Article Per Year (5 Year)
p-Index From 2021 - 2026
9.606
P-Index
This Author published in this journals
All Journal Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JET (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 Jurnal Media Informatika 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 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
Sitorus, Zulham
UNIVERSITAS PEMBANGUNAN PANCA BUDI
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 81 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 81 Documents
Search

 1   2   3   4   5 
Implementation of K-Means Clustering for Inventory Projection Sitorus, Zulham; Syahputra, Irwan; Indra Angkat, Chairul; Sartika, Dewi
International Journal of Science, Technology & Management Vol. 5 No. 3 (2024): May 2024
Publisher : Publisher Cv. Inara Colaboration with www.stie-sampit.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i3.856

Abstract

Inventory forecasting is crucial in effective supply chain management and cost reduction. However, traditional forecasting techniques face significant challenges due to the complexity and variability of demand patterns. This study explores the use of K-means clustering, a data-driven approach that can improve inventory forecasting accuracy. By grouping inventory items based on their unique demand profiles, we can create personalized forecasting models for each cluster. This technique enhances demand estimation, helping businesses make informed decisions and optimize their inventory. Our research delves into the use of K-means clustering to identify patterns and similarities within historical demand data. This clustering process divides inventory items into groups with similar demand characteristics. By applying specific forecasting models to each cluster, we achieve greater precision in our predictions. The proposed methodology is rigorously evaluated using real-world inventory datasets, and the results demonstrate its significant superiority in forecasting accuracy compared to conventional non-clustered methods. This study offers compelling evidence and valuable insights for practitioners seeking to improve their inventory management practices through data-driven techniques.
Analysis Of Indonesian People's Sentiment Towards 2024 Presidential Candidates On Social Media Using Naïve Bayes Classifier and Support Vector Machine Mardiah, Nia; Marlina, Leni; Khairul, Khairul; Sitorus, Zulham; Iqbal, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5766

Abstract

This research aims to analyze the sentiment of the Indonesian public towards the 2024 presidential candidates on social media platforms X and Instagram. The main issue addressed is how to determine public opinion as disseminated on social media regarding the presidential candidates. To address this issue, two classification methods are used: Naïve Bayes Classifier and Support Vector Machine (SVM). The objective of this research is to measure public sentiment, both positive and negative, towards the 2024 presidential candidates using these two methods. The research findings indicate that the implementation of the Naïve Bayes method with manual labeling achieved the highest accuracy of 86% for X data and 85% for Instagram comments data. Meanwhile, with lexicon-based labeling, the highest accuracy was 60% for both X and Instagram data. The SVM method with manual labeling also achieved the highest accuracy of 86% for X data and 85% for Instagram data. With lexicon-based labeling, the highest accuracy was 60% for X data and 70% for Instagram data. This research concludes that both Naïve Bayes and SVM demonstrate strong performance in sentiment analysis on social media, with SVM slightly outperforming in some scenarios. The implementation of these two methods provides valuable insights into public opinion towards the 2024 presidential candidates on social media.
Pemanfaatan Teknologi Virtual Reality (VR) Dalam Pembelajaran Pada Lembaga Kursus Dan Pelatihan Rumah Tik Labuhanbatu Ernawati, Andi; Sitorus, Zulham; Wijaya, Rian Farta; Aulia, Ananda; Siregar, Andree Risky Yuliansyah; Sofyan, Siti Nurhaliza
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 4 No. 1 (2024): Januari 2024
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/jpmg.v4i1.152

Abstract

Learning using technology continues to develop along with developments in technology itself. One technology that is increasingly being used in learning is virtual reality (VR). Virtual Reality is a technology that produces a digital environment that resembles the real world and allows users to interact with that environment. Including in Labuhanbatu Regency, where virtual reality media has been used as a learning medium. However, if we observe that the use of virtual reality as a learning medium has not been distributed thoroughly to every level of student, only the student level can access learning using virtual reality. And if we look more deeply, the virtual reality media content that is presented is able to improve the quality of student learning for each level because virtual reality media will really help improve the imagination and mindset of students at all levels to become more effective and efficient. In Labuhanbatu Regency there are many course and training institutions, judging from the area and the number of course and training institutions in Labuhanbatu Regency, the introduction of virtual reality learning media in Labuhanbatu Regency should be managed generally for all levels of students as a basis for community service activities (PKM). . This activity aims to provide training to students in Labuhanbatu Regency about learning methods using virtual reality technology through videos on cellphones using the Millea Lab Viewer application and VR Player with a virtual box device. Activities carried out focus on introducing and training virtual reality for learning. The methods used include training for students at all levels at the Labuhanbatu Tik House course and training institution regarding the features and concepts of virtual reality, the goals, benefits and practices of using virtual reality. After attending the training, students at the Tik Labuhabatu home course and training institution experienced an increase in their knowledge about virtual reality, as well as their ability to improve the quality and creative imagination in learning virtual reality media content in Labuhanbatu Regency Keywords: virtual reality; learning; content, lkprumahtik, Labuhanbatu
Enhancing Text Messages with a Combination of Vigenère Cipher and One Time Pad Using Random Key LFSR Ibezato Zalukhu, Anzas; Sitorus, Zulham; Suhardiansyah, Suhardiansyah; Septiani, Nadya
Jurnal Sains dan Teknologi Vol. 6 No. 1 (2024): Jurnal Sains dan Teknologi
Publisher : CV. Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/saintek.v6i1.3190

Abstract

In today's global era, the development of information systems is rapidly advancing and becoming increasingly sophisticated, with nearly all elements utilizing information and communication technology in their daily activities. One frequent activity is the transmission or exchange of data over the internet. However, this advancement also raises concerns about the security of messages or data being sent. To mitigate the risk of message misuse, cryptographic techniques can be used to maintain data or message confidentiality by encrypting the information before transmission. This research aims to combine the Vigenère cipher algorithm with a one-time pad using a random key generated by a linear feedback shift register (LFSR) method to enhance the security of text messages. The research methodology involves generating a public key for the One-Time Pad algorithm using LFSR. The encryption process is initially performed with the Vigenère cipher, and the resulting encrypted message is further encrypted using the one-time pad with a key generated by the LFSR method. This algorithm is implemented using the Visual Basic programming language. The research findings indicate that the combination of the two algorithms, with the random key generated by the LFSR for the One-Time Pad, is capable of enhancing text message security by producing random and unique ciphertexts. By using Modulo 256 and ASCII conversion, random ciphertexts can be generated, thereby reducing the likelihood of message breaches. Additionally, this research provides further insights into the process of text message encryption and decryption.
Comparison of K-Means and Self Organizing Map Algorithms for Ground Acceleration Clustering Simamora, Siska; Muhammad Iqbal; Andysah Putera Utama Siahaan; Khairul, Khairul; Zulham Sitorus
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14120

Abstract

This study evaluates earthquake-induced ground acceleration in Indonesia, which is located in the Pacific Ring of Fire zone, using Donovan's empirical method and comparing two clustering algorithms, Self Organizing Map (SOM) and K-Means. The main problem faced is the high risk of earthquakes in Indonesia and the need for effective methods to predict potential damage to buildings and infrastructure. The research objective is to evaluate earthquake-induced ground acceleration and identify acceleration distribution patterns using clustering techniques. The solution methods used include the application of the Donovan method to calculate ground acceleration based on BMKG data, as well as the use of SOM and K-Means algorithms to cluster the ground acceleration data. GIS and Python applications are used to visualize the clustering results. The results show that the Donovan method integrated with SOM and K-Means provides significant insights into the distribution of ground acceleration, thus assisting in risk evaluation, disaster mitigation planning, and the development of more effective earthquake-resistant infrastructure development strategies in Indonesia
Implementasi Sistem Pendukung Keputusan dalam menentukan Kecamatan Terbaik Menggunakan Algoritma Entropy dan Additive Ratio Assessment (ARAS) Ernawati, Andi; Ofta Sari, Ayu; Sofyan, Siti Nurhaliza; Aulia, Ananda; Sitorus, Zulham; 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 Zalukhu, Anzas Ibezato; Irwan Syahputra; Suhardiansyah; Sitorus, Zulham; 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.
Deteksi Outlier Hasil Clustering Algoritma K-Medoids Menggunakan Metode Boxplot Pada Data KIP Kuliah Simorangkir, Elsya Sabrina Asmita; Siahaan, Andysah Putera Utama; Marlina, Leni; Nasution, Darmeli; Sitorus, Zulham
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5479

Abstract

In the process of forming clusters with the K-Medoids algorithm, cluster result anomalies often occur, such as outliers. This value appears as a revelation in existing data patterns. Outliers occur due to measurement errors, rare events, or due to other unexpected factors. In this research, the dataset used is data on prospective KIP recipient students at Budi Darma University, where there is a high level of interest in KIP Kuliah while the quota is limited, which means that KIP Kuliah administrators sometimes have difficulty determining which students are eligible to receive KIP Kuliah. For this reason, the K-Medoids clustering technique was used to cluster data on 54 prospective students who were eligible to receive KIP Kuliah Merdeka and those who were not eligible. From the cluster results, outlier detection was carried out using the box plot method with the aim of finding out whether each cluster member was actually in the appropriate cluster or not. The result is that the data cluster is divided into 2 (K-2). In the max min centroid selection, cluster I consists of 52 members and cluster II consists of 2 members, where the outlier data consists of 3 data, while in random centroid selection (python), cluster I consists of 36 members and cluster II 18 members with data The outlier consists of 4 members. The accuracy of the clustering results between max min and random centroid selection has an accuracy of 64.81%, and the outlier accuracy is 75%.
Komparasi Model Rating Factor Dan Vikor Dalam Pengambilan Keputusan Peluang Usaha Industri Percetakan: Komparasi Model Rating Factor Dan Vikor Dalam Pengambilan Keputusan Peluang Usaha Industri Percetakan Sinyo Andika Nasution, Ahmad; Rian Farta Wijaya; Andysah Putera Utama Siahaan; Muhammad Iqbal; Zulham Sitorus
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 2 (2024): Agustus 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i2.10306

Abstract

Penelitian ini bertujuan untuk mengoptimalkan pengambilan keputusan bisnis di industri percetakan melalui komparasi Model Rating Factor dan metode VIKOR. Industri percetakan menghadapi berbagai tantangan dalam pengambilan keputusan yang kompleks. Model Rating Factor untuk mengidentifikasi faktor-faktor kritis yang mempengaruhi kinerja bisnis percetakan. Faktor-faktor ini kemudian dianalisis dan diberi bobot sesuai dengan tingkat kepentingannya, memberikan dasar yang kuat untuk evaluasi lebih lanjut. Pendekatan multi-kriteria metode VIKOR diterapkan untuk mengintegrasikan berbagai faktor yang telah diidentifikasi dan diberi bobot melalui Model Rating Factor . Metode VIKOR membantu dalam mengatasi konflik antara kriteria yang berbeda dan menghasilkan solusi kompromi yang optimal. Dengan menggabungkan kedua pendekatan ini, penelitian ini menyediakan kerangka kerja yang terstruktur dan sistematis untuk mendukung pengambilan keputusan yang lebih efektif di industri percetakan.Hasil penelitian menunjukkan bahwa penggunaan Model Rating Factor dan metode VIKOR dapat meningkatkan kualitas pengambilan keputusan dengan memberikan panduan yang lebih jelas dalam mengevaluasi dan memilih alternatif keputusan. Sehingga meningkatkan efisiensi operasional dan penggunaan sumber daya secara optimal. Komparasi antara kedua metode menunjukkan bahwa Model Rating Factor unggul dalam penilaian faktor individual, memberikan wawasan mendalam mengenai pengaruh setiap faktor. Di sisi lain, metode VIKOR lebih efektif dalam mengintegrasikan berbagai kriteria dan memberikan solusi yang lebih holistik. Dengan demikian, kombinasi kedua metode ini memberikan kerangka kerja yang lebih kuat dan komprehensif untuk mendukung pengambilan keputusan yang lebih baik dan cepat
Analysis of the Automated Sorting and Counting System for Tilapia Fry Based on Quantity, Size, and Gender Nazar saputra, Risfan; Sitorus, Zulham; Wahyudi, Muhammad; Rusydi Tanjung , Miftah
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.232

Abstract

This research addresses the challenges in aquaculture, specifically in the cultivation of Tilapia in brackish water. The study focuses on enhancing the efficiency and accuracy of sorting and counting fish fry, a factor that significantly influences the profitability of cultivators. An automated sorting and counting system is proposed, capable of categorizing Tilapia fry based on their quantity, size, and gender. This system employs sensors and a microcontroller, such as Arduino, to process the gathered information and control the sorting mechanism. The sorted and counted fry are subsequently separated into different compartments for easy collection and further cultivation. The data collected by the system can be displayed on an LCD screen or stored for future analysis and planning. This research represents a significant advancement in aquaculture technology, potentially leading to increased profitability and sustainability in Tilapia farming. Further research and development are required to refine the system and ensure its effectiveness and reliability under various cultivation conditions.
Co-Authors , Arpan , Fery Anugerah , Rahima Br Purba A.A. Ketut Agung Cahyawan W Abda Abda Ade Surya Bakti Pane Afrizal, Henri Afrizal, Sandi Aldi Kesuma Alvian Alvian Ami Abdul Jabar Amnisuhaila Abarahan Ananda Aulia Andi Ernawati Andi Ernawati Andysah Putera Utama Siahaan Angkat, Chairul Indra Anshari, Ari Antoni, Robin Ardya, Dwika Arief, Muhammad Arif Rahman Astri Mutia Rahma Audry, Beby Aulia, Ananda Ayu Ofta Azhari, M. Idrus azwan, m Baehaqi Bambang Sugito Batubara, Supina Boy Rizki Akbar Br Tarigan, Sella Monika Chelfina Utami Daniel Happy Putra Danu Wardhana Azhari Darmeli Nasution DEWI SARTIKA diansyah, Suhar Diva, Krisna Eko Hariyanto Eko Hariyanto Eko Hariyanto Eko Wahyudi Erbin Sitorus Fachri, Barany Fahmi Izhari Fahmi Kurniawan Farta wijaya, Rian Feby Wulandari Sembirinng 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 Heni Wulandari Hilal Prayogi Hrp, Abdul Chaidir Ibezato Zalukhu, Anzas Ika Devi Perwitasari Indra Angkat, Chairul IQBAL , MUHAMMAD Irwan Syahputra Irwan Syahputra, Irwan Khairul Khairul Khairul, Khairul Kiki Artika Kurniawan, Fahmi Laila Maghfirah Larius Ambasador Parlindungan Leni Marlina Leni Marlina Lia Nazliana Nasution Limbong, Yohannes France M Imam Santoso M. Rasyid M.Rizki Khadafi Mardiah, Nia Marzuki Sianturi, Ismail Maulian Saputra Melva Sari Panjaitan Meri Sri Wahyuni Mhd Arie Akbar Mhd Ihsan Abidi Mohammad Yusuf, Mohammad Muhammad Fahriza Muhammad Hafizh Al-Ghifari Rangkuti Muhammad Iqbal Muhammad Irfan Sarif Muhammad Syahputra Novelan Muhammad Wahyudi Nahampun, Natalia Nainggolan, Andreas Ghanneson Nainggolan, Irfan Nazar Saputra, Risfan Nelviony Parhusip Nurwijayanti Ofta Sari, Ayu Parhusip, Nelviony Pasaribu, Ryan Fahreza Pranoto, Sugeng Putra, Khairil Ragil Satya Adi W Rahmat Hidayat Ramadani, Pebri Ramadhan, Aditya Ramadhani, Aditya Rangga Rafandi Razaq, Abdul Retno Mutiara Rian Farta Wijaya Rian Putra, Randi Rika Uli Samosir, Siska Risky, Raihan Rowiyah Asengbaramae Rusydi Tanjung , Miftah Sahputra, Fajar Said Oktaviandi Septia Harliansyah Septia Harliansyah Septiani, Nadya Sianturi, Ismail Sibarani, Dina Marsauli Simamora, Siska Simorangkir, Elsya Sabrina Asmita Sinambela, Sugi Hartono Sinyo Andika Nasution, Ahmad Sipra Barutu Siregar, Andree Risky Yuliansyah Sitepu, Fernando Siti Nurhaliza Sofyan Sitinur, Siti Nurhaliza Sofyan Sitompul, Jelly Rolley Sofyan, Siti Nurhaliza Solly Ariza Lubis Solly Aryza Sri Wahyuni, Meri Suhardiansyah Suhardiansyah Suhardiansyah Suherman Suherman Sukrianto, Sukrianto Sutiono, Sulis Syahputri, Maulisa Syamsiar, Syamsiar T, Siti Isna Syahri Tanjung, Miftah Rusydi Tiara Aninditha Tumangger, Oktavia Utama, Hendra Vina Arnita Vivin Yulfia Sarah Wahyu Agung Pratama Wahyuni, Meri Sri Wijaya, Rian Farta Wirda Fitriani Yahya, Susilawati Yasri, Afif Zai, Yulianus Zalukhu, Anzas Ibezato Zulfahmi Syahputera Zulfahmi Syahputra Zulfahmi Zulfahmi Zulfahmi Zulfahmi