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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Inotera Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Multica Science and Technology Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat Bangsa Jurnal Malikussaleh Mengabdi
Sukiman, T. Sukma Achriadi
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Website-Based Text Encryption Simulation with Hill Chiper Sukiman, T. Sukma Achriadi; Zulfia, Anni; Karima, Annisa; Ulya, Athiyatul; Rizky, Muharratul Mina
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.5757

Abstract

Data security has become increasingly crucial in the modern digital era, where almost all types of information ranging from text, images, to audio are stored and exchanged in digital form through open networks. The rapid growth of internet-based communication makes data highly vulnerable to interception, modification, or misuse by unauthorized parties. Cryptography is one of the most effective solutions to address these challenges. Among the classical cryptographic techniques, the Hill Cipher remains relevant today because it is based on linear algebra and matrix transformations, which provide a strong mathematical foundation and can be adapted for modern computational implementation. In this study, a web-based application was developed using the Python Flask framework to implement the Hill Cipher algorithm. The application enables users to perform both encryption and decryption of text and images through an interactive interface. Users can input plaintext and key matrices, and the system processes the data to produce encrypted or decrypted outputs in real time. This design not only demonstrates the practicality of applying classical cryptographic concepts with contemporary web technologies but also serves as a valuable educational tool. The results show that the application performs effectively, producing accurate outputs, while also supporting user learning in understanding encryption–decryption processes and guiding efforts to secure digital information.
AI Decision Support for Demand Forecasting and Retail Stock Using Random Forest Zulfia, Anni; Ilfa, Tasya Nadhira; Damia, Zayyani; Sukiman, T. Sukma Achriadi; Karima, Annisa
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.5901

Abstract

Out-of-stock or excess inventory is a major challenge in retail supply chain management, especially in dynamic urban areas. This stock imbalance not only causes financial losses, but can also reduce customer satisfaction due to products being unavailable when needed. This study developed an artificial intelligence (AI)-based decision support system using the Random Forest algorithm to predict daily demand in retail stores. The model was trained using historical sales data that included various variables such as date, product category, and previous sales trends. After the training process, the model was implemented in the form of an interactive web application using Streamlit, which allows users to easily access the system through a browser without the need for special installation. Testing results show that the model is capable of predicting demand for the next 7 days with a fairly good level of accuracy, as indicated by a Mean Absolute Error (MAE) value of ±4.613 units per day. This application not only provides demand predictions but also presents data visualizations and automatic restocking recommendations based on the prediction results. Thus, this system is expected to help store managers make more accurate, efficient, and data-driven restocking decisions. Additionally, the use of Streamlit simplifies the process of distributing the system widely and enhances accessibility for end-users, including those without a technical background. This research opens opportunities for further development through the integration of real-time data and other AI methods to improve prediction accuracy in the future.
The Use of Photodiode Sensors to Detect Sugar Levels in the Human Body Rizky, Muharratul Mina; Ginting, Depi; Sukiman, T Sukma Achriadi
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6318

Abstract

Diabetes mellitus is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production or utilization. Regular monitoring of blood glucose is essential to prevent long-term complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease. However, conventional finger-prick glucometer methods, while accurate, are invasive, cause discomfort, and often discourage patients from performing frequent checks. To address this limitation, this study presents the design, implementation, and evaluation of a non-invasive glucose monitoring system utilizing a photodiode sensor in conjunction with a near-infrared (NIR) light source operating at wavelengths of 1600–1700 nm. The system architecture comprises an NIR LED as the light emitter, a photodiode as the optical receiver, an Arduino Nano microcontroller for data acquisition and signal processing, and an OLED display for real-time result presentation. During measurement, the user’s fingertip is placed between the LED and photodiode, allowing light to pass through the tissue. Variations in glucose concentration affect the absorption and scattering of NIR light, altering the intensity received by the photodiode. This analog voltage output is digitized using the Arduino’s ADC and converted into glucose levels through a calibration curve derived from reference readings taken using a commercial glucometer. Experimental evaluation was conducted on five human subjects under two physiological conditions—before meals (preprandial) and after meals (postprandial). Each condition was measured three times to minimize variability caused by movement or environmental light interference. The photodiode sensor readings were compared against glucometer results to assess accuracy. The system achieved an average accuracy of 87.1%, with individual measurements ranging from 79.2% to 96.9% before meals and 88.9% to 98.2% after meals. Statistical analysis revealed a mean absolute error (MAE) of 9.83 mg/dL and a correlation coefficient (R²) of 0.934, indicating a strong linear relationship between the two measurement methods. Notably, the system tended to slightly overestimate glucose levels before meals and underestimate them after meals, which may be attributed to physiological variations and optical path differences. The results demonstrate that the proposed photodiode-based NIR sensing system is a promising, low-cost, and user-friendly alternative to conventional invasive glucose monitoring. With further improvements in calibration algorithms, sensor placement stability, and ambient light shielding, this approach has the potential to be integrated into wearable devices, enabling continuous glucose tracking and improving patient adherence to self-monitoring routines.
Information Security Risk Analysis Using ISO 31000:2018 and ISO 27001:2022 Ulya, Athiyatul; Karima, Annisa; Sukiman, T. Sukma Achriadi; Zulfia, Anni; Rahmawati, Rafika
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6564

Abstract

Information system risk audits are an important step in ensuring the security, effectiveness, and efficiency of the systems used by organizations. However, the fast advancement of information and communication technologies has made information?security threats more intricate, arising not only from internal sources like employee carelessness but also from external sources such as cyber?attacks, malware, and data?theft. This study aims to analyze information security risks at the Central Statistics Agency (BPS) of Lhokseumawe by referring to two international standards, namely ISO/IEC 27001:2022 and ISO 31000:2018. The research approach used is descriptive qualitative with a case study method. Data collection techniques were conducted through interviews, observations, and document studies. The results of the study indicate that there are still various security gaps, both technical and non-technical, such as weak system authentication, the absence of adequate security policies, and the lack of incident handling procedures. This study successfully compiled a risk register containing 30 types of risks along with their causes, impacts, likelihood levels, and relevant mitigation recommendations. Improvement recommendations include strengthening technical controls, updating information security policies, enhancing human resource capacity, and conducting regular internal audits. The results of this study are expected to serve as a reference for strengthening information security systems in a systematic and standardized manner within the BPS environment.
Twitter Sentiment Analysis on the Iran-Israel Conflict Using the Naïve Bayes Classification Algorithm Karima, Annisa; Ulya, Athiyatul; Achriadi, Teuku Sukma; Zufia, Anni
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26093

Abstract

The armed conflict between Iran and Israel, which has attracted global attention, has sparked various public reactions, including from the Indonesian community. Given its potential impact on global social and economic stability, it is important to systematically analyze public perceptions using a sentiment analysis approach. A total of 310 tweets were collected through a crawling process and processed using several preprocessing stages, such as text cleaning, normalization, stopword removal, tokenization, stemming, and translation. Labeling was performed directly using the Naive Bayes algorithm, by comparing three algorithms: Gaussian Naive Bayes, Multinomial Naive Bayes, and Bernoulli Naive Bayes. Performance evaluation was conducted using metrics such as accuracy, precision, recall, and F1-score. The classification results showed that Multinomial Naive Bayes achieved an accuracy of 75.81%, Gaussian Naive Bayes achieved 77.42%, while Bernoulli Naive Bayes achieved 87.1%. Bernoulli Naive Bayes demonstrated superior performance in handling textual data with word frequency representation. This study contributes to strengthening the use of machine learning methods for public opinion analysis on social media, particularly in the context of geopolitical issues. The findings indicate that Bernoulli Naive Bayes is more suitable for classifying public opinion texts compared to the Gaussian and Multinomial variants.
Decision Support System for Land Suitability Assessment of Horticultural Crops of Legume Commodities Using AHP-VIKOR Ilham Sahputra; Rizky Putra Phonna; Natasya Natasya; Annisa Karima; T. Sukma Achriadi Sukiman
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 4 No. 2 (2024): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v4i2.979

Abstract

This Decision Support System (DSS) is designed to evaluate land suitability for horticultural crops, specifically legumes, using a combination of Analytical Hierarchy Process (AHP) and VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) methods. The system aids farmers in determining the appropriate crops based on the available land conditions. The research includes problem identification, literature review, data collection, and system design. The implementation of the AHP-VIKOR methods has proven effective and accurate in providing horticultural crop recommendations. This system adds value to modern and efficient agricultural land management. The research results show that the AHP-VIKOR methods successfully applied in determining the suitability of land for legumes in the areas of Bireun, Bukit Rata, Sawang, and Pesisir Pelabuhan Kreung Geukuh with satisfactory outcomes. Therefore, the AHP-VIKOR methods are considered optimal for weighting criteria and ranking alternatives in selecting land for legume crops
Pengabdian Kepada Masyarakat: Rancang Bangun Sistem Monitoring Kualitas Air pada Kolam Ikan guna Meningkatkan Produktivitas dan Ekonomi Masyarakat Pesisir Ula, Mutammimul; Erliana, Cut Ita; Ulya, Athiyatul; Zulfia, Anni; Karima, Annisa; Sukiman, T Sukma Achriadi
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.v3i9.3475

Abstract

Pengabdian kepada masyarakat di Desa Pesisir, Kota Lhokseumawe, difokuskan pada penguatan kapasitas petani ikan melalui rancang bangun dan implementasi sistem monitoring kualitas air kolam berbasis digital. Kegiatan ini melibatkan petani ikan lokal dalam pelatihan edukatif-partisipatif, mencakup pemahaman parameter kualitas air, penggunaan sensor digital, dan pemantauan secara real-time. Hasil kegiatan menunjukkan peningkatan pengetahuan dan keterampilan peserta dalam mengelola kolam secara berbasis data, serta kemampuan melakukan intervensi yang tepat untuk menjaga kesehatan ikan dan meningkatkan produktivitas kolam. Selain dampak teknis dan produktivitas, program ini membangun literasi teknologi, respons adaptif terhadap perubahan lingkungan, dan budaya kolaboratif di komunitas pesisir. Hasil pengabdian ini menunjukkan bahwa pendekatan partisipatif berbasis teknologi dapat menjadi model berkelanjutan untuk meningkatkan kesejahteraan sosial-ekonomi, praktik budidaya adaptif, dan transformasi komunitas melalui pemanfaatan teknologi tepat guna.
Co-Authors ANNISA KARIMA Asmaidi Asmaidi Ayu Widari, Lis Cut Agusniar Cut Ita Erliana Damia, Zayyani Fardiansyah Adami Fidyatun Nisa Ginting, Depi Hardisal, Hardisal Ilfa, Tasya Nadhira Ilham Sahputra M. Arinal Ihsan M. Sulthan Hanafi Manurung, Ericky Benna Perolihin Muhammad Zarlis, Muhammad Mutammimul Ula MUTHMAINNAH Natasya Natasya Rafika Rahmawati Rizal, Reyhan Achmad Rizky Putra Phonna Rizky, Muharratul Mina Sahputra, Ilham Saib Suwilo Salamah Sandy, Cut Lika Mestika Sera Delta Tanjung Syahputra, Dinur Syukriah Syukriah, Syukriah Ulya, Athiyatul Veri Ilhadi Wahyu Fuadi Yurni, Irma Zufia, Anni Zulfia , Anni