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All Journal Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia
Santi santi
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Electrical & Electronics Engineering Environmental Science Social Sciences Other

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Web-Based Smart Aquaculture: Comparative Analysis of Mamdani, Sugeno, and Tsukamoto Fuzzy Inference Systems for Shrimp Pond Water Quality Assessment Santi santi; Arna Fariza; Agus Indra Gunawan
Jurnal Teknologi Informasi dan Terapan Vol 13 No 1 (2026): June
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v13i1.493

Abstract

Indonesia possesses vast marine and aquaculture potential; however, national shrimp production in 2024 achieved only 56.67% of its target, largely due to suboptimal water quality management. To address this issue, an intelligent classification system capable of handling uncertainty in aquaculture environments is required. This study presents a comparative evaluation of three fuzzy inference systems (FIS), namely Mamdani, Sugeno, and Tsukamoto, for shrimp pond water quality classification based on four key parameters: temperature, pH, salinity, and dissolved oxygen (DO). Water quality conditions were categorized into four classes: Good, Medium, Bad, and Very Bad using trapezoidal membership functions and expert-defined reference labels derived from aquaculture water quality standards. The dataset consisted of 994 water quality records collected from shrimp ponds in Surabaya, Indonesia, during the period from December 2024 to April 2025. Experimental results indicate that the Mamdani method produced the highest consistency with the expert-defined reference rules, achieving an agreement accuracy of 0.800, precision of 0.825, recall of 0.800, and F1-score of 0.797. In comparison, both Sugeno and Tsukamoto produced lower performance with an accuracy of 0.700 and F1-score of 0.728, although they achieved slightly higher precision values of 0.880. The findings indicate that the Mamdani fuzzy inference system provides more stable and consistent inference behavior relative to the predefined aquaculture reference rules for shrimp pond water quality assessment. Furthermore, the proposed web-based monitoring system demonstrates the practical potential of fuzzy logic approaches in supporting sustainable smart aquaculture management and environmental monitoring.
IMPLEMENTASI KALIBRASI OTOMATIS PADA WATER QUALITY METER UNTUK PEMBELAJARAN MONITORING KUALITAS AIR DI PKP SIDOARJO Arna Fariza; Teguh Hady Ariwibowo; Agus Indra Gunawan; Setiawardhana Setiawardhana; Nu Rhahida Arini; Maulana Bintang Irfansyah; Ahmad Harun; Santi Santi; Nurmala Asifatu Zahro; Rahmat Maghrobi Alwafi; Ainul Muhlasin; Zaky Wahyu Oktavianto; Naufal Pandu; Naufal Nafi' Nusantoro; Muhammad Irfan Tam Tomo
Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia. Vol 5, No 1 (2026): Maret 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jpm.v5i1.2341

Abstract

Kualitas air merupakan faktor utama yang menentukan keberhasilan kegiatan budidaya dan pembelajaran praktikum di bidang akuakultur. Politeknik Kelautan dan Perikanan (PKP) Sidoarjo sebagai institusi pendidikan vokasi membutuhkan perangkat monitoring yang akurat, mudah digunakan, dan relevan untuk mendukung kegiatan praktikum mahasiswa. Kegiatan pengabdian masyarakat ini bertujuan untuk mengimplementasikan modul Water Quality Meter (WQM) yang telah dilengkapi sistem kalibrasi otomatis berbasis Recursive Error Correction (REC) sebagai upaya meningkatkan akurasi pengukuran parameter kualitas air, meliputi pH, suhu, dan salinitas. Metode pelaksanaan terdiri dari tahap perencanaan, persiapan, pelatihan, demonstrasi, serta evaluasi penggunaan alat di fasilitas kolam uji PKP Sidoarjo. Hasil kegiatan menunjukkan bahwa modul WQM 2025 mampu memberikan pembacaan sensor yang stabil dan konsisten ketika digunakan dalam sesi praktik lapangan. Integrasi sistem REC terbukti meningkatkan ketepatan hasil pengukuran tanpa memerlukan proses kalibrasi manual yang kompleks. Peserta kegiatan memperoleh peningkatan pemahaman mengenai pemantauan kualitas air berbasis IoT serta mampu mengoperasikan alat dan platform monitoring secara mandiri. Program ini juga membuka peluang kolaborasi berkelanjutan dalam pengembangan teknologi terapan untuk pendidikan vokasi kelautan dan perikanan
Co-Authors Agus Indra Gunawan Agus Indra Gunawan Ahmad Harun Ainul Muhlasin Arna Fariza Maulana Bintang Irfansyah Muhammad Irfan Tam Tomo Naufal Nafi' Nusantoro Naufal Pandu Nu Rhahida Arini Nurmala Asifatu Zahro Rahmat Maghrobi Alwafi Setiawardhana Setiawardhana Teguh Hady Ariwibowo Zaky Wahyu Oktavianto