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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 ILKOMEDIA: Jurnal Ilmu Komputer dan Multimedia

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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Artificial Neural Network Predicts Motorcycle Sales Level Using Back-propagation Method Reza Pratama; Poningsih Poningsih; Anjar Wanto
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Motorcycles are everyone's choice as a means of transportation because they are affordable and can be used for a long time. The high level of motorcycle sales made CV Apollo Motor dealers experience difficulties in procuring motorcycle variants to be sold. The large number of motorcycle variants in one manufacturer makes sales different for each of these variants; there are variants with high and low sales. Therefore predictions about this matter are essential as information material for the company. Input data was obtained from CV Apollo Siantar from 2018 to 2022 as a sales prediction target consisting of 10 data based on Honda motorcycles. Each data has seven variables and one target. This data will later be transformed into data between 0 to 1 before training and testing are carried out using the Back-propagation algorithm artificial neural network. This study uses the back-propagation algorithm. Based on the analysis results, the best architectural model is 7-3-5-1 because it has the highest level of accuracy compared to other models, which is 100%. MSE Testing of 0.08501.

Pemanfaatan Algoritma BFGS Quasi-Newton untuk Melihat Potensi Perkembangan Luas Tanaman Kopi di Pulau Sumatera Safruddin Safruddin; Elfin Efendi; Rita Mawarni; Anjar Wanto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5524

Coffee is one of Indonesia's essential export commodities and a foreign exchange source for the country. One crucial factor in coffee production development is the planted land area. Therefore, the availability of land for coffee plants in Indonesia needs to be maintained for the continuity of coffee production today and in the future. This study aimed to see the potential for the widespread development of coffee plants on the island of Sumatra. This is because the island of Sumatra is the largest coffee producer in Indonesia, so information about the potential for the development of this plant area needs to be known as early as possible, especially for the agriculture/plantation service and for coffee farmers, so that coffee production can be maintained. The algorithm proposed in this study is the Broyden Fletcher Goldfarb Shanno (BFGS) Quasi-Newton algorithm which can be used to solve data prediction (forecasting) problems. This study uses a dataset of coffee plant areas sourced from the Directorate General of Plantations for 2012-2021. This study was analyzed using 3 (three) network architecture models (4-9-1, 4-18-1, and 4-27-1). Based on the analysis, the results obtained from model 4-18-1 as the best architecture with 100% accuracy with minor MSE testing, which is 0.00036764820. Meanwhile, based on predictions made using the best architecture (predictions for 2022 and 2023), the area of coffee plantations has decreased slightly. So this needs serious attention from the respective provincial governments.

Pengelompokkan Produksi Tanaman Jagung di Sumatera Utara Menggunakan Algoritma K-Medoids Safruddin Safruddin; Joni Wilson Sitopu; Azwar Anas Manurung; Indra Satria; Anjar Wanto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5562

Corn is a strategic commodity with bright marketing prospects, especially in North Sumatra. Therefore efforts to increase corn production need great attention because, with sufficient availability, it is hoped that the community's need for corn can be fulfilled and the selling price remains stable. This study aims to classify corn production in North Sumatra based on districts/cities so that districts/cities can be identified and developed into corn production centers to reduce food imports, specifically corn crops. This research uses a corn production dataset based on districts/cities in North Sumatra consisting of 25 regencies and eight cities in 2019-2021 obtained from the Food Crops and Horticulture Service of North Sumatra Province. The algorithm used is the K-Medoids algorithm with Rapid Miner Studio tools. The results of this study were grouping corn production which was divided into 5 (five) groups, including Group 1 was an area with very high corn production consisting of 1 Regency, Group 2 was an area with high corn production consisting of 2 Regencies, Group 3 was an area with moderate corn production consisting of 4 regencies, Group 4 is an area with low corn production consisting of 3 regencies, and Group 5 is an area with very low corn production consisting of 15 regencies and seven cities. Based on these results, Karo, Dairi, and Simalungun districts can be used as centers for corn production in North Sumatra because these three districts alone produce corn production of 65.7% of the total corn production in North Sumatra.

Penerapan Algoritma Decision Tree C4.5 untuk Klasifikasi Tingkat Kesejahteraan Keluarga pada Desa Tiga Dolok Susi Fitryah Damanik; Anjar Wanto; Indra Gunawan
Jurnal Krisnadana Vol 1 No 2 (2022): Jurnal Krisnadana - Januari 2022
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Klasifikasi tingkat kesejahteraan keluarga di Desa Tiga Dolok merupakan permasalahan yang dialami Masyarakat di desa itu. Dimana klasifikasi Tingkat kesejahteraan keluarga di Desa tersebut belum sepenuhnya akurat sehinga mengakibatkan penyaluran subsidi pemerintah tidak tepat sasaran. Permasalahan klasifikasi tingkat kesejahteraan menjadi tujuan dilakukannya penelitian agar mendapatkan hasil yang akurat dalam status tingkat kesejahteraan keluarga. Untuk mengatasi masalah tersebut diusulkan model baru dengan memanfaatkan sebuah metode komputasi C4.5 agar menghasilkan klasifikasi tingkat kesejahteraan yang akurat. Pada penelitian ini algoritma yang digunakan untuk melakukan klasifikasi tingkat kesejahteraan pada Desa Tiga Dolok adalah algoritma C4.5. Algoritma ini dipilih karena proses klasifikasinya sederhana dan cepat. Data penelitian yang digunakan nantinya adalah Data Isian Dasar Keluarga Desa Tiga Dolok Tahun 2019. Sumber data diperoleh berdasarkan kuisioner yang dibagikan kepada masyarakat Tiga Dolok. Berdasarkan data ini akan dilakukan klasifikasi tingkat kesejahteraan dengan menggunakan aplikasi rapid miner. Dengan metode ini akan dibentuk pohon keputusan agar nantinya mendapatkan hasil klasifikasi yang diinginkan.

Utilization of the ELECTRE and SMART Algorithms for Determining the Head of Administration for the Gunung Maligas Sub-District Office Fajar Ramadan; Rahmat W. Sembiring; Anjar Wanto
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1932

This study aims to apply the ELECTRE (Elimination and Choice Expressing Reality) and SMART (Simple Multi-Attribute Rating Technique) algorithms in determining the administrative head of the Gunung Maligas sub-district office. The head of administration is an important position in a government organization responsible for managing various administrative and coordinating activities. The ELECTRE method produces an alternative ranking of administrative head candidates based on multiple relevant attributes. Work experience, communication skills, organizational knowledge, and leadership skills are considered. The SMART method assigns weights to each point and combines attribute values to produce an overall score for each candidate. The data in this study were obtained through surveys and interviews with related parties. After the data is collected, an analysis process is carried out using the ELECTRE and SMART algorithms to produce a ranking of candidates that best suit the needs of the Gunung Maligas sub-district office. The results of this study are expected to provide objective and accurate recommendations for selecting qualified administrative heads. By using the ELECTRE and SMART algorithm approaches, the process of determining the executive authority can be more efficient and effective and help improve managerial performance and coordination at the Gunung Maligas sub-district office.

Algoritma Machine Learning untuk penentuan Model Prediksi Produksi Telur Ayam Petelur di Sumatera Ihsan Maulana Muhamad; Sigit Anugerah Wardana; Anjar Wanto; Agus Perdana Windarto
Journal of Informatics, Electrical and Electronics Engineering Vol. 1 No. 4 (2022): Juni 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

Laying hens eggs are one of the livestock commodities that make a very large contribution to the supply of eggs as a community need. Therefore, it is necessary to predict the egg production of laying hens in the future so that in the future the need for eggs in Indonesia is stable and can meet the demands of the Indonesian people. The method used in this research is a machine learning algorithm, namely Polak-Ribiere which is one of the artificial neural network methods that is often used to predict data. This study does not discuss the prediction results, but will discuss the ability of the Machine Learning algorithm to make predictions based on the egg production dataset of laying hens obtained from the Central Statistics Agency. The research data used is data on the production of laying hens in Sumatra from 2015-2020. Based on this data, network architecture models will be determined, including 4-5-1, 4-10-1, 4-15-1, 4-20-1, and 4-25-1. Of the five models, training and testing were carried out first and then obtained the results that the best architectural model was 4-25-1 with 0.03144841, the lowest among the other 4 models. So it can be concluded that the model can be used to predict the egg production of laying hens.

Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World Sunil Setti; Anjar Wanto
JOIN (Jurnal Online Informatika) Vol 3 No 2 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i2.205

The Internet today has become a primary need for its users. According to market research company e-Marketer, there are 25 countries with the largest internet users in the world. Indonesia is in the sixth position with a total of 112.6 million internet users. With the increasing number of internet users are expected to help improve the economy and also education in a country. To be able to increase the number of internet users, especially in Indonesia, it is necessary to predict for the coming years so that the government can provide adequate facilities and pre-facilities in order to balance the growth of internet users and as a precautionary step when there is a decrease in the number of internet users. The data used in this study focus on data on the number of internet users in 25 countries in 2013-2017. The algorithm used is Artificial Neural Network Backpropagation. Data analysis was processed by Artificial Neural Network using Matlab R2011b (7.13). This study uses 5 architectural models. The best network architecture generated is 3-50-1 with an accuracy of 92% and the Mean Squared Error (MSE) is 0.00151674.

A Comprehensive Bibliometric Analysis of Deep Learning Techniques for Breast Cancer Segmentation: Trends and Topic Exploration (2019-2023) Agus Perdana Windarto; Anjar Wanto; S Solikhun; Ronal Watrianthos
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5274

The objective of this study is to perform a comprehensive bibliometric analysis of the existing literature on breast cancer segmentation using deep learning techniques. Data for this analysis were obtained from the Web of Science Core Collection (WOS-CC) that spans from 2019 to 2023. The study is based on a comprehensive collection of 985 documents that cover a substantial body of research findings related to the application of deep learning techniques in segmenting breast cancer images. The analysis reveals an annual increase in the number of published works at a rate of 16.69%, indicating a consistent and robust increase in research efforts during the specified time frame. Examining the occurrence of keywords from 2019 to 2023, it is evident that the term "convolutional neural network" exhibited a notable frequency, reaching its peak in 2021. However, the term "machine learning" demonstrated the highest overall frequency, peaking around 2021 as well. This emphasizes the importance of machine learning in the advancement of image segmentation algorithms and convolutional neural networks, which have shown exceptional effectiveness in image analysis tasks. Furthermore, the utilization of latent Dirichlet Allocation (LDA) to identify topics resulted in a relatively uniform distribution, with each topic having an equivalent number of abstracts. This indicates that the data set encompasses a diverse range of topics within the field of deep learning as it relates to breast cancer image segmentation. However, it should be noted that topic 4 has the highest level of significance, suggesting that the application of deep learning for diagnosis was extensively explored in this study.

Model Prediksi Algoritma ANN Pada Jumlah Ekspor Barang Perhiasan Dan Berharga Menurut Negara Tujuan Arifah Hanum; Tri Welanda; Anjar Wanto; Agus Perdana Windarto
TIN: Terapan Informatika Nusantara Vol 3 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v3i1.1773

Currently Indonesia is one of the exporting countries to industrialized and developing countries. The methods carried out in the research of the prediction of the export of jewelry and valuables from this main destination country use the ANN (Artificial Neural Network) method. The research data used comes from the official website of the government, the Indonesian Central Statistics Agency. In this study, the data used is data from 2013 to 2020 consisting of 8 destination countries, namely Switzerland, Singapore, Hong Kong, United Arab Emirates, South Africa, Taiwan, the United States, and India. Based on this data can be determined network architecture model, namely 3 - 4 - 1, 3 - 8 - 1, 3 - 12 - 1, 3 - 16 - 1 and 3 - 20 - 1. After training and testing of the 5 models, it can be obtained that the best architectural model is on the 3-12-1 model with an MSE value of 0.033777975 on the ANN method

Pelatihan Pembuatan Pin Press Digital Bagi Siswa untuk Meningkatkan Keterampilan dan Menumbuhkan Semangat Wirausaha Achmad Daengs GS; Rizky Khairunnisa Sormin; Zulia Almaida Siregar; Riki Winanjaya; Anjar Wanto
JPM: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023): October 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v4i2.1326

This PKM activity aims to develop the skills of Vocational High School (SMK) students in making digital pin presses through special training. Technology and mechanical skills are becoming increasingly important in today's digital era, and vocational schools have a key role in preparing students for the ever-changing world of work. The training was carried out at the Anak Bangsa Private Vocational School located in Simalungun Regency. In this activity, we designed and implemented intensive training for vocational school students on making digital pin presses. This training includes a basic understanding of digital technology, use of relevant hardware and software, as well as technical skills required in the manufacturing process. Apart from that, the team leader also provided material about the entrepreneurial spirit which was carried out using the Zoom application. The training method involves practical teaching and guidance from experienced instructors. The results of the activity show that this training was successful in improving students' skills in making digital pin presses. In addition, students also demonstrated improvements in their understanding of digital technology and its potential use in the world of work. It is hoped that this activity can make a positive contribution to developing the skills of vocational school students and help them prepare to enter an increasingly competitive job market. The results of this training can be used as a basis for developing similar training in other vocational schools and can be a reference for educational institutions and the government in efforts to improve the quality of vocational education in Indonesia.

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 Hutapea, Isniar Yaskinah 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 Salsabila, Sophia 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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