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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Pendidikan Teknologi dan Kejuruan Techno.Com: Jurnal Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JIKO (Jurnal Informatika dan Komputer) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL ILMIAH INFORMATIKA SINTECH (Science and Information Technology) Journal Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Tunas Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Revolusi Indonesia JiTEKH (Jurnal Ilmiah Teknologi Harapan) IJISTECH Journal of Applied Data Sciences RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT DEVICE Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Inovatif BEES: Bulletin of Electrical and Electronics Engineering JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Krisnadana STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Jurnal Krisnadana Journal of Informatics, Electrical and Electronics Engineering

Wanto, Anjar

STIKOM Tunas Bangsa, Pematangsiantar, Indonesia.

Author-ID : 621424

Aerospace Engineering Arts Humanities Astronomy 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Penerapan Algoritma Backpropagation dalam Memprediksi Persentase Penduduk Buta Huruf di Indonesia Imelda Asih Rohani Simbolon; Fikri Yatussa’ada; Anjar Wanto
Jurnal Informatika Upgris Vol 4, No 2: Desember (2018)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v4i2.2423

Illiteracy is one of the most serious issues in Indonesia. The government's ignorance of illiterate people makes the illiteracy rate quite high. It should be one of the government's targets for reducing illiteracy in order to reduce the number of illiterate people. Illiteracy rate in Indonesia itself has reached 34.55% in Papua province. One way to suppress illiteracy rate in Indonesia is by predicting illiterate figures for subsequent years. The data to be predicted is the data of illiterate figures of each province in Indonesia which is sourced from the Indonesian Central Bureau of Statistics from 2011 to 2017. The method used in the prediction is Backpropagation Neural Network. Data analysis was done with the help of matlab software R2011b (7.13). This study uses 5 architectures, 4-5-1, 4-6-1, 4-9-1, 4-14-1 and 4-18-1. From these 5 models the best network architecture is 4-14-1 with 91% accuracy and Mean Squared Error 0,00274166.

ANALISIS ALGORITMA BACKPROPAGATION DALAM PREDIKSI NILAI EKSPOR (JUTA USD) Jonas Rayandi Saragih; Mhd. Billy Sandi Saragih; Anjar Wanto
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 15 No. 2 (2018): Edisi Juli 2018
Publisher : Universitas Pendidikan Ganesha

In a study, the analysis is necessary for the accuracy and accuracy of an education. So also in prediction Export Value (Million USD). This research will discuss the value of export in general in North Sumatra based on Million USD. This research is conducted to know the export development in North Sumatera in the future. This research uses Artificial Neural Network with Backpropagation algorithm. The research data used comes from the Central Bureau of Statistics of North Sumatra from 2012 until 2017. This research will use five architectural models namely 4-5-1, 4-7-1, 4-9-1, 4-10-1 and 4-11-1. The best model of the five models is 4-7-1 with a 100% accuracy rate, with a time of 27 seconds. The error rate used is 0.001 - 0.05. Thus, this model is good enough to predict Export Value in North Sumatra, because its accuracy reaches 100%.

PROYEKSI INDEKS PEMBANGUNAN MANUSIA DI INDONESIA MENGGUNAKAN METODE STATISTICAL PARABOLIC DALAM MENYONGSONG REVOLUSI INDUSTRI 4.0 Ika Okta Kirana; Zulaini Masruro Nasution; Anjar Wanto
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 16 No. 2 (2019): Edisi Juli 2019
Publisher : Universitas Pendidikan Ganesha

Indeks Pembangunan Manusia (IPM) merupakan indikator yang sangat penting dalam mengukur keberhasilan sebuah negara dalam membangun kualitas hidup penduduk/masyarakat nya, termasuk Indonesia. Ekonomi global saat ini sedang pada titik puncak perubahan besar yang sebanding besarnya dengan munculnya revolusi industri 4.0. Penentuan peringkat atau level pembangunan dan ekonomi dari suatu wilayah atau negara dapat dilihat dari IPM. Karena begitu pentingnya Indeks Pembangunan Manusia (IPM), maka perlu dilakukan proyeksi tingkat perkembangan IPM di tahun-tahun selanjutnya, agar pemerintah Indonesia memiliki referensi dan acuan yang jelas untuk menentukan kebijakan ataupun membuat langkah-langkah strategis yang tepat agar Indeks Pembangunan Manusia (IPM) jangan sampai menurun di masa yang akan datang, bahkan meningkat pada tiap tahunnya. Data yang akan diproyeksi pada penelitian ini adalah data Indeks Pembangunan Manusia (IPM) tahun 2010-2018. Sumber data diambil dari Badan Pusat Statistik (BPS) Indonesia. Pada penelitian ini, metode proyeksi yang digunakan untuk melihat perkembangan IPM di Indonesia adalah Statistical Parabolic Projection (Trend Parabolik). Setelah dilakukan perhitungan, diperoleh selisih antara data asli IPM dengan data hasil proyeksi sangat dekat sekali, dengan tingkat MSE sebesar 0,01659. Sehingga dapat disimpulkan bahwa metode Trend Parabolik sangat baik digunakan untuk melakukan proyeksi Indeks Pembangunan Manusia. Oleh karena itu hasil penelitian ini adalah proyeksi Indeks Pembangunan Manusia (IPM) di Indonesia untuk tahun 2019 hingga tahun 2027

Pelatihan dan Bimbingan dalam Pemanfaatan Internet yang Baik dan Aman bagi Pelajar SMK Anak Bangsa Desa Bandar Siantar Kabupaten Simalungun Anjar Wanto; Dedi Suhendro; Agus Perdana Windarto
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 9, No 2 (2018): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v9i2.2116

Perkembangan teknologi khususnya internet telah membawa banyak perubahan. Berkat bantuan internet semua pekerjaan menjadi terasa ringan. Bagi para siswa atau pelajar, internet memudahkan mereka dalam mencari literatur atau bahan-bahan tugas sekolah. Akan tetapi kemampuan siswa dalam menggunakan internet dengan cara yang baik dan aman di era globalisasi dewasa ini masih tergolong rendah, terutama pada siswa-siswi SMK Anak Bangsa desa Bandar Siantar Kabupaten Simalungun. Letaknya yang di pedesaan dan jauh dari perkotaan serta kurangnya perhatian pemerintah daerah dalam melakukan sosialisasi, bimbingan dan pelatihan internet membuat banyak siswa khususnya yang tinggal di pedesaan, kurang memahami pentingnya pemanfaatan internet dengan cara yang positif. Sebagian besar para siswa bisa bebas berselancar di dunia maya dan melakukan aktivitas online mereka tanpa adanya pengawasan. Oleh karena itu kegiatan pelatihan dan bimbingan dalam pemanfaatan internet sangat perlu dilakukan untuk mengingatkan serta memberikan kesadaran bagi para siswa bagaimana cara menggunakan internet dengan cara yang bijaksana agar kedepannya kemampuan akademik maupun pengetahuan mereka terhadap dunia pendidikan dan informasi semakin meningkat. Pelatihan ini nanti nya akan menggunakan 4 macam modul diktat yang masing-masing akan dijelaskan berupa presentasi menggunakan power point. Dengan pelatihan dan bimbingan ini diharapkan para pelajar khususnya disekolah ini mampu memanfaatkan internet dengan arif dan bijaksana dalam rangka mendukung upaya pengembangan SDM yang beradab yang memiliki kemampuan bersaing secara global, tidak hanya mampu bersaing secara intelektual tetapi juga memiliki adab dan perilaku yang baik.

Penentuan Masyarakat Penerima Bantuan Perbaikan Rumah di Kecamatan Siantar Barat Menggunakan Metode ELECTRE Roulina Simarmata; Rahmat W Sembiring; Rafiqa Dewi; Anjar Wanto; Eva Desiana
Journal of Computer System and Informatics (JoSYC) Vol 1 No 2 (2020): Journal of Computer System and Informatics (JoSYC) - Februari 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.084 KB)

Home improvement assistance is a government program for disadvantaged people. Home improvement assistance program is one of the government's efforts as a form of concern related to the condition of the homes of underprivileged communities. Therefore the purpose of this study is to determine the recipient of housing improvement assistance in the West Siantar Subdistrict as a reference material for the Office of Spatial Planning and Settlements (Tarukim) of Pematangsiantar city in providing housing repair assistance to be on target. The DSS method used in this study is the Elimination Et Choix Traduisant La Realita (ELECTRE) method. The alternative data samples used were 5, which were obtained from the Pematangsiantar Tarukim Office. This study also uses 5 criteria, including: roof material conditions, floor conditions, wall conditions, Work and Bathroom ownership. Based on calculations, Alternative 2 (A002) on behalf of Mr. Wariman was chosen as the best. Therefore, Mr. Wariman's family home is a community that is entitled to receive housing repair assistance in the West Siantar sub-district

Prediksi Hasil Produksi Kelapa Sawit PTPN IV Bahjambi Menggunakan Algoritma Backpropagation Venny Vidya utari; Anjar Wanto; Indra Gunawan; Sumarno Sumarno; Zulaini Masruro Nasution
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Oil palm is a tropical plant of the Indonesian natural palmae group which has a tropical climate. The growth and harvest of oil palm also depends on fertilizers and the rainfall that falls every day. To get good production results it requires high ability and a lot of labor. Each production result certainly does not always increase, there must be a time when the production will decrease, therefore an algorithm is needed to predict it so that companies can find out the development of palm oil production in the future. In this study, researchers used the Backpropagation Algorithm. The Backpropagation Algorithm is an algorithm that functions to reduce the error rate by adjusting the weight based on the desired output and target, there are 5 training and data testing architectural models, namely 2-21-1, 2-22-1, 2-24-1, 2-26 -1 and 2-28-1. From the results of testing data on oil palm production, the best architectural model is obtained, namely 2-22-1 which shows that the target is reduced by the output that SSE is 0.35206024, from the data obtained, the performance of the calculation of artificial neural networks with the Backpropagation Algorithm gets an accuracy of 83.3%. . So that it can be used as a benchmark in predicting palm oil production, seen from the comparison of the desired target with the predicted target

Penggunaan Sistem GPS Untuk Keamanan Kendaraan Dengan Kontrol SMS Menggunakan Mikrokontroler Arduino Agung Yusuf Pratama; Muhammad Ridwan Lubis; Anjar Wanto; Indra Gunawan; Ika Okta Kirana
BEES: Bulletin of Electrical and Electronics Engineering Vol 2 No 1 (2021): July 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Motor vehicle theft cases still often occur around us, this happens because there is still a lack of security systems in motorized vehicles that only use ignition keys and key covers, where the weakness of standard security systems like this has been understood by perpetrators of motor vehicle theft. to perform the action. The need for additional security systems is felt to be very necessary, in order to avoid the occurrence of motor vehicle theft. To overcome all this, a motor vehicle security system was created using SMS with an Arduino-based GPS tracking method, to create a GPS Tracker that can control vehicles via SMS (short message service) that can track or assist the vehicle's position using the Arduino Uno GPS (global positioning system). , SIM 800L. If the vehicle is lost, the owner can be tracked only by SMS to the number that has been programmed on the Arduino uno to prevent and make it easier to get back a stolen motor vehicle.

PREDIKSI PRODUKTIVITAS JAGUNG DI INDONESIA SEBAGAI UPAYA ANTISIPASI IMPOR MENGGUNAKAN JARINGAN SARAF TIRUAN BACKPROPAGATION Anjar Wanto
SINTECH (Science and Information Technology) Journal Vol. 2 No. 1 (2019): SINTECH Journal Edition April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i1.355

Corn is a staple food that is still widely consumed by the population of Indonesia. Based on data from the Indonesian Statistics Agency, corn productivity in Indonesia from 2005 to 2015 calculated an unstable curve. Therefore this research was conducted to predict and see the large growth of maize in Indonesia for the following years so that the government has a reference to continuously strive to increase corn productivity in Indonesia in order to remain stable in order to meet the needs of Indonesian people to minimize corn imports. This study uses data on corn productivity in Indonesia in 2005-2015 sourced from the Indonesian Central Bureau of Statistics. The prediction algorithm used is the Backpropagation Neural Network. This algorithm is able to predict data well, especially data that is maintained for a certain period of time. To facilitate data analysis, the author uses the Matlab 2011b application. In this study, a training and testing process will be carried out using 5 network architecture models, namely 5-25-1, 5-43-1, 5-76-1, 5-78-1 and 7-128-1. Of the 5 architectural models, the best is 5-25-1 with the percentage of 88% and the MSE value of 0.00992433.

Algoritma Fungsi Perlatihan pada Machine Learning berbasis ANN untuk Peramalan Fenomena Bencana Anjar Wanto; Sarjon Defit; Agus Perdana Windarto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 2 (2021): April 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Research has been carried out with several training functions using standard backpropagation methods, One-Step Secant (OSS), and Bayesian regulation. The purpose of this study was to (i) analyze the Performance accuracy (Performance) of the standard backpropagation method and (ii) optimize the training function with the One-Step Secant (OSS) and Bayesian regulation methods to obtain comparison results of the three methods in the search for the best results implementation of disaster phenomenon forecasting data. The research method is based on quantitative methods with times-series data on disaster phenomena in Indonesia over the last ten years (2011-2020) which were analyzed using two network architecture models, namely 4-8-1 and 4-10-1. The results showed that the 4-8-1 architectural model with the Bayesian regulation training function method was able to optimize quite well through accelerating training time and resulted in a low MSE measurement, although not the lowest with an epoch value of 197 iterations and a Performance of 0.0148480766. The lowest epoch value is generated by the OSS method, but it Performs poorly. The best Performance is produced by the standard backpropagation method with the traingd training function, but the training process for achieving convergence is also too long. In general, it can be concluded that the 4-8-1 architectural model with Bayesian regulation can be used to predict (predict) the phenomenon of natural disasters in Indonesia because the training time to achieve convergence is not too long and Performs exceptionally well.

The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm Asro Pradipta; Dedy Hartama; Anjar Wanto; Saifullah Saifullah; Jalaluddin Jalaluddin
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.30

Graduating on time is one element of higher education accreditation assessment. In the Strata 1 level, students are declared to graduate on time if they can complete their studies <= eight semesters or four years. BAN-PT sets a timely graduation standard of >= 50%. If the standard is not met, it will reduce the value of accreditation. These problems encourage the Universitas Simalungun Pematangsiantar to conduct evaluations and strategic steps in an effort to increase student graduation rates so that the targets of BAN-PT can be achieved. For this reason it is necessary to know in advance the pattern of students who tend not to graduate on time. In this study, C4.5 Algorithm is proposed to predict student graduation. This algorithm will process student profile datasets totaling 150 data. This dataset has a graduation status label. The value of the label is categorical, that is, right and late. The features or attributes used, namely the name of the student, gender, student status, GPA. The results of the C4.5 algorithm are in the form of a decision tree model that is very easy to analyze. In fact, even by ordinary people. This model will map the patterns of students who have the potential to graduate on time and late.

Co-Authors Abdi Rahim Damanik Abdullah Ahmad Achmad Noerkhaerin Putra Adnan, Syed Muhammad Agung Pratama Agung Wibowo Agung Yusuf Pratama Agus Perdana Windarto Akbari, Imam Anan Wibowo Andi Sanggam Sidabutar Arifah Hanum Arifin Nur, Khairun Nisa Asro Pradipta Astuti, Wiwik Sri Ayu Artika Fardhani Azwar Anas Manurung Azwar Anas Manurung Bil Klinton Sihotang Cici Astria Damanik, Bahrudi Efendi Damayanti, Tri Febri Daniel Sitorus Dedi Kusbiantoro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Deri Setiawan Desi Insani Natalia Simanjuntak Dewi, Rafiqa Dinda Nabila Batubara Edu Wardo Saragih eko hartato Eko Hartato Eko Kurniawan Eko Purwanto Elfin Efendi Eva Desiana Fajar Ramadan Fazira, Rizky Nazwa Febriyanto, R Tri Hadi Fikri Yatussa’ada Fitri Anggraini GS , Achmad Daengs Gumilar Ramadhan Pangaribuan Hardinata, Jaya T Harly Okprana Hartama, Dedy Hartama, Dedy Heru Satria Tambunan Heru Satria Tambunan, Heru Satria Ht. Barat, Ade Ismiaty Ramadhona Hutasoit, Rahel Adelina Hutasoit, Rahel Adelina Ihsan Maulana Muhamad Iin Parlina Iin Parlina Iin Parlina Iin Parlina Iin Parlina Iin Parlina Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Purnama Sari Ilham Syahputra Saragih Imelda Asih Rohani Simbolon Indra Gunawan Indra Gunawan Indra Satria Indra Satria Indra Satria Indri Sriwahyuni Purba Irawan Irawan Irfan Sudahri Damanik Jalaluddin Jalaluddin Jalaluddin Jalaluddin Jaya Tata Hardinata Jeni Sugiandi Jonas Rayandi Saragih Jonas Rayandi Saragih Joni Wilson Sitopu Jufriadif Na`am, Jufriadif Juli Wahyuni Khairun Nisa Arifin Nur Khairunnissa Fanny Irnanda Kirana, Ika Okta M Mesran M Safii M. Safii M.Ridwan Lubis Manurung, Azwar Anas MARIA BINTANG Marseba Situmorang Martina Silaban Mesran, Mesran Meychael Adi Putra Hutabarat Mhd Ali Hanafiah Mhd Gading Sadewo Mhd. Billy Sandi Saragih Mhd.Buhari Sibuea Mora Malemta Sitomorang Muhammad Aliyul Amri Muhammad Aliyul Amri Muhammad Julham Muhammad Julham Muhammad Mahendra Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Syafiq Muhammad Wijaya Napitupulu, Flora Sabarina Nasution, Rizki Alfadillah Nasution, Zulaini Masruro Nazlina Izmi Addyna Ni Luh Wiwik Sri Rahayu Ginantra Nur Ahlina Febriyati Nur Arminarahmah Nur Arminarahmah Nur, Khairun Nisa Arifin Nuraysah Zamil Purba Nurhayati Nurhayati Okprana, Harly Okta Andrica Putra Parlina, Iin Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih, Poningsih Putrama Alkhairi Rahmat W Sembiring Rahmat W. Sembiring Rahmat Zulpani Ramadani, Saputra Rapianto Sinaga Ratih Puspadini Reza Pratama Rita Mawarni Rizky Khairunnisa Sormin Ronal Watrianthos Roulina Simarmata Roy Chandra Telaumbanua Ruri Eka Pranata S Solikhun S Solikhun S Sumarno Sadewo, Mhd Gading Safii, M. Safruddin Safruddin Saifullah Saifullah Samuel Palentino Sinaga Samuel Palentino Sinaga Sandy Putra Siregar Saputra Ramadani Saragih, Irfan Christian Saragih, Jonas Rayandi Saragih, Mhd. Billy Sandi Sari, Riyani Wulan Sari, Riyani Wulan Sarjon Defit Setti, Sunil Sigit Anugerah Wardana Silaban, Herlan F Silfia Andini, Silfia Silitonga, Hotmalina Silitonga, Hotmalina Siregar, Sandy Putra Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Suhada Suhada Suhada Suhada Sumarno Sumarno Sumarno Sumarno Sumarno Sumarno Sundari Retno Andani Sundari Retno Andani Sunil Setti Surya Hendraputra Susi Fitryah Damanik Syafri Maradu Manurung Syafrika Deni Rizki Syahri Ramadhan Teuku Afriliansyah Tia Imandasari Titin Handayani Sinaga Tri Welanda Vasma Vitriani Sianipar Veithzal Rivai Zainal Venny Vidya utari Vitri Roma Sari Wida Prima Mustika Widodo Saputra Widya Tri Charisma Gultom Widyasuti, Meilin Widyasuti, Meilin Winanjaya, Riki Yuhandri Yuhandri, Yuhandri Yuli Andriani Yuri Widya Paranthy Zulaini Masruro Nasution Zulaini Masruro Nasution Zulaini Masruro Nasution Zulaini Masruro Nasution Zulia Almaida Siregar

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