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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Innovation and Applied Technology Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Habitat Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JAST : Jurnal Aplikasi Sains dan Teknologi J-Intech (Journal of Information and Technology)

Arief Andy Soebroto

Universitas Brawijaya

Author-ID : 6133477

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Mechanical Engineering Other

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IMPLEMENTASI FUZZY INFERENCE SYSTEM (FIS) METODE TSUKAMOTO PADA SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KUALITAS AIR SUNGAI Galuh Mazenda; Arief Andy Soebroto; Candra Dewi
Journal of Environmental Engineering and Sustainable Technology Vol 1, No 2 (2014)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Water was one resource that has a very important function for life and human life. River was the main channel as water flowing from upstream to downstream, has many domestic and industrial activity along the stream. The flow dynamics lead to changes in the quality and quantity of the river significantly. Water quality was maintained by analyzing the quality of the river water. Decision Support System (DSS) was a system designed to simplify the determination of water quality officer in making decisions. Inputs are parameter water quality test that consists of physical parameters and chemical parameters.The process of water quality analysis was conducted using Fuzzy Inference System Tsukamoto method. Fuzzy tsukamoto method used to determine the water quality of the river into four (4) classes which meet quality standards (good condition), lightly polluted, contaminated medium, and heavy polluted. The results of tested scenarios obtained an accuracy rate between the results of the calculation method of Fuzzy Tsukamoto with the calculated water quality STORET method at 90%.

SISTEM PAKAR DIAGNOSA PENYAKIT SAPI POTONG DENGAN METODE NAIVE BAYES Indriana Candra Dewi; Arief Andy Soebroto; Muhammad Tanzil Furqon
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

In order to produce quality beef, one of the important factors in maintenance of cattle is to maintain the health of livestock to stay fit. One way to provide an understanding of the breeders is to use expert system. An expert system is one of the artificial intelligence which is adopting of the expert knowledge that used to solve problem that usually can only be solved by expert in the field. Expert systems can be allowed to extend the working range of experts so that expert knowledge can be acquired and used anywhere. In this expert system use a Naive Bayes method as inference methods for diagnosing the disease. Types of diseases that can be recognized by expert system are 11 types of disease while symptoms that can be recognized the expert system are 20 types of symptom. The results of testing the accuracy of the 26 test case data, have generated the level of conformity percentage of 96,15%.

PENGEMBANGAN SISTEM PAKAR DIAGNOSA PENYAKIT SAPI POTONG DENGAN METODE FUZZY K-NEAREST NEIGHBOUR Restia Dwi Oktavianing Tyas; Arief Andy Soebroto; Muhammad Tanzil Furqon
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Early detection and treatment of cow disease is an important thing for increasing productivity of beef. The dependence of the existence of an expert or veterinarian is too high. It is caused by a lack of knowledge of the breeder about cow disease. This is a condition in which an expert is needed. However, An expert or veterinarian is not always there every encountered, especially in country areas. Those problems can be solved by expert systems. This expert system using fuzzy K-Nearest Neighbour method to process the diagnosis. The results show the functional validation testing and system expertise by 100% and accuracy test variation k, variations training data and m by 97.56%.

SISTEM PENDUKUNG KEPUTUSAN DETEKSI DINI PENYAKIT STROKE MENGGUNAKAN METODE DEMPSTER-SHAFER Deby Putri Indraswari; Arief Andy Soebroto; Eko Arisetijono Marhaendraputro
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Stroke is a neurological function disorders caused by impaired blood flow in the brain. Stroke is the third most common cause of death in developed countries, after heart disease and cancer. This causes a stroke to watch. Early prevention through medical examination needs to be done to reduce the high rate of risk of stroke. The detection of the risk of stroke is determined when knowing the criteria of risk factors is complete and structured. But sometimes the detection of the risk of stroke is difficult to determine if there are risk factors that have forgotten or not structured so that doctors can experience problems or ambiguous to make diagnosis. To overcome the problem of semi-structured pattern, it can be solved using decision support systems (DSS) with intelligent computing. SPK early detection of stroke constructed using methods Dempster Shafer. In the study can detect the level of risk of stroke is high risk, medium, and low with 8 input risk factors. Based on the data used in this system is obtained accuracy of 90%. So that it can be concluded that SPK is constructed with Dempster Shafer method to function well for detecting stroke.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN ALGORITMA SIMPLIIFIED SEQUENTIAL MINIMAL OPTIMIZATION (SSMO) PADA SUPPPORT VECTOR MACHINE (SVM) Eugenius Yosep Korsan N; Arief Andy Soebroto; Imam Cholissodin
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Balai Pembibitan Ternak Unggul (BPTU) Sapi Bali di Jembrana, Bali merupakan sebuah tempat pembudidayaan Sapi Bali yang memiliki kualitas unggul.Sapi Bali merupakan jenis sapi yang memiliki ciri khas yang unik. Ciri khas tersebut terletak pada warna kulit Sapi Bali yang mengalami perubahan sesuai dengan jenis kelamin dan usianya. Pemilihan bibit unggul Sapi Bali di BPTU dilakukan dengan berbagai macam cara. Salah satunya melihat pola warna kulit secara langsung yang terdapat pada tubuh Sapi Bali. Proses pemilihan bibit unggul Sapi Bali rentan terjadinya kesalahan yang dilakukan oleh para peternak (human error) dikarenakan jumlah Sapi Bali yang banyak di BPTU Sapi Bali. Pemilihan bibit unggul diklasifikasikan ke dalam tiga kelas yaitu Baik (Bibit Unggul), Sedang, Buruk. Untuk itu, perlu dibutuhkan suatu sistemyang mampu menghasilkan klasifikasi bibit unggul Sapi Bali berdasarkan warna kulit yang diambil menggunakan citra digital.Pada sistem tersebut, akan menerapkan algoritma SimplifiedSequential Minimal Optimization (SSMO)dengan kernel Radial Basis Function (RBF) untuk proses training data dan metode One-Against-All untuk proses klasifikasi berdasarkan fitur rata-rata dari nilai red, green dan blue (RGB). Hasil dari skenario pengujian didapatkan rata-rata tingkat akurasi untuk empat skenario pengujian Sapi Bali Jantan dan Betina sebesar 97.50% dan 67.50%.

Prediksi Tinggi Muka Air (TMA) Untuk Deteksi Dini Bencana Banjir Menggunakan SVR-TVIWPSO Arief Andy Soebroto; Imam Cholissodin; Randy Cahya Wihandika; Maria Tenika Frestantiya; Ziya El Arief
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2 No 2: Oktober 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Abstrak Banjir merupakan salah satu jenis bencana alam yang tidak dapat diprediksi kedatangannya, salah satu penyebabnya adalah adanya hujan yang terus – menerus(dari peristiwa alam). Faktor penyebab banjir dari segi meteorologi yaitu curah hujan yang tinggi dan air laut yang sedang pasang sehingga mengakibatkan tinggi permukaan air meningkat. Analisis terhadap data curah hujan serta tinggi permukaan air setiap periodenya dirasa masih belum dapat menyelesaikan permasalahan yang ada. Oleh karena itu, pada penelitian ini diusulkan teknik integrasi metode Time Variant Inertia Weight Particle Swarm Optimization(TVIWPSO) dan Support Vector Regression(SVR). Implementasi memadukan metode Regresi yaitu SVR untuk forecasting TMA, sedangkan TVIWPSO digunakan untuk mengoptimalisasi parameter – parameter yang digunakan di dalam SVR untuk memperoleh kinerja yang maksimal dan hasil yang akurat. Harapannya sistem ini akan dapat membantu mengatasi permasalahan untuk pendeteksian dini bencana banjir karena faktor cuaca yang tidak menentu. Hasil pengujian yang didapat dari 10 data bulanan yang berbeda menunjukkan bahwa didapatkan nilai error terkecil sebesar 0.00755 dengan menggunakan Mean Absolute Error untuk data Juni 2007 dengan menggunakan integrasi metode SVR-TVIWPSO. Kata Kunci : Support Vector Regression, Tinggi Muka Air, Time Variant Inertia Weight Particle Swarm Optimization. Abstract Flood is one type of natural disaster that can not be predicted its arrival, one reason is the rain that constantly occurs (from natural events). Factors that cause flooding in terms of meteorology are high rainfall and sea water was high, resulting in high water level increases. Analysis of rainfall data and water level in each period it is still not able to solve existing problems. Therefore, in this study the method proposed integration techniques Time Variant Inertia Weight Particle Swarm Optimization (TVIWPSO) and Support Vector Regression (SVR). Implementation combines regression method for forecasting TMA is SVR, while TVIWPSO used to optimize parameters that used in the SVR to obtain maximum performance and accurate results. Hope this system will be able to help solve the problems for the early detection of floods due to erratic weather. The result of forecasting experiment in water level forecasting from 10 monthly different data show that the smallest error rate is amount to 0.00755 using Mean Absolute Error for June 2007 with the integration method SVR-TVIWPSO. Keywords: Support Vector Regression, water level, Time Variant Inertia Weight Particle Swarm Optimization.

Optimasi Kandungan Gizi Susu Kambing Peranakan Etawa (PE) Menggunakan ELM-PSO Di UPT Pembibitan Ternak Dan Hijauan Makanan Ternak Singosari-Malang Imam Cholissodin; Sutrisno Sutrisno; Arief Andy Soebroto; Latifah Hanum; Canny Amerilyse Caesar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 1: Maret 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

AbstrakSusu merupakan salah satu sumber protein hewani yang mengandung semua zat yang dibutuhkan tubuh. Ternak penghasil susu utama di Indonesia yaitu sapi perah, namun produksi susunya belum dapat mencukupi kebutuhan masyarakat. Alternatifnya adalah kambing peranakan etawa (PE). Tingginya kualitas kandungan gizi susu sangat dipengaruhi oleh beberapa faktor salah satunya, yaitu faktor pakan. Bagian peternakan kambing PE di UPT Pembibitan Ternak dan Hijauan Makanan Ternak Singosari-Malang masih menghadapi permasalahan, yaitu rendahnya kemampuan dalam memberikan komposisi pakan terhadap kambing PE. Kekurangan tersebut berpengaruh terhadap kualitas susu yang dihasilkan. Diperlukan pengetahuan rekayasa kandungan gizi susu untuk menentukan komposisi pakan dalam menghasilkan susu premium dengan kandungan gizi optimal. Penulis menggunakan metode Extreme Learning Machine (ELM)dan Particle Swarm Optimization (PSO) untuk membuat pemodelan pakan kambing dalam mengoptimasi kandungan gizi susu kambing. Dalam analisa pengujian konvergensi menggunakan metode ELM-PSO yang dilakukan dengan kasus untuk berat badan kambing 32 kg, serta jenis pakan yang digunakan yaitu rumput Odot 70% dan rumput Raja 30% menghasilkan sistem mencapai kestabilan dalam konvergensi pada iterasi ke-20 dengan fitness terbaik yaitu 16.2712.Kata Kunci: Susu Kambing, Optimasi, Artificial Neural Network (ANN), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Kandungan Nutrisi Pakan.AbstractMilk is one of the animal protein sources which it contains all of the substances needed by human body. The main milk producer cattle in Indonesia is dairy cow, however its milk production has not fulfilled the society needs. The alternative is the goat, the Etawa crossbreed (PE). The high quality of milk nutrients content is greatly influenced by some factors one of them, is the food factor. The PE goat livestock division of the UPT Cattle Breeding and the Cattle Food Greenery in Singosari-Malang still faces the problem, it is the low ability in giving the food composition for PE goat. This flaw affects the quality of the produced milk. It needs the artificial science of the milk nutrients contains in order to determine the food composition to produce premium milk with the optimum nutrients contain. The writer uses the method of the Extreme Learning Machine (ELM) and the Particle Swarm Optimization (PSO) to make the modeling of goat food in optimizing the content of goat milk nutrients. In the analysis of the convergence that is done with the case of 32 kg goat weight, also the food type used is the 70 % Odot grass and 30% Raja grass that system get a stability on the 20th iteration with a fitness value is 16.2712.Keywords: Goat Milk, Optimization, Extreme Learning Machine (ELM), Particle Swarm Optimization (PSO), The Food Nutrients Contain.

Integrasi Metode Fuzzy Additive SVM (FASVM) Menggunakan Model Warna YUV-CMY-HSV Untuk Klasifikasi Bibit Unggul Sapi Bali Melalui Citra Digital Imam Cholissodin; Arief Andy Soebroto; Nurul Hidayat
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2 No 2: Oktober 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

AbstrakBudidaya sapi sangat identik dengan pemilihan bibit unggul, namun permasalahan yang sering muncul adalah cara mengenali bibit unggul tersebut yang relatif tidak mudah, cenderung membutuhkan waktu cukup lama. Peternak masih sering mengamati warna kulit dengan mata secara langsung, yang cenderung kurang teliti. Sehingga dalam penelitian ini, diusulkan metode dengan menggunakan beberapa model warna yang nantinya sebagai rekomendasi untuk fitur yang optimal dalam sistem. Kemudian metode klasifikasi yang digunakan adalah Fuzzy Additive Support Vector Machine (FASVM). Data yang digunakan didapatkan dari Balai Pembibitan Ternak Unggul (BPTU) Sapi Bali. Dari hasil pengujian didapatkan model warna yang paling optimal dan rata-rata akurasi pada Sapi Betina dan Jantan dengan ukuran citra tertentu. Model warna tersebut sangat dipengaruhi oleh kondisi data citra dan juga banyaknya kelas data.Kata kunci: Sapi Bali, Model warna , Intersection kernel, Fuzzy additive SVM, Sequential training SVM AbstractCattle farming is identical with the selection of seeds, but the problems that often arises is how to recognize quality seeds are relatively easy, tend to take a long time. Breeders still often observe skin color with eyes directly, which tend to be less rigorous. Thus, in this study, the proposed method by using several color models that will be voted on features that are optimal in the system. Then the classification method used is Additive Fuzzy Support Vector Machine (FASVM). The data used was obtained from Livestock Breeding Center for Excellence (BPTU) Bali cattle. From the test results obtained the most optimal color models and average accuracy on Cow Females and Males with a particular image size. The color model is highly influenced by the condition of the image data and also the amount of class data. Keywords: Bali cattle, Color model , Intersection kernel, Fuzzy additive SVM, Sequential training SVM

Sistem Monitoring Aliran Sungai dan Lingkungan Berbasis Smart Environment di RW 03 Kelurahan Kauman Kota Malang Sutrisno Sutrisno; Imam Cholissodin; Arief Andy Soebroto; Muh Arif Rahman
JAST : Jurnal Aplikasi Sains dan Teknologi Vol 5, No 1 (2021): EDISI JUNI 2021
Publisher : Universitas Tribhuwana Tunggadewi Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/jast.v5i1.2259

Monitoring of the rivers state and the environment of roads in the city center is often still inadequate. For example, garbage is often found in the river, while on the roads, there is still not yet a sound security system. Kauman RT 03 RW III Klojen Malang is one of the densely populated regions and is located in the center (point of zero) of Malang city at the time ago still does not have a security system or security guard and there is a river flow which is often found garbage piling up and often causes flooding when it rains heavy. Based on field conditions in Kauman and meetings with residents represented by several RT heads in RW 03 Kauman, Klojen Malang requires the use of a smart environment and CCTV technology integration. Therefore the result of dedication to society to apply CCTV's technology, so it has been used at Kauman for environmental and security monitoring. Considering the high level of the busyness of the urban at Kauman, with providing it, they can be monitoring the environment by automatically systems continuously 24 hours every day. Therefore, the system has been being able to facilitate and help people to monitor the environment and river flow to be more effective, efficient, and modern. ABSTRAKMonitoring keadaan sungai dan lingkungan ruas jalan pada masyarakat tengah kota seringkali masih belum memadai. Di aliran sungai misalnya, masih sering dijumpai sampah yang menumpuk, sedangkan di ruas jalan masih belum dijumpai sistem keamanan yang baik. Kampung Kauman RT 03 RW III kecamatan Klojen Kota Malang merupakan salah satu kampung yang padat penduduk dan berada di pusat (titik nol) kota saat ini belum memiliki sistem keamanan ataupun satpam dan terdapat aliran sungai yang seringkali dijumpai sampah menumpuk bahkan sering menyebabkan banjir bila hujan deras. Berdasarkan kondisi lapangan di kampung Kauman dan pertemuan dengan warga yang diwakili oleh beberapa ketua RT di wilayah RW 03 Kauman yang membutuhkan pemanfaatkan integrasi teknologi smart environment dan teknologi CCTV. Hasil kegiatan pengabdian masyarakat telah dapat secara optimal dimanfaatkan untuk memenuhi kebutuhan pengawasan ataupun monitoring lingkungan tersebut. Mengingat tingkat kesibukan masyarakat perkotaan yang tinggi, dengan adanya sistem monitoring mereka dapat mengambil manfaat besar dengan dikembangkannya sistem pengawasan aliran sungai dan lingkungan yang bisa bekerja secara otomatis dan kontinyu selama 24 jam. Sistem yang dibuat telah mampu memudahkan sekaligus membantu masyarakat untuk monitoring lingkungan dan aliran sungai secara lebih efektif, efisien, dan modern.

Pelatihan Pelaporan Keuangan Berbasis Aplikasi Di Lingkup Antar RT Dalam RW Kelurahan Kauman Kecamatan Klojen Malang Sutrisno Sutrisno; Imam Cholissodin; Arief Andy Soebroto; Dian Eka Ratnawati; Lailil Muflikhah
JAST : Jurnal Aplikasi Sains dan Teknologi Vol 4, No 1 (2020): EDISI JUNI 2020
Publisher : Universitas Tribhuwana Tunggadewi Malang

The use of information and communication technology for online-based financial applications has been widely developed, including in the fields of banking, finance, transportation, buying and selling, health, and so on. Likewise, mobile device-based applications such as cell phones, computers, laptops and others are also common and are widely used by the public. In accordance with these conditions, a community service activity was carried out in several RTs in one RW in Kauman Sub-District, Klojen District, Malang City (specifically RT-02 and RT-03 in RW-03) to use a financial application. The developed application is expected to facilitate financial management at the RT level, so that it becomes more effective, efficient, accurate and transparent. The stages of community service activities began with observations and surveys, especially in RT-02 and RT-03 in RW-03 Kauman Sub-District, Klojen District, Malang. The results of this survey formed the basis for implementing the financial application that was developed. After that, socialization and training on the use of applications that had been successfully developed from selected references were performed, so that the people were more accustomed to using the financial service system. With this application, it is hoped that the management of financial services will become easier and application users will also be facilitated by the features provided. The results of this activity are that RT Financial Management System (SIPUT) can be accessed in various platforms both desktop PC and web devices, and this system uses a user friendly display so that RT-02 and RT-03 Staffs in RW-03 Kauman Sub-District can easily conduct financial management quickly and accurately that improves their performance. Therefore, SIPUT is very suitable with the needs of the object of community service. RT staffs can carry out a variety of management of several activities such as making financial management, mail management, and citizen activity management.ABSTRAKPemanfaatan teknologi informasi dan komunikasi untuk aplikasi keuangan berbasis online telah banyak dikembangkan, diantaranya di bidang perbankan, keuangan, transportasi, jual beli, kesehatan, dan sebagainya. Demikian juga aplikasi berbasis perangkat bergerak seperti telepon seluler, komputer, laptop maupun lainnya juga sudah lazim dan banyak digunakan oleh masyarakat. Berdasarkan kondisi tersebut, maka dilaksanakan kegiatan pengabdian masyarakat antar RT dalam satu RW di wilayah Kelurahan Kauman Kecamatan Klojen Kota Malang (khususnya RT-02 dan RT-03 di RW-03) untuk menggunakan aplikasi keuangan. Aplikasi yang dikembangkan diharapkan dapat mempermudah dalam melakukan pengelolaan keuangan di tingkat RT, sehingga lebih efektif, efisien, akurat dan transparan. Tahapan kegiatan pengabdian kepada masyarakat ini diawali dengan melakukan observasi dan survei khususnya RT-02 dan RT-03 di RW-03 Kelurahan Kauman Kecamatan Klojen Kota Malang. Hasil survei ini dijadikan dasar implementasi aplikasi keuangan yang dikembangkan. Selanjutnya dilakukan sosialisasi dan pelatihan penggunaan aplikasi yang telah berhasil dikembangkan dari referensi terpilih, agar masyarakat lebih terbiasa dalam menggunakan sistem layanan keuangan tersebut. Dengan adanya aplikasi ini, diharapkan pengelolaan layanan keuangan menjadi lebih mudah dan pengguna aplikasi juga dimudahkan dengan adanya fitur-fitur yang telah disediakan. Hasil dari kegiatan ini yaitu, Sistem Pengelola Keuangan RT (SIPUT) dapat diakses dalam berbagai platform baik perangkat PC desktop maupun web, lalu sistem ini menggunakan tampilan yang user friendly sehingga Staff RT-02 dan RT-03 RW-03 Kelurahan Kauman dapat dengan mudah melakukan manajemen pengelolaan keuangan dengan cepat dan akurat, sehingga kinerja mereka menjadi lebih baik. Jadi SIPUT ini sangat sesuai dengan kebutuhan objek pengabdian masyarakat. Staff RT dapat melakukan berbagai pengelolan beberapa kegiatan seperti membuat manajemen keuangan, manajemen surat, dan manajemen kegiatan warga.Kata kunci : sistem; pengelola keuangan; Kauman; teknologi web; dekstop

Co-Authors Achmad Arwan Achmad Ridok Adam Hendra Brata Ade Wija Nugraha Adi Setyo Nugroho Admaja Dwi Herlambang Agi Putra Kharisma Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Mustafirudin Ahmad Shofi Nurur Rizal Aizul Faiz Iswafaza Alfarisi, Muhammad Asnin Ali Akbar Alysha Ghea Arliana Amira Ibtisama Ana Kusuma Ardani Andreas Tommy Christiawan Andri Wijaya Kusuma Asrul Syawal Asrul, Divanda Arya Inasta Asus Maizar Suryanto H Austenita Pasca Aisyah Baghaz, Renanda DSP Bambang Gunadi Brilliansyach, Raihan Fikri Candra Dewi Candra Dewi Canny Amerilyse Caesar Catur Ari Setianto Dama Yuliana Deby Putri Indraswari Denny Sagita Rusdianto Destyana Ellingga Pratiwi Destyana Ellingga Pratiwi Dhea Azahria Mawarni Dian Eka Ratnawati Djoko Pramono Dwi Cindy Herta Turnip Dwi Puri Cemani Dzikrullah, Muhammad Aulia Fachruz Edy Santoso Eka Miyahil Uyun Eko Ari Setijono Marhendraputro Eko Arisetijono Elza Fadli Hadimulyo Enggar Septrinas Enggarsita Auliasin Eugenius Yosep Korsan N Evi Irhamillah Azza Faisal Roufa Rohman Faizatul Amalia Fajar Pradana Fauziah Mayasari Iskandar Febrianita Indah Perwitasari Fendy Yulianto Ferdy Wahyurianto Fildzah Amalia Galuh Mazenda Guruh Prayogi Willis Putra Habib Yafi Ardi Hanafi, Andy Hastian Bayu Hendra Darmawan Herman Syantoso Himawan Sutanto I Gede Adi Brahman Nugraha I Putu Bagus Arya Pradnyana Ibnu, Mohammad Ibrahim Kusuma Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra Ekaristio P Indriana Candra Dewi Indriati Indriati Indriati Indriati Ishak Panangian Sinaga Ismiarta Aknuranda Issa Arwani Issa Arwani Karmia Larissa Br Pandia Khoifah Inda Maula Khrisna Widhi Dewanto Krisna Wahyu Aji Kusuma Lailatul Rizqi Ramadhani Lailil Muflikhah Laode Muhamad Fauzan Latifah Hanum Mahdi Fiqia Hafis Maria Tenika Frestantiya Maria Tenika Frestantiya Maria Tenika Frestantiya, Maria Tenika Maya Febrianita Mohammad Imron Maulana Muh. Arif Rahman Muhammad Iqbal Kurniawan Muhammad Rois Al Haqq Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Taruna Praja Utama Mutia Ayu Sabrina Nadya Rahmasari Nadya Sylviani Niftah Fatiha Armin Niken Hendrakusma Wardani Nizar Rahman Kusworo Nurannisa, Nadhira Nuriya Fadilah Nurudin Santoso Nurul Faizah Nurul Faridah, Nurul Nurul Hidayat NURUL HIDAYAT Nurul Hidayat Nurul Hidayat Odhia Yustika Putri Priyambadha, Bayu Randy Cahya Wihandika Raymond Gunito Farandy Junior Rekyan Regasari Restia Dwi Oktavianing Tyas Reynald Daffa Pahlevi Ridwan Fajar Widodo Rio Andika Dwiki Adhi Putra Rio Arifando Risda Nur Ainum Riski Ida Agustiyan Risqi Nur Ifansyah Rivaldy Raihan Syams Rizal Setya Perdana Rizal Setya Perdana Saiful Kirom, Muhammad Ihsan Santoso, Nurudin Sativandi Putra Satrio Agung Wicaksono Sitepu, Yosua Christiansen Stefan Levianto Sukamto, Anjas Pramono Surya Wirawan SUTRISNO Sutrisno Sutrisno Sutrisno, Sutrisno Teddy Syach Pratama Thareq Ibrahim Tiara Rossa Diassananda Tryse Rezza Biantong Vasya, M Azka Obila Vicky Virdus Vivien Fathuroya, Vivien Wayan Firdaus Mahmudy Welly Purnomo Wijaya, Aldi Rahman Wildan Ziaulhaq Wildan Ziaulhaq Wildansyah Maulana Rahmat Yearra Taufan Ardy Rinaldy Yusril Iszha Eginata Zaien Bin Umar Alaydrus Ziya El Arief Ziya El Arief Ziya El Arief, Ziya El

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