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All Journal Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Electrical Technology IT JOURNAL RESEARCH AND DEVELOPMENT INTECOMS: Journal of Information Technology and Computer Science KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik dan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jurnal Sains dan Teknologi Community Engagement and Emergence Journal (CEEJ) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Darma Agung Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) International Journal Of Science, Technology & Management (IJSTM) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Bulletin of Information Technology (BIT) International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Jurnal Fokus Manajemen Jurnal Minfo Polgan (JMP) Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Nasional Teknologi Komputer Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Data Sciences Indonesia (DSI) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Best Journal of Administration and Management Bulletin of Engineering Science, Technology and Industry Jurnal Pengabdian Masyarakat Variasi The Journal of Information Technology, Computer Science, and Electrical Engineering
Sitorus, Zulham
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Framework Data-Driven Customer Analytics pada Sistem Informasi Reservasi dan Transaksi untuk Peningkatan Kinerja Barbershop Muhammad Hafizh Al-Ghifari Rangkuti; Septia Harliansyah; Solly Aryza; Zulham Sitorus
JET (Journal of Electrical Technology) Vol 11, No 1 (2026): EDISI FEBRUARI
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/jet.v11i1.13799

Abstract

Industri barbershop menghadapi tantangan dalam meningkatkan kualitas layanan dan efisiensi operasional seiring meningkatnya kebutuhan pelanggan terhadap layanan yang cepat, personal, dan berbasis digital. Sebagian besar sistem reservasi dan transaksi yang digunakan saat ini masih berfokus pada pencatatan operasional tanpa memanfaatkan data pelanggan sebagai sumber informasi strategis untuk mendukung pengambilan keputusan. Penelitian ini bertujuan untuk mengembangkan Framework Data-Driven Customer Analytics yang terintegrasi dengan sistem informasi reservasi dan transaksi guna meningkatkan kinerja operasional dan kualitas layanan pada usaha barbershop. Framework yang diusulkan memanfaatkan data reservasi, transaksi, frekuensi kunjungan, preferensi layanan, dan pola perilaku pelanggan untuk menghasilkan informasi analitik yang mendukung pengambilan keputusan berbasis data. Pengembangan sistem dilakukan menggunakan metode Waterfall yang meliputi analisis kebutuhan, perancangan framework, implementasi sistem, dan pengujian. Evaluasi sistem dilakukan melalui pengujian fungsional menggunakan Black Box Testing serta analisis kinerja berdasarkan indikator operasional dan layanan pelanggan. Hasil penelitian menunjukkan bahwa framework yang dikembangkan mampu mengintegrasikan data pelanggan secara efektif, menyediakan informasi analitik yang relevan bagi pengelola, meningkatkan efisiensi proses reservasi dan transaksi, serta mendukung penyusunan strategi layanan yang lebih tepat sasaran. Kontribusi penelitian ini terletak pada pengembangan model customer analytics berbasis data yang dapat dimanfaatkan sebagai dasar pengambilan keputusan untuk meningkatkan daya saing dan keberlanjutan bisnis barbershop di era transformasi digital. Kata Kunci: Customer Analytics, Data-Driven Framework, Sistem Informasi Reservasi, Sistem Transaksi, Barbershop, dan Pengambilan Keputusan Berbasis Data.
Empowering Teachers and Students through Machine Learning Training and Education on Personal Data Protection and Intellectual Property Rights in the Era of Artificial Intelligence MUHAMMAD SYAHPUTRA NOVELAN; ZULHAM SITORUS; AYUMI KARTIKA SARI
Jurnal Pengabdian Masyarakat Variasi Vol. 3 No. 2 (2026)
Publisher : LPPM STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/0dd5nt87

Abstract

The rapid advancement of Artificial Intelligence (AI), particularly Machine Learning (ML), has significantly transformed the educational sector by enabling the use of intelligent applications to support teaching and learning activities. However, the widespread adoption of AI also introduces new challenges related to personal data protection and intellectual property rights. This community service program aimed to improve the knowledge and competencies of teachers and students regarding the fundamentals of Machine Learning while enhancing awareness of ethical and lawful AI utilization. The program was conducted in the school's computer laboratory and involved teachers and students as participants. The implementation employed the Participatory Learning and Action (PLA) approach, including needs assessment, educational seminars, hands-on training, AI application demonstrations, practical exercises, interactive discussions, and evaluation through pre-tests and post-tests. The training materials covered Machine Learning concepts, AI applications in education, personal data protection, and intellectual property rights. The results demonstrated a significant improvement in participants' understanding of Machine Learning applications in education, the importance of protecting personal data, and respecting copyright and academic integrity. Participants also showed high enthusiasm throughout the training, indicating that the program successfully enhanced both digital literacy and legal awareness. This community service initiative is expected to serve as a sustainable educational model for promoting innovative, secure, ethical, and legally compliant AI adoption within educational institutions.
Penerapan Big Data dan Algoritma Machine Learning untuk Meningkatkan Efisiensi Proses Pelayanan Izin Usaha di DPMPTSP Kabupaten Tapanuli Selatan Rezkinah Rambe; Muhammad Syahputra Novelan; Zulham Sitorus
Bahasa Indonesia Vol 18 No 4 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i4.513

Abstract

Layanan perizinan usaha merupakan aspek penting dalam meningkatkan kualitas layanan publik dan mendukung iklim investasi daerah. Namun, proses perizinan usaha di DPMPTSP Kabupaten Tapanuli Selatan masih menghadapi berbagai tantangan, seperti waktu pemrosesan yang lama, kesalahan verifikasi, dan pemanfaatan data yang tersedia yang belum optimal. Penelitian ini bertujuan untuk menerapkan teknologi big data dan algoritma machine learning guna meningkatkan efisiensi proses perizinan usaha. Metode yang digunakan adalah pendekatan kuantitatif dengan teknik eksperimental, memanfaatkan dataset layanan perizinan usaha yang terdiri dari berbagai atribut seperti jenis izin, lokasi, waktu pemrosesan, dan status permohonan. Algoritma yang digunakan dalam penelitian ini adalah Random Forest, Naïve Bayes, dan kombinasi antara Random Forest dan Naïve Bayes, dengan evaluasi menggunakan matriks kebingungan serta metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa algoritma Random Forest menunjukkan kinerja terbaik, dengan akurasi 98,5%, presisi 98,57%, recall 98,5%, dan F1-score 98,51%. Sementara itu, Naïve Bayes menunjukkan kinerja terendah dengan akurasi sebesar 51%, dan kombinasi Random Forest dan Naïve Bayes menghasilkan akurasi sebesar 73%. Hal ini menunjukkan bahwa Random Forest lebih mampu menangani data yang kompleks dan menghasilkan prediksi yang lebih akurat dibandingkan dengan metode lainnya.
MEDAN SMART TOURISM INFORMATION SYSTEM BASED ON IOT AND ACO FOR ROUTE RECOMMENDATIONS AND VISITOR MANAGEMENT Septia Harliansyah; Muhammad Irfan Sarif; Zulham Sitorus; Eko Wahyudi; Khairul
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 12 (2025): NOVEMBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21415597

Abstract

The abstract serves as a concise summary of your research paper, highlighting the essential components that provide readers with an overview of your work. It should effectively capture the key issues addressed, the primary objectives of the study, the methods utilized, and the significant results achieved. This summary must be written in a single cohesive paragraph, limited to a maximum of 200 words. Ensure to follow the formatting specifications: use Times New Roman font, size 11, with single spacing, and present it in italics. The goal is to engage the reader while successfully conveying the importance and impact of your findings.
Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Tarif Pajak Penghasilan Di Oenity Hafiz Rodhiy; Zulham Sitorus
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.673

Abstract

Thel Oelnity tax consulting officel is onel of thel companiels that havel a lot of data on goods, data-data, and transaction data elvelry day. In gelnelral, thel Oelnity tax consulting officel only usels this data for relporting purposels only. Tax transaction data collelcteld and storeld can providel uselful knowleldgel for company managelmelnt in carrying out elfforts rellateld to tax increlasels, for elxamplel in telrms of deltelrmining tax financel stratelgiels and supporting delcisions for thel company. Consumelrs who apply for thel procelss of deltelrmining incomel tax ratels usually havel relasons why thely choosel a tax data calculation systelm from a tax consultant rathelr than managing it thelmsellvels. Belcausel tax consultants can providel what thely want, such as convelnielncel, accuracy, speleld, and nelatnelss of incomel tax calculations. Many consumelrs complain about thel incomel tax ratel calculation systelm, whelrel thel layout, making it difficult for consumelrs to gelt thel final tax relsults thely neleld, will also spelnd quitel a long timel just to find thel total incomel tax ratel. Thel Apriori algorithm is onel of thel most frelquelntly useld typels of data analysis in thel world of data procelssing. This analysis procelss is to analyzel thel numbelr of businelssels and thel amount of consumelr incomel by finding associations beltweleln lists of taxels that must bel paid. Thel Apriori algorithm is useld to arrangel itelm layouts and group itelms. From thel relsults of systelm implelmelntation, it was concludeld that using thel Apriori Algorithm melthod can hellp thel procelss of finding incomel tax ratels for elach consumelr data.
Implementasi Sistem Pendukung Keputusan dalam menentukan Kecamatan Terbaik Menggunakan Algoritma Entropy dan Additive Ratio Assessment (ARAS) Andi Ernawati; Ayu Ofta Sari; Siti Nurhaliza Sofyan; Ananda Aulia; Zulham Sitorus; Khairul
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1066

Abstract

In the context of regional development and decision making related to determining the best village, the use of a Decision Support System (DSS) with the application of the Entropy and Additive Ratio Assessment (ARAS) algorithms is a very important approach. The main objective of this research is to propose and implement a method that utilizes the Entropy algorithm to evaluate criteria weights and ARAS to rank villages based on predetermined criteria. This approach begins the process by identifying relevant criteria to determine the best village in an area. Next, the Entropy algorithm is used to measure the level of importance or relative weight of each predetermined criterion. This step helps in assessing how informative each criterion is in the decision-making process regarding determining the best Village. After determining the criteria weights using Entropy, the approach continues with the application of the ARAS method. ARAS is used to rank villages based on normalized values ​​from previously determined criteria. The data normalization process is carried out to ensure the validity of comparisons between villages. The final result of this approach is a ranking of villages indicating the best villages based on the criteria considered. This method was tested in a case study using a dataset involving a number of relevant criteria for assessing village development potential. Experimental results show that the use of the Entropy and ARAS algorithms in the Decision Support System provides an effective and informative framework for decision makers in determining the best Village. In conclusion, this approach provides a solid foundation to support a more effective and precise decision-making process in regional development based on clearly defined criteria.
Penerapan Metode Certainty Factor Pada Sistem Pakar Diagnosa Penyakit Gigi Dan Mulut Anzas Ibezato Zalukhu; Irwan Syahputra; Suhardiansyah; Zulham Sitorus; Khairul
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1102

Abstract

Gigi dan mulut merupakan organ vital yang memainkan peran penting dalam menjaga kesehatan manusia. Kelainan pada gigi dan mulut dapat menjadi pemicu penyakit lain dalam tubuh. Pentingnya menjaga kesehatan gigi dan mulut ditekankan, terutama mengingat fungsinya yang esensial dalam berbicara, menjaga bentuk wajah, dan mengunyah makanan. Sayangnya, dengan perkembangan zaman, pola makan yang tidak sehat, seperti konsumsi makanan siap saji tinggi gula, garam, dan lemak, dapat menyebabkan masalah kesehatan gigi dan mulut. Penyakit gigi dan mulut sering disebabkan oleh mikroorganisme, dan pengetahuan terbatas tentang gejala-gejala penyakit ini dapat menjadi hambatan untuk diagnosis dini. Sebagai solusi, penelitian ini mengusulkan penerapan metode certainty factor dalam sistem pakar untuk mendiagnosis penyakit gigi dan mulut. Metode ini memungkinkan evaluasi tingkat keyakinan pakar terhadap data yang dianalisis, memberikan solusi atau rekomendasi dalam situasi kompleks. Penelitian ini mengacu pada pandangan pakar dokter gigi dan mulut, yang dianggap memiliki pengetahuan dan pengalaman yang mencukupi. Sistem pakar yang diusulkan bertujuan untuk meniru proses penalaran seorang pakar dalam memecahkan masalah spesifik dalam bidang gigi dan mulut. Dengan memanfaatkan certainty factor, sistem ini dapat menyediakan solusi yang lebih dapat diandalkan dan memberikan kontribusi pada upaya pencegahan serta penanganan dini penyakit gigi dan mulut.
Penerapan Data Mining Untuk Klasifikasi Penduduk Miskin Di Kabupaten Labuhanbatu Menggunakan Random Forest Dan K-Nearest Neighbors Andi Ernawati; Khairul; Zulham Sitorus; Muhammad Iqbal; Darmeli Nasution
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1783

Abstract

This study aims to apply and compare the performance of two data mining algorithms—Random Forest (RF) and K-Nearest Neighbors (KNN)—in classifying poverty status among residents of Labuhanbatu Regency. The dataset includes information on occupation, income, housing, and education from 21,137 individuals. After undergoing preprocessing, model training, hyperparameter optimization, and evaluation, both models were assessed using five key metrics: accuracy, precision, recall, F1-score, and AUC. The results show that Random Forest performed slightly better than KNN, achieving an accuracy of 0.6023, precision of 0.4827, recall of 0.4177, F1-score of 0.4479, and an AUC of 0.5681. In comparison, KNN obtained an accuracy of 0.5990, precision of 0.4771, recall of 0.4006, F1-score of 0.4355, and an AUC of 0.5622. Based on these findings, it can be concluded that Random Forest is more effective for poverty classification on this dataset, although the performance difference is relatively small.
Analisis Sentimen Penerapan Deep Learning dan Analisis Sentimen terhadap Gap Kompetensi Lulusan Lembaga Pendidikan dan Pelatihan Vokasi terhadap Dunia Kerja dengan Metode Long Short-Term Memory (LSTM) Susilawati Yahya; Zulham Sitorus; Muhammad Iqbal; Darmeli Nasution; Rian Farta Wijaya
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2031

Abstract

The gap between vocational graduates’ competencies and labor market demands remains a pressing issue in Indonesia. This study aims to analyze alumni perceptions regarding the alignment between competencies acquired during their studies at LP3I Banda Aceh and real-world job requirements. A quantitative approach was adopted using a deep learning method based on Long Short-Term Memory (LSTM). Data were collected through an online survey containing open-ended responses from 934 alumni, followed by preprocessing, tokenization, lexicon-based sentiment labeling, and data splitting into training and testing sets. The models developed included pure LSTM, LSTM with class weights, and Bidirectional LSTM (BiLSTM). Results indicate that BiLSTM achieved the highest performance with 90% accuracy and a weighted F1-score of 0.91. Additionally, 44.5% of respondents expressed neutral or negative sentiments, highlighting a mismatch between acquired competencies and industry demands. These findings underscore the urgency of curriculum evaluation and stronger collaboration between vocational institutions and the labor market. This study demonstrates that deep learning offers an efficient and objective tool for competency mapping in vocational education.
The Influence of the Talented Generation Internship Program (Magenta) on Human Resource Management Readiness At the Port of Indonesia (Persero) I Medan Hendra Utama; Mohammad Yusuf; Zulham Sitorus; Pebri Ramadani
Best Journal of Administration and Management Vol 2 No 4 (2024): Best Journal of Administration and Management
Publisher : International Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56403/bejam.v2i4.182

Abstract

PT Pelabuhan Indonesia (Persero) or Pelindo is a state-owned company which operates in the port services sector which provides opportunities for vocational/equivalent students, college students and fresh graduates to carry out internships in their environment. During the selection process, it was discovered that several of the interns accepted were interns who already had organizational experience. In carrying out an internship, interns not only help carry out supervisor/mentor duties, but interns are also helped to explore and improve their existing competencies so that they are better prepared to face the real world of work. This research aims to determine the influence of organizational experience and internship experience on work readiness of interns. This research uses quantitative research methods in the form of correlational research and explanatory research models, as well as collecting data through distributing questionnaires to interns at PT Pelabuhan Indonesia (Persero) I Medan. In processing the data, researchers used partial test methods and simultaneous tests for the variables organizational experience, internship experience, and work readiness with the help of SPSS version 26. The results of the study showed that organizational experience had a positive and significant effect on work readiness, internship experience had a positive and significant effect on work readiness, organizational experience and internship experience simultaneously influence work readiness
Co-Authors , Arpan , Fery Anugerah A.A. Ketut Agung Cahyawan W Abda Abda Abdul Razaq Ade Alma Yuni Ade Guna Suteja Ade Surya Bakti Pane Aditya Ramadhani Afrizal, Henri Afrizal, Sandi Aldi Kesuma Alvian Alvian Alviona Marsya Ami Abdul Jabar Ami Abdul Jabar Amnisuhaila Abarahan Ananda Aulia Ananda Aulia Andi Ernawati Andi Ernawati Andi Ernawati Andysah Putera Utama Siahaan Angkat, Chairul Indra Anshari, Ari Antoni, Robin Anzas Ibezato Zalukhu Ardya, Dwika Arief, Muhammad Arif Rahman Astri Mutia Rahma Aulia, Ananda Ayu Ofta Ayu Ofta Sari Ayumi Kartika Sari azwan, m Baehaqi Bambang Sugito Bambang Sugito Batubara, Supina Boy Rizki Akbar Boy Rizki Akbar Br Tarigan, Sella Monika Chelfina Utami Chelfina Utami Daniel Happy Putra Danu Wardhana Azhari Darmeli Nasution Desy Ramatika DEWI SARTIKA Dhimas Prayogi diansyah, Suhar Didi Riswan`` Diva, Krisna Dwina Pri Indini Eko Hariyanto Eko Hariyanto Eko Hariyanto Eko Wahyudi Erbin Sitorus Fachri, Barany Fahmi Izhari Fahmi Kurniawan Fajar Aulia Lubis Feby Wulandari Sembirinng Fery Anugerah Fikri Zuhaili Simbolon Gilang Ramadhan Gultom, Ananda Christianto Hafiz Rodhiy Haliza, Siti Nur Hamzah, Iswadi Harmiati Bungsu Bangun Hartono Sinambela, Sugi Helmy, Ahmad Hendra Harnanda Hendra Utama Heni Wulandari Heri Eko Rahmadi Putra Heri Kurniawan Hilal Prayogi Hindra Syahputra Hrp, Abdul Chaidir Ibezato Zalukhu, Anzas Ibrahim Ika Devi Perwitasari Indra Angkat, Chairul IQBAL , MUHAMMAD Irwan Syahputra Irwan Syahputra, Irwan Josua M.H Simaremare Khairul Khairul Khairul Khairul, Khairul Kiki Artika Kurniawan, Fahmi Laila Maghfirah Laila Maghfirah Larius Ambasador Parlindungan Leni Marlina Leni Marlina Lia Nazliana Nasution Limbong, Yohannes France M Imam Santoso M. Azhari Rizko M. Rasyid M.Rizki Khadafi Maida Indrayani Mardiah, Nia Marzuki Sianturi, Ismail Maulian Saputra Meiarni Situkkir Melva Sari Panjaitan Meri Sri Wahyuni Mhd Arfan Sitorus Mhd Arie Akbar Mhd Ihsan Abidi Mohammad Yusuf Mohammad Yusuf, Mohammad Muhammad Fahriza Muhammad Fahriza Muhammad Hafizh Al-Ghifari Rangkuti Muhammad Iqbal Muhammad Iqbal Muhammad Irfan Sarif Muhammad Raihan Harahap Muhammad Syahputra Novelan Muhammad Wahyudi Nahampun, Natalia Nainggolan, Andreas Ghanneson Nainggolan, Irfan Nazar Saputra, Risfan Nelviony Parhusip Nurwijayanti Oktavia Tumangger Parhusip, Nelviony Pasaribu, Ryan Fahreza Pebri Ramadani Pranoto, Sugeng Putra, Khairil Ragil Satya Adi W Rahima Br Purba Rahmat Hidayat Rahmat Hidayat Raihan Risky Ramadani, Pebri Ramadhan, Aditya Ramadhani, Aditya Ramli S Siburian Rangga Rafandi Razaq, Abdul Retno Mutiara Rezkinah Rambe Rian Farta Wijaya Rian Farta Wijaya Rian Putra, Randi Rika Uli Samosir, Siska Risky, Raihan Robin Antoni Rowiyah Asengbaramae Rusydi Tanjung , Miftah Ryan Fahreza Pasaribu Sahputra, Fajar Said Oktaviandi Sarifuddin Septia Harliansyah Septiani, Nadya Sianturi, Ismail Sibarani, Dina Marsauli Simamora, Siska Simorangkir, Elsya Sabrina Asmita Sinambela, Sugi Hartono Sinyo Andika Nasution, Ahmad Sipra Barutu Sipra Barutu Siregar, Andree Risky Yuliansyah Sitepu, Fernando Siti Nurhaliza Sofyan Siti Nurhaliza Sofyan Sitinur, Siti Nurhaliza Sofyan Sitompul, Jelly Rolley Sofyan, Siti Nurhaliza Solahuddin Asri Ritonga Solly Ariza Solly Ariza Lubis Solly Aryza Sri Wahyuni, Meri Sugeng Pranoto Suhardiansyah Suhardiansyah Suhardiansyah Suherman Suherman Sukrianto, Sukrianto Sulis Sutiono Susilawati Yahya Sutiono, Sulis Syahputri, Maulisa Syamsiar, Syamsiar T, Siti Isna Syahri Tanjung, Miftah Rusydi Tiara Aninditha Utama, Hendra Vina Arnita Vivin Yulfia Sarah Wahyu Agung Pratama Wahyuni, Meri Sri Wijaya, Rian Farta Wirda Fitriani Yasri, Afif Yulianus Zai Zulfahmi Syahputera Zulfahmi Syahputra Zulfahmi Zulfahmi Zulfahmi Zulfahmi