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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar IJISTECH (International Journal Of Information System & Technology) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JiTEKH (Jurnal Ilmiah Teknologi Harapan) IJISTECH Journal of Social Responsibility Projects by Higher Education Forum Bulletin of Multi-Disciplinary Science and Applied Technology Jurnal Lentera Pengabdian Jurnal Kajian Ilmiah Teknologi Informasi dan Komputer Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi
Annisa Fadillah Siregar
Universitas Budi Darma, Medan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Sistem Pendukung Keputusan Menentukan E-Commerce Terbaik Menggunakan Metode Topsis Siregar, Farid Akbar; Siregar, Annisa Fadillah; Setiadi, Eka Widya Ningsih
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.419

Abstract

One of the trading activities that has become increasingly popular recently is online buying and selling transactions. The development of the digital world indirectly influences the growth of online buying and selling transactions or e-commerce. This rapid growth has led to a variety of service and product offerings from various e-commerce platforms, often leaving users confused about choosing the platform that best fits their needs and availability. Users frequently face complex questions such as which platform offers the best service quality, which platform provides the most optimal transaction security, and which platform is the most reliable for transactions. Therefore, an evaluation is needed to help users assess which platform best meets their needs. This study utilizes the TOPSIS method, as this method is considered to have a simple concept in producing alternative decisions in an accurate mathematical form. The results of this study, using 5 criteria and 8 alternative e-commerce platforms, indicate that Shopee (A1) is the best alternative with a score of 0.9564.
Sistem Pendukung Keputusan Menggunakan Intuitionistic Fuzzy Set Method Untuk Penentuan Personel Pengamanan Vip Direktorat Manik, Jens Presisken; Sinurat, Sinar; Siregar, Annisa Fadillah
JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 3 No. 01 (2024): Desember
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/jikteks.v3i01.113

Abstract

Keamanan merupakan aspek yang sangat penting dalam menjaga integritas dan keselamatam individu,terutama dalam konteks pengaman VIP (Very Important Person). Direktorat Pengamanan VIP (PAMOBVIT) adalah sebuah organisasi yang bertanggung jawab untuk menyediakan personal pengamanan berkualitas tinggi utuk melindungi VIP. Proses penentuan personal pengamanan yang efektif dan efesien sangat penting untuk memastikan keberhasilan operasi pengamanan VIP. (DIPAMOBVIT).VIP, Tourist Security, dan Audit Sistem Keamanan Objek Penting Nasional (Perpol RI No.14 Tahun 2018). Adapun solusi terhadap permasalahan diatas yaitu dengan membangun suatu Sistem Pendukung Keputusan untuk membantu penentuan personil pengamanan VIV. Metode yang dipilih untuk mendukung pemecahan masalah diatas adalah metode Intuitionistic Fuzzy Sets yaitu dengan cara memberikan bobot pada tiap-tiap alternatif pilihan yang ada. Penelitian ini menghasilkan sebuah Sistem Pendukung Keputusan yang dapat merekomendasikan penentuan personil pengamanan VIV menggunakan metode Intuitionistic Fuzzy Sets. Dilakukan uji coba dengan memasukkan sampel data sebanyak 10 nama personil. Dengan adanya Sistem Pendukung Keputusan dapat memberikan rekomendasi untuk penentuan personil pengamanan VIV berdasarkan rangking, dari 10 nama personil berdasarkan rangking terkecil yaitu variabel: A10, A9, A5, A2, dan A1.
Penerapan Sistem Pendukung Keputusan Dalam Penilaian Kinerja Supervisor Dengan Menggunakan Metode Maut Dan Pembobotan Entropy Devi, Wanda Tofani; Mesran, M; Siregar, Annisa Fadillah
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.616

Abstract

Position positions in PT. Bintang Mutiara Cemerlang is a supervisor, where the problem in this company is the supervisor's performance appraisal process which is less effective because it is seen based on the length of work alone, causing injustice to other supervisors who have not worked long enough. Therefore, a decision support system is created that is capable of supporting the performance appraisal procedure. This decision support system applies the MAUT method and the Entropy method to the process to see the value obtained in the system. Each criterion has its own weight so that the alternatives can be ranked. The MAUT (Multi Attribute Utility Theory) method is a quantitative method in which there are structured stages to find out and describe the variables in it. After ranking, the results obtained from the application of the MAUT and Entropy methods are the A10 alternative on behalf of Shadad Putra S.H with a value of 0.84060 as the best alternative in assessing supervisor performance at PT. Shining Pearl Star.
Sosialisasi Anti Bullying sebagai Upaya Pencegahan Tindak Perundungan di SD Negeri 068004 Medan Tuntungan Sari, Arini Vika; Siregar, Annisa Fadillah
Lentera Pengabdian Vol. 3 No. 02 (2025): April 2025
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/lp.v3i02.807

Abstract

Maraknya kasus bullying atau perundungan yang terjadi di Indonesia terutama di sekolah sungguh sangat mengkhawatirkan. Pemerintah sebenarnya sudah melakukan upaya dalam mencegah dan menanggulangi fenomena ini. Namun, hasilnya belum signifikan. Untuk itu, perlu semua elemen turut membantu dan mencegah tindakan bullying yang terus terjadi di mana-mana. Berdasarkan latar belakang tersebut kegiatan pengabdian masyarakat perlu dilakukan dalam bentuk sosialisasi. Tim dosen Universitas Budi Darma memilih SD Negeri 068004 Medan Tuntungan untuk kegiatan pengabdian masyarakat sebab sekolah tersebut diketahui masih sering melakukan tindakan bullying seperti mengejek dan memukul sesama teman. Hasil kegiatan pengabdian di SD Negeri 068004 Medan Tuntungan menunjukkan bahwa peserta didik dengan antusias mampu mengetahui dan memahami pengertian, bentuk, dampak dan cara pencegahan dari Tindakan bullying. Selain itu, peserta didik juga mampu memahami pentingnya bersikap baik, sopan dan santun kepada semua orang terutama kepada teman di sekolah dan tidak melakukan tindakan bullying karena tindakan tersebut tergolong perilaku menyimpang secara sosial dan emosional.
Landscape of AHP Integration in Decision Support Systems: A Bibliometric Analysis of Scopus Publications Saputra, Imam; Mesran, Mesran; Utomo, Dito Putro; Siregar, Annisa Fadillah
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7451

Abstract

This study employs bibliometric analysis to provide a comprehensive overview of the research landscape concerning the integration of the Analytic Hierarchy Process (AHP) and Decision Support Systems (DSS). Utilizing 1770 documents retrieved from the Scopus database (1985-2025) and employing Biblioshiny for analysis, this research examines publication trends, citation patterns, keyword co-occurrence, collaboration networks, and thematic evolution within the field. The findings reveal a significant growth in publications, particularly after 2015, highlighting the increasing scholarly interest. Citation analysis identifies influential works and key contributing countries. Keyword analysis underscores "decision support systems," "analytic hierarchy process," and "decision making" as central themes, with emerging interest in areas like "artificial intelligence." Collaboration network analysis illustrates significant co-authorship patterns and international collaborations. Thematic mapping further categorizes research themes, identifying well-established "Motor Themes" (e.g., "decision support system," "GIS") and fundamental "Basic Themes" (e.g., "decision making," "analytic hierarchy process"). This study provides valuable insights into the intellectual structure, evolutionary trends, and collaborative dynamics of the AHP-DSS integration research field, highlighting its robust nature and potential future directions.
Pemetaan Lanskap Penelitian Fungsi Hash dan Secure Hash Algorithm: Studi Bibliometrik Menggunakan Biblioshiny Saputra, Imam; Siregar, Annisa Fadillah
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7762

Abstract

Hash functions and secure hash algorithms are vital components in modern cybersecurity, essential for ensuring data integrity and authenticity. With the development of new attacks and the emergence of novel applications, the research landscape in this field has become highly dynamic and complex. This study aims to map the research landscape related to hash functions and secure hash algorithms using a comprehensive bibliometric study approach. Publication data comprising 494 journal and conference proceeding articles were collected from the Scopus database using a specific query. Bibliometric analysis was performed using Biblioshiny software, covering basic characteristics analysis, keyword co-occurrence, citation analysis (most cited works, intellectual structure), collaboration, thematic mapping, and thematic evolution. The results show significant publication growth over time, identifying key contributors (countries, institutions, authors) as well as the most relevant publication sources. Keyword analysis and thematic mapping revealed dominant research themes and clusters (e.g., core cryptography, hardware implementation, image security applications, potential in the healthcare sector), while citation analysis highlighted the most influential articles and authors forming the knowledge foundation. Thematic evolution demonstrated a shift in research focus from fundamental algorithms towards broader application exploration and related techniques in more recent periods. This study provides a comprehensive data-driven overview of the structure, trends, and dynamics of research on hash functions and secure hash algorithms. These findings contribute to understanding the status of this field and identify potential areas for future research, assisting researchers and practitioners in navigating the extensive literature.
Sistem Pendukung Keputusan Pemilihan Tenaga Hononer Terbaik Menggunakan Metode Additive Ratio Assessment (ARAS) Dengan Pembobotan Rank Order Centroid (ROC) Simangunsong, Evi O; Hasibuan, Nelly Astuti; Siregar, Annisa Fadillah
Jurnal Kajian Ilmiah Teknologi Informasi dan Komputer Vol 1 No 2 (2023): May 2023
Publisher : CV. Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/jutik.v1i2.109

Abstract

Honorary workers are employees who have not been appointed as permanent employees who receive an honorarium every month from the agency or company where they work. SMK N 1 Balige is one of the schools that still needs honorary teachers. Each school certainly makes policies to create a teaching and learning process between teachers and students that is more conducive and optimal. One of the policies of SMK N 1 Balige is to select the best honorary teachers. This policy can encourage honorary teachers to work more professionally. However, this assessment is still carried out manually so that it affects the results of decisions that are not objective. Then a decision support system is needed by applying two methods, namely the Additive Ratio Assessment (ARAS) and Rank Order Centroid (ROC) methods to produce accurate decisions and get the best alternative from the input matrix. The ARAS method is used as the ranking for the final results and the ROC method is used for weighting. The application of a decision support system using the ROC method is able to give weight to each criterion that will be used in the ARAS method calculation process. By applying the ARAS method, the best alternative was produced in the name of Donna Napitupulu with alternative code A3 with a result of 0.976 followed by alternative A1 in the name of Anita Teresia Sianipar with a result of 0.929.
PENGENALAN POLA BUNGA BERBASIS CITRA MENGGUNAKAN JARINGAN SARAF TIRUAN DENGAN ALGORITMA PERCEPTRON Fahrezi, Azrial; Saputra, Imam; Siregar, Annisa Fadillah
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, Nomor 04, Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i04.18128

Abstract

Flowers are transformations of buds, including stems and leaves, with shapes and colors adapted to the plant's functions. They also serve as sites for fertilization and pollination. Flowers come in various shapes and colors, with over 250,000 flowering plant species known and classified into 350 families. Therefore, employing technology for flower pattern recognition is crucial for enhancing accuracy and efficiency. One effective method involves using Artificial Neural Networks (ANN) in conjunction with the perceptron algorithm. This algorithm has proven effective in image-based pattern recognition due to its ability to learn complex and linear patterns from image data. This study explores the use of neural networks, specifically the perceptron method, in recognizing flower patterns. The test utilizes sunflower image samples, with the perceptron algorithm applied to produce accurate and effective data in flower pattern recognition.
IMPLEMENTASI JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI TINGKAT PRODUKSI JAGUNG GILING MENGGUNAKAN METODE BACKPROPAGATION (STUDI KASUS: MIKRA MAKMUR BERSAMA) Aritonang, Reza Sri Rezeki; Saputra, Imam; Siregar, Annisa Fadillah
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, Nomor 04, Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i04.18160

Abstract

This study aims to implement Artificial Neural Networks (ANN) to predict corn flour production levels at the agricultural company Mikra Makmur Bersama using the backpropagation learning method. As a machine learning technique, ANN has the potential to enhance prediction accuracy by effectively analyzing historical data. Data on corn flour production from 2021 to 2023 was collected from the company and used to train the ANN model with a backpropagation architecture. This process involves feedforward and backward propagation to optimize neuron weights, aiming to produce accurate and reliable predictions. The backpropagation algorithm updates weights based on prediction errors and can adapt to complex patterns in the data. The results show that the implemented ANN model successfully predicted corn flour production levels with significant accuracy, as tested with data from 2021 to 2023. This study is expected to serve as a reference for applying ANN technology in other agricultural sectors and encourage the use of advanced methods to enhance efficiency and productivity.
Co-Authors Ade Rizka Aritonang, Reza Sri Rezeki Devi, Wanda Tofani Dito Putro Utomo Fahrezi, Azrial Farid Akbar Siregar Imam Saputra Imam Saputra Kurnia Ulfa Manik, Jens Presisken Mesran, Mesran Miya Andriyani Nelly Astuti Hasibuan Nola Dita Puspa Rizka, Ade Rizkah Fadilllah Sari, Arini Vika Setiadi, Eka Widya Ningsih Simangunsong, Evi O Sinurat, Sinar