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All Journal Jurnal Teori dan Aplikasi Fisika Journal of Innovation in Applied Natural Science
Junaidi
Universitas Lampung
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Electrical & Electronics Engineering Energy Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics

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Rancang Bangun Mesin CNC Laser 4 Axis menggunakan Motor Stepper Tipe Nema 23 Terintergrasi Mach3 USB untuk Aplikasi Mesin Cutting Otomatis Hesti Wahyu Handani; Sri Ratna Sulistiyanti; Yanti Yulianti; Posman Manurung; Junaidi
Jurnal Teori dan Aplikasi Fisika Vol. 13 No. 02 (2025): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v13i02.413

Abstract

Perancangan dan pembuatan mesin CNC Laser 4 Axis menggunakan motor stepper tipe nema 23 terintegrasi Mach3 USB untuk aplikasi mesin cutting otomatis telah dilakukan. Alat ini merupakan suatu alat laboratorium bidang manufaktur yang digunakan untuk memotong material berbahan akrilik secara otomatis dengan dimensi pemotongan mencapai 1000 mm x 2000 mm. Alat ini memiliki mata potong berupa laser dioda ukuran 40 watt yang mampu memotong lembaran akrilik dengan ketebalan 3 mm. Alat ini dikontrol menggunakan kontroler Mach3 board dan dikomunikasikan dengan software Mach3 menggunakan perintah berupa G-code. Alat ini mampu memotong lembaran akrilik ketebalan 3 mm dengan kecepatan maksimum 55 mm/menit. Untuk hasil pemotongan optimal, proses pemotongan akrilik dilakukan pada jarak laser terhadap akrilik yaitu sejauh 15 mm. Alat ini memiliki kesalahan relatif yaitu 0,27% dan deviasi sebesar 0,25 mm. Berdasarkan spesifikasi tersebut, mesin CNC Laser ini dapat diaplikasikan untuk mesin cutting otomatis untuk material berbahan dasar akrilik.
Beyond the Canopy: Resolving Topographic and Acoustic Complexities with Machine Learning for Karst Avifauna Monitoring Anggyta Fitryan; Ahmad Faruq Abdurrahman; Nuryani; Surya Prihanto; Yusril Al Fath; Ayu Aprilia; Junaidi; Arif Surtono
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.52

Abstract

Background of study: Tropical karst landscapes harbor exceptional avian biodiversity but pose unique monitoring challenges due to complex topography, cave reverberation, and humidity-driven sound distortion. Conventional ecoacoustic methods fail in these environments, with indices showing weak correlations (r=0.20-0.43) for avian diversity due to insect masking and abiotic interference. Over 83% of karst-endemic birds lack standardized monitoring protocols despite escalating extinction risks.Aims and scope of paper: This review aims to: (1) quantify limitations of current ecoacoustic methods in karst ecosystems, (2) develop a machine learning-enhanced framework addressing topographic and reverberation effects, and (3) establish conservation-ready protocols for endangered karst avifauna. The study synthesizes evidence from 29 studies across hardware innovation, signal processing, and policy applications.Methods: We systematically analyzed 29 studies on acoustic monitoring in karst ecosystems, focusing on machine learning innovations, topographic adaptations, and conservation applications.Result: Topography drives 47% of soundscape variation, surpassing vegetation effects. Machine learning (CNNs/MFCCs) boosts detection accuracy by 22-80% in reverberant caves. Hybrid protocols enable 25-m resolution habitat mapping and precise disturbance monitoring, overcoming tropical "latitude paradox" limitations.Conclusion: This review establishes the first karst-adapted ecoacoustic framework, integrating machine learning with topographic variables to transform monitoring from biodiversity proxy to precision tool. Critical next steps include developing species-specific call libraries, wind-reverberation filters, and policy integration of acoustic baselines for IUCN assessments. The proposed protocols address urgent conservation needs for Earth's most threatened avian sanctuaries.
Co-Authors Ahmad Faruq Abdurrahman Anggyta Fitryan Ayu Aprilia Hesti Wahyu Handani Nuryani Posman Manurung Sri Ratna Sulistiyanti Surtono, Arif Surya Prihanto Yanti Yulianti Yusril Al Fath