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All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Informatika Kaputama (JIK) Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology MALLOMO: Journal of Community Service Journal of Renewable Energy, Electrical, and Computer Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pengabdian Masyarakat Bangsa MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Informatika: Jurnal Pengembangan IT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS)
Yesy Afrillia
Universitas Malikussaleh
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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PKM Strategi Pemanfaatan Teknologi Informasi untuk Menghadapi Cyberbullying di Kalangan Siswa Retno, Sujacka; Maida, Eka; Fhonna, Rizky Putra; Afrillia, Yesy; Fachrurrazi, Sayed; Yusuf, Edi
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 9 (2025): November
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i9.3469

Abstract

Perkembangan teknologi informasi membawa dampak positif terhadap kemajuan pendidikan, namun di sisi lain juga menimbulkan fenomena negatif seperti cyberbullying yang semakin marak di kalangan siswa. Cyberbullying sebagai bentuk kekerasan psikologis berbasis digital dapat mengganggu kesehatan mental, motivasi belajar, hingga prestasi akademik peserta didik. Pengabdian ini bertujuan untuk menganalisis strategi pemanfaatan teknologi informasi dalam mengidentifikasi, mencegah, dan menanggulangi cyberbullying di lingkungan sekolah melalui integrasi pendekatan teknologi dan edukatif. Metode pengabdian yang digunakan adalah studi literatur dengan mengkaji hasil pengabdian terdahulu, jurnal terakreditasi, serta laporan lembaga pendidikan nasional maupun internasional. Hasil kajian menunjukkan bahwa pemanfaatan artificial intelligence (AI) untuk deteksi ujaran kebencian, penggunaan learning management system (LMS) yang dilengkapi fitur pelaporan anonim, serta penerapan sistem pengawasan berbasis machine learning dapat membantu mengurangi insiden cyberbullying. Namun, efektivitas teknologi tersebut sangat bergantung pada kesadaran etika digital dan kemampuan literasi siber siswa. Oleh karena itu, kolaborasi antara sekolah, guru, dan orang tua dalam memberikan edukasi literasi digital menjadi aspek krusial. Sinergi antara inovasi teknologi dan program pendidikan karakter mampu membangun lingkungan digital yang aman, inklusif, dan mendukung kesejahteraan psikologis siswa.
Strategic Framework for Implementing Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) for Personalized AI in Informatics Engineering: A Case Study of Malikussaleh University Abil Khairi; Wahyu Fuadi; Yesy Afrillia
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This study develops a strategic framework for integrating Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to support personalized Artificial Intelligence (AI) applications within the Informatics Engineering Department at Malikussaleh University. By utilizing localized datasets, the framework aims to enhance research productivity and improve educational outcomes while prioritizing data privacy and security. The study examines the opportunities and challenges associated with embedding these technologies into the university’s existing infrastructure, proposing a phased approach to adoption. Emphasis is placed on the modernization of academic practices through AI-driven tools that cater to local educational and research needs. The findings offer insights into implementing advanced AI systems that could serve as a model for similar educational settings focused on sustainable AI adoption.
Application of the Naïve Bayes Method in Optimizing Marketing Performance at PT. Semen Indonesia Mahesa Reglisalo; Dahlan Abdullah; Yesy Afrillia
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This study examines the application of the Naïve Bayes method to improve marketing performance at PT. Semen Indonesia. In an increasingly competitive business environment, effective data management is crucial for strategic decision-making. Currently, PT. Semen Indonesia utilizes the SAP system to manage sales and financial data, but it lacks an automated system to analyze marketing performance. This research aims to develop a Naïve Bayes-based classification system to monitor marketing performance, considering attributes such as profit, market share, sales volume, and customer satisfaction. The Naïve Bayes method was chosen for its accuracy in handling large-scale data and its ability to provide fast and efficient predictions. Marketing performance data is processed using this method to categorize marketing performance as “good” or “poor.” The analysis results show that the developed system achieves a classification accuracy of 43.75% for the “good” category and 56.25% for the “poor” category. This system assists management in designing more effective marketing strategies by leveraging historical data to predict trends and market needs. Keywords: Naïve Bayes, marketing performance, PT. Semen Indonesia, data analysis, classification system, profit, market share
Machine Learning Algorithms Comparison for Gender Identification Aldo januansyah. H; Muhammad Fikry; Yesy Afrillia
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.885

Abstract

Abstract. In this study, we presents a comprehensive analysis of gender identification methods utilising eight distinct classification models: K-Nearest Neighbors (KNN), Naive Bayes, Decision Tree, Random Forest, Logistic Regression, XGBoost, Support Vector Machine (SVM), and Neural Network. Gender identification is a critical task with significant applications in marketing, social analysis, and security systems, necessitating the exploration of various methodologies to achieve optimal performance. The dataset employed in this research underwent normalisation using the Min-Max scaling technique, which enhances the performance of classification models by ensuring that all features contribute equally, particularly when the data exhibits varying ranges of values. The results reveal that the K-Nearest Neighbors (KNN) model significantly outperformed the other models, achieving an impressive accuracy of 0.9758 with a support of 951, underscoring the effectiveness of the KNN algorithm in gender identification tasks and establishing it as a reliable choice for applications requiring high accuracy. Furthermore, the study emphasises the critical importance of selecting appropriate models in machine learning tasks and the substantial impact of data normalisation on model performance. Overall, this research provides valuable insights into the KNN algorithm, demonstrating its ease of implementation and exceptional effectiveness in achieving high precision in gender identification tasks, with implications for future research and practical applications across various fields. Keywords : classification models; data normalisation; gender identification; K-Nearest Neighbours; machine learning.
Quality Analysis of Web-Based Visitor Management System (DATENG) Using Cypress Testing and Task-Based Usability Testing Methods Based on ISO 9241-11 (Case Study of PT Perta Arun Gas) Rizky Putra Fhonna; Yesy Afrillia; Ilham Sahputra; Sayed Fachrurrazi; Faiz Fadhilla
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27052

Abstract

Manual management of visitor data in the company environment has the potential to cause various problems, such as time inefficiency, the risk of data loss, and the occurrence of physical queues during certain operational hours. These conditions can hinder the smooth running of operational activities and reduce the quality of service to guests. Therefore, a web-based visitor management system called DATENG was developed which aims to support the process of recording, scheduling, and verifying visits in an integrated and structured manner. This research activity focuses on testing and evaluating the quality of the DATENG system to ensure that the system can function properly and is easy to use by users. The method used consists of two main approaches, namely functionality testing and usability evaluation. Functionality testing is carried out using the Cypress Testing method with an end-to-end testing approach to verify that all system features are running according to the needs that have been set. Furthermore, usability evaluation is carried out using a task-based testing method based on the ISO 9241-11 standard, which includes measuring aspects of effectiveness, efficiency, and satisfaction. The test results show that all the key features of the DATENG system can function properly without significant functional errors being found. Usability evaluations show that users are able to complete each task with a high success rate, relatively efficient turnaround time, and a good level of user satisfaction. Based on these results, it can be concluded that the DATENG system has good system quality and is able to support the visitor management process effectively, efficiently, and provide a positive user experience in accordance with the company's operational context.
Pendampingan Penggunaan Aplikasi GeoGebra Berbasis Teknologi Informasi dalam Pengembangan Media Pembelajaran Interaktif Eri Saputra; Cut Agusniar; Rizky Putra Fhonna; Yesy Afrillia; Effan Fahrizal; Muhammad Ikhwanus
Jurnal Pengabdian Masyarakat Bangsa Vol. 4 No. 4 (2026): Juni
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v4i4.4563

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi siswa matematika di SMA Negeri 1 Kota Lhokseumawe dalam memanfaatkan aplikasi GeoGebra berbasis teknologi informasi untuk mengembangkan media pembelajaran interaktif. Permasalahan yang ditemukan di lapangan menunjukkan bahwa pemanfaatan teknologi pembelajaran masih terbatas dan belum terintegrasi secara optimal dalam perangkat pembelajaran, khususnya Rencana Pelaksanaan Pembelajaran (RPP). Metode pelaksanaan kegiatan menggunakan pendekatan pelatihan dan pendampingan yang terdiri atas empat tahap, yaitu analisis kebutuhan, pelatihan, pendampingan implementasi, serta evaluasi dan refleksi program. Hasil kegiatan menunjukkan adanya peningkatan kompetensisiswa dalam penguasaan GeoGebra, pengembangan media pembelajaran interaktif, serta integrasi teknologi dalam RPP. Hasil evaluasi menunjukkan peningkatan pada berbagai indikator, termasuk penguasaan GeoGebra sebesar 85% dan kepuasansiswa mencapai 92%. Kegiatan ini menunjukkan bahwa pendampingan berbasis teknologi efektif dalam meningkatkan kompetensi pedagogik digitalsiswa serta mendorong inovasi pembelajaran matematika yang lebih interaktif dan bermakna.
ANALISIS SENTIMEN REVIEW APLIKASI STOCKBIT DI GOOGLE PLAY STORE DAN X(TWITTER) MENGGUNAKAN SUPPORT VECTOR MACHINE: SENTIMENT ANALYSIS OF STOCKBIT APPLICATION REVIEWS ON GOOGLE PLAY STORE AND X (TWITTER) USING SUPPORT VECTOR MACHINE Yusril; Wahyu Fuadi; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6446

Abstract

This study examines sentiment analysis of user reviews of the Stockbit application obtained from the Google Play Store and platform X (formerly Twitter). The aim of this research is to classify user opinions into two sentiment categories: positive and negative, using the Support Vector Machine (SVM) method. A total of 3,000 review data points were used in this study, consisting of 2,100 training data points and 900 test data points (stratified split with a 70:30 ratio) to ensure balanced sentiment distribution. The research process includes text preprocessing, feature weighting using Term Frequency-Inverse Document Frequency (TF-IDF), sentiment classification with the SVM algorithm, and model performance evaluation. Based on the evaluation results, the SVM model demonstrated high performance with an accuracy of 95.5%, precision of 93.5%, recall of 97.4%, and an F1-score of 95.3%. Although its accuracy is lower than that of Maulana et al.'s (2024) study, which achieved 99.50% on the Pluang application, this research excels in using data from two different platforms and evaluating class imbalance, making the analysis results more representative of real-world conditions. These findings indicate that SVM remains an effective method for text-based sentiment analysis in digital financial service applications.
PENERAPAN ALGORITMA RANDOM FOREST UNTUK MENENTUKAN KELAYAKAN PENERIMA BLT: IMPLEMENTATION OF THE RANDOM FOREST ALGORITHM FOR DETERMINING BLT RECIPIENTS' ELIGIBILITY Muhammad Iqbal; Dahlan Abdullah; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6503

Abstract

Indonesia faces significant challenges regarding poverty, particularly among low-income communities. The government has introduced various programs, including the Direct Cash Aid Program (BLT), to alleviate poverty. However, identifying eligible recipients in Bandar Dua Subdistrict, Pidie Jaya, remains complex and time-consuming. This research aims to implement the Random Forest algorithm to determine the eligibility of cash aid recipients in Bandar Dua, Pidie Jaya, providing accurate and efficient classification based on predefined criteria. The study focuses on BLT recipients in Bandar Dua, comprising 45 villages, using data from 2020 to 2022. The Random Forest algorithm is applied, considering criteria such as income, housing conditions, and the number of dependents. The expected outcomes include valuable insights for the local government in determining the eligibility of cash aid recipients, a classified dataset using the Random Forest algorithm, and a reference for future research. According to the test results using the Random Forest algorithm, an accuracy of 83.33%, precision of 89.04%, and recall of 91.55% were achieved.  
KEAMANAN ENDPOINT API MENGGUNAKAN OAUTH2 PADA UNIT LAYANAN TERPADU UNIVERSITAS MALIKUSSALEH: APPLICATION PROGRAMMING INTERFACE (API) SECURITY AT THE INTEGRATED SERVICE UNIT OF MALIKUSSALEH UNIVERSITY Gilang Ramadhan Purba; Rizal; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6543

Abstract

Malikussaleh University, as a higher education institution, strives to improve service quality through its Integrated Service Unit (ULT). However, monolithic systems often become an obstacle due to their rigidity and difficulty in development. This research aims to design and build an efficient and secure ULT system model by adopting a microservice architecture. The methodology includes designing the microservice architecture, developing APIs, and implementing security using Laravel Passport, which supports the OAuth2 standard to protect Machine-to-Machine (M2M) communication. Each service, such as administration, academic, and personnel services, is broken down into independent services packaged in Docker containers. The results show the successful implementation of a system prototype where each service can communicate securely via API. Testing proved that the token-based and scope-based authentication and authorization mechanisms successfully protected endpoints from unauthorized access. Thus, the implemented microservice architecture model and API security are proven to be a solution for a modular, secure, and efficient service digitalization in the university environment.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUNSCREEN KULIT BERJERAWAT MENGGUNAKAN METODE FUZZY ANALYTICAL HIERARCHY PROCESS Elvina Mutiara Vina; Wahyu Fuadi; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7744

Abstract

Tingginya paparan sinar ultraviolet di wilayah tropis meningkatkan urgensi penggunaan sunscreen, terutama bagi pemilik kulit berjerawat yang memerlukan ketelitian dalam memilih produk agar tidak memperburuk kondisi kulit. Banyaknya pilihan merek di pasaran sering kali menimbulkan kesulitan bagi konsumen dalam menentukan produk yang paling sesuai. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pendukung keputusan (SPK) pemilihan merek sunscreen terbaik untuk kulit berjerawat menggunakan metode Fuzzy Analytical Hierarchy Process (F-AHP). Metode ini dipilih karena mampu mengakomodasi ketidakpastian dan subjektivitas dalam penilaian kriteria. Data diperoleh melalui observasi, wawancara, dan kuesioner kepada 300 responden. Kriteria yang digunakan meliputi harga, tekstur, komposisi, kandungan SPF, dan jenis sunscreen. Hasil penelitian menunjukkan bahwa komposisi bahan merupakan kriteria paling dominan, diikuti oleh tekstur produk. Berdasarkan hasil perhitungan F-AHP, Azarine Calm My Acne Sunscreen meraih peringkat pertama dengan skor 0,6876, disusul oleh Facetology Triple Care Sunscreen (0,6371) dan Wardah UV Shield Acne Calming Sunscreen (0,6297).
Co-Authors Abadi, Sabani Abdul Hadi Abil Khairi Adek, Rizal Tjut Aldo januansyah. H Ananda Faridhatul Ulva Annas, Muhammad Aqmal, Jamalul Arif, Abdul Halim Arif, M. Arif Saputra Arifa, Cut Hilma Asmi, Nurul Annisa Asrianda Asrianda Asrifan, Andi Asrillah Asrillah Aswandi, Sakti Ayu Indah Lestari Berutu, Indah Fachlira Bustami Bustami Cut Agusniar Dahlan Abdullah Dasril Dasril David Sarana Deassy Siska EDI YUSUF, EDI Effan Fahrizal Ekamaida, Ekamaida Elvina Mutiara Vina Eri Saputra eva darnila, eva darnila Fadlisyah Fadlisyah Fadlisyah Faiz Fadhilla Fakhruddin Ahmad Nasution Farhan Dika Fatika, Dian Fidyati, Fidyati Fikria, Putri Fuadi, Wahyu Gilang Ramadhan Purba Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Herman Fithra Hidayat, Amam Taufiq ilham - sahputra Ilsa Hidayat Intan Putri Dinanti Jamalul Aqmal Julianansa, Ririn Kasihan Muhammad Fajar Kautsar, Al Khairuni Khairuni Lidya Rosnita Mahadika Luqman Mahesa Reglisalo Muhammad Fikry Muhammad Ikhwanus Muhammad Iqbal Muhammad Muhammad Muhammad Yusuf Mukhlis Mukhlis Mukti Qamal Muzaffar Rigayatsyah Muzaffar Rigayatsyah NELI SUSANTI, NELI Nurdin Nurdin Nurqamarina Rahma, Mutiara Rahmawati, Rahmawati Rini Meiyanti Risawandi, Risawandi Riza, Saiful Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Rozzi Kesuma Dinata Safriand, Safriand Sari, Rika Yulia Sayed Fachrurrazi Selian, Riko Ardiansyah Siregar, Winda Ramadhani Sofyan Sofyan Suci Ramadani Sujacka Retno Teuku M. Arief Afwan Tursina Dewi Uliana, Lisa Ulva Ilyatin Veri Ilhadi Wahyu Fuadi Wahyu Fuadi Wardana, Ade Bagus Widari, Liz Ayu Winda Yanti Yusril Zahratul Fitri, Zahratul Zara Yunizar Zuhra, Elviza Zulfan