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Dahlan Abdullah

Universitas Malikussaleh

Author-ID : 217988

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Web-Based Complaints Service Information System at Dewantara District Office Amrina, Amrina; Aslam, Aslam; Islam, Khoirul; Sutapa, I Ketut; Kurniawansyah, Kurniawansyah; Abdullah, Dahlan; Ardian, Zalfie
International Journal of Engineering, Science and Information Technology Vol 4, No 1 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i1.490

The Complaint Service Information System is a web-based platform designed for the Dewantara District Office. The title Complaint Service Information System is based on the need for technological solutions to improve the quality of public services, especially in handling public complaints. This system was chosen because it facilitates more efficient complaint reporting, increases transparency, and speeds up responses to issues raised by the public. By applying information technology in handling complaints, it is hoped that we can create a public service environment that is more responsive, open and adaptive to the ever-growing needs of society. The process of creating a complaint service information system involves several main stages. First, the needs analysis stage is carried out to identify and understand the needs of users and related parties in handling complaints. This involves a survey and analysis of associated documents. Next, the system design and design stage involves database structure, user interface, and business logic. This Information System design process involves critical steps to ensure the success and effectiveness of the system, including coding, creating a user interface, and setting up a database. The results of designing the Complaint Service Information System include a simple and responsive user interface, an online complaint form, a status tracking system, and analytical reports. A structured and secure database stores, manages, and retrieves complaint data. Afterwards, the implementation phase involves running the entire system and, if necessary, data migration. Through the creation of this Information System, it is hoped to evaluate the impact of the level of accessibility and ease of navigation in the system on employee performance in searching, monitoring and managing incoming complaints. With a web-based approach, this system provides easy, fast access for users from various locations and increases transparency in managing services provided to the community.

Android-Based Drug Information Application Using Augmented Reality Technology Khalis, Muhammad; Abdullah, Dahlan; Ardian, Zalfie; Berkah Nadi, Muhammad Abi; Nadia Karunia, Meutia; Hasibuan, Abdurrozzaq
International Journal of Engineering, Science and Information Technology Vol 4, No 2 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i2.504

The use of Augmented Reality technology in the pharmaceutical sector, particularly in pharmacies, has introduced significant innovations in providing drug information to consumers. AR applications can help healthcare workers and patients better understand drug use through three-dimensional visualization superimposed on the real environment. Observations at Sultan Abdul Aziz Syah Peureulak Hospital indicate that 70% of patients still experience confusion regarding the drug information provided by pharmacy staff. This difficulty is caused by the complexity of the information, lack of personal interaction, or low health literacy. To address this problem, the Android-based Mediscan application was developed using AR technology. This application utilizes Unity and Vuforia Engine software to present drug information visually in card form via the smart device screen. Users can point the camera at a particular drug and receive complete information regarding general indications, dosage, drug class, contraindications, and side effects. This research aims to develop the Mediscan application, calculate the level of patient understanding, measure consumer satisfaction, and evaluate the impact of using AR in presenting drug information. The System Development Life Cycle methodology with the Waterfall model was used in this research. The results show that AR technology can be implemented in Android-based applications to present drug information visually and interactively. The majority of patients feel more informed and gain a better understanding of the medication they are taking. AR technology in the Mediscan application improves user experience, supports the education and training of medical personnel and patients, and enhances the quality of healthcare services in hospitals. This application also makes it easier for medical personnel and pharmacists to convey drug information more effectively and efficiently.

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

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

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

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

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

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.

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.

Co-Authors - Hartono . Zulfan Abdul Wahab Achmad Harristhana Mauldfi Sastraatmadja Aditia, Donny Adli Zain, Razlan Affiza, Denhaz Pattra Afisman, Heri Juni Afriza, Muhammad Ridho Agus Sukoco Akbar, Abdul Hanif Akhyar, Daniel Al- Amin Ali Nasith Alimul Haq, Nur Ambas, Jamin Amrina, Amrina Ananda Faridhatul Ulva Andi Latif, Sarifudin Andik Bintoro ani, Muli Ansyari, Taufik Habib Anuar Bahri, Khairil Ar Razi, Ar Razi Arifah, Mutia Arifin, Arifin Aslam Aslam, Aslam Aulia Barus, M Farhan Ayu Anggreni, Made Berkah Nadi, Muhammad Abi Chaliza Nur, Wan Amalia Cindy Rahayu Cut Agusniar Cut Ita Erliana Cut Yusra Novita Darmawanta Sembiring Defi Irwansyah Deisye Supit Devin Mahendika Dita Amelia, Dita Eko Prastyo Elviwani Elviwani Elviwani Elviwani Elviwani, Elviwani Emy Yunita Rahma Pratiwi ER. UMMI KALSUM Erianto Ongko Erlina Erlina Erlina Erlina Fadlisyah Fadlisyah Fadlisyah Farida Juliarta, Evie Fazil, M Fidyatun Nisa Fikri, Khusnul Firman Aziz Gamar Al Haddar Gio, Prana Ugiana 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 Putu Agus Dharma Hita I Putu Gede Adiatmika Ika Rahayu Satyaninrum IKhwanda Putra, Al Malikul Imanullah, Imanullah 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 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 Lestari, Veronika Nugraheni Sri Lidya Rosnita Limbong, Hendra Putranta Lubis, Fauzan Arbi M Farhan Aulia Barus M FAUZAN Maharani Asnur, Sardian 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 Miswar Miswar Mohammad, Wily Mohd Said, Noraslinda Mohd Syahrin 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 Muslem Muslem Muslem Muslem, Muslem Muthmainnah Muthmainnah Muzaffar Rigayatsyah Muzaffar Rigayatsyah N. Nazaruddin Nadia Karunia, Meutia Nana Citrawati Lestari Nasution, Zainannur Ni Ketut Dewi Irwanti Noviany, Henny Nunsina, Nunsina Nurdin Nurdin Nurhaedah Nurhaedah Nurhasanah Nursyamsi SY Oksfriani Jufri Sumampouw Paisal Halim Pasaribu, Hafni Maya Sari Pertiwi, Anggun Pikri, Faizal Poetri AL-Viany Maqfirah Puji, Ari Andriyas Putra, Arwin Rahmat, Rezqiqah Aulia Ramli, Rahmat Rasna, Rasna Reskiawan, Bimas - Rezzy Eko Caraka Riansyah, Muhammad Richki Hardi Rini Meiyanti Risawandi, Risawandi Rizki Suwanda Rizki Wahyuri Roslaini, Roslaini S, Syarifuddin Sabriana, Riska Safwandi Safwandi Safwandi Safwandi, Safwandi 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 Sutarna, Agus Syamsiah Badruddin Tahulending, Anneke A 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 Yuniningsih Yuniningsih Yusra, Muhammad Zafera Adam, Jeanne d'Arc Zahratul Fitri, Zahratul Zainannur Nasution Zara Yunizar Zega, Subhansah Zulfahmi Zulfahmi

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