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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Brilliance: Research of Artificial Intelligence SIGEH ELT : Journal of Literature and Linguistics Jurnal Malikussaleh Mengabdi Jurnal Teknologi Rekayasa Informasi dan Komputer
Karima, Annisa
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Mathematics Social Sciences Other

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A GENRE-BASED DISCOURSE ANALYSIS: CHRISTMAS INVITATION LETTER IN GKPS INDONESIA Karima, Annisa; Saragih, Frans Dhaniko Cristian; Priyatama, Muhammad Rangga; Simorangkir, Nico Sahpudan; Zein, T. Thyrhaya
SIGEH ELT : Journal of Literature and Linguistics Vol 5, No 1 (2025): SIGEH ELT : Journal of Literature and Linguistics
Publisher : Universitas Muhammadiyah Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36269/sigeh.v5i1.2968

Abstract

This study examines the genre-based discourse of Christmas invitation letters within the Simalungun Christian Church (GKPS) in Indonesia. Using Swales' (1990) genre move analysis and the multimodal approach of Kress and Van Leeuwen (1996), the study identifies six key moves present in the structure of the invitations: opening, congratulating the recipient, stating the purpose and message, providing event details, making formal requests, and concluding with official signatures. These moves highlight how the invitations not only communicate event information but also reflect Christian religious values and Indonesian cultural norms. The analysis underscores the importance of language and visual elements in conveying social and religious unity within the community. This research contributes to a broader understanding of how genre functions within religious and cultural contexts
PKM Strategi Pengembangan Teknologi Informasi Dalam Pemasaran Digital Di Gampong Kota Lhokseumawe ilhadi, veri; Karima, Annisa; Afra, Liza; Ulya, Athiyatul; Maulani, Emi; Amna, Khairul
Jurnal Malikussaleh Mengabdi Vol. 3 No. 2 (2024): Jurnal Malikussaleh Mengabdi, Oktober 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i2.20425

Abstract

Teknologi informasi menjadi faktor kunci dalam transformasi berbagai sektor, termasuk pemasaran UMKM di era digital untuk Gampong  kota lhokseumawe. Gampong  dengan potensi ekonomi UMKM yang sedang berkembang sampai dengan berkembang yang menjadi tantantang dalam usaha dan dapat memanfaatkan strategi pemasaran digital secara optimal. Pengabdian ini bertujuan untuk merancang Strategi Pengembangan Sistem Informasi untuk mendukung pemasaran digital UMKM di tingkat Gampong . Metode yang digunakan penerapan sistem informasi berbasis web dan media sosial untuk meningkatkan jangkauan pasar, efisiensi transaksi, dan daya saing produk. Fokus utama adalah penerapan sistem informasi berbasis web dan media sosial untuk meningkatkan jangkauan pasar, efisiensi transaksi, dan daya saing produk. Hasil pengabdian ini menunjukkan bahwa integrasi teknologi informasi dengan strategi pemasaran digital dan ekonomi kreatif dapat membantu UMKM Gampong  meningkatkan pendapatan, memperluas pangsa pasar, dan menciptakan peluang inovasi baru. Penelitian ini memberikan rekomendasi langkah-langkah dalam penerapan sistem informasi untuk mendukung pemasaran digital, meliputi pelatihan pelaku UMKM, optimalisasi media sosial, dan pengembangan konten kreatif sebagai elemen kunci keberhasilan di era digital.
Prediction of Crime Cases in 2025 in India Using the Fuzzy Time Series Chen Model Method karima, Annisa; Zulfia, Anni; Sukiman, T. Sukma Achriadi; Ulya, Athiyatul
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5745

Abstract

India's natural beauty and culture, which attract the attention of international tourists, are less able to increase tourist visits due to high crime cases. Tourists' fear of visiting the country has a direct impact on decreasing economic turnover, so the local economy has become very low. Predictions of criminal cases aim to provide an overview of cases that will occur in the next period, therefore the government can take appropriate policies to reduce crime cases. These predictions enable policymakers to plan strategic and data-based preventive measures. The method used is the Fuzzy Time Series Model Chen, because this method can overcome data uncertainty, and offers simplicity and ease in application. Valid and credible criminal statistics data in India is obtained from the site www.kaggle.com. A trusted platform that provides various quality datasets. This data will be used as a basis for the analysis and prediction of criminal cases in India. The results of this research show that in the range of 60 months from January 2020 to December 2024 using the Fuzzy Time Series Chen Model method to predict the number of criminal cases in India produced predictions in January 2025 with cases of 188.36 cases with a MAPE error ratio of 9.08% which is included in outstanding forecasting category.
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.
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.
PERANCANGAN SISTEM INFORMASI ADMINISTRASI TERPADU BERBASIS WEBSITE UNTUK MANAJEMEN DATA AKADEMIK DAN KEGIATAN MAHASISWA DI PRODI SISTEM INFORMASI UNIVERSITAS MALIKUSSALEH MENGGUNAKAN METODE PENGEMBANGAN AGILE Nisa, Fidyatun; Darma, Ade; Karima, Annisa
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3885

Abstract

Program Studi Sistem Informasi Universitas Malikussaleh masih mengelola data secara manual dan terpisah, seperti melalui Google Drive dan Google Forms, yang menyebabkan ketidakteraturan, keterlambatan akses, dan potensi kesalahan input. Untuk mengatasi hal ini, dikembangkan Sistem Informasi Administrasi Terpadu berbasis web menggunakan metode Agile dengan pendekatan Extreme Programming (XP). Pengembangan dilakukan melalui tahap perencanaan, perancangan, pengkodean, dan pengujian, menggunakan ReactJS, ExpressJS, serta pengujian Black Box dan User Acceptance Testing (UAT). Hasilnya adalah sistem real-time yang mendukung pengelolaan data akademik, kegiatan mahasiswa, dan informasi prodi secara terstruktur. Pengujian menunjukkan sistem ini memenuhi kebutuhan pengguna, meningkatkan efisiensi kerja, serta mendukung pengambilan keputusan berbasis data.
Rancang Bangun Prototype Smart Dispenser Berbasis IoT (Internet Of Things) Karima, Annisa; Nasir*, Muhammad; Mursyidah, Mursyidah
Jurnal Teknologi Rekayasa Informasi dan Komputer Vol 4, No 1 (2021): JURNAL TRIK - POLITEKNIK NEGERI LHOKSEUMAWE
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jtrik.v4i1.2580

Abstract

Sistem yang ada pada dispenser saat ini banyak yang masih secara manual, itu dianggap kurang menguntungkan dikarenakan sering orang lupa untuk mematikan keran dispenser sementara air didalam gelas sudah penuh terisi sehingga air bisa tumpah dan terbuang sia-sia. Kemudian Penggunaan dispenser bukan saja digunakan sebagai peralatan rumah tangga namun juga digunakan pada perkantoran dan perusahaan, Pada perkantoran dan perusahaan besar tersedia dispenser pada setiap ruangan hal ini menjadi sebuah kendala bagi Office Boy dalam mengontrol ketersedian air galon pada setiap ruangan disetiap harinya, dengan begitu waktu yang seharusnya digunakan untuk mengerjakan hal-hal lainnya menjadi terbuang karena pengontrolan secara manual. Penerapan Iot (Internet of things) pada dispenser ini bertujuan untuk memberikan kemudahan pada pekerjaan Office boy dalam proses pengontrolan ketersediaan air pada galon dispenser disetiap ruangan kantor dan mengurangi rasa khawatir bagi pengguna akan terjadi tumpahan air karena terisi terlalu penuh saat ditinggal ketika pengisian air dengan sendirinya. Hardware yang digunakan adalah sensor ultrasonik sebagai pengukur ketinggin air didalam galon dispenser sehingga ketika air galon sudah habis maka sensor ultrsonik akan memberi perintah kepada wemos untuk mengirim notifikasi melalui aplikasi Telegram kemudian pada dispenser terdapat sensor ultrasonik untuk mendeteksi adanya gelas , saat sensor ultrasonik telah mendeteksi adanya gelas maka Motor DC akan memompa atau menarik air dari galon agar air dapat keluar mengisi gelas, setelah air terisi penuh maka pompa akan mati dan berhenti mengisi air kedalam gelas. Berdasarkan hasil pengujian delay waktu yang dibutuhkan dispenser untuk menuangkan air kedalam gelas berukuran 230 ml ialah 9 detik. Pada monitoring ketersedian air galon jarak sensor dengan permukaan air galon 5cm air dalam kondisi penuh dan saat jarak sensor dengan permukaan air galon 25cm air dalam kondisi habis pada kondisi tersebut Office boy akan menerima notifikasi melalui aplikasi telegram bahwa air telah habis. Perbandingan jarak ukur sensor ultrasonik dengan penggaris memiliki kesalahan sebesar  0%-10%. Dari hasil pengujian rata-rata nilai persentase error sistem dijalankan sebesar 30% dan rata-rata persentase nilai akurasi alat sebesar 70%.
Co-Authors Achriadi, Teuku Sukma Afra, Liza Damia, Zayyani Darma, Ade Emi Maulani Fidyatun Nisa Ilfa, Tasya Nadhira Khairul Amna, Khairul Mursyidah Mursyidah Nasir*, Muhammad Priyatama, Muhammad Rangga Rafika Rahmawati Rizky, Muharratul Mina Saragih, Frans Dhaniko Cristian Simorangkir, Nico Sahpudan Sukiman, T. Sukma Achriadi T. Thyrhaya Zein Ulya, Athiyatul Veri Ilhadi Zufia, Anni Zulfia, Anni