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All Journal Building of Informatics, Technology and Science Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi
Miftakhurrokhmat, Miftakhurrokhmat
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Computer Science & IT

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Robusta Coffee Plant Disease Identification using Dempster Shafer Method in Expert Systems Sidauruk, Acihmah; Miftakhurrokhmat, Miftakhurrokhmat; Pujianto, Ade; Salmuasih, Salmuasih
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6272

Abstract

Robusta coffee is one type of coffee that can grow well in Indonesia. Robusta coffee has 2.2% more caffeine and less sugar than Arabica coffee. This coffee may be a more interesting coffee variety from different levels of taste and thickness. In addition, Robusta coffee is very accommodating to the economy of several coffee-producing countries around the world, including Indonesia. A number of factors, especially pests and diseases, can reduce the productivity and quality of coffee plants. This is also confirmed by coffee experts who conducted research on pests and diseases in Robusta coffee plants. This study aims to develop an expert-based system that can identify problems and diseases in Robusta coffee plants using the Dempster Shafer method, and developed in a web-based platform. From the data collected from literature studies, dialogue with farmers, and consultation with an expert, 13 types of pests and diseases were obtained, and 27 symptoms of the disease. The results of this study are the development of a web-based expert system that can diagnose pests or diseases from several symptom inputs filled in by users or coffee farmers. The results of the trial of 13 test cases on the diagnosis of pests and diseases of Robusta coffee plants obtained an average accuracy value of 94%. This shows that this expert system can analyze the types of pests or diseases in Robusta coffee plants very well using the Dempster Shafer method.
Pemanfaatan Image Collector berbasis Mobile dan Desktop dalam Pembentukan Dataset Citra Miftakhurrokhmat, Miftakhurrokhmat; Bachtiar, Fajar Donny
Jurnal Ilmiah IT CIDA Vol 7 No 1: Juni 2021
Publisher : STMIK AMIKOM Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (970.764 KB) | DOI: 10.55635/jic.v7i1.147

Abstract

Perkembangan teknologi informasi yang begitu pesat telah membawa perubahan baik di bentuk aplikasi terapan teknologinya, mengubah perilaku manusia, dan budaya kerja secara tidak langsung. Salah satunya adalah pemanfaatan teknologi face recognition (pengenalan wajah) diterapkan dalam hal seperti presensi kelas [1], pendeteksian presensi menggunakan masker [2], dan cek kesehatan anak dari wajah [3]. Pemanfaatan face recognition sebagai suatu solusi mensyaratkan tindakan pembelajaran (training) dengan menggunakan dataset.Dataset sendiri dibentuk dari pengumpulan citra baik wajah atau beberapa bagian tertentu, melalui cara manual dengan meminta citra atau dengan mengarahkan menggunakan aplikasi tertentu. Penelitian ini bertujuan membangun purwarupa aplikasi berbasis mobile menggunakan bahasa Pascal, framework Delphi FireMonkey FMX dengan harapan mempermudah pengumpulan citra, dan mengunduh citra sebagai suatu dataset.Kata Kunci: pengenalan wajah, dataset, citra, pascal, firemonkey
Co-Authors Acihmah Sidauruk Ade Pujianto, Ade Bachtiar, Fajar Donny Salmuasih, Salmuasih