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Pendekatan User-Centered Design untuk Pengembangan Front-End Aplikasi Keuangan UMKM Berbasis Web Darmanto, Darmanto; Muhammad, Ar-Razy; Rustiarni, Rustiarni; Oki Gianto, Rahmad
Jurnal Informasi, Sains dan Teknologi Vol. 8 No. 2 (2025): Desember: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v8i2.357

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the economy of Ketapang Regency but still face challenges in financial recording and management. Many MSME actors have not yet utilized digital technology optimally, leading to manual bookkeeping processes that are prone to errors. This study aims to develop a web-based financial bookkeeping application using the User-Centered Design (UCD) approach, focusing on user needs. The UCD method was applied through four stages: understanding the context of use, specifying user requirements, designing solutions, and evaluating the results. The developed application includes key features such as product management, supplier management, sales recording, receipt printing, and financial reporting. Based on usability testing involving 25 respondents, the application achieved an average satisfaction level of over 85% across aspects of learnability, efficiency, memorability, error handling, and satisfaction. The findings indicate that the application effectively supports MSME actors in recording financial transactions more efficiently, accurately, and reliably. Future improvements may include the integration of digital payment systems, enhanced data security, and interactive graphical financial analysis features.
Mendorong produk lokal menuju pasar digital: Strategi dan dampak pada penjualan amplang Kite Ketapang Darmanto Darmanto; Novi Indah Pradasari; Ar-Razy Muhammad; Muhamad Dani
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 9, No 2 (2026): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v9i2.3371

Abstract

Kegiatan ini bertujuan untuk menganalisis penerapan strategi digital marketing dalam meningkatkan volume penjualan produk lokal Amplang Kite di Kabupaten Ketapang. Metode yang digunakan adalah pendekatan deskriptif kualitatif melalui observasi, wawancara, pendampingan, dan analisis data hasil pemasaran digital. Digital marketing diterapkan melalui beberapa platform seperti Instagram, TikTok, Facebook, WhatsApp, dan Shopee. Hasil menunjukkan bahwa strategi ini berhasil meningkatkan visibilitas produk, kesadaran merek (brand awareness), dan interaksi dengan konsumen. Penjualan terbanyak diperoleh melalui WhatsApp dan Instagram, dengan kontribusi signifikan terhadap peningkatan volume penjualan dalam kurun waktu enam bulan. Selain menjangkau konsumen lokal, promosi digital juga mulai menarik minat dari pasar internasional seperti Brasil dan Malaysia. Faktor utama keberhasilan strategi ini terletak pada penggunaan konten visual yang menarik, konsistensi promosi, serta pemanfaatan data audiens untuk segmentasi pasar yang tepat. Penelitian ini merekomendasikan optimalisasi konten digital dan perluasan pasar global sebagai strategi lanjutan. Dengan demikian, digital marketing terbukti memberikan dampak nyata dalam memperluas jangkauan pemasaran dan meningkatkan daya saing produk UMKM lokal.
IoT and Machine Learning-Based Smart Watering Model for Water Optimization in Vegetable Gardens Novi Indah Pradasari; Eka Wahyudi; Darmanto; Ar-Razy Muhammad; Rizqia Lestika Atimi; Indra Pratiwi
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7532

Abstract

Efficient water management has become increasingly important in modern agriculture due to growing increasing demand for finite water supplies and the necessity of promoting sustainable farming practices. Traditional time-based irrigation approaches often result in inefficient water use and limited adaptability to dynamic environmental conditions. This study presents the design and preliminary validation of an Internet of Things (IoT)- and Machine Learning (ML)-based smart irrigation framework at Technology Readiness Level (TRL) 3. The proposed framework integrates real-time sensor measurements, external weather information, and a Random Forest–based forecasting algorithm to determine crop water demand support adaptive irrigation scheduling. Experimental and simulation-based evaluations demonstrated that the Random Forest model achieved satisfactory predictive performance, with an RMSE of 0.19 L/m² and an MAE of 0.16 L/m². Furthermore, the proposed framework showed the potential to reduce irrigation water consumption by approximately 30% compared with conventional fixed-schedule irrigation while maintaining adequate water availability for crop growth. The integration of multi-source environmental data and predictive analytics enabled more accurate irrigation decisions, contributing to improved water-use efficiency and reduced irrigation-related operational costs. These findings highlight integrating connected sensing systems with machine learning techniques can facilitate evidence-based irrigation management while promoting long-term agricultural sustainability.
Prototyping IoT-Based Safety Telemetry System for Forest Firefighters Eka Wahyudi; Novi Indah Pradasari; Ar-Razy Muhammad; Darmanto; Dedy Hidayat Kusuma; Indra Pratiwi; Herman
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7533

Abstract

Forest fires significantly impact the environment, carbon emissions, and public health. Ensuring the safety of forest firefighters remains a critical challenge, as they operate in high-risk environments with limited communication infrastructure. This study develops an Internet of Things (IoT)-based safety telemetry system utilizing LoRa communication to monitor firefighters’ physiological and environmental conditions in real time. The system is built on an ESP32 microcontroller integrated with sensors for body temperature, heart rate, ambient temperature and humidity, CO and CO₂ concentrations, as well as a GPS module for location tracking. Sensor data are transmitted via a LoRa SX1278 module to a Raspberry Pi–based gateway and subsequently forwarded to a cloud server for visualization and monitoring. System performance was evaluated in forested and residential environments over distances of up to 1 km. The results demonstrated an average data transmission success rate of 97% with a latency of 1.47 seconds, indicating reliable LoRa communication in areas with limited cellular network coverage. Furthermore, the sensors achieved measurement errors below 3%, while the system operated continuously for 12.5 hours with a power consumption of only 0.68 W, demonstrating high accuracy, reliability, and energy efficiency. The system also provides an early warning mechanism for hazardous conditions encountered by firefighters. User evaluations revealed an 89% satisfaction rate, particularly regarding the effectiveness of the early warning feature and overall system usability. These findings demonstrate that the proposed LoRa-based IoT telemetry system can effectively enhance firefighter safety through accurate, reliable, and energy-efficient real-time monitoring.