangku
Journal of the Indonesian Mathematical Society VOLUME 28 NUMBER 3 (NOVEMBER 2022)
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.28.3.1185.323-344

The problem that arises in the Cox model is that there are more than two types of covariates and the presence of random effects is a non-proportional hazard (NPH). One example of a case that involves many factors is student retention. Low student retention can lead to dropping out of college or failure in completing studies. The purpose of this study is to overcome the problem of NPH caused by the presenceof time-independent covariates, time-dependent covariates, and random effects. The research method uses simulation. Some of the modified models are the stratified Cox model, the extended Cox model, and the frailty model. The developed model is applied to distance education student retention data. The results of the study show that frailty and study programs provide considerable diversity in explaining thetotal diversity of the model. It can be concluded that frailty needs to be considered by UT to improve the quality of services to students. In addition, other covariates that have a significant effect on UT student learning retention modeling are age, domicile, gender, GPA, marital status, employment status, number of credits taken, and number of registered courses.

N-Level Structural Equation Models (nSEM): The Effect of Sample Size on the Parameter Estimation in Latent Random-Intercept Model Eminita, Viarti; Saefuddin, Asep; Sadik, Kusman; Syafitri, Utami Dyah
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol 6, No 1 (2024)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/inprime.v6i1.38914

Multilevel Structural Equation Modeling (MSEM) is claimed to address hierarchical data structures and latent response variables, but it becomes unstable with an increasing number of levels. N-Level SEM (nSEM) is an SEM framework designed to handle a growing number of levels in the model. The nSEM framework uses the Maximum Likelihood Estimation (MLE) method for parameter estimation, which requires a large sample size and correct model specification. Therefore, it is essential to consider the necessary minimal sample size to ensure accurate and efficient parameter estimation in the nSEM model. This study examined how sample size affects the performance of parameter estimators in nSEM models. We propose a method to evaluate the effect of many environments to estimate the results of factor loadings and environmental variance produced by the model. In addition, we also assess the impact of environment size on the estimation results of factor loadings and individual variance. The results were then applied to actual data on student mathematics learning motivation in Depok. The findings show that neither the number of environments nor the size of the environment affects the performance of fixed parameter estimation in the nSEM model. nSEM indicates excellent performance in estimating environmental variance at level 2 when the number of environments increases. Conversely, increasing the size of the environment worsens the performance of estimating individual variance parameters. Overall, the nSEM framework for the latent random-intercept (LatenRI) model performs well with increasing sample sizes. The application data on LatenRI models show almost similar estimation results.Keywords: Hierarchical data; Latent random intercept model; Multilevel structural equation modeling; n-Level structural equation modeling.AbstrakMultilevel Structural Equation Modeling (MSEM) diklaim dapat mengatasi struktur data hierarki dan variabel respons laten, namun menjadi tidak stabil dengan bertambahnya jumlah level. N-Level SEM (nSEM) adalah kerangka kerja SEM yang dirancang untuk menangani semakin banyak level dalam model. Kerangka kerja nSEM menggunakan metode Maximum Likelihood Estimation (MLE) untuk estimasi parameter, yang memerlukan ukuran sampel yang besar dan spesifikasi model yang benar. Oleh karena itu, penting untuk mempertimbangkan ukuran sampel minimal yang diperlukan untuk memastikan estimasi parameter yang akurat dan efisien dalam model nSEM. Studi ini menguji bagaimana ukuran sampel mempengaruhi kinerja penduga parameter dalam model nSEM. Kami mengusulkan metode untuk mengevaluasi pengaruh banyak lingkungan dalam memperkirakan hasil factor loadings dan varians lingkungan yang dihasilkan oleh model. Selain itu, kami juga menilai dampak ukuran lingkungan terhadap hasil estimasi factor loadings dan varians individu. Hasilnya kemudian diterapkan pada data aktual motivasi belajar matematika siswa di Depok. Hasil menunjukkan bahwa baik jumlah lingkungan maupun ukuran lingkungan tidak mempengaruhi kinerja estimasi parameter tetap pada model nSEM. nSEM menunjukkan kinerja yang sangat baik dalam memperkirakan varians lingkungan pada level 2 ketika jumlah lingkungan meningkat. Sebaliknya, peningkatan ukuran lingkungan akan memperburuk kinerja pendugaan parameter varians individu. Secara keseluruhan, kerangka nSEM untuk model intersepsi acak laten (LatenRI) bekerja dengan baik dengan meningkatnya ukuran sampel. Data penerapan model LatenRI menunjukkan hasil estimasi yang hampir serupa.Kata Kunci: Data hirarki; Model intersep acak laten; Model persamaan structural multilevel; Model persamaan structural n-level. 2020MSC: 62D99

Perbandingan Kinerja Model Berbasis RNN pada Peramalan Data Ekonomi dan Keuangan Indonesia: Performance Comparison of RNN-Based Models in Forecasting Indonesian Economic and Financial Data Alkahfi, Cahya; Kurnia, Anang; Saefuddin, Asep
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 4 (2024): MALCOM October 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i4.1415

Peramalan deret waktu merupakan salah satu elemen kunci dalam analisis ekonomi dan keuangan. memungkinkan pemangku kepentingan untuk membuat perkiraan terhadap berbagai indikator ekonomi sebelum data resmi dirilis. Dalam konteks ini, model pembelajaran mesin seperti Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), dan Gated Recurrent Unit (GRU) menunjukkan potensi yang menjanjikan dalam memprediksi data deret waktu. Sejumlah penelitian juga menegaskan bahwa LSTM dan GRU mampu mengungguli kinerja RNN. Kedua model tersebut memiliki mekanisme untuk mengatasi masalah vanishing gradient yang sering ditemui pada model RNN konvensional. Penelitian ini menitikberatkan untuk menguji kinerja ketiga model tersebut pada data-data yang ada di Indonesia. Agar hasil lebih komprehensif, penelitian ini akan menguji model pada tiga jenis data yang berbeda meliputi IHSG, nilai ekspor dan PDB. Hasil penelitian ini mengindikasikan bahwa secara keseluruhan, model GRU menunjukkan kinerja terbaik, diikuti oleh model LSTM yang juga kompetitif dibandingkan RNN. Selain akurasi, model GRU dan LSTM juga menonjol dalam hal stabilitas kinerja, ditandai dengan simpangan baku yang relatif kecil jika dibandingkan dengan RNN. Keunggulan ini menjadi semakin signifikan terutama saat diterapkan pada model PDB dimana hanya tersedia untuk periode waktu yang pendek.

Co-Authors . Marzuki . Sutriyati Achmad ACHMAD . Achmad Ramzy Tadjoedin adwendi, satria june Agus M Soleh Agus Mohamad Soleh Agustifa Zea Tazliqoh Ahmad A. Mattjik Ahmad Ansori Mattjik Aji H. Wigena Aji Hamim Wigena Aldi, Muhammad Nur Alif Supandi Alifviansyah, Kevin Alinda F. M. Zain Alkahfi, Cahya Ananda Shafira Ananda, Frisca Rizki Anang Kurnia Andres Purmalino Ani Suryani Anik Djuraidah Arief Daryanto Arista Marlince Tamonob Arman Arman Arman Arman Arman Arman Arman Arman Arnita Arnita Azagi, Ilham Alifa Bagus Sartono Bambang Indriyanto Basita Ginting Budhi Purwandaya, Budhi Budi Marwoto Budi Susetyo Bunasor Sanim Cece Sumantri Chalid Talib Citra Jaya Daowen Zhang Dede Dirgahayu Domiri Dede Dirgahayu Domiri, Dede Dirgahayu Dewi Juliah Ratnaningsih Diah Krisnatuti Dian Handayani Dian Kusumaningrum Dian Kusumaningrum, Doni Suhartono Dudung Darusman Eka Intan Kumala Putri Embay Rohaeti Eminita, Viarti Enny Kristiani Enny Kristiani Erfiani Erfiani Erfiani Eri Purnomohadi Etih Sudarnika Etty Riani Euis Sunarti Eva Z Yusuf Fatah Sulaiman Fitrah Ernawati Frisca Rizki Ananda Fulazzaky, Tahira H. R. Eddie Gurnadi HAJRIAL ASWIDINNOOR Hanny Nurlatifah Harapin Hafid H. Hardiansyah . Hardinsyah Hari Wijayanto Hartoyo, harry Hasnataeni, Yunia Hendra Prasetya Hengki Muradi Heny Suwarsinah Hermanto Siregar Hidayat Syarief Hilman Dwi Anggana Husaini . I Made Sumertajaya I Wayan Mangku Ida Mariati Hutabarat Indahwati Itasia Dina Sulvianti Jajang Jajang Jodi Vanden Eng Joko Affandi Joko Affandi Joko Sutrisno JOKO SUTRISNO Khairil Anwar Notodiputro Kristiani, Enny Kusman Sadik Lia Budimulyati Salman Lia Ratih Kusuma Dewi Lilik Noor Yuliati Lismayani Usman Lukmanul Hakim Lukmanul Hakim M. Yunus M. Yunus Maghfiroh, Firda Aulia Mangara Tambunan Margono Slamet Marimin , Marimin Marimin Marizsa Herlina Marliati . Marliati Marliati Mirnawati Sudarwanto Muggy David Cristian Ginzel Muhammad Nur Aidi Muradi, Hengki Musa Hubeis mutiah, siti Ni Nyoman Sawitri Nimmi Zulbainarni Ningsih, Wiwik Andriyani Lestari Ninuk Purnaningsih Nirawita Untari Nunung Nuryartono Nuramaliyah, Nuramaliyah Nurlatifah, Hanny Nurul Hidayati Nusar Hajarisman Pang S. Asngari Pien Budiyanto Prabowo Tjitropranoto Pradina, Fathia Anggriani Priyadi Kardono Purnomohadi, Eri R. Ruswandi Rahardiantoro, Septian Rahmadi Sunoko Rahmadi Sunoko Ratna Megawangi Rimun Wibowo Ristu Haiban Hirzi, Ristu Rita Kusriastuti Rizal Syarief Rizal Syarief Rizka Rahmaida Ronny Rachman Noor Rudy Priyanto S. Damanhur, Didin Santun R.P. Sitorus SANTUN R.P. SITORUS Sarah Putri Sarsidi Sastrosumarjo Sausan Nisrina Setiadi Djohar Setiawan Setiawan Siti Sundari Sitti Nurhaliza Sjafri Mangkuprawira Sjafri Mangkuprawira Soedijanto Padmowihardjo Soekirman Soekirman Soetrisno Hadi Sony Sunaryo Sri Yusnita Burhan Suhartono . Suhartono . Sumardjo Sumarjo Gatot Irianto Sumartono Sumartono Sutarman Sutarman . Suwarsinah, Heny Syafri Mangkuprawira Syafri Mangkuprawira Syarifah Iis Aisyah TADJOEDIN, ACHMAD RAMZY Tagor Alamsyah Harahap Talib, Chalid Tati Rajati Tati Suprapti Tiyas Yulita triguna, gunadi Ujang Sumarwan Umi Cahyaningsih Upik Kesumawati Hadi Utami Dyah Syafitri Wahida Ainun Mumtaza William A. Hawley Wiwik Andriyani Lestari Ningsih Yani Nurhadryani Yekti Widyaningsih Yenni Angraini Yudhistira Arie Wijaya Yuni Ros Bangun Yusuf, Eva Z Zinggara hidayat

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