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Dahlan Abdullah

Universitas Malikussaleh

Author-ID : 217988

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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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

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

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

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

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.

Web-based Rabies Disease Diagnosis Expert System with Forward Chaining and Dempster Shafer Methods Salat, Junaidi; Rasna, Rasna; Ichsan, Muhammad; Abdullah, Dahlan; Lamsir, Seno
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.801

Rabies is a hazardous zoonotic disease that poses a significant threat to both animals and humans, as it can result in death. The disease is caused by a single-stranded RNA virus commonly found in infected animals' saliva, which can be transmitted to humans through bites. Although many people keep animals as pets, many lack adequate knowledge about the potential risks of rabies transmission. In Indonesia, most cases of rabies transmission to humans are caused by bites from infected dogs, followed by bites from monkeys and cats. The absence of an effective treatment for Rabies makes prevention and early diagnosis extremely important. One approach that could help manage the disease is creating an expert system for rabies diagnosis. The Rabies Disease Expert System is developed based on a needs analysis conducted through interviews with veterinarians to understand the classification of symptoms and the diagnostic process for Rabies. It's important to note that while the system is a valuable tool, it does have limitations and should not replace the role of a veterinarian. The system employs two critical methodologies: the Forward Chaining and Dempster-Shafer algorithms. These algorithms allow the system to trace the progression of symptoms and calculate the probability of a rabies infection. The system is an interactive platform where users—such as animal owners or medical professionals—can input observed symptoms in either animals or humans. Based on these inputs, the system provides a probable diagnosis. For example, the expert system might determine that a dog is in the 'Excitation Stage' of Rabies with a 54% confidence level. The integration of Forward Chaining and Dempster-Shafer methods ensures that the system continuously refines its diagnostic accuracy, aiming for a confidence level close to 100%. This expert system offers a promising tool to aid in the early detection and management of Rabies, potentially reducing the risk of widespread transmission.

The Decision Support System for Feasibility Testing of Healthy Canteens at Universitas Malikussaleh Using the Multi-Attribute Utility Theory Method Ulfa, Nur Saufani; Abdullah, Dahlan; Agusniar, Cut
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.815

This research aims to develop a decision support system based on the Multi-Attribute Utility Theory (MAUT) method to evaluate the feasibility of healthy canteens at Malikussaleh University. The system is designed to assess the feasibility of canteens based on six main criteria: Selection of Raw Materials, Storage of Food Ingredients, Food Processing, Food Storage, Food Transportation, and Food Serving. This study evaluated 20 canteens on campus, with feasibility values calculated based on the weights assigned to each Criterion. The results showed that the canteen with the alternative code A11 (Kopita BI) received the highest score of 0.956, followed by A6 (Umi), with a score of 0.798, and A10 (Alisha), with a score of 0.620. Out of the 20 canteens evaluated, only three canteens were categorized as "Feasible," 3 as "Sufficiently Feasible," and the remaining 14 were deemed "Not Feasible." These findings highlight the urgent need to improve the quality of most canteens. The criteria for Selection of Raw Materials and Food Processing had the highest weights, emphasizing the importance of these two aspects in maintaining food quality and health standards. Implementing this system simplifies data management and analysis and provides clear recommendations for canteen managers to improve service and health standards. Thus, this system is expected to promote healthier and higher-quality campus canteens. This research enhances canteen service quality in university environments and can serve as a reference model for other educational institutions in evaluating and improving their canteen facilities.

Data Mining Analysis of Commodity Distribution in Central Aceh Through an Integrated Auction Market System Using the Android-Based Association Rule Mining Method Amelia, Dita; Abdullah, Dahlan; Fitri, Zahratul
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.834

Commodity distribution in Central Aceh faces inefficiencies due to lengthy distribution chains and limited price control, which often leads to higher costs for consumers and lower profits for farmers. To address these issues, this study develops an integrated auction market system based on Android, utilizing the Association Rule Mining (ARM) method to optimize the distribution and pricing of commodities. ARM is a data mining technique that uncovers high-frequency patterns in transaction data. By applying ARM with the apriori algorithm, the system identifies key associations among commodities, allowing for more efficient and targeted price recommendations. The system calculates the highest bid for each commodity and recommends optimal pricing strategies to sellers based on frequent pattern analysis, improving transparency and reducing distribution inefficiencies. Testing and implementation of this system indicate that it successfully reduces distribution costs while increasing the effectiveness and speed of the auction process. Overall, the Android-based auction market system shows promise as a tool for enhancing distribution efficiency, optimizing bid values, and supporting local economies in Central Aceh through more equitable commodity pricing. The final result of this process resulted in four association rules based on predefined parameters, namely a minimum support of 20% and a minimum confidence of 50%. These rules indicate that 60% of the transactions in the Integrated Auction Market system that include Cassava also include Carrots. In other words, a bidder who buys Cassava has a 60% probability of also buying Carrots. This rule is significant as it shows that 20% of all transactions recorded in the system contain both items. This analysis provides important insights into the relationship patterns between items that can be used to provide item recommendations based on purchasing patterns.

Performance Efficiency of Muhammadiyah University Sumatera Area Using Data Envelopment Analysis (DEA) Sulistyandari, Sulistyandari; Fikri, Khusnul; Puji, Ari Andriyas; Abdullah, Dahlan
International Journal of Applied Management and Business Vol. 1 No. 2 (2023)
Publisher : ADPEBI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/ijamb.v1i2.695

Purpose – This paper seeks to examine the efficacy of predicting turnover for employees and entrepreneurs from Estonia, Latvia, and Lithuania using attitudes towards benefits, pay satisfaction, pay, gender, and age across a four-year time frame. Methodology/approach – A survey that included information on attitudes towards benefits and pay satisfaction was used to collect data from 153 Estonian, 157 Latvian, and 146 Lithuanian employees and 243 Latvian, 103 Estonian, and 109 Lithuanian entrepreneurs. Findings – It was found that . Attitudes towards benefits were generally significant predictors of turnover for employees and entrepreneurs over a four-year time period while satisfaction with pay was typically significant for employees but not for entrepreneurs. Novelty/value – As employee retention has been an important factor in the Baltic region over the last two decades it is vital to understand how to retain employees. Keywords Employee turnover, Entrepreneurs, Pay, Estonia, Latvia, Lithuania.

SISTEM PENDETEKSI POLA TAJWID AL- QURAN HUKUM IDGHAM MUTAQARIBAIN PADA AL-QURAN MENGGUNAKAN METODE GOWER & LEGENDRE Abdullah, Dahlan
Jurnal Teknologi Terapan and Sains 4.0 Vol 1 No 2 (2020): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v1i2.3260

Seluruh umat muslim di dunia ini memiliki landasan hukum yaitu Al-Quran dan Al-Hadist. Setiap muslim tentu menyadari bahwa Al-Qur'an adalah kitab suci yang merupakan pedoman hidup dan dasar setiap langkah hidup. Al-Quranul Karim adalah Kalamullah, Kitab suci yang agung umat Islam dan Al-Quran ditulis dalam bahasa Arab. Hampir semua Muslim di seluruh dunia mengetahui bagaimana cara membaca Al-Quran, tetapi tidak semuanya dapat membaca Al-Quran dengan benar berdasarkan makhraj dan Tajwidnya. Oleh karena itu, sistem pendeteksi Tajwid diperlukan untuk membantu pengguna menemukan hukum-hukum Tajwid di dalam Al-Quran. Dalam penelitian ini, metode Gower & Legendre digunakan untuk menghitung jarak keakuratan pola Tajwid pada citra Al-Quran. Hasil pengujian menunjukan bahwa keakuratan sistem ini sebesar 70% hingga 90%. Persentase detection rate tersebut menunjukkan bahwa metode Gower & Legendre dapat digunakan sebagai salah satu pendekatan untuk pendeteksian pola Tajwid pada citra Al-Quran. Kata kunci : Pengolahan Citra, Al-Quran, Tajwid, Gower & Legendre, Big Theta

Analysis of Boarding House Feasibility and Satisfaction Using Data Mining with the C4.5 Algorithm Based on Service Quality and Facilities Manik, Aktina; Abdullah, Dahlan; Ar Razi, Ar Razi
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.896

This research develops a boarding house eligibility classification system using the C4.5 algorithm based on service quality and available facilities. The system evaluates boarding house eligibility by considering various factors such as management services, cleanliness, security, room facilities, public facilities, internet access, comfort, and price. Each of these factors is given a specific weight based on its importance to the tenants, and they are used to classify boarding houses as luxury, standard, and economical. The classification results show that 43% of luxury boarding houses were deemed eligible, while 57% were not. In the standard boarding house category, 21% were classified as eligible, and 79% as ineligible, while in the economical category, 23% were eligible and 77% were ineligible. Using the Confusion Matrix and Classification Report, model evaluation revealed precision ranging from 0.4 to 1.0, recall from 0.67 to 1.0, and F1-scores from 0.5 to 0.91, demonstrating a reasonably high overall accuracy. Additionally, feature importance analysis revealed that price, water and electricity availability, and room facilities are the most influential factors in determining boarding house eligibility. The system's performance was tested against a dataset of real-world boarding houses, and the results suggest that it can accurately classify boarding houses based on key factors that affect tenant satisfaction. The system has the potential to serve as a valuable decision-making tool for boarding house owners, helping them improve service quality and for prospective tenants, enabling them to make more informed housing choices based on their preferences and needs.

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 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 Aswita Indah Luthfiana Hasibuan 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 Deslana Roidja Hapsarini 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 Fikri, Khusnul Firman Aziz Gamar Al Haddar Gio, Prana Ugiana Habib Muharry Yusdartono Haedir, Haedir Halim, Paisal Hamdhana, Defry 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 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 Khairul Fuadi Khairullah Yusuf Komang Ayu Krisna Dewi Kosasih Kosasih , Kosasih Kurniawansyah, Kurniawansyah Kurniawati Kurniawati 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 Luana Sasabone 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 Miswar Mochamad Gilang A Mubarok Mohammad, Wily Mohd Said, Noraslinda Mohd Syahrin Muchlis ABD Muthalib Muhamad Stiadi 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 Muthmainnah Muthmainnah Muzaffar Rigayatsyah Muzaffar Rigayatsyah N. Nazaruddin Nadia Karunia, Meutia Nashihin Nasution, Zainannur Nefo Preyandre Ni Ketut Dewi Irwanti Nisa, Fidyatun Noviany, Henny Nunsina, Nunsina Nurdin Nurdin Nurhasanah Nursyamsi SY Nuruddin Oksfriani Jufri Sumampouw 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 Taufiq Taufiq Teuku Mudi Hafli Touwe, Yohana S Touwe, Yohana S. Tri Suryowidiyanti Ulfa, Nur Saufani Ultra Prayogi Ulumul Haq, Bahrul Utomo, Muhammad Fikri 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 Yuarini Wahyu Pertiwi 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

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