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All Journal Jurnal Informatika dan Teknik Elektro Terapan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknologi dan Informasi Jurnal Mnemonic INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Information Systems and Technology (JISTech) Media of Computer Science Jurnal Pusat Kolaborasi Pengabdian Kepada Masyarakat JROCK (Journal Research on Computing Knowledge)
Syaban, Kharis
Universitas Sembilanbelas November Kolaka
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science

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Journal : Media of Computer Science

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Expert System for Determining Diseases and Pests in Seaweed Using Forward Chaining (Case Study : Watorumbe Village, Mawasangka Tengah) Asriani, Ika; Muchtar, Mutmainnah; Ismail, Rima Ruktiari; Paliling, Alders; Sya'ban, Kharis; Karim, Rahmat
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.175

Abstract

Seaweed is a marine organism that plays a crucial role in both ecosystem and economy. However, it often faces attacks from diseases and pests that can jeopardize the productivity and sustainability of the seaweed industry. Hence, the development of an expert system to diagnose seaweed diseases and pests becomes imperative. This research aims to develop an Expert System for Determining Diseases and Pests in Seaweed using the Forward Chaining method, with a case study conducted in the Watorumbe Village, Mawasangka Tengah Sub-district, Southeast Sulawesi. The Forward Chaining method is employed to identify symptoms appearing in seaweed and determine potential diseases or pests. Testing is carried out with 30 data samples compared against expert diagnoses, resulting in an accuracy rate of 90%. Therefore, this system has the potential to assist seaweed farmers in diagnosing diseases and pests more quickly and accurately, thereby enhancing the productivity and sustainability of seaweed cultivation efforts.
Co-Authors Al Jum'ah, Muhammad Na'im alders paliling Arysespajayadi Arysespajayadi Asriani, Ika Dimas Febriyan Priambodo Dirman Ery Muchyar Hasiri Hamid Wijaya Hardianto Henny Hamsinar Hidayatullah, Muh. Ilham Ismail, Rima Ruktiari Jayanti Yusmah Sari La Ode Hasnuddin S. Sagala Mardiawati Miftachurohmah, Nisa Muh. Na’im Al Jum’ah Muliyadi Mutmainnah Muchtar Nirsal Nirsal Nisa Miftahurochmah Nurjannah Nurjannah Rabiah Adawiyah Rahmat Karim Resitha Sampe Membunga Rima Ruktiari Sabi, Musini Sarimuddin, Sarimuddin Suci Pricilia Lestari Suharsono Bantun Sunyanti Sunyanti, Sunyanti