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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Format : Jurnal Imiah Teknik Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO JURNAL MEDIA INFORMATIKA BUDIDARMA Zero : Jurnal Sains, Matematika, dan Terapan JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Building of Informatics, Technology and Science Journal of Information Systems and Informatics JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Reswara: Jurnal Pengabdian Kepada Masyarakat Syntax: Journal of Software Engineering, Computer Science and Information Technology Yayasan Cita Cendikiawan Al Khwarizmi Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer TIERS Information Technology Journal Jurnal IPTEK Bagi Masyarakat Jurnal Pengabdian Masyarakat IPTEK Journal of Information Systems and Technology Research Jurnal Sistem Komputer Triguna Dharma (JURSIK TGD) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Paradigma DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Journal of Computer Science and Research Journal of Embedded Systems, Security and Intelligent Systems Jurnal INFOTEL Jurnal Pengabdian Masyarakat Nasional Conference Proceedings International Conference on Education Innovation and Social Science International Journal of Informatics and Data Science
Asyahri Hadi Nasyuha
(Scopus ID: 57214154368), Universitas Teknologi Digital Indonesia, Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Integrating ISO 27001 and Indonesia's Personal Data Protection Law for Data Protection Requirement Model Nugraha, Arya Adhi; Nasyuha, Asyahri Hadi
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.754

Abstract

This research explores the integration of ISO/IEC 27001:2022 with Indonesia's Personal Data Protection (PDP) Law to establish a robust framework for data protection and information security within organizations operating in Indonesia. The research addresses the challenges of aligning the comprehensive information security management systems (ISMS) standard of ISO/IEC 27001:2022 with the specific legal requirements of the PDP Law, which governs personal data collection, processing, and protection. Employing the Action Design Research (ADR) methodology, the study involves a thorough review of existing literature, consultations with domain experts, and the development of a structured framework for integration. Key findings highlight the complementary nature of ISO/IEC 27001:2022's risk-based approach and the PDP Law's emphasis on data subject rights, consent management, and breach notification. The integration framework provides organizations with a unified approach to meet both international standards and local regulatory requirements, enhancing overall data protection. The research concludes with insights and recommendations for organizations seeking to navigate the complex landscape of data protection compliance, emphasizing the importance of harmonizing security measures with legal mandates to build a comprehensive and effective data protection strategy.
KNN Approach to Evaluating the Feasibility of Using Scientific Publications as Final Projects Abror, Dzulchan; Nasyuha, Asyahri Hadi; Chung, Meng-Yun; Perangin-angin, Moch. Iswan
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14370

Abstract

This study aims to explore the feasibility of using scientific publications as a substitute for traditional final assignments in higher education by applying the K-Nearest Neighbors (K-NN) algorithm. Traditional final assessments, such as theses, are widely used in evaluating students, but with the increasing availability of peer-reviewed scientific publications, there is potential to use them as a more dynamic and relevant assessment tool. This study uses a dataset containing scientific publications and theses, with features such as research quality, relevance, methodology, and clarity. This study applies the K-NN algorithm to classify these materials and determine whether scientific publications can serve as an effective substitute. The results show that the K-NN algorithm, using k=4, achieved 95% accuracy, successfully distinguishing between scientific publications and theses. However, some misclassifications occurred, indicating areas for improvement, such as incorporating additional features such as citation counts or peer-review scores. These findings suggest that scientific publications, if properly classified, can indeed replace traditional final assignments, encouraging critical thinking and engagement with current research. Future research should refine the feature set and explore other machine learning models to improve accuracy. The practical implications of this research are the potential to develop more innovative and relevant approaches to assessment in higher education, which are more aligned with modern educational practice.
Menilai Kepuasan Produk Menggunakan CSI Berdasarkan Respons Konsumen Nasyuha, Asyahri Hadi; Habibie, Dedi Rahman; Kurniawati, Deborah; Suryati, Pulut
FORMAT Vol 14, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i1.006

Abstract

The main issue addressed in this research is identifying the factors that influence customer satisfaction and understanding how well a product meets customer expectations. A questionnaire was distributed to collect data from consumers, and the CSI method was applied to assess the overall satisfaction level based on key aspects such as Product quality, Product durability, Price, Service, Purchasing process and Shipping process. The results showed that most consumers were satisfied with the product, with quality and after-sales service being the most significant factors contributing to overall satisfaction. However, areas such as pricing and ease of use were identified as needing improvement. The study also found that the CSI method provides a reliable means of measuring customer satisfaction and offers valuable insights into areas for product improvement. Based on the findings, the research suggests focusing on enhancing after-sales service and adjusting pricing strategies to better meet consumer expectations. Further research could expand the study to include external factors such as market competition and industry trends, while incorporating advanced analytical methods like regression analysis or machine learning for more in-depth predictions of customer satisfaction.
A Comparative Study of Three Decision Support Methods: Proving Consistency in Decision-Making with Identical Inputs Nasyuha, Asyahri Hadi; Dhuhita, Windha Mega Pradnya; Harmayani, Harmayani; Marwanta, Y. Yohakim; Chung, Meng-Yun; Ikhwan, Ali
TIERS Information Technology Journal Vol. 6 No. 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i1.6157

Abstract

Decision-making in complex environments often requires evaluating multiple alternatives against various criteria, which can sometimes result in inconsistent outcomes when different decision support methods are employed. Such inconsistencies pose significant challenges for decision-makers in determining the most reliable methodology. To address this gap, the present study examines whether three widely adopted decision support methods, Simple Additive Weighting (SAW), Simple Multi-Attribute Rating Technique (SMART), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), produce consistent results when applied to identical input values, criteria, and alternatives. The primary aim is to explicitly assess the consistency of decision-making outcomes across these methods under controlled conditions. The evaluation was conducted using a set of alternatives, with A1 consistently emerging as the top choice. Specifically, the SAW method produced a final score of 0.8998 for A5, the SMART method assigned a value of 0, and the TOPSIS method yielded a closeness coefficient of 0.826 for the same alternative. The unique contribution of this study lies in its systematic, side-by-side comparison of SAW, SMART, and TOPSIS using precisely the same dataset, an approach seldom addressed in prior research. By empirically demonstrating that these methods generate identical rankings under strictly controlled scenarios, this research provides new evidence supporting the methodological robustness and practical interchangeability of these widely used decision support techniques. The findings underscore the reliability of these methods in facilitating objective decision-making and offer valuable guidance for researchers and practitioners in selecting the most suitable DSS method without concern for inconsistent results.
Implementasi Data Mining dan Machine Learning untuk Segmentasi Pelanggan: Pendekatan Hybrid Menggunakan Big Data Prayitno, Edy; Perdana, Ivan Jaka; Nasyuha, Asyahri Hadi
Jurnal Ilmiah FIFO Vol 17, No 1 (2025)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2025.v17i1.007

Abstract

Deteksi dini penyakit jantung merupakan langkah penting untuk meningkatkan kualitas diagnosis dan perawatan pasien. Namun, metode prediksi manual yang sering digunakan tenaga medis memiliki keterbatasan dalam efisiensi waktu, akurasi, dan kemampuan menangani volume data yang besar. Dalam bidang kecerdasan buatan, algoritma machine learning seperti Adaptive Boosting (AdaBoost), Gradient Boosting, dan Extreme Gradient Boosting (XGBoost) menawarkan potensi untuk meningkatkan akurasi prediksi, terutama dalam mengatasi tantangan pada dataset kecil yang sering mengalami ketidakseimbangan kelas dan risiko overfitting. Penelitian ini bertujuan untuk menganalisis kinerja ketiga algoritma boosting tersebut dalam memprediksi penyakit jantung. Hasil penelitian menunjukkan bahwa XGBoost memberikan performa terbaik dengan akurasi sebesar 84.78% dan ROC-AUC 0.9410, menjadikannya algoritma paling efektif dalam menangani pola data yang kompleks. Gradient Boosting menjadi model paling efisien dengan waktu pelatihan tercepat, yaitu 0.3655 detik, dengan akurasi dan ROC-AUC yang kompetitif. Sementara itu, AdaBoost menunjukkan kelemahan dalam menangani ketidakseimbangan kelas tetapi tetap memberikan hasil yang baik untuk kelas mayoritas. Berdasarkan evaluasi precision, recall, dan F1-score, XGBoost direkomendasikan untuk aplikasi prediksi penyakit jantung, terutama dalam situasi yang memerlukan akurasi tinggi, sedangkan Gradient Boosting cocok untuk kebutuhan real-time.
Comparison of WSM and Weight Product Methods with WSM-Score and Vector Approaches Nasyuha, Asyahri Hadi; Tujantri , Harkam; Veza, Okta; Nurarif, Saiful; Chung, Meng-Yun
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14817

Abstract

Fertilizers are essential in modern agriculture as they supply vital nutrients to plants, enhancing growth and yield. However, selecting the most appropriate fertilizer involves multiple criteria and a diverse range of available options. This study conducts a comparative analysis of two Multi-Criteria Decision-Making (MCDM) methods: the Weighted Sum Model (WSM) and the Weight Product (WP) method, supplemented by WSM-Score and vector-based approaches. The evaluation is based on four criteria price, quality, ease of availability, and fertilizer form across seven alternatives: Urea, Compost, TSP, KCL, Gandasil, NPK, and ZA. Using normalized weights from expert judgment, both methods were used to rank the alternatives. A key contribution of this study is the integration of WSM-Score and vector approaches, which enhance traditional MCDM by improving score comparability (WSM-Score) and enabling geometric interpretation of alternative positioning (vector). Results show that Compost (A2) ranks highest across all methods, indicating convergence despite differences in computational logic. WSM offers ease of interpretation, while WP better accounts for proportional differences but is more sensitive to low-performing criteria. The findings suggest that method selection should be context-dependent. Although the ranking results are consistent, the absence of empirical validation through expert comparison or field data limits the generalizability of the conclusions. Further research should include such validation to strengthen the reliability of MCDM-based decision support systems in agricultural applications.
EDUKASI LITERASI DIGITAL UNTUK MENINGKATKAN KEAMANAN DATA BAGI MASYARAKAT DESA PURWOMARTANI Subagyo, Aloysius Agus; Nasyuha, Asyahri Hadi; Pratiwi, Hani Dita
Jurnal Pengabdian Masyarakat Nasional Vol 5, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pemanas.v5i1.33489

Abstract

Masyarakat Desa Purwomartani mulai mengadopsi teknologi digital dalam kegiatan sehari-hari, seperti administrasi desa, pemasaran UMKM, dan komunikasi melalui media sosial. Namun, rendahnya literasi digital khususnya dalam aspek keamanan data menimbulkan risiko pencurian data pribadi, penyalahgunaan informasi, dan serangan siber. Program ini bertujuan untuk meningkatkan literasi digital masyarakat dengan fokus pada edukasi keamanan data melalui pelatihan, simulasi, dan pendampingan. Metode yang digunakan meliputi observasi awal, pelatihan interaktif, simulasi teknis, serta monitoring dan evaluasi. Hasil dari kegiatan menunjukkan peningkatan signifikan dalam pemahaman masyarakat terhadap ancaman siber dan kemampuan mereka dalam menerapkan praktik keamanan data, seperti penggunaan kata sandi yang kuat dan perangkat lunak keamanan. Program ini juga menghasilkan modul pelatihan, panduan teknis, video kegiatan, dan naskah untuk publikasi jurnal. Implikasi dari kegiatan ini adalah terbentuknya kesadaran digital yang lebih baik di masyarakat serta penguatan kapasitas perangkat desa dan pelaku UMKM dalam mengelola informasi secara aman. Program ini diharapkan menjadi model edukasi keamanan digital berkelanjutan di tingkat desa.
Frequent Pattern Mining for Cyberattack Detection Using FP-Growth on Network Traffic Logs Hamsar, Ali; Maulana, Fajar; Hendra, Yomei; Nasyuha, Asyahri Hadi; Aly, Moustafa H
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15221

Abstract

Cybersecurity threats have become increasingly complex, coordinated, and adaptive, creating significant challenges for traditional intrusion detection systems (IDS) that rely on static, signature-based mechanisms. These systems often fail to recognize novel, evolving, or multi-vector attacks that do not match predefined patterns. To overcome these limitations, this study proposes a data-driven framework that applies the Frequent Pattern Growth (FP-Growth) algorithm to analyze co-occurring events within network traffic logs. Using the CIC-IDS2017 benchmark dataset, which includes a wide range of real-world attack scenarios, network events were preprocessed and transformed into transactional data. This transformation enabled the efficient extraction of frequent itemsets and association rules without the computational burden of candidate generation. The experimental results show that the proposed method effectively uncovers meaningful attack correlations, such as brute force attempts preceding privilege escalation or malware infections leading to large-scale DDoS attacks. The model achieved a precision of 77.27%, recall of 70.83%, and F1-score of 73.91%, confirming its reliability in detecting sophisticated attack chains. A heatmap visualization was also generated to improve interpretability, allowing security analysts to quickly identify critical attack relationships. In conclusion, this research demonstrates that FP-Growth provides a scalable, interpretable, and computationally efficient approach to cyberattack detection, with potential integration into real-time IDS environments. Future work will focus on temporal sequence mining and hybrid models combining FP-Growth with machine learning to enhance adaptive, context-aware threat detection.
A Decision Support System for Selecting the Best Private Universities in Yogyakarta Using MARCOS Method Nasyuha, Asyahri Hadi
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 2 (2024): April: Computer Science
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v2i2.37

Abstract

Decision-making in higher education often involves evaluating multiple and sometimes conflicting criteria, particularly in regions such as Yogyakarta, Indonesia, which hosts more than one hundred private universities. Selecting the best institution is therefore a critical and complex task for students, parents, and policymakers. Traditional decision support system (DSS) methods such as SAW, TOPSIS, and AHP are widely applied but remain prone to sensitivity in weight assignment and rank reversal, which may compromise reliability. This study proposes the use of the MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution) method, a recent multi-criteria decision-making (MCDM) technique introduced in 2019, to overcome these shortcomings. MARCOS simultaneously considers both ideal and anti-ideal solutions to achieve more stable rankings. A DSS model was developed and applied to five private universities in Yogyakarta UII, UMY, UAJY, USD, and UTDI evaluated across six criteria: accreditation, doctoral lecturers, research publications, facilities, tuition fees, and graduate employability. The results revealed that Universitas Islam Indonesia (UII) obtained the highest utility score (f(Ki)=0.7404 and ranked first, followed by Universitas Muhammadiyah Yogyakarta (0.6931), Universitas Atma Jaya Yogyakarta (0.6498), Universitas Sanata Dharma (0.6126), and Universitas Teknologi Digital Indonesia (0.5831). Sensitivity analysis further demonstrated that the ranking of UII remained unchanged across weight variations, confirming the robustness of MARCOS. Comparisons with TOPSIS also showed fewer rank reversals, reinforcing the stability of MARCOS in multi-criteria decision-making. This research contributes a novel application of MARCOS in higher education and offers stakeholders a transparent, objective, and data-driven tool for selecting the best private universities in Yogyakarta.
Sistem Pakar Mendiagnosa Penyakit Cutaneous Larva Migrans Menggunakan Metode Dempster Shafer Nasyuha, Asyahri Hadi; Triaji, Bagas; Leswanto, Tomi
Jurnal Ilmiah FIFO Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2024.v16i1.008

Abstract

Cutaneous Larva Migrans merupakan suatu penyakit yang di sebabkan oleh parasit yang masuk ke dalam kulit dan berkembang biak sehingga menimbulkan infeksi pada kulit. Ada beberapa jenis parasit yang menyebabkan penyakit cutaneous larva migrans yaitu, Uncinaria Stenocephala Bunostum Phelebotonum Ancylostoma Braziliense dan Ancylostoma Caninum. Penyakit cutaneous larva migrans tidak terlalu familiar dikalangan masyarakat umum, oleh sebab itu kurangnya perhatian terhadap gejala awal penyakit ini. Akibatnya masyarakat baru menyadari terkena cutaneous larva migrans saat berada pada tahap lanjut. Maka dari itu dibuatlah sistem kecerdasan berbasis desktop yang menganut bidang ilmu sistem pakar yang menggunakan metode dempster shafer.Dempster shafer adalah suatu teori matematika untuk pembuktian berdasarkan fungsi kepercayaan dan pemikiran yang masuk akal, yang digunakan untuk mengkombinasikan potongan informasi yang terpisah untuk mengkalkulasikan kemungkinan dari suatu peristiwa. Sistem pakar ini dapat dipergunakan sebagai pedoman bagi dokter atau para ahli untuk mendiagnosa penyakit cutaneous larva migrans. Sistem pakar ini bisa dimanfaaatkan dalam melakukan pencarian dan penelusuran pengetahuan bagi yang ingin mendapatkan informasi terkait solusi penyakit cutaneous larva migrans.
Co-Authors A F Limas Ptr A, Azanuddin Abdul Karim Abdullah, MT, Dr. Rijal Afdal Al Hafiz Agustina Sidabutar Ahmad Fitri Boy Ahyanuardi Ahyanuardi Al Hafiz, Afdal Alda Fadilla Ali Hamsar Ali Ikhwan Ali Ikhwan Aloysius Agus Subagyo Aly, Moustafa H Amrullah Amrullah Andriyani, Widyastuti Anik Oktavia Utami Anwar, Badrul Ardianto Pranata Ardianto Pranata Pranata Asmar Yulastri Azanuddin Azanuddin Azanuddin Azanuddin Azanuddin Azanuddin B. Herawan Hayadi Badrul Anwar Bagas Triaji Berto Nadeak Buyung Solihin Hasugian Catur Setyono Chung, Meng-Yun Cindy Vivin Avilia Damayanti, Ariesta Deborah Kurniawati Deborah Kurniawati Dedi Rahman Habibie Dedi Rahman Habibie Dedi Rahman Habibie Dedy Irfan Devri Suherdi Dicky Nofriansyah Dini Fakta Sari Dini Fakta Sari, Dini Fakta Dison Librado Dzulchan Abror Edy Prayitno Edy Prayitno Egi Afandi Egi Affandi Elyas, Ananda Hadi Erna Hudianti Pujiarini Evi Rosalina Widyayanti Faisal Taufik Fauzi Erwis Fauzi Erwis FERI SETIAWAN Fina Febriyani Ganefri . Ganefri Ganefri Ginting, Erika Fahmi Habibie, Dedi Rahman Hafizah Hafizah Hamsar, Ali Harmayani Hasan Maksum Hendra Jaya Hendra, Yomei Hendryan Winata Hera Wasiati Hutagalung, Juniar Ibnu Rusydi Ikhwan Ruslianto Ita Mariami Iwan Purnama Jalius Jama jufri halim Junaidi Junaidi Karina Andriani Khairul Khoiri, Muhammad Hafidz Ady Latifah Hanum Leswanto, Tomi Lince Tomoria Sianturi Lucia Nugraheni Harnaningrum Lusiyanti Lusiyanti Lusiyanti Lusiyanti Lusiyanti, Lusiyanti M. Giatman M. Syaifuddin Mardiah Nasution Mariami, Ita Marsono Marsono Marsono Marsono Marsono Marwanta, Y. Yohakim Masyuni Hutasuhut Maulana, Dandi Maulana, Fajar Mesran, Mesran Mesti woro Mahatmi Moch Iswan Perangin-Angin Moch. Iswan Perangin Angin Moch. Iswan Perangin-angin Mochammad Iswan Moses Adeolu Agoi Moses Adeolu AGOI Moustafa H. Aly Moustafa H. Aly Moustafa H. Aly Muhammad Hafidz Ady Khoiri Muhammad Syahril Muhammad Zunaidi Mukhlis Ramadhan Muskhir, Mukhlidi Nasution, Hanifah Nur Nizwardi Jalinus Novica Irawati Nugraha, Arya Adhi Nur Yanti Nur Yanti Lumban Gaol Nur Yanti, Nur Nurarif, Saiful Pane, Usti Fatimah Sari Sitorus Perangin Angin, Moch Iswan Perangin-angin, Moch. Iswan Perdana, Ivan Jaka Pratiwi, Hani Dita Pulut Suryati Pulut Suryati, Pulut Purwadi Purwadi Putri Febrianty Ramadhan, Muhammad Sabir Ramadhan, Mukhlis Refdinal, Refdinal Rico Imanta Ginting Rikie Kartadie Rizky, Firahmi Roziyani Setik Saiful Nurarif Saniman Saniman Santoso, Ismawardi Satria Fandani Setiawan, Feri Sigit Candra Setya Simatupang, Wakhinuddin Sinta Mega Sinaga Solly Aryza Sri Redjeki Sri Redjeki Suardi Yakub Sudarmanto Sudarmanto, Sudarmanto Sukardi, Sukardi Trinanda Syahputra Trinanda Syahputra Tugiono Tugiono Tujantri , Harkam Veza, Okta Wahyudi, Udin Dwi Widiarti Rista Maya Wijang Widhiarso WINDHA MEGA PRADNYA DHUHITA Yohanni Syahra Yolanda Wiguna Yuni Franciska Tarigan Yustria Handika Siregar Zakarias Situmorang Zulfi Azhar Zulham Sitorus Zulham Zulham Zulham Zulham Zulkifli Zulkifli Zunaidi, Muhammad