Model peringatan dini cuaca berbasis SMS dan WhatsApp bagi nelayan Desa Kramat

Abstract

Nelayan pesisir Desa Kramat, Kecamatan Pakuhaji, Kabupaten Tangerang, menghadapi keterbatasan akses terhadap informasi peringatan dini cuaca dan gelombang tinggi. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan memetakan kebutuhan informasi, merumuskan model konseptual sistem peringatan dini berbasis SMS dan WhatsApp, serta mengevaluasi penerimaan terhadap intervensi edukatif yang menggunakan informasi resmi BMKG. Pendekatan deskriptif dipadukan dengan Participatory Action Research melalui survei pendahuluan, Focus Group Discussion, observasi, praktik penggunaan Info BMKG, dan kuesioner pascakegiatan 15 butir. Kelompok sasaran utama terdiri atas 25 nelayan; pelaksanaan juga didukung 13 pegawai dan 3 taruna, sehingga timpengabdian berjumlah 41 orang. Sebelum kegiatan, lebih dari 78% nelayan menyatakan belum pernah menerima peringatan cuaca secara langsung. Evaluasi pascakegiatan menunjukkan penilaian dominan Baik hingga Baik Sekali terhadap materi, metode, pemateri, praktik, dan fasilitas. Karena sistem backend, API, SMS Gateway, dan WhatsApp Business API belum diimplementasikan sebagai prototipe operasional serta tidak tersedia data pre-test/post-test, hasil tidak ditafsirkan sebagai bukti efektivitas sistem otomatis. Temuan mendukung kelayakan konsep dan penerimaan awal, yang perlu dilanjutkan dengan pengembangan prototipe dan pengujian terukur.

Coastal fishers in Kramat Village, Pakuhaji District, Tangerang Regency, face limited access to early-warning information on weather conditions and high waves. This Community Service (PkM) activity aimed to map information needs, formulate a conceptual model of an early-warning system based on SMS and WhatsApp, and evaluate participants’ acceptance of an educational intervention using official information from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG). A descriptive approach was combined with Participatory Action Research through a preliminary survey, Focus Group Discussion, observation, hands-on use of the Info BMKG application, and a 15-item post-activity questionnaire. The main target group consisted of 25 fishers; the activity was also supported by 13 staff members and 3 cadets, bringing the community service team to a total of 41 people. Before the activity, more than 78% of the fishers reported that they had never directly received weather warnings. The post-activity evaluation showed predominantly Good to Very Good ratings for the materials, methods, facilitators, practical activities, and facilities. Because the backend system, API, SMS Gateway, and WhatsApp Business API had not yet been implemented as an operational prototype and no pre-test/post-test data were available, the findings were not interpreted as evidence of the effectiveness of the automated system. The findings support the feasibility of the concept and its initial acceptance, which should be followed by prototype development and measurable testing.