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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 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) 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 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
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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.
Optimizing Insurance Customer Segmentation with C4.5 Decision Tree Algorithm Setya, Sigit Candra; Perangin-angin, Moch. Iswan; Marsono, Marsono; Nasyuha, Asyahri Hadi; Harnaningrum, Lucia Nugraheni
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7358

Abstract

Insurance companies rely on premium payments as their primary source of revenue. However, economic instability often causes delays in premium payments, impacting revenue recording. This study applies the C4.5 Decision Tree algorithm to classify insurance customers based on premium amount, age, income, and claim history, thereby improving product recommendations. The research utilizes data mining techniques to analyze customer attributes and generate decision rules for optimal insurance product selection. The findings indicate that customers with a premium of IDR 500,000 are best suited for PRUMed Cover (PMC), while those with IDR 1,000,000 are recommended PRUCritical Benefit 88 (PCB88). For customers with IDR 750,000, additional factors such as age and income level influence the recommended insurance type. The entropy and information gain calculations identify premium amount as the most significant attribute for decision-making, followed by age, income, and claim history. By implementing this method, insurance companies can enhance customer segmentation, streamline product selection, and optimize marketing strategies. The transparent and interpretable decision tree structure ensures regulatory compliance while improving customer satisfaction. Future research should explore additional variables, such as behavioral data and regional trends, and compare C4.5 with other classification algorithms like Random Forest or Support Vector Machines (SVM) to enhance accuracy and scalability.
Sistem Pendukung Keputusan Pemilihan Bibit Padi Unggul Menggunakan Metode Simple Additive Weighting (SAW) Febriyani, Fina; Nasyuha, Asyahri Hadi; Kurniawati, Deborah
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7627

Abstract

The selection of superior rice seeds is a crucial stage in improving agricultural productivity in Indonesia. However, farmers often select seeds subjectively without systematically considering important factors. To address this issue, this study designs and develops a Decision Support System (DSS) based on the Simple Additive Weighting (SAW) method to assist farmers in selecting the best rice seeds using six criteria: pest resistance, harvest age, amylose content, yield, irrigation water efficiency, and rice texture. Data were collected through interviews with five farmers in Mangir Lor. The results showed that the rice variety Inpari 32 achieved the highest score of 0.87, thus recommended as the best alternative. The SAW method proved effective in managing multicriteria data and producing objective and accurate results. This DSS is expected to serve as a practical decision-making tool for farmers in selecting high-quality rice seeds and contribute to the achievement of sustainable national food security.
Sistem Pendukung Keputusan Rekomendasi Rumah Kost di Sekitar Kampus Menggunakan Metode SAW Utami, Anik Oktavia; Nasyuha, Asyahri Hadi; Suryati, Pulut
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7629

Abstract

Yogyakarta, known as a student city, is a major destination for students from various regions in Indonesia to pursue higher education, including at the Universitas Teknologi Digital Indonesia (UTDI). The majority of UTDI students come from outside the city and therefore require temporary housing such as boarding houses (kost). However, selecting a suitable kost is often challenging due to the abundance of choices and various criteria that must be considered, such as distance to campus, rental price, facilities, safety, house rules, and cleanliness. This study aims to design and develop a Decision Support System (DSS) to provide the best boarding house recommendations around UTDI using the Simple Additive Weighting (SAW) method. SAW was chosen due to its capability to handle multi-criteria decision-making in a simple yet effective manner. Data collection methods include literature studies and questionnaires distributed to students. The evaluation process involved assigning weights to each criterion, followed by normalization and preference score calculation for each boarding house alternative. The final results show that the system successfully provides objective recommendations, with the highest-ranking boarding house being Kost Melati with a score of 1.798, followed by Kost Putri Raflesia (1.6), and Kost Ijo Putri (1.55). The developed DSS simplifies the previously manual and subjective kost selection process into a more structured and accurate system. In conclusion, the SAW method proves effective in supporting decision-making for kost selection around the UTDI campus. This research is expected to serve as a foundation for developing similar systems with more complex or combined methods for optimal results.
Co-Authors A F Limas Ptr A, Azanuddin Abdul Karim Abdullah, MT, Dr. Rijal Abror, Dzulchan 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 Anwar, Badrul Ardianto Pranata Ardianto Pranata Pranata Asmar Yulastri Azanuddin Azanuddin B. Herawan Hayadi Badrul Anwar Bagas Triaji Buyung Solihin Hasugian Candra Setya, Sigit Chung, Meng-Yun Damayanti, Ariesta Deborah Kurniawati Dedi Rahman Habibie Dedi Rahman Habibie Dedy Irfan Devri Suherdi Dicky Nofriansyah Dini Fakta Sari, Dini Fakta Dison Librado Edy Prayitno Edy Prayitno Egi Affandi Elyas, Ananda Hadi Erna Hudianti Pujiarini Faisal Taufik Fauzi Erwis Febriyani, Fina FERI SETIAWAN Ganefri Ganefri Ginting, Erika Fahmi Habibie, Dedi Rahman Hafizah Hafizah Hamsar, Ali Hasan Maksum Hendra Jaya Hendra, Yomei Hendryan Winata Hera Wasiati Hutagalung, Juniar Ibnu Rusydi Irawati, Novica Ita Mariami Iwan Purnama Jalius Jama jufri halim Junaidi Junaidi Khairul Khoiri, Muhammad Hafidz Ady Latifah Hanum Leswanto, Tomi Lucia Nugraheni Harnaningrum Lusiyanti Lusiyanti Lusiyanti Lusiyanti Lusiyanti, Lusiyanti M. Giatman Mardiah Nasution Mariami, Ita Marsono Marsono Marsono Marsono Marsono Marwanta, Y. Yohakim Masyuni Hutasuhut Maulana, Dandi Maulana, Fajar Mesran, Mesran Moch Iswan Perangin-Angin Mochammad Iswan Moustafa H. Aly Moustafa H. Aly Muhammad Syahril Muhammad Zunaidi Mukhlis Ramadhan Muskhir, Mukhlidi Nasution, Hanifah Nur Nizwardi Jalinus 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 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 Simatupang, Wakhinuddin Sinta Mega Sinaga Solly Aryza Sri Redjeki Sri Redjeki Suardi Yakub Sudarmanto Sudarmanto, Sudarmanto Trinanda Syahputra Trinanda Syahputra Tugiono Tugiono Tujantri , Harkam Utami, Anik Oktavia Veza, Okta Vina Winda Sari Wahyudi, Udin Dwi Widiarti Rista Maya WINDHA MEGA PRADNYA DHUHITA Yohanni Syahra Yohanni Syahra Yolanda Wiguna Yuni Franciska Tarigan Yustria Handika Siregar Zakarias Situmorang Zulfi Azhar Zulham Sitorus Zulham Zulham Zulkifli Zulkifli Zunaidi, Muhammad