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All Journal JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Bulletin of Information Technology (BIT) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Journal of Innovative and Creativity ORAHUA : Jurnal Pengabdian Kepada Masyarakat Journal of Computer Science Artificial Intelligence and Communications
Fera Damayanti
Politeknik Negeri Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Design And Development Of An Iot-Integrated Automatic Fish Feeder For Freshwater Aquaculture Systems Mardiana Mardiana; Zumhari Zumhari; Ulfa Hasnita; Fera Damayanti
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i1.6940

Abstract

. The study purpose was to design and evaluate an IoT-based Automatic Fish Feeder system that integrates sensing, processing, communication, and energy subsystems to improve feeding efficiency in freshwater aquaculture. This research addresses common challenges in manual feeding practices, including inconsistent feeding schedules, inaccurate feed volumes, and lack of real-time monitoring. The system incorporates an ESP32 microcontroller, ultrasonic sensor, servo actuator, and the Blynk platform, supported by a solar-powered energy subsystem, to create a reliable and autonomous feeding mechanism. The objective of the study was to assess the system’s performance through quantitative indicators including response time, sensor accuracy, notification reliability, WiFi stability, feed volume consistency, and energy autonomy. Materials and methods. This study employed a quantitative experimental approach in which the prototype underwent repeated testing under controlled and semi-field conditions. Performance data were collected through direct measurements, digital logs from the Blynk application, and hardware-based monitoring tools. Each subsystem was analyzed based on predefined performance thresholds, and system evaluation was conducted using measurement and structural modeling principles adapted from engineering validation frameworks. Results. The findings indicate that the ESP32 microcontroller produced a consistent response time below two seconds, while the ultrasonic sensor achieved accuracy above ninety-five percent after calibration. Notification reliability exceeded ninety percent, and WiFi stability reached more than ninety-five percent uptime. The solar energy subsystem provided sufficient power for continuous operation, and feed dispensing remained consistent across multiple trials. These outcomes show that the system fulfills its intended functional criteria. Conclusions. The study concludes that the IoT-based feeder operates effectively as an integrated automated system capable of enhancing feeding consistency and reducing manual workload in aquaculture. The prototype is reliable, energy-efficient, and suitable for further development and field-scale implementation.
Optimasi Random Forest Melalui Feature Engineering dan SMOTE untuk Klasifikasi Kesehatan Mental Rovidatul Hikmah Tanjung; Fera Damayanti; Ahmad Zaki
Bulletin of Information Technology (BIT) Vol 7 No 2 (2026)
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i2.2722

Abstract

Student mental health is a crucial factor affecting academic performance, productivity, and overall quality of life in university environments. The high prevalence of psychological disorders today demands an accurate early detection system to provide timely and efficient intervention. This study aims to develop a student mental health classification model by integrating feature engineering techniques and the Synthetic Minority Oversampling Technique (SMOTE) with the Random Forest algorithm. The feature engineering stage is conducted through the creation of a composite feature, Mental_Score, to represent students' psychological conditions more holistically and deeply. In addition, SMOTE is applied to address the data imbalance issue, making the model more sensitive in detecting the at-risk student group as the minority class. Experimental results show that the proposed model achieves an accuracy of 97%. The application of SMOTE proved effective in increasing the minority class recall to 60% and raising the F1-score from 0.57 to 0.75, significantly strengthening the detection capability for the at-risk group. Although the McNemar test yields a p-value of 1.000 due to a ceiling effect since both models are already optimal, the proposed model still offers a practical advantage in maintaining detection sensitivity. Feature importance analysis confirms that Mental_Score is the most influential attribute with a contribution value of 0.3280. This study contributes to providing a more accurate machine learning-based framework for the early detection of student mental health.
Transformasi Literasi Digital Berbasis Artificial Intelligence Dalam Meningkatkan Kapasitas Ekonomi dan Administrasi Masyarakat Desa Andi Alviadi Nur Risal; Febriyansyah Ramadhan; Clara Diva; Fera Damayanti; Putra Edi Mujahid
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.999

Abstract

Pengabdian ini bertujuan untuk menganalisis transformasi literasi digital berbasis Artificial Intelligence (AI) dalam meningkatkan kapasitas ekonomi dan administrasi masyarakat desa. Metode Pengabdian yang digunakan adalah pendekatan kualitatif deskriptif dengan desain community-based participatory research. Data dikumpulkan melalui observasi, wawancara mendalam, dan focus group discussion (FGD) yang melibatkan aparatur desa, pemuda, pelaku UMKM, dan masyarakat umum. Hasil Pengabdian menunjukkan bahwa intervensi berupa pelatihan dan pendampingan literasi digital berbasis AI mampu meningkatkan kemampuan masyarakat dalam memanfaatkan teknologi secara produktif. Pada aspek ekonomi, pelaku UMKM mengalami peningkatan efisiensi dalam pembuatan konten promosi serta perluasan jangkauan pemasaran digital. Sementara itu, pada aspek administrasi, aparatur desa menunjukkan peningkatan efisiensi dalam penyusunan dokumen dan pelayanan publik. Selain itu, terjadi perubahan perilaku masyarakat dari penggunaan teknologi yang bersifat konsumtif menjadi produktif. Meskipun demikian, Pengabdian ini juga menemukan adanya kendala berupa keterbatasan infrastruktur, akses internet, dan variasi tingkat literasi digital masyarakat. Secara keseluruhan, Pengabdian ini menyimpulkan bahwa transformasi literasi digital berbasis AI memiliki potensi besar dalam mendorong peningkatan kapasitas ekonomi dan administrasi masyarakat desa secara berkelanjutan.
Transformasi Pemasaran Konvensional ke Digital Marketing Meningkatkan Daya Saing pada UMKM T’Day Co and Tea di Medan Johor Tuti Adi Tama Nasution; Ulfa Hasnita; Mardiana; Fera Damayanti; Rovidatul Hikmah Tanjung
JURPIKAT Vol 7 No 1 (2026): 7.1 2026
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v7i1.2821

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peran penting dalam pertumbuhan ekonomi lokal, namun masih banyak yang mengalami keterbatasan dalam hal pemasaran, khususnya pada era digital. Kegiatan Pengabdian Kepada Masyarakat (PkM) ini bertujuan untuk meningkatkan daya saing UMKM T’Day Co and Tea, sebuah usaha minuman kekinian yang berlokasi di Kelurahan Pangkalan Mansyur, Kecamatan Medan Johor, Kota Medan, melalui penerapan strategi digital marketing. Metode pelaksanaan kegiatan meliputi observasi awal, analisis SWOT, pembuatan konten promosi digital, pelatihan pengelolaan media sosial, serta optimalisasi penggunaan fitur periklanan online. Hasil kegiatan menunjukkan adanya peningkatan pemahaman mitra terhadap pemasaran digital, peningkatan interaksi pelanggan di media sosial, serta kenaikan jumlah kunjungan dan pesanan. Dengan adanya pendampingan ini, UMKM mitra memiliki strategi pemasaran yang lebih terarah dan mampu menjangkau pasar yang lebih luas secara digital. Kegiatan ini diharapkan menjadi model pemberdayaan UMKM berbasis digital marketing yang dapat diterapkan di wilayah lain.
Classification of Customer Credit Risk Levels Using the Random Forest Method: A Case Study on Microfinance Institutions Fera Damayanti; Arief Budiman; Siti Sundari; Theodora MV Nainggolan
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.20

Abstract

Credit risk classification plays a crucial role in supporting financial institutions, especially microfinance institutions, in assessing the ability of customers to repay loans. This study aims to develop a credit risk classification model using the Random Forest method, which is known for its accuracy and robustness in handling classification problems. The research uses a dataset obtained from a microfinance institution consisting of various customer attributes such as income, age, loan amount, repayment history, and employment status. The dataset is preprocessed and divided into training and testing sets to evaluate model performance. The Random Forest algorithm is then applied to build a classification model that categorizes customers into three credit risk levels: low, medium, and high. The results show that the Random Forest model achieves a high level of accuracy, with a classification precision of 89%, recall of 87%, and F1-score of 88%. These findings indicate that Random Forest is an effective technique for credit risk classification and can be implemented by microfinance institutions to support better decision-making in credit approval processes. This research also highlights the potential of machine learning techniques in enhancing credit risk management and minimizing non-performing loans.
Analisis Dampak Penyuluhan Literasi Keuangan Digital Terhadap Pemahaman Finansial Siswa Efori Bu’ulolo; Bister Purba; Rovidatul Hikmah Tanjung; Muhammad Iqbal; Fera Damayanti
ORAHUA : Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 01 (2025): Juli
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/orahua.v3i01.181

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pemahaman siswa terhadap konsep dasar literasi keuangan digital melalui penyuluhan yang dilaksanakan di MIS Al-Hidayah CK Medan pada tanggal 15–19 Mei 2025. Sasaran kegiatan adalah 26 siswa kelas V dengan pendampingan dari 3 guru. Metode penyuluhan menggunakan pendekatan ceramah interaktif, audio-visual, storytelling, dan simulasi sederhana terkait pengelolaan keuangan. Evaluasi dilakukan melalui pre-test dan post-test untuk mengukur peningkatan kognitif siswa. Hasil menunjukkan adanya peningkatan signifikan, dengan rata-rata skor pre-test sebesar 48,38 dan post-test sebesar 78,54, menghasilkan peningkatan rata-rata sebesar 30,15 poin atau sekitar 62%. Penilaian guru terhadap pelaksanaan kegiatan menunjukkan skor rata-rata 4,7 dari 5 pada berbagai aspek, termasuk materi, metode, dan antusiasme siswa. Kegiatan ini menunjukkan bahwa pendekatan penyuluhan yang kontekstual dan menyenangkan mampu meningkatkan pemahaman keuangan digital anak usia sekolah dasar secara efektif. Namun, kegiatan masih memiliki keterbatasan dalam cakupan dan jangka waktu evaluasi. Oleh karena itu, kegiatan serupa disarankan dilakukan secara berkelanjutan dengan cakupan yang lebih luas dan penguatan media pembelajaran digital.
Co-Authors Ahmad Zaki Andi Alviadi Nur Risal Arief Budiman Bister Purba Clara Diva Efori Bu’ulolo Febriyansyah Ramadhan mardiana Mardiana Mardiana Muhammad Iqbal Putra Edi Mujahid Rovidatul Hikmah Tanjung Siti Sundari Theodora MV Nainggolan Tuti Adi Tama Nasution Ulfa Hasnita Zumhari Zumhari