Claim Missing Document
Check
Articles

Found 4 Documents
Search

Pemberdayaan ekonomi ibu rumah tangga Desa Pasar Melintang melalui pemanfaatan teknologi informasi dan kecerdasan buatan Windi Saputri Simamora; Siti Sarah Harahap; Andre Pratama
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 2 (2026): April
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.
Model Fuzzy Logic Untuk Memprediksi Resiko Kecelakaan Kerja Berbasis Smart Construction Siti Sarah Harahap; Muhammad Furqon Siregar
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16376

Abstract

A fuzzy logic model can be applied in predicting the risk of work accidents, where an intelligent framework that integrates the Internet of Things (IoT). Fuzzy Logic Model, Work accident risk, and Safety Recommendation Engine (SRE) for predicting the risk of work accidents in a smart construction environment. Existing construction safety systems generally use a threshold-based approach and are not yet able to provide transparency in decision-making. To overcome these limitations, this study uses parameters such as working temperature, noise level, worker fatigue, compliance with the use of personal protective equipment (PPE), and distance to hazardous areas. A total of 500 synthetic work safety scenarios were built based on construction project conditions validated by OHS experts. The evaluation was carried out by comparing the proposed framework with Decision Tree, Random Forest, XGBoost, and Fuzzy Mamdani. The results of the study show that this model design has better classification performance and is able to explain the factors causing risk through the Risk Explanation Index (REI). In addition, the Safety Recommendation Engine successfully produces mitigation recommendations according to the dominant factors causing risk. This research contributes to the development of Artificial Intelligence Models in work safety management and supports the implementation of Smart Construction. Keywords: Artificial Intelligence, Decision Tree, Fuzzy Logic, Internet Of Things, Smart Construction
Model Monitoring IoT Menggunakan Logika Fuzzy Untuk Prediksi Tingkat Kelelahan Mesin Real-Time Muhammad Furqon Siregar; Siti Sarah Harahap
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 1 (2026): Edisi April
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Modern industrial technology development demands high efficiency levels and zero downtime for production machinery. The phenomenon of machine fatigue, which accumulates due to excessive workload without early detection, frequently triggers sudden catastrophic failures. This study aims to propose an intelligent monitoring model based on Internet of Things (IoT) technology integrated with fuzzy logic to detect machine fatigue in real-time. A DS18B20 temperature sensor and an MPU6050 accelerometer vibration sensor are implemented on the physical layer to perform actual data acquisition aligned with ISO 10816-3 standard. These physical parameters are then transmitted to a cloud server via the MQTT protocol, where the Mamdani fuzzy logic method processes the inputs to generate the machine's status. The research results show that this model successfully detects and classifies machine fatigue into Safe, Warning, and Danger statuses with 100% prediction accuracy matching MATLAB simulations, and demonstrates an average transmission latency of 0.86 seconds (well below 1.2 seconds). This system is proven reliable to be integrated as a key decision part of preventive maintenance strategy in modern manufacturing.
IDENTIFIKASI DALAM SISTEM KEPUTUSAN TERHADAP TINGKAT KECANDUAN PEMAIN GAME MOBILE LEGENDS MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Tar Muhammad Raja Gunung; Siti Sarah Harahap
Djtechno: Jurnal Teknologi Informasi Vol 5, No 3 (2024): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v5i3.4981

Abstract

Penelitian ini membahas kecanduan bermain game Mobile Legends, yang telah menjadi tantangan signifikan dalam konteks kesehatan mental modern. Game ini menggabungkan elemen tradisional dan fitur sosial yang kuat, yang dapat memengaruhi kesejahteraan individu. Penelitian ini menggunakan metode Simple Additive Weighting (SAW) untuk mengukur tingkat kecanduan pemain dengan mengambil sampel dari 10 akun Mobile Legends teratas. Hasil analisis menunjukkan bahwa Bubleee dan Dazzle berada di tingkat kecanduan tertinggi dengan nilai 0.93, diikuti oleh THINKER, Nata, dan Rey Grsng dengan nilai 0.90. Tig3r S3ni, ERIN, Sall, MyBoy, dan sen05 juga dikategorikan dalam tingkat kecanduan tinggi dengan nilai berkisar antara 0.75 hingga 0.85. Temuan ini menyoroti pentingnya penanganan yang tepat terhadap kecanduan game demi menjaga kesejahteraan mental para pemain.