Karakterisasi Mutu Fisik Biji Kakao Aksesi Papua Barat Menggunakan Pengolahan Citra Digital

Abstract

Karakterisasi biji kakao umumnya masih dilakukan secara manual yang memiliki hasil kurang efisien. Dengan teknologi saat ini, karakterisasi biji kakao bisa dilakukan dengan menggunakan pengolahan citra digital. Penelitian ini bertujuan untuk melakukan karakterisasi parameter dimensi dan warna fisik biji kakao kering menggunakan pengolahan citra digital, serta membangun metode karakterisasi fisik biji kakao kering dengan pengolahan citra digital. Prosedur penelitian meliputi persiapan sampel, pengukuran manual biji kakao, penentuan parameter citra digital biji kakao, pengambilan citra, pembuatan program pengolahan citra, serta perbandingan antara manual dan program. Hasil penelitian menunjukkan persentase kesesuaian antara penggolongan secara program dengan manual pada parameter area dengan massa, rasio height/width (H/W), rataan warna red, rataan warna green, rataan warna blue, dan rataan penjumlah red, green dan blue (RGB) dengan nilai light (L) masing-masing memiliki persentase sebesar 54,55%, 87,87%, 78,79%, 66,66%, 69,69%, dan 87,87%. Parameter citra digital biji kakao yang berpotensi digunakan untuk karakterisasi biji kakao adalah width, height, rataan warna red, rataan warna green, dan rataan warna blue. Berdasarkan karakterisasi, CKR 12 tergolong aksesi yang unggul, baik berdasarkan mutu SNI BSN 01-2323-2008 maupun dengan program pengolahan citra pada parameter fisik.

Cocoa bean characterization is generally still done manually, which has less efficient results. With current technology, the characterization of cocoa beans can be done using digital image processing. This study aims to characterize the physical dimensions and color parameters of dried cocoa beans using digital image processing, as well as develop a method for the physical characterization of dried cocoa beans using digital image processing. The research procedure includes sample preparation, manual measurement of cocoa beans, determination of digital image parameters of cocoa beans, image capture, image processing program creation, and comparison between manual and program. The results showed that the percentage of conformity between program and manual classification on the parameters of area to mass, height/width ratio (H/W), average red color, average green color, average blue color, and average sum of red, green, and blue (RGB) with the value of light (L) each had a percentage of 54.55%, 87.87%, 78.79%, 66.66%, 69.69%, and 87.87%. Digital image parameters of cocoa beans that can potentially be used for cocoa bean characterization are width, height, red color average, green color average, and blue color average. Based on characterization, CKR 12 is classified as a superior accession, both based on the quality of SNI BSN 01-2323-2008 and with image processing programs based on physical parameters.