Development of Artificial Intelligence for Variable Rate Application Based Oil Palm Fertilization Recommendation System

Firmansyah, Erick; Pardamean, Bens; Ginting, Candra; Mawandha, Hangger Gahara; Putra, Dian Pratama; Suparyanto, Teddy

doi:10.1109/icimtech53080.2021.9535082

Cited by 11 publications

(8 citation statements)

References 16 publications

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“…Digitalisasi menjadikan seseorang yang tidak ahli menjadi seorang ahli hanya dengan bermodalkan gadget (gawai), tentu dengan adanya proses ini menjadikan sebuah pemikiran baru untuk memanfaatkan adanya digitalisasi tersebut. Proses digitalisasi tersebut berkembang menjadi sebuah sistem pakar, dimana sistem pakar ini merupakan sistem informasi berisi pengetahuan seorang pakar dan kemudian dimanfaatkan sebagai prosesi konsultasi [6].Pengetahuan sistem pakar ini juga mendukung dalam dunia pertanian dimana sistem pakar yang diprogram untuk sektor pertanian dapat memberikan rekomendasi untuk pengambilan keputusan secara cepat dan efisien daripada sistem non-pakar dalam memecahkan masalah yang bersifat kompleks.…”

Section: Pendahuluanunclassified

Identifikasi Jerapan Fosfat (P) dengan Sistim Pakar Menggunakan Metode Fuzzy Logic berdasarkan pH Tanah Berbasis Aplikasi Android

Teddy Suparyanto,

Suwarno,

Nanda Satya Nugraha

2023

JPP

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Pertanian presisi saat ini menjadikan suatu indicator keberhasilan dalam pelaksanaan budidaya yang dilakukan dilapangan. Pertanian presisi atau Precision Agriculture memperkenalkan konsep atau prinsip mendasar dalam penerapan aplikasi yang akan digunakan adapun prinsip tersebut merupakan factor suksesi dalam pelaksanaan pemupukan yang berdasarkan 4 T yaitu tepat jenis, tepat waktu, tepat cara, tepat sumber, dan tepat jumlah. Lahan pertanian yang digunakan umumnya tidak seragam dari segi kesuburan terutama hara tanah yang akan mempengaruhi produksi pertanian ke depannya. Oleh karena itu, diperlukan pengambilan contoh tanah yang tepat dan pembuatan peta tanah yang dapat dilakukan dengan cara pembuatan pemetaan konduktivitas elektrik tanah (berupa induksi elektromagnetik dan elektroda kontak). Metode Fuzzy Logic atau disebut juga metode logika fuzzy menjadi salah satu pilihan dalam menentukan penentu jerapan P, dimana jerapan tersebut akan menjadikan sistem yang baik apabila diketahui secara komprehensif oleh sang pakar. Hasil penelitian memeberikan hasil pada jerapan P yang terjadi pada pH tanah dibawah 3 - 5 dijerap oleh ion – ion masam seperti Aluminium (Al) dan Besi (Fe) dengan bentuk ikatan Al-P dan Fe-P, berdasarkan hal tersebut maka ikatan pada penurunan tiap 1 digit pH maka akan meningkatkan daya jerap sebesar 78% dan pada pH 5 – 6 meningkatkan daya jerap hingga 47 – 52% tiap penurunan digitnya. Hal ini tentu dapat merugikan karena apabila informasi tidak tersampaikan maka akan membuat hilangnya P didalam tanah. Aplikasi Android yang dikerjakan saat ini dalam masa beta-test.

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Section: Pendahuluanunclassified

Identifikasi Jerapan Fosfat (P) dengan Sistim Pakar Menggunakan Metode Fuzzy Logic berdasarkan pH Tanah Berbasis Aplikasi Android

Teddy Suparyanto,

Suwarno,

Nanda Satya Nugraha

2023

JPP

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“…Firmansyah [40] propose an AI-based expert system for fertilizer recommendations in palm oil crops. Gorai T. [10]discusses the RS-based approaches for soil fertility assessment in terms of effectively utilizing fertilizers using different indices.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The proposed solution is based on the YOLO algorithm in conjunction with Convolution Neural Network (CNN) model. Erick Firmansyah et al [40] recommend an AI-based expert system for the accurate utilization of fertilizer. Udoumoh U. and Ikrang [42] review new technologies, such as GIS, GPS, and Remote Sensing (RS) for soil nutrient management to develop an efficient fertilizer recommendation system.…”

Section: Literature Reviewmentioning

confidence: 99%

Internet of Things (IoT) Assisted Context Aware Fertilizer Recommendation

et al. 2022

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An accurate amount of fertilizer according to the real-time context is the basis of precision agriculture in terms of sustainability and profitability. Many fertilizers recommendation systems are proposed without considering the real-time context in terms of soil fertility level, crop type, and soil type. The major obstacle in developing the real-time context-aware fertilizer recommendation system is related to the complexity associated with the real-time mapping of soil fertility. Furthermore, the existing methods of determining the real-time soil fertility levels for the recommendation of fertilizer are costly, timeconsuming, and laborious. Therefore, to tackle this issue, we propose a machine learning-based fertilizer recommendation methodology according to the real-time soil fertility context captured through the Internet of Things (IoT) assisted soil fertility mapping to improve the accuracy of the fertilizer recommendation system. For real-time soil fertility mapping, an IoT architecture is also proposed to support context-aware fertilizer recommendations. The proposed solution is practically implemented in real crop fields to assess the accuracies of IoT-assisted fertility mapping. The accuracy of IoT-assisted fertility mapping is assessed by comparing the proposed solution with the standard soil chemical analysis method in terms of observing Nitrogen (N), Phosphorous (P), and Potassium (K). The results reveal that the observations by both methods are in line with a mean difference of 0.34, 0.36, and -0.13 for N, P, and K observations, respectively. The context-aware fertilizer recommendation is implemented with the Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), and K-Nearest Neighbor (KNN) machine learning models to assess the performance of these machine learning models. The evaluation of the proposed solution reveals that the GNB model is more accurate as compared to the machine learning models evaluated, with accuracies of 96% and 94% from training and testing datasets, respectively.INDEX TERMS Internet of Things (IoT), machine learning, soil fertility mapping, fertilizer recommendation, support vector machine (SVM), Gaussian Naïve Bayes (GNB), logistic regression (LR), k-nearest neighbor (KNN).

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“…One of the raw materials for monolaurin is from Palm Kernel Oil (PKO) [9][10][11][12]. Indonesia is known as one of the largest palm oil producing countries in the world, with land area in 2018 reaching 14 million hectares and palm kernel oil production reaching 8,5 million tons [13][14][15][16][17]. Furthermore, the PKO in Indonesia has been used in the oleochemical and food industries as margarine, shortening, Cocoa Butter Substitute (CBS), Cocoa Butter Equivalent (CBE), and Cocoa Butter Replacer (CBR) [18].…”

Section: Introductionmentioning

confidence: 99%

Glycerolysis of palm kernel oil catalized by MgO on mono and diglyceride composition and their antibacterial activity

Ngatirah,

Kusumastuti,

Tarigan

et al. 2024

BIO Web Conf.

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Monoglyceride and diglyceride are known as emulsifiers that have been used in the food industry. Furthermore, both mono and diglyceride also have the potential to be utilized as antibacterial compounds. Both of them can be produced from natural source, such as palm kernel oil, via glycerolysis reaction. This study aims to determine the effect of temperature and time of glycerolysis reaction on the composition of mono and diglyceride and their capability as an antibacterial agent. This study used a split-plot design with the temperature of glycerolysis as the main plot (80°C, 90°C, and 100°C) and the time of glycerolysis as the subplot (3, 4, and 5 hours). Several parameters were analyzed, including acid value, percent conversion, and antibacterial activity. Then, Gas Chromatography-Mass Spectrometry (GC-MS) was used to analyze glycerolysis products. Our results showed that the variations in temperature and time of glycerolysis had no effect on acid numbers, percentage conversion, and antibacterial activity. In addition, the glycerolysis products have a higher zone of inhibition against Bacillus subtilis compared to Escherichia coli. The highest percentage of conversion was obtained at glycerolysis temperature of 100°C and 5 hours. From the results of GC-MS analysis, monolaurin was obtained at 12.06 percent area.

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Development of Artificial Intelligence for Variable Rate Application Based Oil Palm Fertilization Recommendation System

Cited by 11 publications

References 16 publications

Identifikasi Jerapan Fosfat (P) dengan Sistim Pakar Menggunakan Metode Fuzzy Logic berdasarkan pH Tanah Berbasis Aplikasi Android

Identifikasi Jerapan Fosfat (P) dengan Sistim Pakar Menggunakan Metode Fuzzy Logic berdasarkan pH Tanah Berbasis Aplikasi Android

Internet of Things (IoT) Assisted Context Aware Fertilizer Recommendation

Glycerolysis of palm kernel oil catalized by MgO on mono and diglyceride composition and their antibacterial activity

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