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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Abdi Ilmu International Journal of Advances in Data and Information Systems Indonesian Journal of Education, Social Sciences and Research (IJESSR) Jurnal Ilmiah MADIYA: Masyarakat Mandiri Berkarya International Journal of Research in Vocational Studies (IJRVOCAS) Majalah Iptek Politeknik Negeri Medan Polimedia Internasional Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) Journal Global Technology Computer Jurnal Pengabdian Barelang Komposit : Jurnal Pengabdian Dan Pemberdayaan Masyarakat Journal of Computer Science Advancements
Husna, Meryatul
Politeknik Negeri Medan
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Digitalisasi UKMK Rumah Indonesia Kecamatan Medan Baru Kota Medan Sumatera Utara Ajulio Padly Sembiring; Meryatul Husna; Sharfina Faza; Silmi, Silmi; Rina Anugrahwaty
Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 2 No. 1 (2024): Edisi Juni
Publisher : Jurusan Teknik Sipil, Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/komposit.v2i1.1495

Abstract

UKM Rumah Indonesia adalah sebuah Usaha Kecil dan Menengah yang bergerang dalam bidang kerajinan, seperti pakaian adat, simbol-simbol adat di sumatera utara. UKM Rumah Indonesia sudah memesarkan produknya cukup luas namun pasar yang menjadi konsumen dari UKM ini masih sangat terbatas karena kurangnya informasi dan kurang menariknya kemasan yang di gunakan UKM Rumah Indonesia, dari ini akan di bangun sebuah metode pemasaran yang baik dan efektif untuk meningkatkan penjualan dan meningkatkan kualitas kemasan untuk setiap produk yang di hasilkan UKM Rumah Indonesia.
Predictive Analytics for IMDb Top TV Ratings: A Linear Regression Approach to the Data of Top 250 IMDb TV Shows Husna, Meryatul; Purba, Lampson Pindahaman; Rinaldy, Muhammad Eri; Lubis, Arif Ridho
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.7600

Abstract

In the era of a growing entertainment industry, understanding audience preferences and predicting the financial performance of entertainment products such as films and television shows has become increasingly important. Previous research has demonstrated various approaches in understanding the factors that influence the financial performance of entertainment products. However, there is still a need for research to investigate other aspects of film and television show evaluation. This study aims to explore the contribution of linear regression in analysing the ratings and financial performance of IMDb's top TV shows. Through the incorporation of various data-informed and interpretative approaches, it is expected to gain a deeper understanding of the factors that influence the success of a television show. Using data from the Top 250 IMDb TV Shows, a predictive analysis was conducted to understand the relationship between the number of episodes and IMDb ratings. The results of the information showed a negative relationship between the number of episodes and IMDb rating, with the linear regression model predicting a decrease in IMDb rating as the number of episodes increases. Implications of this research include recommendations for content creators to consider both quality and quantity of content in the development of TV shows.
APLIKASI DIAGNOSA PENYAKIT TANAMAN BUAH MENGGUNAKAN METODE RULE BASED REASONING Husna, Meryatul; Faza, Sharfina; Lukcyhasnita, Andam; Yusnida, Yuyun; Siregar, Mhd. Ikhsan P.
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2326

Abstract

Produktivitas tanaman buah di Indonesia, seperti mangga, sering kali terancam oleh berbagai penyakit yang dapat menurunkan kualitas dan kuantitas hasil panen, serta menyebabkan kerugian ekonomi bagi petani. Identifikasi dini penyakit sangat penting, namun tidak semua petani memiliki pengetahuan yang memadai untuk melakukan diagnosa yang akurat. Penelitian ini bertujuan untuk mengembangkan sebuah aplikasi berbasis web yang menggunakan metode Rule-Based Reasoning (RBR) dalam mendiagnosa penyakit tanaman mangga berdasarkan gejala yang diamati. Aplikasi ini dirancang untuk memberikan diagnosa yang akurat dan cepat, serta rekomendasi penanganan yang tepat, melalui antarmuka yang mudah digunakan oleh petani. Data untuk sistem ini diperoleh dari survei lapangan, sementara pengujian sistem dilakukan melalui metode blackbox untuk mengevaluasi akurasi dan keandalannya. Hasil pengujian menunjukkan bahwa sistem memiliki tingkat akurasi sebesar 80%, dengan potensi peningkatan melalui pengumpulan data tambahan dan pengembangan lebih lanjut. Sistem ini diharapkan dapat meningkatkan produktivitas tanaman buah lokal, khususnya mangga, serta mendukung kesejahteraan petani dengan solusi yang praktis dan efisien.
Implementation of 3D IoT Mapping Tourism in Identifying Green Tourism Potential Hasibuan, Annalisa Sonaria; Chan, Andi Supriadi; Destiadi, Rezha; Husna, Meryatul
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 4 (2024): IJRVOCAS - Special Issues - International Conference on Science, Technology and
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i4.376

Abstract

Tourism is a key sector in Indonesia's economic development, contributing significantly to national growth. With a target of generating USD 30 billion in foreign exchange and attracting 22.3 million international tourists by 2024, the sector aligns with the 2020-2024 RPJMN narrative to strengthen economic resilience. Emphasizing sustainable and green tourism, Indonesia promotes eco-green principles to reduce environmental impacts, conserve natural and cultural heritage, and empower local communities. The study highlights the use of Internet of Things (IoT) and 3D mapping technologies to enhance tourism management and promotion, focusing on Lingga Village in Karo Regency, North Sumatra. These innovations aim to present spatial data interactively, improving accessibility and tourist experiences. Survey results show that 85.4% of respondents strongly support the use of 3D modeling for tourism promotion and education. Despite its potential, challenges such as limited budgets, small sample sizes, and community engagement remain obstacles. This research underlines the importance of integrating green tourism, technology, and sustainable practices to achieve equitable regional growth and environmental conservation in Indonesia.
Implementasi Metode Rule-Based dalam Sistem Pakar Pemilihan Program Studi Menggunakan Bahasa Prolog Faza, Sharfina; Rizka, Ade; Husna, Meryatul; Anugrahwaty, Rina; Fawwaz, Insidini
Journal Global Technology Computer Vol 4 No 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i2.7293

Abstract

The alignment between study programs and students' interests and abilities is a crucial factor in academic success at the university level. Unfortunately, many prospective students face confusion when choosing majors due to limited knowledge about the characteristics of each program and its relationship with career prospects, potentially affecting their academic performance and career paths. To address this challenge, our research presents a solution in the form of a rule-based expert system developed using Prolog language. This system is designed to provide study program recommendations through analysis of user responses to various structured questions. Using score calculation methods and matching against established value parameters, the system can propose the most relevant majors among four options: Computer Engineering (CE), Information Management (MI), Multimedia Graphics Engineering Technology (TRMG), and Software Engineering Technology (TRPL). Through this implementation, prospective students receive recommendations aligned with their potential and interests, facilitating more accurate decision-making. In addition to functioning as an assistive instrument in career and academic counseling for high school students, this research also lays the foundation for the development of more sophisticated expert systems with enhanced assessment weights and precision levels in the future.
Penerapan Teknologi Digital Pada UMKM Gerai Jajan Hana Sei Kambing Kecamatan Medan Sunggal Kota Medan Sumatera Utara Sembiring, Ajulio Padly; Husna, Meryatul; Marliana Sari; Rina Anugrahwaty; Wiwin Sry Adinda Banjarnahor
Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 3 No. 1 (2025): Edisi Juni
Publisher : Jurusan Teknik Sipil, Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/komposit.v3i1.1998

Abstract

Pemanfaatan teknologi digital pada Usaha Mikro, Kecil dan Menengah Gerai Jajan Hana akan sangat membantu memperluas jangkauan pasar yang akan berdampak pada meningkatnya penjualan Usaha Mikro, Kecil dan Menengah Gerai Jajan Hana, manajemen operasional, pembukuan keuangan dan tata kelola yang lebih baik. Dengan hadirnya tim pengabdian ini telah dapat membantu Usaha Mikro, Kecil dan Menengah dalam proses digitalisasi produk dan tata kelola operasional dan keuangan yang cepat dan tepat. Teknologi yang diberikan berupa sebuah website mandiri yang dapat dikelola mandiri oleh mitra pengabdi, dimana isi dari website dapat disesuaikan dengan kebutuhan mitra, baik untuk katalog atau daftar produk yang ditawarkan maupun untuk pengelolaan manajemen pelanggan. Dengan penerapan teknologi digital ini sangat diharapkan akan banyak membantu mitra dalam meningkatkan omset penjualannya yang berujung pada meningkatnya kesejahteraan mitra dan karyawan yang terlibat didalamnya. Hasil pada pengabdian ini adalah sebuah website informasi, pembukuan digital, pelatihan digital marketing dan memberikan alat berupa hardware yang dapat mendukung aktivitas digitalisasi.
Digitalisasi Data Pengurus dan UMKM Dampingan Asosiasi Pendamping Usaha Mikro Cooperative Indonesia (PUMIKOP) Kota Medan Sumatera Utara Meryatul Husna; Sharfina Faza; Rina Anugrahwaty; Julham, Julham; Sembiring, Ajulio Padly
Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 3 No. 1 (2025): Edisi Juni
Publisher : Jurusan Teknik Sipil, Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/komposit.v3i1.1999

Abstract

Kecepatan kinerja sebuah organisasi tidak lepas dari peranan teknologi informasi, begitu juga halnya dengan Asosiasi Pendamping Usaha Mikro Cooperative Indonesia (PUMIKOP) SUMUT. Pengelolaan data pengurus dan UMKM dampingan PUMIKOP SUMUT masih dilakukan secara manual sehingga jika data tersebut hilang atau rusak sulit dibuat kembali serta ketika ada masyarakat UMKM membutuhkan bantuan untuk konsultasi kegiatan itu membutuhkan waktu yang lama karena dilakukan dengan cara manual untuk memproses. Pengolahan data secara konvensional tentu akan membutuhkan waktu yang cukup lama, tempat penyimpanan yang sulit menjamin data tetap aman. Dalam hal akses data pun akan terasa susah karena hanya dapat dilakukan di kantor saja. Dengan memanfaatkan sistem informasi berbasis web maka permasalahan tersebut dapat diatasi. Data pengurus dan UMKM dampingan membutuhkan sesuatu terhadap usahanya maka dapat langsung memilih konsultan yang disesuaikan dengan kebutuhan UMKM mitra, serta langsung mendapatkan verifikasi ID yang terdapat pada website resmi yang membuat jadi lebih aman, cepat dan mudah saat dicari serta dapat diakses dari mana saja dan kapan saja.
Implementasi Sistem Informasi Manajemen Berbasis Sistem Pengolahan Data dan Nilai Siswa untuk Efektifitas Layanan Sekolah husna, meryatul; Sinambela, Lamtiur; Putri, Maharani
Jurnal Ilmiah Madiya (Masyarakat Mandiri Berkarya) Vol. 3 No. 1 (2022): Edisi Mei 2022
Publisher : Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/madiya.v3i1.725

Abstract

Dalam Era Global saat ini Sistem Informasi Manajemen merupakan bagian yang tak terpisahkan dari suatu organisasi dimana sistem informasi yang menghasilkan hasil keluaran (output) dengan menggunakan masukan (input) dan berbagai proses yang diperlukan untuk memenuhi tujuan tertentu dalam suatu kegiatan manajemen.sistem manajemen basis data merupakan perangkat lunak yang dapat di gunakan untuk mendefinisikan, menciptakan, mengelola dan mengendalikan pengaksesan basis data. Sebuah Sistem Informasi yang efektif menyediakan informasi yang akurat, tepat waktu dan relevan bagi penggunanya sehingga dapat digunakan untuk pengambilan keputusan. Beberapa sekolah baik sekolah negeri maupun swasta termasuk Sekolah Methodist 12 Medan, masih menggunakan pengelolaan data secara manual baik data siswa, data guru bahkan data pengolahan nilai siswa, padahal data yang harus dikelola jumlahnya sangat banyak. Pengelolaan data yang baik sangat dibutuhkan demi menjamin bahwa data-data tersebut dapat digunakan untuk menghasilkan informasi yang akurat. Dalam pelaksanaan IT di Sekolah Methodist – 12 Medan,  tidak  ada aplikasi yang memudahkan pengelolaan data sekolah, yaitu data pegawai atau guru, data nilai dan lain sebaganya, kemudian masih kurangnya optimalisasi pencarian terhadap siswa tertentu bahkan belum digunakannya perangkat lunak aplikasi untuk menampilkan data dan rekapitulasi data nilai yang dibutuhkan dalam pembuatan laporan bulanan. Hal ini tentu sangat tidak tepat dalam proses kerja terkhusus di pihak sekolah.  Perlu dilakukan peningkatan dalam pengelolaan data di Sekolah Methodist 12 Medan, sehingga dapat melancarkan kinerja guru maupun pegawai. Oleh karena itu perlu dilakukan program atau kegiatan pelatihan penggunaan prangkat lunak aplikasi pengelolaan data sekolah berbasis Aplikasi. In the current Global Era, Management Information Systems are an inseparable part of an organization. Information systems produce outputs using inputs and various processes needed to fulfill specific objectives in management activity. This software can be used to define, create, manage and control database access. An effective information system provides accurate, timely, and relevant information for its users so that it can be used for decision-making. Some schools, both public and private schools, including the Methodist 12 Medan School, still use manual data management, both student data, teacher data, and even student score processing data, even though the data that must be managed is extensive. Good data management is needed to ensure that the data can be used to produce accurate information. In the implementation of IT at the Methodist School – 12 Medan, there is no application that facilitates the management of school data, namely employee or teacher data, value data, and so on, then there is still a lack of optimization of searches for certain students, and even application software has not been used to display data and recapitulation value data needed in making monthly reports. This is certainly not very appropriate in the work process, especially at the school. It is necessary to improve data management at the Methodist 12 Medan School so that it can launch the performance of teachers and employees. Therefore, it is necessary to conduct training programs or activities on the use of Application-based school data management application software.
The Application of Artificial Intelligence in Processing Health Data in Biomedical Information Prayudani, Santi; Lase, Yuyun Yusnida; Husna, Meryatul; Adam, Hikmah Adwin
Journal of Computer Science Advancements Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i2.2245

Abstract

The increasing complexity and volume of health data in modern biomedical systems have necessitated advanced technologies for effective data processing and analysis. Traditional methods often fall short in managing real-time, multidimensional data generated from various biomedical sources, such as electronic health records (EHRs), wearable devices, and genomic data. This research investigates the application of artificial intelligence (AI) in optimizing the processing and interpretation of biomedical health data. The objective of this study is to explore how AI-based technologies, including machine learning and deep learning algorithms, enhance the efficiency, accuracy, and predictive capabilities in biomedical information systems. By identifying patterns, anomalies, and correlations in large datasets, AI offers potential improvements in disease diagnosis, patient monitoring, and treatment personalization. This research employs a qualitative systematic review method, analyzing peer-reviewed literature published between 2015 and 2024 from major databases such as PubMed, IEEE Xplore, and Scopus. The analysis focuses on case studies, comparative evaluations, and implementation outcomes of AI in various biomedical domains. The findings reveal that AI applications significantly improve data processing speed and accuracy, enable early diagnosis of diseases such as cancer and diabetes, and support predictive analytics for patient outcomes. However, challenges remain in areas such as data privacy, ethical compliance, and algorithm transparency. In conclusion, the integration of AI into biomedical data systems holds transformative potential for healthcare delivery, though further interdisciplinary collaboration is required to address its limitations and ensure equitable access and ethical use.
A Performance Enhancement Strategy for Sentiment Classification Models On Political Social Media Using Hyperparameter Tuning And Boosting Chan, Andi Supriadi; Husna, Meryatul; Putra, Pandu Pratama
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1455

Abstract

This study aims to develop an optimized machine learning-based sentiment classification model for election-related issues. A dataset comprising 10,001 entries was collected from the social media platform X and manually labeled into three sentiment classes: positive, negative, and neutral. The preprocessing stage involved text cleaning, stemming, and feature transformation using the Term Frequency-Inverse Document Frequency (TF-IDF) method. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was employed. Three baseline classification algorithms—K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Gaussian Naive Bayes (GNB)—were initially evaluated to establish a performance benchmark. Model development proceeded by applying hyperparameter optimization using the Optuna framework and further enhancing the models via boosting with Extreme Gradient Boosting (XGBoost). Experimental results revealed that the combination of SVM with Optuna and XGBoost achieved the best performance, reaching 97% accuracy, precision, recall, and F1-score across all classes. In contrast, the KNN and GNB models experienced a notable decline in performance following hyperparameter tuning, although partial recovery was observed when combined with boosting. These findings suggest that hyperparameter tuning and boosting are not universally effective across all classifiers, yet their synergistic application significantly enhances performance in SVM-based models. This study highlights the importance of model-specific optimization strategies in building robust sentiment analysis systems, particularly for handling unbalanced public opinion data in social media contexts.
Co-Authors Adam, Hikmah Adwin Ajulio Padly Sembiring Ajulio Padly Sembiring Andam Lukcyhasnita Andi Supriadi Chan, Andi Supriadi Dani Gunawan Demora Ari Destiadi, Rezha Fawwaz, Insidini Faza, Sharfina Hasibuan, Annalisa Sonaria Hikmah Adwin Adam Janferson Panggabean Julham Julham Julham Julham Kadri Yusuf Lubis, Arif Ridho Lukcyhasnita, Andam Marliana Sari Pandu Pratama Putra, Pandu Pratama Poppy Andriyani Prayudani, Santi Purba, Lampson Pindahaman Putri, Maharani Rina Anugrahwaty Rina Anugrahwaty, Rina Rinaldy, Muhammad Eri Rizka, Ade Rizki Syahputra Romi Fadillah Rahmat Sembiring, Ajulio Padly Silmi Silmi Silmi Simarmata, Anggi C Simarmata Sinambela, Lamtiur Siregar, Mhd. Ikhsan P. Winda Syafitri Wiwin Sry Adinda Banjarnahor Yusnida, Yuyun Yuyun Yusnida Lase