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All Journal Syntax Jurnal Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Speed - Sentra Penelitian Engineering dan Edukasi International Journal of Advances in Intelligent Informatics ITEj (Information Technology Engineering Journals) JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer International Journal of Artificial Intelligence Research SISFOTENIKA Jurnal SOLMA IJEBD (International Journal Of Entrepreneurship And Business Development) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) International Journal of Supply Chain Management Journal on Education Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH JUSIM (Jurnal Sistem Informasi Musirawas) JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research Industrial Engineering Journal (IEJ) Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal JTIK (Jurnal Teknik Informatika Kaputama) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology Bulletin of Computer Science Research Cendikia : Media Jurnal Ilmiah Pendidikan Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Janitra Informatika dan Sistem Informasi Brilliance: Research of Artificial Intelligence TECHSI - Jurnal Teknik Informatika Jurnal Energi Elektrik Jurnal Teknologi Terapan and Sains 4.0 Pusaka : Journal of Tourism, Hospitality, Travel and Business Event Variasi : Majalah Ilmiah Universitas Almuslim Journal on Research and Review of Educational Innovation Sahabat Sosial: Jurnal Pengabdian Masyarakat Indonesian Journal of Education (INJOE) Journal International Journal of Teaching and Learning (INJOTEL) INTERNATIONAL JOURNAL OF HUMANITIES, SOCIAL SCIENCES AND BUSINESS (INJOSS) INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) International Journal of Language and Ubiquitous Learning Journal Emerging Technologies in Education Bulletin of Engineering Science, Technology and Industry International Journal of Applied Management and Business Jurnal Info Kesehatan Journal of Industrial Engineering and Management Jurnal Informatika Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Dahlan Abdullah
Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry 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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation Other

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Identification of Ergonomic Risk on Workers Using Quick Exposure Check and Rapid Upper Limb Assessment Methods Erliana, Cut Ita; Irwansyah, Defi; Abdullah, Dahlan; Zega, Subhansah; Hasibuan, Muammar Faturrahman
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.432

Abstract

Pulau Tiga Palm Oil Mill (PKS) is one of the business units of PT. Nusantara I Plantation located in Pulau Tiga Village, Tamiang Hulu District, Aceh Tamiang Regency, is engaged in palm oil processing. Some workstations at PKS Pulau Tiga still use a manual work system, then the factor of long working hours, which is 12 hours of work/day, can make it easier for workers to experience fatigue and result in musculoskeletal complaints for workers. The purpose of this study is to identify which workstations are most at risk and which workstation facilities must be improved. The methods used in this study are the QEC, NBM, and RULA Methods.
Bibliometric analysis of model vehicle routing problem in logistics delivery Zuhanda, Muhammad Khahfi; Hartono, Hartono; Sidik Hasibuan, Samsul Abdul Rahman; Abdullah, Dahlan; Gio, Prana Ugiana; Caraka, Rezzy Eko
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp590-600

Abstract

This bibliometric analysis focuses on the vehicle routing problem (VRP) model in the field of logistics delivery. The study utilizes a comprehensive dataset of 2,000 VRP-related publications obtained from the Scopus database, spanning the years 2007 to 2023. Through the application of bibliometric methods, this research aims to uncover key insights regarding research trends, country contributions, and recent topics within the VRP research network. Various bibliometric indicators, including publication count, author productivity, relevant sources, institutional affiliation, and citation frequency, are employed to conduct the analysis. The findings shed light on the evolution and trajectory of VRP research, while also highlighting noteworthy countries and topics that have received significant attention. This study not only enhances the overall understanding of VRP but also serves as a foundation for future investigations aimed at enhancing the efficiency and effectiveness of logistics delivery.
Plagiarism Detection Application for Computer Science Student Theses Using Cosine Similarity and Rabin-Karp Ansyari, Taufik Habib; Abdullah, Dahlan; Rosnita, Lidya
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.686

Abstract

Plagiarism detection is critical in maintaining academic integrity, particularly in higher education. This study focuses on developing a plagiarism detection application for Computer Science student theses. The application leverages the Cosine Similarity and Rabin-Karp algorithms to accurately and efficiently detect textual similarities. Developed using JavaScript, the application provides an intuitive interface and reliable performance, making it a practical tool for educational institutions. The application includes features allowing users to upload thesis documents, analyze textual content, and measure plagiarism levels by comparing them to an existing dataset. The Cosine Similarity algorithm measures the overall similarity between documents, while the Rabin-Karp algorithm focuses on identifying exact matches in phrases and sentences. The results demonstrate the efficacy of both algorithms. For titles, the Cosine Similarity algorithm achieved a 100% similarity rate for identical documents while detecting minor plagiarism with a similarity level of 5.86% for other documents. For abstracts, it achieved 100% similarity for the first document, 2.78% for the second document, and 8.37% for the third document. These findings highlight the algorithm's ability to detect exact matches and partial overlaps in textual content. The Rabin-Karp algorithm showed comparable performance, particularly in detecting phrase-level similarities. For titles, it recorded 100% similarity for identical documents, 11.42% for the second document, and 16.92% for the third document. For abstracts, the algorithm also achieved 100% similarity for the first document, 11.42% for the second document, and 16.81% for the third document. The study confirms that both algorithms complement each other in detecting different forms of plagiarism. The Cosine Similarity algorithm excels in identifying global patterns of similarity, while the Rabin-Karp algorithm is more suited for finding exact matches in specific phrases or sentences. This dual approach provides a comprehensive solution for detecting plagiarism in academic theses. The findings from this research are promising and highlight the potential of the application as a reliable tool for ensuring academic integrity. Future improvements could include expanding the dataset, enhancing the user interface, and integrating additional algorithms for cross-language plagiarism detection. This application contributes to academic honesty and is a valuable resource for educators, researchers, and students in combating plagiarism effectively. 
Application of Multiple Linear Regression Method for Predicting Fish Production Based on Cultivation Type Limbong, Hendra Putranta; Abdullah, Dahlan; Anshari, Said Fadlan
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.717

Abstract

One of the contributors to Indonesia's economy is the fisheries sector, which has a high potential for development. Fisheries are a highly promising subsector for development in Indonesia's growth efforts. Based on data from the Central Bureau of Statistics of Dairi Regency, three types of aquacultures remain actively utilized in each subdistrict: ponds/freshwater ponds and paddy fields. This research aims to develop a fish production prediction system based on aquaculture types using the Multiple Linear Regression method. The accuracy of the prediction results will be measured using the Mean Absolute Percentage Error (MAPE). The results of this study indicate that in almost every subdistrict, especially pond aquaculture, the MAPE value is 20%, which means it has good accuracy. However, exceptions are found in the Siempat Nempu Hulu subdistrict, which has a MAPE value of 34.29%, and the Silahisabungan subdistrict, which has a MAPE value of 43.78%. Despite these values, they are still categorized as sufficient since they are 50%. The lower the MAPE value, the more accurate the prediction results. The findings of this research show that the multiple linear regression method can be considered correct. For future predictions, some results show negative values. For instance, in Silimapunggapungga subdistrict, a decline in production is predicted for 2024 with -114.779 tons and 2025 with -134.316 tons. The pessimistic prediction results are caused by the decrease in the X2 variable (area size), leading to a minor Y (production) value, potentially becoming negative if the contribution of X2 is no longer sufficient to balance the values of X1 (b1) and a. On the other hand, the Lae Parira subdistrict is predicted to experience an increase in production in 2024 by 87.024 tons and in 2025 by 84.380 tons. This system is implemented using the Python programming language. It is expected to help relevant stakeholders understand production trends and enhance the efficiency of fisheries resource management in the Dairi Regency.
Prediction of Plantation Crop Production Based on Environment Using Linear Regression and Single Exponential Smoothing Methods Sari, Marlina; Abdullah, Dahlan; Maryana, Maryana
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.669

Abstract

Indonesia, as an agrarian country, heavily relies on the plantation sector as a key driver of its national economy. One significant region contributing to this sector is West Aceh Regency, which consists of 12 districts and is renowned for cultivating five main plantation commodities: oil palm, coconut, rubber, coffee, and cocoa. This research aims to develop a plantation crop production prediction system to support efficient resource planning and management in this sector. The system employs Linear Regression and Single Exponential Smoothing (SES) with a smoothing constant (alpha) of 0.2. The system's primary objective is to analyze historical production data at the district level and generate reliable predictions of future production trends. Linear Regression models the relationship between time (independent variable) and production volume (dependent variable), effectively capturing long-term trends. SES complements this by addressing short-term fluctuations, applying a weighted average where recent data carries greater importance. Prediction accuracy is evaluated using the Mean Absolute Percentage Error (MAPE). Findings reveal that Linear Regression consistently achieves high accuracy, with MAPE values below 20% in most districts, particularly for coffee and cocoa. Conversely, SES demonstrates varying results, performing well in some cases, such as coconut production in Arongan Lambalek (MAPE 20%), but poorly in others, such as oil palm in Bubon (MAPE = 91.06%). In comparison, Linear Regression in Bubon yields a more moderate MAPE of 35.16%. The system is integrated into a user-friendly, web-based platform, accessible to stakeholders like farmers, policymakers, and government agencies. By offering actionable insights into production trends, it aids in mitigating risks, optimizing resource allocation, and enhancing plantation management efficiency. This research underscores the importance of predictive analytics in agricultural planning, with potential applications in other agrarian regions.
Implementation of Data Mining for Nutrition Clustering of Toddlers at Posyandu Using K-Means Algorithm Kamilah, Muna; Abdullah, Dahlan; Suwanda, Rizki
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.718

Abstract

This study aims to determine the nutritional status of toddlers in the Peulimbang sub-district using a clustering method that can group toddlers based on their dietary indicators, such as gender (jk), age (u), height (tb), weight (bb), and upper arm circumference (Lila). By using data analysis techniques such as K-Means clustering, this study successfully identified several groups of toddlers with different nutritional statuses, ranging from malnutrition to good nutrition to obesity nutritional status. The data for this study were taken directly from the Peulimbang Health Center, and as many as 765 toddler data were collected from 16 villages in the Peulimbang area. The programming language used in this study is PHP, which functions in web development and is often used to process data sent via web formula, interact with databases, and manage user sessions. Based on the results of clustering with the K-Means method using Euclidean Distance as a measurement between points, toddler data has been grouped into three Clusters, namely C1, C2, and C3. Cluster C1 covers 22.81% of 147 malnourished toddlers, C2 covers 48% of 323 well-nourished toddlers, and C3 covers 29.19% of 205 obese toddlers. Based on the clustering results, improving nutrition education programs for parents is essential, especially in areas with poor or lacking nutritional status. This program can include counseling on the importance of balanced nutrition, nutritious cooking methods, and choosing the right Food for toddlers. Thus, this study is expected to contribute to improving toddlers' nutritional status and overall public health in the Peulimbang District area.
Comparative Analysis of K-Means and K-Medoids to Determine Study Programs Salamah, Salamah; Abdullah, Dahlan; Nurdin, Nurdin
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.673

Abstract

Education is the main foundation for the advancement of civilization. A high level of education in society is directly proportional to the progress of that civilization. Higher education plays an important role in shaping quality human resources and contributing to community and national development. In today’s era of information and technology, data processing and analysis are key to understanding the development of study programs in higher education institutions. Clustering techniques are used to identify patterns and relationships in large and complex datasets, which are crucial in determining study programs at educational institutions. This research compares two popular clustering methods, K-Means and K-Medoids to determine study programs. The data used consists of odd semester grades of 87 students in the third-years of high school with 5 variables. The information of clusters is based on the minimum academic criteria of 18 study programs representing 7 faculties in Malikussaleh University and grouped into 5 clusters. The evaluation of clusters is conducted using the Davies-Bouldin Index (DBI). The result of the study indicate that K-Means algorithm has 5 clusters with cluster members of 31, 5, 13, 26 and 17, and a DBI value of 1,19010. Meanwhile, the K-Medoids algorithm has 5 clusters with cluster members of 33, 15, 17, 17 and 5, and a DBI value of 1,27833. Based on the DBI value, the K-Means algorithm demonstrates better cluster quality compared to the K-Medoids algorithm.
A Smart Accounting System for Real-Time Mosque Financial Fund Management Based On Android and Web Mobile through The Implementation of The Agile Development Scrum Method: (Case Study: The Baiturrahim Mosque is Located in Uteun Bayi Village, Banda Sakti District, Lhokseumawe City) Ardian, Zalfie; Abdullah, Dahlan; Bintoro, Andik; Yusra, Muhammad; Akbar, Abdul Hanif; Lubis, Fauzan Arbi
JINAV: Journal of Information and Visualization Vol. 5 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav3044

Abstract

The Smart Accounting System (SAS) is an accounting system that optimizes the financial administration of an entity or company by utilizing artificial intelligence and information technology to streamline the accounting process. Mosques may encounter a variety of financial challenges; among these are fund management, income, and expenses. Distrust among the congregation may result from a lack of transparency in mosque financial management. Consequently, it is crucial to preserve transparency and furnish transparent financial statements. In order to resolve these financial challenges, it is crucial to implement effective financial management, establish a realistic budget, enhance transparency, and engage the congregation in the mosque's financial management. The Agile Development Scrum method is employed to design the Smart Accounting System, which is based on Android mobile and web. The Agile approach enables the team to effortlessly adjust to changes during the development process, as it fosters congregational engagement throughout the entire development cycle. The mosque treasurer or finance team's participation is indispensable in the context of the Smart Accounting System to guarantee that the appropriate requirements are satisfied. Agile ensures superior system quality by emphasizing continuous testing and feedback from the mosque congregation. The proper location for field studies and initial data sources for the development of the Smart Accounting System is Baiturrahim Mosque, located in Uteun Bayi Village, Lhokseumawe City. Additionally, the Agile Scrum methodology will be implemented to execute the system design. The subsequent phase involves the implementation of the Black Box system testing method and User Acceptance Testing (UAT)
Recipient Feasibility Decision Support System Micro Small Medium Business Assistance Use Method Analytic Hierarchy Process and Simple Additives Weighting Abdullah, Dahlan; Erliana, Cut Ita; Bintoro, Andik; Hartono, Hartono; Ikhwani, Muhammad; Nazaruddin, Nazaruddin
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2321

Abstract

Study This aims To determine the eligibility of MSME assistance recipients with the method AHP (Analytic Hierarchy Process) And SAW (Simple Additives weighting). The AHP method is used to determine the weight of each criterion. Meanwhile, SAW is used To determine the rank selection of beneficiaries. This is very important for Indonesia's economy during the crisis, Where MSME's own Power stands to face a crisis economy. Criteria used in a way This uses six measures: type of business, Amount of power Work, turnover per month, amount of assets, sector MSME, And sector business. Decision support systems are designed to support someone who must make certain decisions. That is, interactive, Flexible, Data quality, and Expert Procedure. Study System Supporters Decision Appropriateness Recipient Help Business Micro Community Use Analytic Hierarchy Process (AHP) and Simple Additive Methods weighting (SAW), Study This done in Subdistrict Intersection Three Regency Pidie Aceh Province to facilitate the Selection of Eligibility of Government Assistance Recipients For Build a business Micro Society. Testing is done in this study, namely black box testing. Results Testing black box shows that the system can walk with Good by function, with results calculation method AHP and results calculation method SAW in determining eligibility selection MSME aid recipients. The results of the level of accuracy testing on the AHP and SAW methods with six criteria and alternatives the requirements is 75%.
Performance of K-Nearest Neighbor Algorithm and C4.5 Algorithm in Classifying Citizens Eligible to Receive Direct Cash Assistance in Bandar Mahligai Village Chaliza Nur, Wan Amalia; Abdullah, Dahlan; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.752

Abstract

Direct Cash Assistance, commonly called BLT, is one of the many programs the Indonesian government held to reduce the poverty rate of the Indonesian population. This study compares the KNN and C4.5 methods to determine the eligibility of residents eligible to receive Direct Cash Assistance in Bandar Mahligai Village. This study began with collecting resident data from the Bandar Mahligai village office. Then, the data obtained was taken into several attributes to be used in the classification process, namely the name of the head of the family, KK number, NIK, number of dependents, occupation, income, and monthly expenses. After the data is collected, the data will be classified using the KNN and C4.5 algorithms. There is a significant difference between the two algorithms in the classification process; the KNN algorithm by looking for the nearest neighbor data value, in this study, the K value = 9, while the C4.5 algorithm by building a decision tree from the attribute values taken based on resident data used as training data. The classification results of the two methods will be compared using a confusion matrix to obtain a higher accuracy technique. The results of testing using a confusion matrix for both algorithms are the accuracy produced by the KNN and C4.5 algorithms in classifying residents eligible for Direct Cash Assistance (BLT) of 90% in the system that has been built. The results of comparing the KNN and C4.5 algorithms for this study show that the KNN algorithm is better because the accuracy level reaches 90% in manual and system calculations. While the C4.5 method only gets 85% for the accuracy of its manual calculations, it receives an accuracy level of 90% in the system that has been built.
Co-Authors - Hartono . Zulfan A. Z, Abdullah Abdul Wahab Achmad Harristhana Mauldfi Sastraatmadja Aditia, Donny Adli Zain, Razlan Affiza, Denhaz Pattra Afisman, Heri Juni Afriza, Muhammad Ridho Agil, Helvina Agus Sukoco Akbar, Abdul Hanif Akhyar, Daniel Al Kautsar Aidilof, Hafizh Al- Amin Ali Nasith Alimul Haq, Nur Ambas, Jamin Amny Yasira Amrina, Amrina Ananda Faridhatul Ulva Andik Bintoro ani, Muli ANNISA KARIMA Ansyari, Taufik Habib Anuar Bahri, Khairil Ar Razi, Ar Razi Arifah, Mutia Arifin, Arifin Arnawan Hasibuan Aslam Aslam, Aslam Aulia Barus, M Farhan Ayu Anggreni, Made Berkah Nadi, Muhammad Abi Chaizir, Muhammad Chaliza Nur, Wan Amalia Cindy Rahayu Cut Agusniar Cut Ita Erliana Cut Yusra Novita Darmawanta Sembiring Dedi Fariadi Defi Irwansyah Defi Irwansyah Deisye Supit Devin Mahendika Dita Amelia, Dita Eko Prastyo Elviwani Elviwani Elviwani Elviwani Elviwani, Elviwani Emy Yunita Rahma Pratiwi, Emy Yunita Rahma ER. UMMI KALSUM Erianto Ongko Erlina Erlina Erlina Erlina Fachry Abda El Rahman Fadlisyah Fadlisyah Fadlisyah Fajriana, Fajriana Fakhruddin Ahmad Nasution Farida Juliarta, Evie Fazil, M Fidyatun Nisa Fikri, Khusnul Firman Aziz Fuadi, Khairul Gamar Al Haddar Gio, Prana Ugiana Habib Muharry Yusdartono Haedir, Haedir Hapsarini, Deslana Roidja Haris Danial Hartono Hartono Hartono Hartono Hartono, Natalia Rumanti Hasanun Hasibuan, Abdurrozzaq Hasibuan, Fadilah Suryani Hasibuan, Muammar Faturrahman Heri Juni Afisman Herry Rachmat Widjaja Hery Budiyanto HS, Nurmadina I Ketut Sutapa I MADE MULIARTA . I P G. Adiatmika I Putu Agus Dharma Hita Ika Rahayu Satyaninrum IKhwanda Putra, Al Malikul Imanda, Nanda Imanullah, Imanullah Indah Sulistiani Indra Pilianti D Indra Tjahyadi Indrawati Irdanil Kamal, Irdanil Irianto, Sugeng Irma Oktari Irwansyah, Defi Islam, Khoirul Iswan Riyadi Iswandi Iswandi Iswandi Iswandi Iylia Azlan, Rabiatul Juarni Siregar Judijanto, Loso Kamilah, Muna Kartika Kartika Kartini Rahayu Khairullah Yusuf Komang Ayu Krisna Dewi Kosasih , Kosasih Kurniawansyah, Kurniawansyah La Ode Muhammad Idrus Hamid B Lahap, Johanudin Lamsir, Seno Laros Tuhuteru Latif, Sarifudin Andi Lestari, Nana Citrawati Lestari, Veronika Nugraheni Sri Lidya Rosnita Limbong, Hendra Putranta Lubis, Fauzan Arbi Lubis, Muhammad Hanafi Sahar Luh Yusni Wiarti M Farhan Aulia Barus M Fauzan Maharani Asnur, Sardian Mahesa Reglisalo Manik, Aktina Marganda Simarmata Marlina Sari Maryana Maryana Maryana Maryana, Maryana Masriadi Maulana, Fatur Rahman Maulinda, Rerin Maya Savira Meilyana Meilyana Meutia Rahmi Mirna Dewi Misbahul Jannah Misbahul Jannah Miswar Miswar Mochamad Gilang A Mubarok Mohammad, Wily Mohd Said, Noraslinda Mohd Syahrin Muhamad Stiadi Muhammad Daud Muhammad Daud Muhammad Fikry Muhammad Ichsan Muhammad Ihsan Dacholfany Muhammad Ikhsan Setiawan Muhammad Ikhsan Setiawan Muhammad Ikhwani Muhammad Khahfi Zuhanda Muhammad Khalis, Muhammad Muhammad Riansyah Muhammad Zarlis Muhammad Zarlis, Muhammad Muharam, Suhari muli ani Munirul Ula Muslem Muslem Muslem Muslem, Muslem Muthalib, Muchlis Abd Muthmainnah Muthmainnah Muzaffar Rigayatsyah Muzaffar Rigayatsyah N. Nazaruddin Nadia Karunia, Meutia Nashihin Nasution, Zainannur Nefo Preyandre Ni Ketut Dewi Irwanti Noviany, Henny Nunsina, Nunsina Nurdin Nurdin Nurdin Nurdin Nurhasanah Nursyamsi SY Nuruddin Oksfriani Jufri Sumampouw Paisal Halim Pasaribu, Hafni Maya Sari Pertiwi, Anggun Pikri, Faizal Poetri AL-Viany Maqfirah Puji, Ari Andriyas Putra, Arwin Putu Eka Wirawan Rafi’i, Rafi’i Rahma Fitria, Rahma Rahma, Hilmia Rahmat, Rezqiqah Aulia Ramlan, Rifqi Ramli, Rahmat Rasna, Rasna Razi, Ar Reskiawan, Bimas - Rezzy Eko Caraka Riansyah, Muhammad Richki Hardi Rifkial Iqwal Rini Meiyanti Risawandi, Risawandi Rizki Suwanda Rizki Wahyuri Rizky Putra Fhonna Roslaini, Roslaini S, Syarifuddin Sabriana, Riska Safwandi Safwandi Safwandi Safwandi, Safwandi Said Anshari Said Fadlan Anshari salamah salamah Salat, Junaidi Samsul A Rahman Sidik Hasibuan Sandya, Deasy Saputra, Nanda Saputra, Rizwan Sasabone, Luana Satria Pati Alam Sayed Fachrurrazi Selamat Meliala Setiawan, Muhammad Ikhsan Sima, Yenny Simarmata, Marganda Sitti Nur Alam Subhan, Roni Sulistyandari, Sulistyandari Surnihayati Surnihayati Susanti, Putu Herny Sutarna, Agus Syahputra, Wawan Syamsiah Badruddin Syarifuddin Syarifuddin Tahulending, Anneke A Tarigan, Tasya Amelia Taufiq Taufiq Teuku Mudi Hafli Touwe, Yohana S Touwe, Yohana S. Tri Suryowidiyanti Ulfa, Nur Saufani Ultra Prayogi Ulumul Haq, Bahrul Veronika Nugraheni Sri Lestari Victor E. D Palapessy Wa Ode Riniati Wahyu Pertiwi, Yuarini wandi, risa Wenny J, Syilvia Widiyani, Maya Yeni Risyani Yesy Afrillia Yuliah, Yuliah Yulisda, Desvina Yuniningsih Yuniningsih Yusra, Muhammad Zafera Adam, Jeanne d'Arc Zahratul Fitri, Zahratul Zainannur Nasution Zalfie Ardian Zara Yunizar Zega, Subhansah Zulfahmi Zulfahmi Zulfia , Anni