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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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BICLUSTERING APPLICATION IN INDONESIAN ECONOMIC AND PANDEMIC VULNERABILITY Ningsih, Wiwik Andriyani Lestari; Sumertajaya, I Made; Saefuddin, Asep
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Biclustering is an analytical tool to group data from two dimensions simultaneously. The analysis was first introduced by Hartigan (1972) and applied by Cheng and Church (2000) to the gene expression matrix. The Cheng and Church (CC) algorithm is a popular biclustering algorithm and has been widely applied outside the field of biological data in recent years. This algorithm application in economic and Covid-19 pandemic vulnerability cases is exciting and essential to do in order to get an overview of the spatial pattern and characteristics of the bicluster of economic and COVID-19 pandemic vulnerability in Indonesia. This study uses secondary data from some ministries. Forming a bicluster using the CC algorithm requires determining the delta threshold so that several types of delta thresholds are formed to choose the best (optimum) using the evaluation of the average value of mean square residue (MSR) to volume ratios. The similarity of the optimum bi-cluster with the other is also seen based on the Liu and Wang index values. The 0.01 delta threshold is chosen as the optimum threshold because it produces the smallest average value of MSR to volume ratios (0.00032). Based on Liu and Wang Index values, the optimum threshold has a similarity level below 50% with other types of delta thresholds, so the threshold is the best unique threshold. The optimum threshold resulted in six biclusters (six spatial patterns). Most regions in Indonesia (11 provinces) tend to have low economic and COVID-19 pandemic vulnerability in the first spatial pattern characteristic variables.

A STUDY OF SMALL AREA ESTIMATION TO MEASURE MULTIDIMENSIONAL POVERTY WITH MIXED MODEL POISSON, ZIP, AND ZINB Adwendi, Satria June; Saefuddin, Asep; Susetyo, Budi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

The research began with calculating the value of multidimensional poverty at the district level in West Java Province from SUSENAS 2021. The calculation of multidimensional poverty was based on individuals in each district or city household. The dimensional weights are weighed the same, and the indicators in the dimensions are also weighed the same. Furthermore, the simulation study used the Poisson, ZIP, and ZINB mixed models to examine the model's performance on data with cases of excess zero values and overdispersion. The simulation was by generating data without overdispersion and with overdispersion. Overdispersion data was generated with parameters of ω (0.1, 0.3, 0.5, and 0.7), and the model was evaluated from the AIC value. The best method in the simulation study was used to estimate multidimensional poverty in sub-districts in West Java Province using PODES 2021. Simulation studies on data without overdispersion showed no difference in the model's goodness. Overdispersion data shows Mixed Model ZIP and ZINB are better than Mixed Model Poisson. The percentage of the multidimensional poverty population at the sub-district level in West Java Province is quite diverse, from 0.04% to 75.54%.

Bayesian Spatial BYM CAR Model for Estimating the Relative Risk of Dengue Hemmorhagic Fever in Bandung Ananda Shafira; Asep Saefuddin; Kusman Sadik
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9272

Dengue Hemorrhagic Fever (DHF) is an endemic disease whose transmission is influenced by spatial and environmental factors, including population density, altitude, household sanitation, and clean and healthy living behaviors. In 2022, the city of Bandung reported a high incidence of DHF cases, highlighting the need for spatial modeling to capture interdependencies among geographic regions. This study aims to examine the impact of different parameter settings in hyperprior distributions on the Besag-York-Mollie conditional autoregressive (BYM CAR) model, estimate the relative risk (RR) of DHF, and map district-level risk to support the identification of priority areas for targeted prevention. The BYM CAR model was employed within a Bayesian framework, and the posterior distributions were obtained using Markov Chain Monte Carlo (MCMC) with the Gibbs sampling algorithm. Five hyperprior scenarios based on the Inverse-Gamma distribution were compared to evaluate their influence on model performance. The results show that hyperprior selection substantially affects model outcomes, with the best model obtained when the prior for the structured spatial component was specified as Inverse-Gamma(0.1, 0.1), and the unstructured spatial component as Inverse-Gamma(1, 0.01). Gedebage, Arcamanik, and Rancasari districts were identifies as high-risk areas, while Babakan Ciparay and Bandung Kulon exhibited the lowest RR estimates. This spatial risk mapping offers insights for policymakers in formulating more targeted and efficient DHF prevention strategies.

APPLICATION OF THE COKRIGING METHOD TO ESTIMATE IRON DEFICIENCY PREVALENCE BASED ON FERRITIN AND C-REACTIVE PROTEIN Mutiah, Siti; Aidi, Muhammad Nur; Saefuddin, Asep; Ernawati, Fitrah
Media Penelitian dan Pengembangan Kesehatan Vol. 35 No. 3 (2025): MEDIA PENELITIAN DAN PENGEMBANGAN KESEHATAN
Publisher : Poltekkes Kemenkes Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34011/jmp2k.v35i3.3167

Analisis data spasial memiliki peranan penting dalam bidang kesehatan, khususnya ketika distribusi masalah kesehatan tidak merata di seluruh wilayah. Salah satunya adalah metode Cokriging, yang diterapkan untuk memprediksi prevalensi di daerah yang belum teramati, sekaligus mengatasi tantangan ketidaklengkapan data spasial akibat keterbatasan biaya, sumber daya, atau akses ke lokasi tertentu. Penelitian ini bertujuan untuk mengestimasi prevalensi kekurangan zat besi di Indonesia menggunakan metode Cokriging. Sebagai analisis lanjut dari data Riset Kesehatan Dasar (Riskesdas) 2018, penelitian ini menggunakan data dari 15.045 individu yang memiliki informasi kadar ferritin dan C-Reactive Protein (CRP), yang tersebar di 154 kabupaten/kota di empat pulau: Sumatera, Jawa, Kalimantan, dan Sulawesi. Ferritin digunakan sebagai variabel utama, sementara CRP sebagai variabel sekunder. Evaluasi model dilakukan dengan Leave-One-Out-Cross-Validation (LOOCV), dan akurasi model diukur menggunakan Mean Error (ME) dan Root Mean Squared Error (RMSE). Hasil penelitian menunjukkan prevalensi kekurangan zat besi bervariasi signifikan antar wilayah. Kabupaten Batang dan Minahasa Selatan teridentifikasi dalam kategori "tidak ada masalah kesehatan". Selain itu 274 kabupaten/kota di Indonesia berada pada kategori prevalensi ringan, seperti Kabupaten Berau, Gunung Mas, dan Bangkayang, sementara 132 kabupaten/kota tercatat dengan prevalensi sedang seperti Kabupaten Sidenreng Rappang, Tapanuli Tengah, dan Sukoharjo. Kabupaten Pare-pare terdeteksi pada prevalensi tinggi (≥40%), tingginya prevalensi di wilayah ini perlu dicermati lebih lanjut karena kemungkinan disebabkan oleh jumlah sampel yang sangat sedikit. Temuan ini menunjukkan bahwa sebagian besar kabupaten/kota di Indonesia tergolong dalam kategori prevalensi ringan hingga sedang. Gambaran ini dapat menjadi dasar penting dalam merancang kebijakan kesehatan terkait penanggulangan kekurangan zat besi di Indonesia.

Biclustering Performance Evaluation of Cheng and Church Algorithm and Iterative Signature Algorithm Sumertajaya, I Made Sumertajaya; Ningsih, Wiwik Andriyani Lestari; Saefuddin, Asep; Rohaeti, Embay
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 3 (2023): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i3.14778

Biclustering has been widely applied in recent years. Various algorithms have been developed to perform biclustering applied to various cases. However, only a few studies have evaluated the performance of bicluster algorithms. Therefore, this study evaluates the performance of biclustering algorithms, namely the Cheng and Church algorithm (CC algorithm) and the Iterative Signature Algorithm (ISA). Evaluation of the performance of the biclustering algorithm is carried out in the form of a comparative study of biclustering results in terms of membership, characteristics, distribution of biclustering results, and performance evaluation. The performance evaluation uses two evaluation functions: the intra-bicluster and the inter-bicluster. The results show that, from an intra-bicluster evaluation perspective, the optimal bicluster group of the CC algorithm produces bicluster quality which tends to be better than the ISA. The biclustering results between the two algorithms in inter-bicluster evaluation produce a deficient level of similarity (20-31 percent). This is indicated by the differences in the results of regional membership and the characteristics of the identifying variables. The biclustering results of the CC algorithm tend to be homogeneous and have local characteristics. Meanwhile, the results of biclustering ISA tend to be heterogeneous and have global characteristics. In addition, the results of biclustering ISA are also robust.

Implementation of Gamma Regression and Gamma Geographically Weighted Regression on Case Poverty in Bengkulu Province Azagi, Ilham Alifa; Sumertajaya, I Made; Saefuddin, Asep
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.22930

Spatial analysis involves leveraging spatial references inherent in the data being analyzed. The method to be used in spatial analysis is the Geographically Weighted Regression (GWR) method. GWR is an extension of the linear regression model at each location by adding a weighting function to the model. Generally, the GWR model uses residuals with a normal distribution in its analysis. One distribution that can be used is the gamma distribution. With the development of methods in statistics, when a response variable follows a gamma distribution, analysis is performed using Gamma Regression (GR). GR analysis is conducted because the response variable meets the gamma distribution assumption. One method used for spatial effects with a gamma-distributed response variable is the Gamma Geographically Weighted Regression (GGWR) method. In 2022, Bengkulu Province was among the ten poorest provinces in Indonesia. Therefore, the main objective is to compare the GR and GGWR models and analyze the factors affecting poverty in Bengkulu Province using these models. The results of this study show that the GR model has an R² accuracy of 87.93%, while the GGWR model has an R² accuracy of 95.87%. This indicates that the best model for the analysis is the GGWR. An example of the GGWR model equation for poverty in Bengkulu Province is Y=exp⁡(-6.039+3.15×〖10〗^(-6) X_1-0.055X_2+0.156X_4-0.00021X_5+0.004X_7-0.021X_8-0.006X_9+4.794×〖10〗^(-5) X_10). The factors influencing the GGWR model in Bengkulu Province are Population, Life Expectancy, Average Years of Schooling, Adjusted Per Capita Expenditure, School Participation Rate, Per Capita Expenditure on Food, Households Receiving Rice for the Poor, and Gross Regional Domestic Product. The benefit of this research is to serve as a reference for the provincial government of Bengkulu regarding the variables that influence poverty. It is expected that this will help the government reduce the poverty rate in Bengkulu Province.

Systematic Literature Review of Competitive Advantage and Marketing Capability of Small Medium Enterprises (SMEs) Nurlatifah, Hanny; Saefuddin, Asep; Marimin, Marimin; Suwarsinah, Heny
Journal of Economics, Business, and Accountancy Ventura Vol. 24 No. 2 (2021): August - November 2021
Publisher : Universitas Hayam Wuruk Perbanas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14414/jebav.v24i2.2797

The discussion about the formation of competitive advantage in work organizations such as SMEs is still not widely discussed. The current literature still discusses marketing activities in general, not specifically for SMEs. This article aims to find out the factors that influence SMEs' competitive advantage and marketing capabilities. The literature review method systematically uses three stages. First planning for selecting source articles, second implementing and reporting stage. The PRISMA Literature Review Model selects articles and data visualization using VOS Viewer software. The findings of this article are the related potential relationships between marketing capabilities as forming competitive advantages for small and medium enterprises. Eleven topics are frequently discussed in a collection of journals, and the dominant words are sustainable marketing orientation, marketing, and Company Performance. The three groups can be grouped into personality development, business management, and abilities. Differences in the types of business groups and business sizes as differentiators of business performance results are not widely seen in article searches. These findings suggest further research to examine business groups' role and size in determining SMEs' competitive advantage and marketing capabilities.

Evaluating Ensemble Learning Techniques for Class Imbalance in Machine Learning: A Comparative Analysis of Balanced Random Forest, SMOTE-RF, SMOTEBoost, and RUSBoost Fulazzaky, Tahira; Saefuddin, Asep; Soleh, Agus Mohamad
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.15937

Purpose: This research aims to identify the optimal ensemble learning method for mitigating class imbalance in datasets utilizing various advanced techniques which include balanced random forest (BRF), SMOTE-random forest (SMOTE-RF), RUSBoost, and SMOTEBoost. The methods were systematically evaluated against conventional algorithms, including random forest and AdaBoost, across heterogeneous datasets with varying class imbalance ratios. Methods: This study utilized 13 secondary datasets from diverse sources, each with binary class outputs. The datasets exhibited varying degrees of class imbalance, offering scenarios to assess the effectiveness of ensemble learning techniques and traditional machine learning approaches in managing class imbalance issues. Study data were split into training (80%) and testing (20%), with stratified sampling applied to maintain consistent class proportions across both sets. Each method underwent hyperparameter optimization with distinct settings with repetition over 10 iterations. The optimal method was evaluated based on balanced accuracy, recall, and computation time. Result: Based on the evaluation, the BRF method exhibited the highest performance in balanced accuracy and recall when compared to SMOTE-RF, RUSBoost, SMOTEBoost, random forest, and AdaBoost. Conversely, the classical random forest method outperformed other techniques in terms of computational efficiency. Novelty: This study presents an innovative analysis of advanced ensemble learning techniques, including BRF, SMOTE-random forest, SMOTEBoost, and RUSBoost, which demonstrate significant effectiveness in addressing class imbalance across various datasets. By systematically optimizing hyperparameters and applying stratified sampling, this research produces findings that redefine the benchmarks of balanced accuracy, recall and computational efficiency in machine learning.

Comparison of Ensemble Forest-Based Methods Performance for Imbalanced Data Classification Hasnataeni, Yunia; Saefuddin, Asep; Soleh, Agus Mohamad
Scientific Journal of Informatics Vol. 12 No. 2: May 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i2.24269

Purpose: Classification of imbalanced data presents a major challenge in meteorological studies, particularly in rainfall classification where extreme events occur infrequently. This research addresses the issue by evaluating ensemble learning models in handling imbalanced rainfall data in Bogor Regency, aiming to improve classification performance and model reliability for hydrometeorological risk mitigation. Methods: Four ensemble methods: RF, RoF, DRF, and RoDRF were applied to rainfall classification using three resampling techniques: SMOTE, RUS, and SMOTE-RUS-NC. The data underwent preprocessing, stratified splitting, resampling, and 5-fold cross-validation. Performance was evaluated over 100 iterations using accuracy, precision, recall, and F1-score. Result: The combination of DRF with SMOTE-RUS-NC yielded the most balanced results between accuracy (0.989) and computation time (107.28 seconds), while RoDRF with SMOTE achieved the highest overall performance with an accuracy of 0.991 but required a longer computation time (149.30 seconds). Feature importance analysis identified average humidity, maximum temperature, and minimum temperature as the most influential predictors of extreme rainfall. Novelty: This research contributes a comprehensive comparison of ensemble forest-based methods for imbalanced rainfall data, revealing DRF-SMOTE as an optimal trade-off between performance and efficiency. The findings contribute to improved rainfall classification models and offer practical insight for disaster mitigation planning and resource management in tropical regions.

Induksi Mutasi pada Stek Pucuk Anyelir (Dianthus caryophyllus Linn.) melalui Iradiasi Sinar Gamma Aisyah, Syarifah Iis; Aswidinnoor, Hajrial; Saefuddin, Asep; Marwoto, Budi; Sastrosumarjo, Sarsidi
Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) Vol. 37 No. 1 (2009): Jurnal Agronomi Indonesia
Publisher : Indonesia Society of Agronomy (PERAGI) and Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor, Indonesia

It has been a common knowledge that LD50 is commonly used in estimating optimal doses of gamma irradiation in a breeding program. This research was aimed at observing radiosensitivity of five carnation's genotypes to gamma irradiation, to find the LD50 of carnation's cuttings, and to obtain solid mutants from five numbers of Carnation. For cuttings, carnation genotype number 10.8 was the most insensitive to gamma rays, whereas number 24.15 was the most sensitive one. LD50 of carnation's cuttings were obtained around 49 -72 gray. There were 19 mutants produced from this treatment. The desired mutans were mostly produced from the treated 24.1 genotype whereas the character mutans were mostly observed in MV2 generation. Irradiation treatment on genotype 24.1 produced most stabile mutans while the less was in genotype 24.14. The produced mutants were qualitatively different in colour and petal shape, and stabile till third generation. Key words: LD50, gamma irradiation, induced mutation, carnation.

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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