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All Journal KOMPUTEK Nusantara Hasana Journal Jurnal INFOTEL
Safrian Andromeda
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Mechanical Engineering Nursing

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MACHINE TO MACHINE (M2M) CONNECTIVITY BUSINESS FEASIBILITY ANALYSIS AND STRATEGY DEVELOPMENT CASE STUDY OF PT XYZ, A COMPANY IN INDONESIA, WITH SWOT ANALYSIS Safrian Andromeda; Bahar Amal; Ni Luh Bella Dwijaksara
Nusantara Hasana Journal Vol. 3 No. 8 (2024): Nusantara Hasana Journal, January 2024
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v3i8.1099

Abstract

From 2016 to 2018, the number of new Very Small Aperture Terminal (VSAT) customers at PT XYZ declined. According to Safrian (2018), VSAT is included in quadrant two of the (Strength, Weakness, Opportunity, and Threat) SWOT diagram, so it requires diversification to create new opportunities and increase revenue. This research was conducted to analyze the feasibility of using M2M as a form of diversification. M2M was compared with VSAT using the Return on Investment (ROI) method and performance testing. Alternative M2M business strategies are also using the SWOT analysis. From the ROI results, M2M had 74%. M2M connectivity can provide more benefits with more efficient investment. From the performance test, M2M latency of 33ms is in the outstanding category, while VSAT of 596ms is in the poor category. The SWOT analysis found that the company entered quadrant one, with the strategy chosen being the SO strategy, which focuses on developing M2M technology.
Perancangan Prototipe Sistem Tugas Akhir dan OpenLib Berbasis Web Nurpulaela, Lela; Arnisa Stefanie; Ibrahim; Safrian Andromeda; Egi Sunardi; Sandi
KOMPUTEK Vol. 9 No. 2 (2025): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v9i2.3419

Abstract

Program Studi Teknik Elektro Universitas Singaperbangsa Karawang (Unsika) menghadapi tantangan dalam mengelola tugas akhir dan sumber daya perpustakaan. Proyek ini bertujuan untuk meningkatkan efisiensi dan kualitas layanan melalui pengembangan Sistem Manajemen Proyek Akhir dan OpenLib yang terintegrasi. Sistem ini memungkinkan mahasiswa untuk mengunggah Tugas Akhir sebagai referensi penelitian dan memantau kemajuannya. Selain itu, OpenLib mengatur dokumen-dokumen penting seperti laporan Proyek Akhir dan laporan Magang. Dengan menggunakan metodologi waterfall, sistem ini menggabungkan framework ASP.NET Core 8, MySQL 8, dan protokol HTTPS untuk memastikan manajemen data yang aman. Pengujian black-box dilakukan untuk memverifikasi fungsionalitas dan kesesuaian dengan kebutuhan pengguna. Hasil penelitian menunjukkan bahwa sistem ini secara efektif mengarahkan pengelolaan tugas akhir dan koleksi perpustakaan digital. Kata Kunci: Sistem Manajemen Tugas Akhir, OpenLib, Koleksi Perpustakaan Digital, Metodologi Waterfall, Pengujian Black-box
IoT-Based: Smart Hydroponic Farming with SSD MobileNet and Fuzzy Logic Arnisa Stefanie; Lela Nurpulaela; Yuliarman Saragih; Safrian Andromeda; Muhammad Fachri Azizi; Muhammad Rifqi Setyanto; Selfi Arfianti; Sandi Sandi
JURNAL INFOTEL Vol 17 No 4 (2025): November
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i4.1424

Abstract

Traditional hydroponic systems largely rely on manual observation and regulation of essential environmental variables, such as pH, nutrient concentration, temperature, and humidity. This dependence often causes inefficiency, inconsistent crop quality, and greater labor requirements. To overcome these limitations, this study proposes an IoT-based Smart Hydroponic System that integrates fuzzy logic control with computer vision using the SSD MobileNet architecture. The objective of this research is to design and implement an intelligent automation framework capable of improving hydroponic cultivation through continuous data monitoring, analytical decision-making, and autonomous environmental adjustment. Within this framework, fuzzy logic dynamically stabilizes nutrient and pH levels, while the SSD MobileNet model analyzes plant images to classify growth stages and determine harvest readiness. Experimental testing produced an average classification loss of 0.1283, demonstrating reliable detection accuracy. Compared with conventional methods, the proposed integration enhances adaptability, precision, and computational efficiency for edge-level IoT applications. This system introduces a novel and scalable approach to precision agriculture, enabling more effective automation and decision making in hydroponic farming. Future studies are encouraged to expand their implementation to various plant species and adaptive learning models for broader applicability.
Co-Authors Arnisa Stefanie Bahar Amal Egi Sunardi Ibrahim Lela Nurpulaela Muhammad Fachri Azizi Muhammad Rifqi Setyanto Ni Luh Bella Dwijaksara Sandi Sandi Sandi Selfi Arfianti Yuliarman Saragih