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All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Multica Science and Technology Brilliance: Research of Artificial Intelligence Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Malikussaleh Mengabdi
Ulya, Athiyatul
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Mathematics Physics Social Sciences Other

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Prediction of Shrimp Sales Using the ARIMA (AutoRegressive Integrated Moving Average) Method at UD Udang Makmur Peureulak Veri Ilhadi; Muliana Muliana; Zulfia , Anni; Ulya, Athiyatul; Sahputra , Ilham
Multica Science and Technology 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.v4i2.978

Abstract

UD. Udang Makmur is a shrimp farming business that often faces challenges in accurately predicting sales stock due to reliance on manual forecasting methods. This study aims to develop a web-based sales prediction application utilizing the AutoRegressive Integrated Moving Average (ARIMA) method. The application uses daily sales data from January to December 2023 for analysis. The results indicate that the ARIMA (2,1,1) model delivers accurate predictions, achieving a Mean Squared Error (MSE) of 0.264295. Forecasts for the next 24 periods demonstrate a stable projection, with predicted values converging around 2.5 and a narrow 95% confidence interval. These findings highlight the model's reliability and low uncertainty for the forecasted time frame. The application was successfully tested using the Black-Box method, confirming its functionality and effectiveness in supporting sales predictions.
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.
Peningkatan Literasi Kesehatan Mental di Pesantren Budi Luhur Bogor Khusnia, Alfun; Ulya, Athiyatul; Rahmah , Siti; Elbasyarah, May Salwa
Jurnal Penyuluhan dan Pemberdayaan Masyarakat Vol. 4 No. 2 (2025): Jurnal Penyuluhan dan Pemberdayaan Masyarakat (Mei)
Publisher : CV. Era Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59066/jppm.v4i2.1277

Abstract

Masalah kesehatan mental menjadi isu yang semakin mengkhawatirkan, termasuk di lingkungan pesantren. Pesantren sebagai lembaga pendidikan Islam menghadapi tantangan besar dalam merespons kondisi ini, mengingat masih rendahnya pemahaman tentang kesehatan mental, kuatnya stigma, dan terbatasnya akses terhadap layanan psikologis profesional. Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan literasi dan kesadaran tentang kesehatan mental di kalangan santri di Pesantren Budi Guna, Bogor, melalui pendekatan berbasis nilai-nilai Al-Qur’an. Kegiatan ini dilaksanakan dengan pendekatan partisipatif, mencakup sosialisasi, pelatihan deteksi dini gangguan mental dan diskusi interaktif. Objek kegiatan ini adalah santri di pesantren Budi Guna, Bogor. Hasil kegiatan menunjukkan peningkatan pemahaman santri tentang konsep dasar kesehatan mental dan gejalanya. Internalisasi ajaran Al-Qur’an seperti dzikir (QS. Ar-Ra’d: 28), sabar dan tawakal (QS. Al-Baqarah: 286; QS. Ali Imran: 159), serta optimisme dalam menghadapi kesulitan (QS. Al-Insyirah: 5–6), terbukti efektif membangun ketenangan psikologis dan ketahanan spiritual. Kegiatan ini merekomendasikan perlunya program pembinaan berkelanjutan guna meningkatkan literasi kesehatan mental. Dengan demikian, pesantren dapat menjadi lingkungan pendidikan yang mendukung kesejahteraan mental santri secara holistik dan berkelanjutan.
Pengembangan Rencana Strategis Sistem Informasi Asrama Mahasiswa Nusantara Berbasis Framework Anita Cassidy Rahmawati, Rafika; Arini, Diandra Diva; Nurlaili, Aisma; Septiani, Berlian Viga; Ulya, Athiyatul
Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.393

Abstract

Perkembangan IS/IT menuntut seluruh lembaga organisasi dan bisnis, termasuk lembaga pendidikan dan asrama mahasiswa, untuk memiliki sistem informasi yang strategis dan terintegrasi untuk menunjang kegiatan operasional dan pencapaian visi misi organisasi. Asrama Mahasiswa Nusantara (AMN) Surabaya menghadapi tantangan dalam pengelolaan sistem informasi yang belum terintegrasi dan strategis, sehingga menghambat efektivitas layanan operasional dan pencapaian visi organisasi. Untuk mengatasi masalah tersebut, perencanaan strategis sistem informasi dengan menggunakan framework Anita Cassidy yang berfokus pada penyelarasan sistem informasi dengan tujuan bisnis. Proses perencanaan strategis SI dengan Anita Cassidy meliputi tahapan visioning, analysis, direction, dan recommendation. Pengumpulan data dilakukan melalui wawancara dan analisis strategis melibatkan tools pendukung seperti SWOT, Value Chain, Porter's Five Forces, dan McFarlan Strategic Grid. Penelitian menghasilkan solusi strategis sistem informasi yang disusun dalam roadmap pengembangan 5 tahun dengan skala prioritas berdasarkan ketergantungan sistem, nilai bisnis, risiko, serta estimasi biaya dan waktu. Rencana strategis ini diharapkan menjadi pedoman pengembangan sistem informasi yang berkelanjutan dan sejalan dengan visi AMN Surabaya.
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.
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.
Co-Authors Achriadi, Teuku Sukma Afra, Liza Arini, Diandra Diva Elbasyarah, May Salwa Emi Maulani Karima, Annisa Khairul Amna, Khairul Khusnia, Alfun Muliana Muliana Nurlaili, Aisma Rafika Rahmawati Rafika Rahmawati Rahmah , Siti Rizky, Muharratul Mina Sahputra , Ilham Septiani, Berlian Viga Sukiman, T. Sukma Achriadi Veri Ilhadi Zufia, Anni Zulfia , Anni Zulfia, Anni