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Kusrini

Universitas Amikom Yogyakarta

Author-ID : 302666

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

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Implementation of topsis algorithm for evaluating lecturer performance Fatkhurrochman, Fatkhurrochman; Kusrini, Kusrini; Alfatta, Hanif
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Higher education is an education unit that able to carry out academic, professional and / or vocational programs. Lecturers are professional and scientific educators with the main task of transforming and developing, and disseminating science, technology and art through education, research and community service. The performance evaluation applies seven criterias, namely: attendance, teaching, research, dedication, loyalty, cooperation and responsibility. The problems are; the lecturersâ€™ performance evaluation is not optimal yet because there is no specific method to implement it. Therefore, it is necessary to build a decision support system by applying the Technique For Others Reference by Similarity to Ideal Solution (TOPSIS). This system will later help us in determining the best lecturer in accordance with the regulation. The TOPSIS method uses the principle that the chosen alternative must have the longest (farthest) distance from the negative ideal solution from geometric point of view using the relative proximity of an alternative. The alternative means the lecturersâ€™ performance with predetermined criterias. This method produces a lecturers rankings based on the best performance on numerical scores and sorted by the greatest preference scores. The particular study used 5 lecturers as alternative to be tested. They were Lecturers 1, Lecturers 2, Lecturers 3, Lecturers 4, and Lecturers 5. The results showed that Lecturer 1 was the best lecturer with the biggest preference score of 0.612.

Determination of receipt of UPZ assistance using the SAW method Listyanto, Ahmad Wildan; Kusrini, Kusrini; Sudarmawan, Sudarmawan
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Zakat has a very strategic position in giving the impact of welfare and improving the community's economy if the collection and distribution are managed in trustworthy, transparent and professional. An institution on zakat management is National Zakat Agency (BAZNAS), which an institution manages the zakat management nationally, and non-structural government institution that is independent and responsible to President through the Minister of Religion. BAZNAS is located in capital city and assisted by zakat collection unit (UPZ). Along this time, they conduct manually in determining the person who will receive the assistance, but it often occur errors in its implementation. Therefore, a decision support system is needed to assist UPZ in determining the person who will receive the assistance. The decision support system was designed using SAW (Simple Additive Weighting) method, then the administrators obtain an alternative data in the form of lists of students who receive the UPZ assistance. The SAW algorithm is an algorithms for decision making. The SAW algorithm is also known as an algorithm with additive weighting method. The method requires normalization process of decision matrix (x) into a scale and can be compared to the entire available alternative ratings. The study showed that SAW can be applied to determine the acceptance of UPZ assistance by the calculation results of 16. The result of calculation and recommendation of decision support system for person who receive the UPZ acceptance, have the same data on output, namely Astin Dwi Wulan.

Data Clustering for Sentiment Classification with Naïve Bayes and Support Vector Machine Yanuargi, Bayu; Ema Utami; Kusrini; Parikesit, Arli Aditya
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 6 (2024): December 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i6.6139

Visitor reviews play a crucial role in determining the success of a business, particularly those offering hospitality and services, such as hotels. The growth of internet technology has made it easier for guests to share their experiences, which can influence potential customers. Google Maps is one of the platforms used for giving and searching reviews This research uses data crawled from Google Maps Review using the playwright library. However, the large volume of reviews can make analysis and topic-based categorization—such as service quality, hotel location, and operational hours—challenging. To address this, DBSCAN is used to cluster reviews based on these topics. Clustering helps improve sentiment classification, making it more targeted and allowing a comparison of two machine learning algorithms: Naïve Bayes and Support Vector Machine (SVM). Naïve Bayes achieved higher accuracy (0.87) in the operational hours cluster, while SVM scored 0.78. However, SVM showed improved accuracy in the location (0.89) and service (0.88) clusters, with Naïve Bayes maintaining a stable 0.86 accuracy in both. Both models demonstrated an average training time of less than one second, excluding preprocessing.

Evaluating Transformer Models for Social Media Text-Based Personality Profiling Hartanto, Anggit; Ema Utami; Arief Setyanto; Kusrini
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6157

This research aims to evaluate the performance of various Transformer models in social media-based classification tasks, specifically focusing on applications in personality profiling. With the growing interest in leveraging social media as a data source for understanding individual personality traits, selecting an appropriate model becomes crucial for enhancing accuracy and efficiency in large-scale data processing. Accurate personality profiling can provide valuable insights for applications in psychology, marketing, and personalized recommendations. In this context, models such as BERT, RoBERTa, DistilBERT, TinyBERT, MobileBERT, and ALBERT are utilized in this study to understand their performance differences under varying configurations and dataset conditions, assessing their suitability for nuanced personality profiling tasks. The research methodology involves four experimental scenarios with a structured process that includes data acquisition, preprocessing, tokenization, model fine-tuning, and evaluation. In Scenarios 1 and 2, a full dataset of 9,920 data points was used with standard fine-tuning parameters for all models. In contrast, ALBERT in Scenario 2 was optimized using customized batch size, learning rate, and weight decay. Scenarios 3 and 4 used 30% of the total dataset, with additional adjustments for ALBERT to examine its performance under specific conditions. Each scenario is designed to test model robustness against variations in parameters and dataset size. The experimental results underscore the importance of tailoring fine-tuning parameters to optimize model performance, particularly for parameter-efficient models like ALBERT. ALBERT and MobileBERT demonstrated strong performance across conditions, excelling in scenarios requiring accuracy and efficiency. BERT proved to be a robust and reliable choice, maintaining high performance even with reduced data, while RoBERTa and DistilBERT may require further adjustments to adapt to data-limited conditions. Although efficient, TinyBERT may fall short on tasks demanding high accuracy due to its limited representational capacity. Selecting the right model requires balancing computational efficiency, task-specific requirements, and data complexity.

Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method Fitrony, Fachri Ayudi; Supraba, Laksmita Dewi; Rantung , Tessa; Agastya , I Made Artha; Kusrini , Kusrini
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2251

New student admission is an important aspect in higher education management, including Nahdlatul Ulama University (UNU) Pasuruan. Relevant prediction of total new students is needed to support resource planning such as teaching staff, facilities, and budget. This study aims to evaluate the historical pattern of new student admissions at UNU Pasuruan and predict the number of new students in the coming years using the ARIMA (Auto Regressive Integrated Moving Average) method. The data used is historical data on new student admissions in the last five years, which is analyzed to identify trends, seasonality, and fluctuation patterns. The analysis is performed using statistical software such as Python to improve the accuracy and efficiency of the process. This study approach includes several main steps, namely collecting historical data on the number of new students, testing stationarity using the Augmented Dickey-Fuller (ADF) test, identifying model parameters through ACF and PACF graphs, and estimating ARIMA model parameters. The resulting model is evaluated using prediction error metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The study findings describe that the ARIMA model (6,0,1) produces an RMSE value of 21.88 and a MAPE of 0.2%. In addition to having the smallest error score, the ARIMA model (6,0,1) also has the smallest AIC score of the various models that can be used for predictions, which is 447.44 and the largest log likelihood value, which is -214.72. The largest prediction of the number of new students is in July, which is 92.72 and the smallest in February, which is 24.43. This prediction is expected to help university management in optimizing resource planning, increasing management efficiency, and anticipating fluctuations in the number of new students in the future. This study offers new findings in the form of the use of predictive models based on historical data to support strategic decision- making, such as resource allocation and promotion planning. With these results, universities can anticipate changes in the number of enrollments more effectively, which were previously only done based on subjective estimates. The model built can also be applied to similar datasets in the future with appropriate parameter adjustments.

Optimizing rice leaf disease classification through convolutional neural network architectural modification and augmentation techniques Firdaus, Mohamad; Kusrini, Kusrini; Agastya, I Made Artha; Martínez-Béjar, Rodrigo
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3429-3438

This research focuses on advancing the accuracy of rice leaf disease classification through the integration of convolutional neural network (CNN) and deep learning models. With Indonesia ranking third in global rice production, effective crop management is crucial for sustaining agricultural output. This study employs innovative data augmentation techniques, including random zoom and others, to enhance model training robustness. The experimentation involves eight scenarios with varied architectural configurations applied to a residual network-50 (ResNet50) layers model, aiming to optimize disease classification performance. Featuring random zoom without the multilayer perceptron (MLP) component, emerges as the most effective, demonstrating superior accuracy and performance metrics. A grid search is conducted to optimize MLP layers, revealing a three-layer configuration as most effective. We found that the data augmentation and MLP layer can increase the accuracy of the disease classification task. The method proposed in this study is likely to have a much higher proportion of correct disease classification by combining MLP and zoom augmentation. Specifically, the model with three MLP layers and zoom augmentation demonstrated significantly higher accuracy, achieving a test accuracy, precision, recall, and F1-score of 0.92, 0.94, 0.92, and 0.92, respectively.

Perbandingan Performansi Algoritma Multiple Linear Regression dan Multi Layer Perceptron Neural Network dalam Memprediksi Penjualan Obat: Comparison of the Performance of Multiple Linear Regression Algorithms and Multi Layer Perceptron Neural Networks in Predicting Drug Sales Arifuddin, Danang; Kusrini, Kusrini; Kusnawi, Kusnawi
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 2 (2025): MALCOM April 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i2.1952

Penelitian ini mengevaluasi pemilihan atribut dari variabel internal (jumlah penjualan) dan eksternal (cuaca, harga komoditas, inflasi) menggunakan metode korelasi, serta membandingkan performansi algoritma Multiple Linear Regression (MLR) dan Multi-Layer Perceptron Neural Network dengan backpropagation (MLPNN-b) dalam memprediksi penjualan obat analgesik di “Apotek XYZ”. Metrik evaluasi Mean Squared Error (MSE) dan Mean Absolute Percentage Error (MAPE) digunakan untuk mengukur akurasi prediksi. Hasil menunjukkan bahwa atribut internal "h-7" memiliki korelasi tertinggi (0,35) terhadap penjualan harian, sementara variabel eksternal seperti suhu harian, harga bawang merah, dan suku bunga juga memberikan kontribusi. Algoritma MLPNN-b dengan parameter tertentu mencapai MAPE 22,3% dan MSE 19.588 pada atribut tunggal, sedangkan MLR memiliki kinerja lebih merata pada atribut kombinasi dengan MAPE 25,6% dan MSE 22.768. Namun, kedua model masih mengalami underfitting dengan tingkat kesalahan prediksi yang cukup tinggi. Penelitian ini menyimpulkan bahwa meskipun MLPNN lebih unggul dalam menangkap hubungan non-linear dibandingkan MLR, akurasi prediksi masih belum optimal. Oleh karena itu, eksplorasi model hybrid serta integrasi lebih banyak variabel eksternal direkomendasikan untuk meningkatkan prediksi penjualan dan mendukung sistem manajemen stok farmasi yang lebih akurat.

Analisis Perbandingan Metode Decision Tree Dan K-Nearest Neighbor Untuk Klasifikasi Cyberbullying Pada Sosial Media Twitter Maradona, Maradona; Kusrini, Kusrini; Alva Hendi Muhammad
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.591

This research focuses on analyzing the impact of social media on society, particularly addressing the issue of cyberbullying on the Twitter platform. Based on statistics, the majority of internet users in Indonesia actively utilize social networks, with Twitter being the most dominant platform used for communication and interaction. Therefore, cyberbullying cases often occur on this social media platform. In this study, two classification methods, namely Decision Tree and K-Nearest Neighbor (KNN), were employed to classify cyberbullying-related messages on Twitter. The aim of this research is to compare the performance of these two methods and to identify early signs of cyberbullying as relevant digital evidence for legal proceedings. The dataset used in this study consists of 650 comment records from the period 2019 to 2021, with predefined labels. The analysis results indicate that K-Nearest Neighbor achieved the highest accuracy, reaching 75.99%, compared to Decision Tree with 65.00%. Hence, K-Nearest Neighbor is considered a more effective method for cyberbullying analysis on the Twitter platform. Additionally, the identification of early signs of cyberbullying in comment id 2 can serve as relevant digital evidence for legal purposes. This research provides better insights into the effectiveness of classification in addressing cyberbullying issues on the Twitter platform.

Hybrid Deep Learning and USE Algorithm for Essay Scoring: Accuracy and Performance Analysis Sriyanto, Agus; Kusrini , Kusrini
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14784

The main challenge in digital education, particularly in the automatic assessment of essay answers in online learning systems, lies in the complexity of natural language understanding and semantic evaluation required to achieve the level of precision equivalent to human judgment. This study aims to develop and analyze the performance of a hybrid model that combines deep learning with a semantic similarity-based approach to essay auto-grading. The methods used include the collection of essay answer data from various disciplines, text processing to extract semantic representations, and the calculation of the degree of similarity between the participant's answers and the answer key using the similarity measure. The evaluation was carried out by comparing the results of automatic assessments with manual assessments by teachers. The results showed that the developed model achieved the highest accuracy level of 90.22% at 0.8 treshold, with a precision of 84.63%, a recall of 100%, and an F1 score of 91.68%. To strengthen the reliability of the findings, statistical validation was carried out using error evaluation metrics. RMSE value is 0.32 and RMAE value is 0.19. These findings show that the model is able to mimic human judgment reliably and consistently, and can distinguish linguistic variations that arise in different types of essay questions. This system offers an effective solution for the automation of assessments in an online learning environment, while maintaining the integrity and objectivity of the evaluation.

Klasifikasi Gambar Bahasa Isyarat Indonesia (Bisindo) Pada Komunitas Tuli Menggunakan Machine Learning Candra, Kurnia Khoirul; Kusrini, Kusrini
e-Jurnal JUSITI (Jurnal Sistem Informasi dan Teknologi Informasi) Vol. 14 No. 1 (2025): e-Jurnal JUSITI
Publisher : Universitas Dipa Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36774/jusiti.v14i1.1649

Bahasa isyarat merupakan sebuah cara komunikasi khusus yang digunakan para penyandang disabilitas khususnya penyandang Tuli. Pada sebuah sistem pengembangan komunikasi di masa kini bahasa utama yang digunakan komunitas Tuli di Indonesia adalah Bahasa Isyarat Indonesia (BISINDO). Tujuan penelitian ini yaitu mengimplementasikan metode klasifikasi gambar BISINDO menggunakan metode machine learning, mengetahui akurasi penerapan gambar BISINDO dengan menggunakan machine learning. Jenis penelitian ini adalah penelitian kualitatif, klasifikasi gambar Bahasa Isyarat Indonesia (BISINDO) menggunakan teknik machine learning. Metode ini digunakan untuk menggunakan model Convolutional Neural Networks (CNN) yang tersedia pada dataset gambar dapat meningkatkan akurasi. Hasil pada penelitian yang dilakukan penulis menunjukkan bahwa metode CNN memiliki akurasi 98,07% dan metode machine learning memiliki akurasi 100%. Kesimpulan menunjukkan implementasi metode Convolutional Neural Network (CNN) dengan menggunakan arsitektur SSD MobileNet dan machine learning dalam melakukan deteksi objek pada simbol abjad Bahasa Isyarat Indonesia (BISINDO) berjalan dengan baik dan menghasilkan keberhasilan pendeteksian simbol abjad BISINDO dengan peningkatan akurasi yang baik.

Co-Authors - Saifulloh A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA ABADI Abda Abda Abdi Firdaus Abdillah, Yahya Auliya Abdul Haris Abdul Malik Zuhdi Abdul Ra'uf Alfansani Abdul Rokhim Abdullah Sukri, M Iqbal Abdullah, Mochamad Fadillah Achmad Agus Athok Miftachuddin Achmad Wazirul Hidayat Achmad Yusron Arif Adadilaga Arya Priwanegara Ade Pujianto, Ade Adhani, Muhammad Azmi Adhien Kenya Estetikha Adiatma, Biva Candra Lutfi Aditya Hastami Ruger Aflahah Apriliyani Afryansih, Nila Agam Saka Jati Agastya , I Made Artha Agastya, I Made Artha Agatha Deolika Agatstya, I Made Artha Agianto Syam Halim agung budi Agung Budi Agung Budi Prasetio Agung Budi Prasetyo Agung Jasuma Agung Jasuma Agung Nugroho Agus Harjoko AGUS PURWANTO Agus Sriyanto AGUS SULISTIYONO Agus Susilo Nugroho Agustina Rahmawati Agustina, Nova Ahmad Almas'ud ZD Ahmad Harmain Ahmad Sanusi Mashuri Ahmad Yusuf Ahmad Zarkasih Ahsan, Muhammad Salimy Aidina Ristyawan, Aidina Aiman Ayadi Aisha Alfani Aji Santoso, Bayu Aji Susanto Anom Purnomo Ajie Kusuma Wardhana Akhmad Syarif Akhmad Syarif Akrilvalerat Deainert Wierfi Alfahmi Muhammad Arif Alfatta, Hanif Ali Asgar Zainal Abidin Alva Hendi Muhammad Amanullah, Raynaldi Fatih Amborowati, Armadyahah Amir Bagja Amir Fatah Amir Fatah Sofyan Amrina Rosyada anas, hasni Anastasia Meyliana Andayani Andayani Andhika Wisnu Widyatama Andi Bahtiar Semma Andi Muhammad Irfan Andi Sunyoto Andi Suyoto Andi Syahrul Ramdana Andika, Roy Andri Rachmatullah Andri, Agung Andria Andria Andris Faesal Andriyan Dwi Putra Andriyanto, Rifki Angga Kurniawan Angga Kurniawan Anggi Muhammad Rifa'i Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto, Anggit Dwi Anggit Hartanto Anggraeni, Meita Dwi Aninda Astuti Anjar Anjani Putra Anwar Sadad Aolia Ikhwanudin Aolia Ikhwanudin Apriliyani, Aflahah Aprison Wolla Gole Ardana, Wildan Muhammad Ardana, Wildan Muhammmad Ardiansyah, Fachri Arfiani Nur Khusna Arham Rahim Ari Ari Suhartanto Ari Suhartanto Ari Yuana, Kumara Arief Setyanto Arief Setyanto Arief Setyanto Arief, M Rudyanto Arief, M. Rudyanto Arief, Muh. Rudyanto Arief, Muhammad Rudyanto Arief, Rudyanto Ariel Yonatan Alin Arif Budiman Arif Fajar Solikin Arif Fajar Solikin Arif Fajar Solikin Arifuddin, Danang Arik Sofan Tohir Aris Subadi Arli Aditya Parikesit Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Arnap, Adam Arnila Sandi Arridho, Muhammad Noor Artha Agastya, I Made Arwendra Adi Putra Asnawi, Muhamad Fuat Asri, Saffinah Indah Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasrini Assani, Moh. Yushi Atin Hasanah Awaludin Abid Azi, Amanda Azib Widad Zuhaily Imam Azis Wahyudi Aziz Muslim Aziz Muzani, Ma'ruf Aziz, Moh Abdul Azkar, Azkar B, Isdayani B. R., Endah Bagas Dwi Novianto Bahrun Ghozali Banu Santoso Bayu Setiaji Béjar, Rodrigo Martínez Bentar Candra P Bernadhed, Bernadhed Bimantyoso Hamdikatama Bisono, Hadi Hikmadyo Braeken, An Brenstein Mawene Buana, Yopy Tri Burhanudin Dwi Prakoso Candra Adipradana Candra Rusmana Candra, Kurnia Khoirul Choerun Asnawi Christian Budi Andrianto, Christian Budi Christin Nandari Dengen Christin Nandari Dengen Christin Nandari Dengen Christin Nandari Dengen D. Diffran Nur Cahyo da Silva, Bruno Danang Eko Prayogo Danang Wahyu Widodo Darmawan, Eko Rahmad Darno - David Agustriawan David Junggu Manggala Pasaribu dayat subekti Dede - Sandi Dede Husen Dedi Gunawan Dema Matias L Tobing Dengen, Christin Nandari Desty Yani Destyanto, Febrian Devina Ninosari Dhani Ariatmanto Dhani Ariatmanto DHANI ARIATMANTO Dias Ayu Budi Utami Dibyo Sudarsono Didik Irawan Dimaz Arno Prasetio Dina Maulina Dina Maulina Dina Maulina Dina Maulina Djatmiko, Widdi Doni Briyan Wahyudi Donny Yulianto Dwi Astuti Dwi Cahyani, Atika DWI ISKANDAR Dwi Utami Dwi Yuli Prasetyo Dwinda Etika Profesi Dwinda Etika Profesi Dzalfa Tsalsabila Rhamadiyanti Dzulhijjah, Dwi Ahmad Eddy Nurraharjo Eka Wahyu Pujiharto Eka Wahyu Sholeha Eka Yulia Sari Ekastini Ekastini Ekastini Ekastini Eko Boedijanto Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Purwanto Eko Purwanto Eko Purwanto Eldas Puspitarini, Eldas Elfandry Bayunanda Elfrida Ratnawati Elik Hari Muktafin Elik Hari Muktafin Elik Hari Muktafin Eliza Staviana Elok Noor Farida, Elok Noor Elvis Pawan Elvis Pawan Ema Utami Ema Utami Ema Utami Ema Utami Emha T aufiq Luthfie Emha Taufik Luthf Emha Taufiq Luthfi EmhaTaufiq Lutfi, EmhaTaufiq Enni Lidrawati Erfan Tongalu Eri Sasmita Susanto Erwin Apriliyanto Erwin Apriliyanto Eva Oktaviani Fahma Inti Ilmawati Fahrullah, Fahrullah Fajar Dwi Insani Fajar Sodik Fajar Sudana Putra Fandli Supandi Fandli Supandi Fansuri, Muhammad Febrian Fareza Aditiyanto Nugroho Fatkhurohman, Ari Fatkhurrochman, Fatkhurrochman Fauji Maulana Ramlan, Fauji Maulana Fauzi, Moch Farid Fauzy, Marwan Noor Febrianti, Winda Febriyanti, Nada Rizki Fendy Nugroho Fendy Prasetyo Nugroho Fendy Prasetyo Nugroho Fernandito, Durand Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Firman Sriyono Firmanda Fasya Firza Septian Fitriani Fitriani Fitriyandhi, Ari fitriyanto, nur Fitrony, Fachri Ayudi Fiyas Mahananing Puri Friden E Neno Fryda Fatmayati Gifari, Okta Ihza Gigih Setyaji Guido Adolfus Suni Gutama, Deden Hardan Hadi Sucipto Hadryan Eddy Hafidz Sanjaya, Hafidz Halimi, Ahmad Hamada Zein Hamdikatama, Bimantyoso Hanafi Hanafi Hanafi Handoko Adji Pangestu Hanif Al Fatta Hari Agustiyo Hari Muktafin, Elik Haris, Ruby hartanto, david budi Hartono, Anggit Dwi Haryo, Wasis Hasan, Nur Fitrianingsih Hasan, Nurul Rahmawati Hasim, Hasim As'ari Hasirun Hasirun Hasirun, Hasirun Hasnan Afif Helmawati, Nita Henderi Henderi . Hendriansyah Santosa Hendrik Hendrik Henri Kurniawan Henri Kurniawan Herawati, Maimi Heri Abijono Heri Abijono, Heri Heri Sismoro Herlinawati, Noor Hery Nurmawan Hery Siswanto Hidayat, Fajar Maula Hidayatunnisa'i Hulvi, Alfajri I Made Adi Purwantara I Made Artha Agastya I Putu Agus Ari Mahendra I Wayan Pandu Ibnu Ickwantoro Ichsan Wasiso Ichsan Wasiso Idris Idris Ikhwan Baidlowi Sumafta Ikhwanudin, Aolia Ikmah Ikmah Ilkham, Sundari Ilkham, Sundari Ilmawati, Fahma Inti Ilmi, M. Bahril Imam Listiono Indarto, Aan Iqbal Irfan Purwanto Irma Darmayanti Irwan Oyong Jangkung Tri Nugroho Jazi Eko Istiyanto Jeki Kuswanto Jeki Kuswanto Jemi Yohanis Babys Jhoanne Fredricka Jimmy H Moedjahedy Joang Ipmawati JOKO PRAYITNO José Ramón Martínez Salio Julia Kurniasih Jumaris Jumaris, Jumaris Jumiati Jumiati Junaidi Junaidi Junaidi Sabtu Juwari Juwari Juwariyah, Siti Kaharuddin Kanafi Kanafi Kasman, Haris Saktiawan Kelik Sussolaikah Kemal Pasha Khoironi, Khoironi Khoirul Islam Khoirun Nisa Khomsatun Khomsatun Khusnawi Khusnawi Kristian, Taufik Aldri Kristina Vaher Kumara Ari Yuana Kumara Ari Yuana Kurni, Samuel Everth Andrias Kurniadi, Harso Kurniasari, Iin Kusnawi , Kusnawi Kusnawi Kusnawi Kusrini, Mashudi Kusuma Chandra Kirana La Aba Laka, Beatus Mendelson Lasimin Lewu, Retzi Y. Liana Trihardianingsih Lili Kartikawati Linda, Kumara Dewi Lisda Lisda Listyanto, Ahmad Wildan López, Alba Puelles Lukman Bachtiar Lutfan Lazuardi M rudyanto Arief M Rudyanto Arief M Vaizul Rahman M. Afriansyah M. Dedi Iskandar M. Idris Purwanto M. Ilham Arief M. Irwan Ukkas Irwan Ukkas Ukkas M. Nurul Wathani M. Rudiyanto Arief M. Rudyanto Arief M. RUDYANTO ARIEF M. Rudyanto Arief M. Rudyanto Arief M. Suyanto M. Suyanto, M. M. Syukri Mustafa M. Zainal Arifin M.Andi Rohmat Madhika, Yudha Randa Mahendra, Awanda Putra MAHMUDI Mahmudi Mahmudi Majid Rahardi Mangun, Syamsul Syahab Mansur Mansur Maradona, Maradona Mardiana Mardiana marhalim, marhalim Marissa Utami Marta Ardiyanto Martínez-Béjar, Rodrigo Marwan Noor Fauzy MASRIYAH Masruri, Nizar Haris Masud, Ibnu Mat Sudir maulana, fahrizal Mawene, Brenstein Maykel Sonobe Maykel Sonobe Megantara, Muhamad Arldi MEI PARWANTO KURNIAWAN Metha, Halifa Sekar Miftachuddin, Achmad Agus Athok Mochamad Fadillah Abdullah Moenawar Kholil Moh Er Kamim Moh Royandi Azka Moh. Badri Tamam Mohamad Firdaus, Mohamad Mohammad Diqi Mohammad Rezza Pahlevi Moningka, Nirwan Muahidin, Zumratul Muchamat Zainal Arifin Muflich, Alwie Mufti Ari Bianto Muh Saerozi Muh. Rudyanto Arief Muh. Rudyanto Arief Muhamad Fatahillah Z Muhamad Iksan, Muhamad Muhamad Kurniawan Muhamad Nanda Utama Muhamad Ryandy Ghonim Asgar Muhamad Yusuf Muhammad Agus Muljanto Muhammad Alfariz Muhammad Anwar Fauzi Muhammad Egy Pratama Muhammad Fahmi Muhammad Fajar Apriyanto Muhammad Fajrian Noor Muhammad Firdaus Abdi Muhammad Firdaus Abdi Muhammad Koprawi Muhammad Mariko Muhammad Nafi’Uddin Muhammad Resa Arif Yudianto Muhammad Riandi Widiyantoro Muhammad Riza Eko S Muhammad Rudyanto Arief Muhammad Rudyanto Arief Muhammad Rudyanto Arief Arief Muhammad Salimy Ahsan Muhirin Muktafin, Elik Hari Mukti Ali Mulia Sulistiyono Mulyaningtyas, Widya Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin, Muqorobin Musa Hendri Janto Rahanra Muslihah, Isnawati Musthofa Galih Pradana Mutiara Dwi Anggraini Mutiara Dwi Anggraini Muzakir, Muhammad MZ, Reza Rafiq Nabawi, Isnan Nabila Payapo Nadea Cipta Laksmita Nafis Sururi Nanang Prasetiyantara Nasiri, Asro Neno, Friden Elefri Ngaeni, Nurus Sarifatul Ni Nyoman Utami Januhari, Ni Nyoman Nibras Faiq Muhammad Nikko Listio Wicaksono NINIK TRI HARTANTI Noor Abdul Haris Norhikmah Norhikmah Noto Narwanto Nova Agustina Noviyanti P Noviyanti P. Nugroho, Agung Nugroho, Hanantyo Sri Nugroho, Rakhmat Prasetyo Agung Nuk Ghurroh Setyoningrum Nuk Ghurroh Setyoningrum Nulngafan, Nulngafan Nur Hamid Sutanto Nurcahyo, Azriel Christian Nurdianingsih, Neneng Nurita Evitarina Nurmalasari, Maulidya Dwi Nurwijayanti Oktafiqurahman, Andi Olajuwon, Sayyid Muh. Raziq Onde, Mitrakasih La ode Oscar Samaratungga Paiman Paiman Pamekas, Bondan Wahyu Pamoengkas, Muhamad Agoeng Pamungkas, Prima Giri Pamungkas, Sapto Paradise, Paradise Parsiyono Parsiyono Patmawati Hasan Pawit Srentiyono Perdana Putra, Muhammad Ricky Perdana, Muhammad Ricky Prabowo Budi Utomo Pradipta, Dody Prameswari, Sonia Anjani Pramono Pramono Pramudya Insan Prasetio, Agung Budi Prasetio, Dimaz Arno Prasetyo, Adi Prastowo, Wahit Desta Prastyo, Rahmat Pratama, Bayu Trisna Pratama, Muhammad Egy Profesi, Dwinda Etika Profesi, Dwinda Etika Pujianto, Ade Puri, Fiyas Mahananing Purnamasari, Resti Rachmawati Oktaria Mardiyanto Rachmawati Oktaria Mardiyanto Rahmat Saleh Sukur Rajnaparamitha Kusumastuti Rama Ashari Rama Saktriawindarta RAMADHAN, SYAIFUL Ramlan Ramlan Rantung , Tessa Rasyid, Magfirah Reflan Nuari Rendy Bagus Pratama Retantyo Wardoyo Retzi Yosia Lewu Ridlan Ahmad Riduan, Nor Ridwan Joko Purnomo Rifan Ferryawan Rifqi Hammad Rifqi Hammad Rini Wijayanti Rini, Rini Riovan Styx Roring Ripto Sudiyarno Ririn Putri Damaiyanti Riska Dwi Handayani Risna Sari Rita Wati Ritham Tuntun Riyan Abdul Aziz Rizal Khadarusman Rizal Sapta Dwi Harjo Rizkayati, Anisa Rizki Firdaus Mulya Rizki Mawan Rizky Aries Saputra Rizqi Sukma Kharisma Robi Wariyanto Abdullah Rohman, Arif Nur Rona Guines Purnasiwi Rooy Thaniket Rosadi, Ilham Aziz Rudyanto Arief S, Muhamad Rois S, Muhammad Sabri Safagi, Ardian Yuligar Sahirul Muklis Saifudin, Saifudin Saiful Bahri Saikin Saleh, Robby Febrianur Samponu, Yohakim Benedictus Samponu, Yohakim Benedictus Santosa, Hendriansyah SANTRI SANTRI Saputra, Mahmuda Saputra, Rizky Aries Saputro, Moh. Rizal Bayu Saputro, Uyock Anggoro Sarawan, Tommy Sari, Yayak Kartika Sari, Yunita Sartika Sarji, Sarji Selvy Megira, Selvy Semma, Andi Bahtiar Sentoso, Thedjo Sepriadi - Bumbungan Sepriadi Bumbungan Setianto, Yuni Ambar Setiawan, Moh. Arif Ma'ruf Setyanto, Arif Sewindu Putro Sigit Pambudi Simone Martin Marotta Siswo Utomo, Mardi Siti Delimasari Siti Fatonah Siti Hartinah Siti Maesaroh Siti Nurhayati Siti Rahayu Siti Rihastuti Siti Rokhmah Siti Solekhah Slamet Slamet Slamet Slamet Sobirin, Rahmat Sofyan Pariyasto Solikin, Arif Fajar Sri Handayani Sri Hartati Sri Lestari Rahayu Sri Wahyuningsih Sri Wulandari Sri Wulandari Sri Wulandari Sri Yanto Qodarbaskoro Sriyati, Sriyati Sry Faslia Hamka Sudarmawan Sudarmawan Sudarmawan - Sudarmawan . Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan, Sudarmawan Sudarsono, Dibyo Sudarto Sudarto Sudiana Sudiana Sugi Harsono Sugihandono, Agus Suhardi Marli Suhendri Sukasna . Sukasna, Sukasna Supraba, Laksmita Dewi Supriantara Supriantara Supriatin Supriatin Supriyati Supriyati Surya Wibowo, Sapta Hary Suyono, Ayu Adelina Swardiana, I Wayan Pandu Swastikawati, Claudia Syafutra, Arif Dwi Syah, Firdiyan Syaiful Huda Syaiful Huda Syaiful Ramadhan Syamsu Hidayat Tala, WD. Syarni Tamaulina Br Sembiring Tampubolon, Jandri Tamuntuan, Virginia Teguh Arlovin Teguh Sri Pamungkas Theofanis Orphanoudakis Thiro Kabul Y, Yudhis Tika Dedy Prastyo Tito Prabowo Toifur, Tubagus Tolla, Yefta Tonny Hidayat TONNY HIDAYAT Tri Andi Tri Anggoro Tri Haryanti Tri Nugroho, Arief Tubagus Toifur Tukan, Ewaldus Ambrosius Turmuzi Tutik Maryana Tutut Dwi Prihatin Ula, M. Izul Umam Faqih Zubaedi Umdatur Rosyidah Uyock Anggoro Saputro Veny Cahya Hardita Vera Wati Victor Saputra Ginting Victor Saputra Ginting Vinnesa Patricia Carolina Wahyu Adie Saputro Wahyu Nugraha Wahyu Nur Alimyaningtias Wahyu Pujiharto, Eka Wahyu Sindu Prasetya Wahyu Wijaya Widiyanto Wahyudi, Alfian Cahyo Walidy Rahman Hakim Wangsa, Sabda Sastra Wariyanto Abdullah, Robi Wartono Wartono wati, Vera Wati, Vera Wauran, Alfrets Septy Wicaksono, Kurniawan Widdi Djatmiko Widiyanto, Wahyu Wijaya Widyanto, Agung Wijaya, Jodi Winarnie Winarto, Hendri Wira Dimuksa Wiwi Widayani Wiwi Widayani, Wiwi Wiwit Supriyanti Wulandari, Sri Y. P., Ryan Dwi Yanuargi, Bayu Yeyen Dwi Atma Yoga Handoko Agustin Yohanes Setyo Prabowo, Yohanes Setyo Yossy Ariyanto Yovita Kinanti Kumarahadi Yuana, Kumara Ari Yudha Chirstianto F Yuli Astuti Yuliana Yuliana, Yuliana Yuliani, Enie Yulita Fatma Andriani Yulius Nahak tetik Yuni Ambar S Yunita, Risca Yunita, Selviana Yusrinnatul Jinana triadin Yustian Servanda Yusuf Fadlila Rachman Yusuf Fadlila Rachman Yusuf Wahyu Setiya Putra Yuza, Adela Zaenul Amri Zakaria Zakaria Zenal Muttaqin Zeni Muhamad Noer Zuhri, Muhammad Rafli Zul Hisyam Zulkarnain, Imam Alfath Zulkarnain, Jefri Zulkipli Zulkipli Zulpan Hadi Zumarni, Zumarni

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