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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Computer Networks, Architecture and High Performance Computing Brilliance: Research of Artificial Intelligence Ulead : Jurnal E-pengabdian
Simamora, Windi Saputri
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Development of Android-Based Smart System for Gingivitis Diagnosis Using Certainty Factor Hadistio, Ryan Rinaldi; Simamora, Windi Saputri; Muis, Abdul
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13361

Abstract

Gingivitis is a gum disease that causes bleeding, swelling, redness, discharge, changes in normal contours, and although health authorities take this seriously, sometimes some patients consider it normal. This study aims to educate the public about the importance of understanding the condition of their bodies, especially the most vulnerable teeth. Lack of time to consult an expert leads to this disease being neglected. Therefore, it is necessary to develop a consultation application in the form of an expert system. The built system adopts the deterministic factor method. The certainty factor works by reading the entire data submitted by the expert and giving the result as a percentage of confidence that the patient has gingivitis. The experts used in this system are dental experts. Data obtained from direct experts and consultations resulted in new knowledge in the form of the percentage of trust patients suffering from gingivitis. The data collected are symptoms and solutions obtained from experts. This research provides a new service for patients suffering from gingivitis without the need to see a specialist directly. Based on the testing data provided to the patient and based on the patient's condition at that time, the test results of the system reached a confidence level of 98.74%. So that the results of consultation are obtained in the form of information about the disease and the solutions needed.
Edukasi Kesadaran Keamanan Data/Informasi dan Bermedia Digital pada Siswa/i SMA Kemala Bhayangkari Medan Simamora, Windi Saputri; Harahap, Siti Sarah; Hadistio, Ryan Rinaldi
ULEAD : Jurnal E-Pengabdian Volume 3 Nomor 1 Juli 2023
Publisher : Fakultas Ilmu Komputer, Universitas Katolik Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/ulead.v3i1.2797

Abstract

Dalam dunia digital yang semakin kompleks, penting bagi siswa/i untuk memiliki pemahaman yang baik tentang risiko-risiko yang terkait dengan penggunaan teknologi informasi dan media digital. Melalui penyuluhan dan workshop, siswa/i akan mendapatkan pemahaman praktis dan keterampilan dalam menghadapi risiko-risiko terkait keamanan data/informasi dan bermedia digital. Materi yang disampaikan meliputi pencurian identitas, penipuan online, privasi online, penipuan phishing, perbankan online, virus, tipuan email, dan praktik penggunaan internet yang aman. Selain itu, forum diskusi juga akan memberikan kesempatan bagi siswa/i untuk berdiskusi dan berbagi pandangan terkait keamanan data/informasi dan bermedia digital. Dengan menerapkan solusi-solusi tersebut, diharapkan siswa/i SMA akan memiliki pemahaman yang lebih baik tentang keamanan data/informasi dan bermedia digital. Mereka akan menjadi pengguna yang lebih bertanggung jawab dan cerdas dalam menghadapi risiko-risiko di dunia maya. Selain itu, kegiatan ini juga akan memberikan dampak positif yang luas dalam menciptakan lingkungan belajar yang aman dan produktif.
Implementation of Fuzzy Logic in Detecting Air Temperature Based on Microcontroller Harahap, Siti Sarah; Simamora, Windi Saputri; Hadistio, Ryan Rinaldi
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3023

Abstract

The environment, technology, and many facets of daily living are all significantly impacted by temperature conditions. Knowing environmental health, agriculture, industry, electrical technology, weather and natural disasters, transportation, and even scientific research are just a few of the many reasons why temperature conditions are crucial. Fuzzy algorithms are used to more flexibly process temperature data while creating a temperature detector employing fuzzy logic. We can base our conclusions on a wider range of criteria than merely right or wrong thanks to fuzzy logic. A temperature sensor, microprocessor, and display (such an LCD or LED screen) are some basic electronic components that can be used to create a temperature detector.
Analysis of the Multi Objective Optimization by Ratio Analysis (MOORA) Method in Determining Pilot Areas at PT. XYZ Simamora, Windi Saputri; Harahap, Siti Sarah; Idaman, Akbar; Simatupang, Septian
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4149

Abstract

This research analyzes the application of the Multi Objective Optimization by Ratio Analysis (MOORA) method model in determining the Pilot Area at PT XYZ. This method is used to evaluate various performance criteria, including customer satisfaction, productivity, service quality, and operational efficiency. Currently, the Pilot Area assessment and selection process at PT XYZ is still done manually, which causes a lack of accuracy and efficiency. MOORA was chosen for its ability to handle multi-criteria decision-making problems more systematically and objectively. The analysis results showed that Alternative Area 7 obtained the highest final score of 0.39, placing it as an area with superior performance. The application of MOORA is proven to improve accuracy and efficiency in the Pilot Area determination process, providing a more objective basis for decision-making. By using MOORA, PT XYZ can evaluate area performance more comprehensively and accountably. This research recommends that PT XYZ implement the MOORA method thoroughly and conduct periodic evaluations of the methods used. For theory development, PT XYZ can add specific evaluation criteria according to company needs. The implementation of these suggestions is expected to improve the quality of service and competitiveness of PT XYZ in the global market. Further research is expected to compare MOORA with other methods to strengthen the validity of the results. Thus, this research not only provides a practical contribution to PT XYZ but also adds academic insight into the application of multi-criteria optimization methods in the context of performance management and service improvement.
Pengamanan Citra Menggunakan Kombinasi Algoritma Kriptografi Hill Cipher dan Teknik Transposisi Segitiga Simamora, Windi Saputri; Efendi, Syahril; Nababan, Erna Budhiarti
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.4713

Abstract

Cara untuk mengamankan citra dapat dilakukan dengan kriptografi. Penelitian pada algoritma kriptografi sudah cukup banyak berkembang. Beberapa penelitian menyebutkan bahwa menggabungkan dua algoritma kriptografi dapat lebih meningkatkan keamanan dari citra dibandingkan dengan hanya satu algoritma. Penelitian ini melakukan enkripsi menggunakan kombinasi dua algoritma yaitu teknik transposisi segitiga dan Hill Cipher. Proses penggabungan dua algoritma dilakukan dengan terlebih dahulu mengenkripsi menggunakan teknik transposisi segitiga dan kemudian dilanjutkan dengan Hill Cipher. Begitu juga dengan proses dekripsi yang dilakukan secara kebalikannya. Pada penelitian ini menghasilkan performa yang lebih baik dibandingkan dengan menggunakan satu metode yang dapat dilihat pada nilai rata-rata MSE yang besar yaitu 10878,992 dan rata-rata PSNR yang kecil yaitu 0,781. Hal tersebut menandakan dengan menggabungkan dua algoritma dapat membuat pesan menjadi lebih aman. Metode dalam penelitian ini juga berhasil mengembalikan citra dangan baik tanpa adanya penambahan maupun pengurangan yang dapat dilihat dari hasil MSE dan PSNR yaitu 0 dan ∞.
Analysis of Factors Causing Toddler’s Malnutrition in Medan City Using the Random Forest Method Simamora, Windi Saputri; Harahap, Siti Sarah; Pratama, Andre
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15380

Abstract

Malnutrition and severe malnutrition in toddlers remain critical public health concerns that impair physical growth, cognitive development, and long-term productivity. Deficiencies in essential nutrients increase the risks of stunting, weakened immunity, and developmental delays. Although interventions such as supplementation and routine anthropometric monitoring are implemented, comprehensive identification of multidimensional causal factors is still limited, reducing the effectiveness of targeted policies. This study aims to predict toddler nutritional status using a quantitative data mining approach. A dataset consisting of 328 samples and 17 features was collected from health facilities in Medan City, including Puskesmas, the Health Office, and Posyandu. A Random Forest Classifier was developed with missing-value handling, feature engineering, and feature importance analysis to identify dominant predictors of nutritional outcomes. The model achieved an overall accuracy of 92.42 percent and showed strong performance in identifying the “Normal” class, although predictive sensitivity for minority classes such as “Gizi Kurang” and “Gizi Buruk” remained comparatively lower. Feature importance analysis indicated that complete immunization and health insurance ownership were the most influential determinants of nutritional status. This research provides a machine learning–based tool for early nutritional risk prediction and offers data-driven insights to support more precise malnutrition interventions. Future enhancement may include expanding feature diversity and applying advanced interpretability techniques to strengthen model reliability. The findings reinforce the importance of evidence-based nutrition policy strategies that prioritize early prevention and improved child health outcomes.
Security Evaluation of Indonesian LLMs for Digital Business Using STAR Prompt Injection Agnes Irene Silitonga; Irwandi, Hafiz; Silitonga, Agnes Irene; Rudy Chandra; Simamora, Windi Saputri
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15662

Abstract

The adoption of Large Language Models (LLMs) in digital business systems in Indonesia is rapidly increasing; however, systematic security evaluation against Indonesian language prompt injection remains limited. This study introduces the Indonesian Prompt Injection Dataset, consisting of 50 attack scenarios constructed using the STAR framework, which combines structured instruction variations with sociotechnical context to expose potential model vulnerabilities. The dataset was used to evaluate three commercial LLM platforms ChatGPT using a GPT-4 class lightweight variant (OpenAI), Gemini 2.5 Flash (Google), and Claude Sonnet 4.5 (Anthropic) through controlled experiments targeting instruction manipulation in Indonesian. The results reveal distinct robustness profiles across models. Gemini 2.5 Flash exhibits moderate observed resilience, with 76% of scenarios classified as medium risk and 12% as high risk. ChatGPT demonstrates higher observed robustness under the tested scenarios, with 88% of cases classified as low risk and no high-risk outcomes. Claude Sonnet 4.5 shows intermediate observed resilience, with 72% low-risk and 28% medium-risk scenarios. High-risk cases primarily involve direct role override, urgency- or emotion-based prompts, and anti-censorship instructions, while structural ambiguities and multi-intent manipulations tend to result in medium risk, and mildly persuasive prompts fall under low risk. These findings suggest that while contemporary LLM defense mechanisms are effective against explicit attacks, contextual and emotionally framed manipulations continue to pose residual security challenges. This study contributes the first Indonesian-language prompt injection dataset and demonstrates the STAR framework as a practical and standardized approach for evaluating LLM security in digital business applications.
Pemberdayaan ekonomi ibu rumah tangga Desa Pasar Melintang melalui pemanfaatan teknologi informasi dan kecerdasan buatan Simamora, Windi Saputri; Harahap, Siti Sarah; Pratama, Andre
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 2 (2026): April (In Progress)
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i2.38823

Abstract

Abstrak Desa Pasar Melintang di Kecamatan Lubuk Pakam merupakan wilayah dengan mayoritas masyarakat yang menggantungkan hidup pada sektor pertanian padi sawah. Namun, keterbatasan akses informasi dan rendahnya literasi digital, khususnya pada kalangan ibu rumah tangga, menghambat optimalisasi pemanfaatan teknologi informasi dan Artificial Intelligence (AI) dalam mendukung aktivitas ekonomi produktif. Program pengabdian ini bertujuan untuk: (1) meningkatkan literasi digital dasar, (2) mengembangkan keterampilan pemasaran digital berbasis media sosial, dan (3) meningkatkan kemampuan pemanfaatan AI untuk mendukung kegiatan ekonomi rumah tangga. Metode yang digunakan adalah Participatory Action Research (PAR) yang melibatkan partisipasi aktif masyarakat dalam setiap tahapan, meliputi identifikasi kebutuhan melalui diskusi dengan perangkat desa, perencanaan program berbasis kebutuhan peserta, pelaksanaan pelatihan berbasis praktik langsung, evaluasi menggunakan pre-test dan post-test, serta penyusunan tindak lanjut. Pelatihan mencakup penggunaan media sosial untuk pemasaran serta pemanfaatan tools AI seperti ChatGPT dan Canva AI dalam pembuatan konten promosi. Hasil menunjukkan adanya peningkatan pemahaman peserta yang signifikan, ditandai dengan kenaikan nilai rata-rata dari 65,45 pada pre-test menjadi 80 pada post-test. Selain itu, peserta juga mengalami peningkatan keterampilan dalam membuat konten digital dan memanfaatkan AI untuk promosi usaha. Program ini berkontribusi terhadap pemberdayaan ekonomi melalui perluasan peluang peningkatan pendapatan berbasis pemasaran digital. Temuan ini menunjukkan bahwa pendekatan partisipatif yang kontekstual efektif dalam meningkatkan literasi digital serta mendorong pembangunan desa yang lebih adaptif terhadap transformasi digital. Kata kunci: literasi digital; teknologi informasi; kecerdasan buatan; pemberdayaan masyarakat; ibu rumah tangga. Abstract Pasar Melintang Village in Lubuk Pakam District is an area where most residents rely on rice farming as their primary livelihood. However, limited access to information and low digital literacy, particularly among housewives, hinder the optimal use of information technology and Artificial Intelligence (AI) in supporting productive economic activities. This community service program aims to: (1) improve basic digital literacy, (2) develop social media-based digital marketing skills, and (3) enhance the use of AI to support household economic activities. The method used is Participatory Action Research (PAR), involving active community participation in all stages, including needs identification through discussions with village officials, program planning based on participants’ needs, hands-on training implementation, evaluation using pre-test and post-test instruments, and follow-up planning. The training covered social media utilization for marketing and the use of AI tools, such as ChatGPT and Canva AI, for creating promotional content. The results show a significant improvement in participants’ understanding, indicated by an increase in the average score from 65.45 in the pre-test to 80 in the post-test. Participants also improved their skills in creating digital content and utilizing AI for business promotion. The program contributes to economic empowerment by expanding opportunities to increase income through more effective digital marketing. These findings suggest that a contextual and participatory approach effectively enhances rural digital literacy and supports more adaptive village development in the digital era. Keywords: digital literacy; information technology; artificial intelligence; community empowerment; housewives.
Co-Authors Abdul Muis Agnes Irene Silitonga Akbar Idaman Efendi, Syahril Erna Budhiarti Nababan Hadistio, Ryan Rinaldi Irwandi, Hafiz Pratama, Andre Rudy Chandra Simatupang, Septian Siti Sarah Harahap