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All Journal SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Andries Anwar
Universitas Bina Darma
Religion Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Nursing Public Health Social Sciences

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Pemanfaatan Teknologi Berbasis Internet of Things (IOT) Pada Budidaya Ikan: Automatic Fish Feeder Sunda Ariana; Nina Paramithya; Yanti Pasmawati; Fero Triando; Muhamad Ariandi; Noer Fadzri Perdana Dinata; Andries Anwar; Sulaiman Helmi; Dewi Sartika
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 3 No. 4 (2023): Juli 2023 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v3i4.463

Abstract

Pemberian pakan ikan merupakan aktivitas paling penting dan harus dilakukan secara konsisten baik jumlah maupun waktu pemberian pakan. Jika tidak dilakukan secara konsisten maka akan mempengaruhi pertumbuhan ikan dan tentunya berdampak pada hasil panen. Untuk mengatasi permasalahan tersebut, maka tujuan kegiatan pengabdian masyarakat ini memanfaatkan teknologi berbasis internet of things (IOT) dalam merancang alat pakan ikan secara otomatis (automatic fish feeder). Metode kegiatan yang dilakukan adalah pelatihan dan pendampingan. Mitra adalah Desa Gelebek Dalam dan Korem 44/Gapo. Komponen dan alat yang disiapkan antara lain power supply, real time clock (RTC), sensor ultrasonik, arduino uno, mega+wifi r3 atmega 2560+esp 8266, lcd 20x4, buzzer, kipas, lcd keypad shield, switch/saklar, panel box, motor servo. Analisis hasil menggunakan metode performance dan kuesioner. Hasil uji coba menunjukkan bahwa alat automatic fish feeder memiliki kinerja atau performa yang baik. Terbukti dari semua sistem dan proses dapat dijalankan dengan baik dan sesuai dengan fungsi maupun manfaat yang diharapkan. Selain itu, alat ini juga dapat membantu pembudidaya mengontrol pemberian pakan ikan secara jarak jauh. Sehingga, peternak ikan tidak mengalami keterlambatan dalam pemberian pakan dan juga early warning sebelum persediaan pakan habis. Selain kebergunaan, pelatihan ini juga memberikan pengetahuan tentang perawatan alat serta mampu meningkatkan kemampuan dan pengetahuan tentang perlunya teknologi berbasis IOT.
Integrasi SERVQUAL, Kaizen, dan Time Study dalam Evaluasi Lean Management untuk Peningkatan Kinerja Layanan Mahasiswa Puri Sastia Arimbi; Yanti Pasmawati; Septa Hardini; Andries Anwar
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 12 No 1 (2026): February
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol12.no1.a20699

Abstract

This study aims to evaluate the implementation of Lean Management in improving service performance at the Student Service Center of Universitas Bina Darma. The service problems include long waiting times, queue congestion, and the absence of clear task distribution among staff, which potentially leads to process waste and reduced service quality. The study employed a descriptive quantitative approach integrating three methods: SERVQUAL to measure student satisfaction (363 respondents), Kaizen to assess employee performance (5 staff members), and time study to analyze process efficiency and waste. Data were analyzed using satisfaction gap calculation, performance indicator assessment, standard time measurement, and classification of value-added and non-value-added activities. The results show that the empathy and assurance dimensions have positive gaps, while responsiveness shows a negative gap indicating low service speed. Standardization and just in time are categorized as high, whereas waste elimination and employee involvement remain low. Although operator capacity is sufficient, the lack of task distribution causes queues and dominant waiting waste as well as non-value-added activities. Therefore, Lean Management improves service performance, but optimization requires workflow restructuring, process digitalization, and increased employee involvement in continuous improvement.
Analisis Efektivitas Customer Relationship Management (CRM) Berbasis Otomatisasi dan Artificial Intelligence Choirummansyah Muiz; Yanti Pasmawati; Andries Anwar; Syahril Rizal
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 12 No 1 (2026): February
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol12.no1.a20718

Abstract

Digital transformation in higher education has accelerated the integration of Customer Relationship Management (CRM) systems with Artificial Intelligence (AI) to enhance service quality and user loyalty. However, empirical studies examining the combined effects of service personalization, response speed, and interaction automation on user loyalty within higher education remain limited. This study aims to analyze the effectiveness of AI-based CRM implementation in the Career Center website of Universitas Bina Darma. A quantitative approach was employed using survey data collected from 215 respondents. Multiple linear regression analysis was conducted to examine the effects of Service Personalization (X1), Response Speed (X2), and Interaction Automation (X3) on User Loyalty (Y). The results indicate that all variables have a positive and significant effect on user loyalty (p < 0.05). Service personalization emerged as the most dominant factor (β = 0.413), followed by interaction automation (β = 0.265) and response speed (β = 0.231). The model demonstrates moderate explanatory power with an R² of 0.267 and an Adjusted R² of 0.257. These findings suggest that in the higher education context, AI-driven personalization and adaptive service delivery play a more critical role in fostering user loyalty than mere technical efficiency. Practically, the study recommends prioritizing data-driven personalization strategies in developing AI-based CRM systems in universities.
Co-Authors Choirummansyah Muiz Dewi Sartika Fero Triando Nina Paramithya Noer Fadzri Perdana Dinata Puri Sastia Arimbi Septa Hardini Sulaiman Sulaiman Sunda Ariana, Sunda Syahril Rizal Yanti Pasmawati