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All Journal Buletin Peternakan Jurnal Pengabdian kepada Masyarakat Nusantara
Ismoyowati Ismoyowati
Universitas Jenderal Soedirman
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Veterinary Other

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Developing Strategy to Reduce the Mortality of Native Chicken using Qualitative Modeling Ismoyowati Ismoyowati; Elly Tugiyanti; Diana Indrasanti; Novie Andri Setianto; Vony Armelia
Buletin Peternakan Vol 46, No 1 (2022): BULETIN PETERNAKAN VOL. 46 (1) FEBRUARY 2022
Publisher : Faculty of Animal Science, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21059/buletinpeternak.v46i1.70195

Abstract

Smallholder native chicken farming continues to face challenges that include simple farming management as well as ND and AI diseases that lead to decreased productivity and increased mortality rate. The aim of the study was to develop a strategy to reduce the mortality rate of native chickens in extensive and semi-intensive rearing systems. This study uses survey method with 78 extensive and 88 semi-intensive native chicken farmers as respondent. This study explores the disease incidence, illness treatment, mortality rate, as well as AI and ND antibody titers which then analyzed descriptively. System dynamic model using Ventana software (VENSIM) was used to identify the contributing factors to the mortality rate of native chicken in smallholder farming. The results showed that the common diseases among native chickens reared in semi-intensive and extensive farming are AI, ND, CRD, and pullorum, with a high rate of disease-specific mortality (>5%). Compared to native chickens in semi-intensive farming, those of in extensive farming showed a higher natural immunity against AI and ND. The qualitative modeling produced seven reinforcing loops and five balancing loops. Some challenges in developing native chicken farming were disease incidence due to lack of proper land and cage, the occurrence of selling unhealthy chickens, farmers opting out for poultry vaccination, high operational cost, lack of business motivation, limited knowledge on poultry management and health, lack of extension programs, and traditional management. We concluded that the rate of disease-specific mortality (ND and AI) remained high in native chickens reared both in extensive and semi-intensive farming. It takes an effort to improve farming management, vaccination, and the government’s contribution through extension programs to decrease disease incidence and mortality rate of native chickens.
Penerapan Sistem Smart Farming Berbasis Internet of Things (IoT) pada Kandang Closed House Ayam Broiler di Lingkungan Tropis Anas Alvandika; Ismoyowati Ismoyowati; Novie Andri Setianto; Ardiansyah Ardiansyah; Rizki Nugroho Kurniawan; Galuh Agung Wicaksono; Ivan Darmawan; Muhammad Sairelian Fawwaz Rafif
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 1 (2026): Edisi Januari - April
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v7i1.7541

Abstract

Produktivitas ayam broiler bergantung pada kestabilan mikroklimat kandang yang presisi. Ketidakterkendalian mikroklimat sering memicu stres panas dan menurunkan efisiensi pakan, terutama di wilayah tropis. Kegiatan ini melakukan pengembangan inovasi sistem smart farming berbasis Internet of Things (IoT) pada kandang closed house ayam broiler. Sistem mengintegrasikan sensor suhu, kelembapan, cahaya, kebisingan, kecepatan udara, serta gas (O₂, CO₂, NH₃) dengan dashboard berbasis cloud dan pendekatan logika kendali Hysteresis–Finite State Machine (FSM). Metode deskriptif-eksploratif diterapkan selama 33 hari pemeliharaan untuk menilai kinerja sistem dan respon pengguna. Hasil menunjukkan suhu rata-rata 28,6°C, kelembapan 86,5%, kebisingan 60,4 dB, cahaya 15,4 lux, oksigen 20,4%, CO₂ 1.236 ppm, dan ammonia 0,041 ppm, semuanya dalam rentang optimal. Sistem bekerja stabil dan dapat meningkatkan kemampuan peternak dalam pengambilan keputusan berbasis data. Hasil ini terbukti efisien, adaptif terhadap iklim tropis, dan aplikatif bagi peternak menuju Smart Precision Livestock Farming (SPLF) berkelanjutan.
Co-Authors Anas Alvandika Ardiansyah -- -- Diana Indrasanti Elly Tugiyanti Galuh Agung Wicaksono Ivan Darmawan Muhammad Sairelian Fawwaz Rafif Novie Andri Setianto Rizki Nugroho Kurniawan Vony Armelia