Pengembangan Sistem Penilaian Kematangan Tandan Buah Segar Kelapa Sawit menggunakan Citra 680 dan 750 NM

Abstract

<p class="Abstrak">Salah satu permasalahan utama dalam industri kelapa sawit adalah proses sortasi Tandan Buah Segar (TBS) di pabrik kelapa sawit. Parameter yang digunakan dalam sortasi TBS adalah jumlah brondolan kelapa sawit. Pada saat ini, sortasi dilakukan oleh <em>grader</em> yang bersifat subyektif dan sering kali tidak konsisten. Hal ini terjadi karena keterbatasan penglihatan dan kemampuan manusia untuk mengolah informasi jumlah brondolan setiap TBS dalam waktu yang terbatas. Oleh karena itu, pada penelitian ini dikembangkan sistem penilaian kematangan TBS kelapa sawit berbasis spektroskopi dan nilai kontras citras. Sumber cahaya yang digunakan pada penelitian ini adalah lampu berjenis <em>Light-emitting Diode</em> (LED) dengan panjang gelombang 680 dan 750 nm. Akuisisi citra TBS dilakukan dengan menggunakan kamera DSLR yang telah dimodifikasi. sehingga diperoleh dua citra TBS pada panjang gelombang 680 dan 750 nm. Kemudian, dilakukan perhitungan nilai kontras kedua citra tersebut. Dalam penelitian ini, terdapat 24 TBS yang digunakan sebagai data latih, dengan komposisi 10 TBS matang dan 14 TBS mentah. Data uji yang digunakan berjumlah 77 TBS yang terdiri dari 38 matang dan 39 mentah. Pada penelitian ini, <em>Support Vector Machine</em> (SVM) digunakan sebagai metode klasifikasi. Akurasi data latih yang diperoleh adalah 66,67%. Sedangkan akurasi data uji dari sistem yang dikembangkan dalam penelitian ini adalah 57,14%. Hasil yang diperoleh ini masih perlu diperbaiki untuk meningkatkan akurasi sistem dengan cara menambah jumlah data, baik data latih maupun uji, serta menggunakan pembelajaran mesin.</p><p class="Abstrak"> </p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="Abstrak"><em>One of the main problems in the palm oil industry is the grading of Fresh Fruit Bunches (FFB) in the palm oil mills. The parameter used for the process is the number of fruitlets detached from the bunch. Nowadays, the FFB grading is conducted by graders which is subjective and often inconsistent due to the limitation of human vision and ability to process information on the number of fruitlets detached per FFB in a very limited time. Therefore, this study developed a grading system to assess and estimate the FFB maturity based on spectroscopy and image contrast value. From the literature review, visible light and NIR spectrum in 680 and 780 nm can be used as light sources to detect the maturity level of FFB. DSLR camera is used to acquire the FFB image. Using this scheme, two FFB images in 680 and 750 nm are obtained. The next process is to calculate the image contrast. In this research, there are 24 FFB that are used as training data that consists of 10 ripe and 14 unripe. A total of 77 FFB are used as test data that consists of 38 ripe and 39 unripe. Support Vector Machine (SVM) is used in this research to classify the maturity level of FFB. The accuracy of the training dataset is 66.67%. Meanwhile, the accuracy of the test data is 57.14%. Future works will focus on enhancing accuracy of the system through increasing the number of training and testing data using machine learning.</em></p>

Palm Oil Fresh Fruit Bunch Loss And Post Harvest Risk Analysis At Koperasi Petani Sawit Mandiri (KOPSA-M) Pangkalan Baru, Siak Hulu Kampar Riau

“…Also, sunlight hitting the oil palm fruit will cause the fruit to look very flash and reddish so that if the harvester is unable to know the characteristics of the ripe fruit, it will cause the raw FFB Losses due to cutting unripe fruit include losing part of the potential production of palm oil (MKS), disrupting production preservation, and injuring the stem so that it experiences stress (Pahan, 2008) Another incident that harvesters at KOPSA-M often do is that ripe fruit is not harvested because the harvesters are not careful in seeing the FFB harvest. The ripe fruit that is not harvested willthe next harvest time and become losses from the FFB production (Setiawan and Ananda, 2020) 3. Clean the weeded circle around the trees and land area Plantation crops are the forest plants where several wild plants are easy to grow and develop quickly around the plants.…”

“…After the weighing process at the collection point (TPH), the FFB will be transported into the truck and immediately taken to the palm oil mill (PKS). (Setiawan and Ananda, 2020). Arriving at the PKS, the fresh fruit bunches (FFB) will be taken to the sorting place where the milling employee will reselect the fruit.…”