Deteksi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit dengan Algoritme K-Means

Sari, Wahyuni Eka; Muslimin, Muslimin; Franz, Annafi; Sugiartawan, Putu

doi:10.31598/sintechjournal.v5i2.1146

Cited by 4 publications

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“…Ketiga jenis tersebut ditemukan di beberapa hutan secara alami. Perbedaan warna buah ini dilihat dari bagian eksokarpnya akibat perbedaan pigmentasi lapisan luar buah kelapa sawit (Sari et al, 2022). Warna buah virescens yaitu saat muda hijau kemudian saat matang menjadi merah semu kuning.…”

Section: Hasil Dan Pembahasanunclassified

Keragaman Genetik Varietas Kelapa Sawit (Elaeis guineensis Jacq.)

Rahmawati

2023

Jurnal Kridatama Saintek

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Oil palm (Elaeis guineensis Jacq.) is one of the leading national commodities because of its large contribution to the Indonesian national economy. In the plantation industry, palm oil is known as a commodity that has high value because it is an ingredient for producing palm oil. The genetic diversity of Indonesian oil palm accessions is currently very low. In an effort to increase genetic diversity, germplasm exploration has been carried out at the genetic diversity center of oil palm. In addition to exploration, other efforts have been made to increase genetic variation by introduction. Oil palm is a type of plant that comes from the Arecaceae family. Oil palm plants usually grow on peat soil types spread across the islands of Sumatra, Kalimantan and Sulawesi. This is a type of plant that has a fairly high level of risk of being attacked by pests. In its distribution, there are two types of oil palm that are usually cultivated by farmers, namely Elaeis guineensis Jacq., and Elaeis oleifera. Differences in properties can be seen from the morphology of the oil palm fruit endocarp ehich has different levels of thickness as a form of genetic diversity. Oil palm varieties are distinguished by the thickness of the endocarp, and also by the color of the fruit. Based on the thickness of the endocrap, oil palm is divided into three types, namely Pisifera, Dura, and Tenera. If based on the color of the fruit, there are Nigrescens, Virescens, and Albescens. One of the methods that can be used for genetic analysis is Random Amplified Polymorphic DNA (RAPD).Keywords: diversity, accession, endocarp, palm oil

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Section: Hasil Dan Pembahasanunclassified

Keragaman Genetik Varietas Kelapa Sawit (Elaeis guineensis Jacq.)

Rahmawati

2023

Jurnal Kridatama Saintek

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“…Penelitian terkait lainnya tentang mendeteksi kematangan pada buah kelapa sawit dengan memanfaatkan algoritma K-Means oleh Sari tahun 2022. Dalam penelitian ini, dilakukan dengan membagi tandan buah segar kelapa sawit menjadi 4 tahapan kematangan [11]. Penelitian terkait lainnya tentang mengimplementasikan fuzzy inference system mamdani pada prediksi jumlah produksi minyak kelapa sawit oleh Maibang tahun 2019.…”

Section: Pendahuluanunclassified

Sistem Pemilah Otomatis Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Logika Fuzzy Mamdani Dan Sensor TCS3200

Salsabilla,

Nirmala,

Rismawan

2023

JoSYC

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The palm oil sector has a strategic impact on the growth of Indonesia's economy, because the fruit of palm oil produces oil which can be used as alternative fuel, food oil and basic materials for various industries. Currently, oil palm fruit is sorted manually based on color, which takes much longer. As a result, a system was created to categorize oil palm fruit according to their state of maturity. This system uses the TCS3200 sensor as the main sensor to detect the color of oil palm fruit and implements the Mamdani fuzzy logic method to classify it. Arduino Uno can control the hardware components used in the system. Data obtained from RGB color values (red, green, blue) obtained by the TCS3200 sensor is used as input in the system. Meanwhile, the outcomes this system produced are in the form of maturity levels of oil palm fruit which are classified into 3 categories, namely unripe, ripe and past ripe. Based on tests carried out with the confusion matrix, the accuracy value obtained was 95.6%.

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“…Research by Sari, KAMI, Muslimin, M., Franz, A., & Sugiartawan, P. (2022) entitled Detection of Maturity Levels of Fresh Palm Fruit Bunch using the K-Means Algorithm. The results of the K-Means clustering research are a method of grouping objects based on their proximity to the average value of the cluster center for a certain number of clusters, k [12]. Research by Pratama, Faiq Husain, Agung Triayudi, dan Eri Mardiani (2022) entitled K-medoids and k-means data mining for the classification of palm oil production potential in Indonesia.…”

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confidence: 99%

Clustering Productive Palm Land using the K- Means Clustering Algorithm

Sihite,

Eka Prasetyaningrum

2023

jinita

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Indonesia is a country with a tropical climate that has many oil palm plantations. CV. Alkema Deo is one of the companies that manage oil palm plantations in Sampit City, East Kotawaringin Regency, Central Kalimantan. CV. Alkema Deo was founded in 2016 and has two plantation locations located on Jl. General Sudirman Km. 18, East Kotawaringin and Seibabi Village, Telawang District, East Kotawaringin. In this study, a qualitative approach was applied using a descriptive research pattern. In qualitative research, data is obtained from sources using various data collection techniques. Research using qualitative methods emphasizes the analysis of thought processes related to the dynamics of the relationship between observed phenomena, and always uses scientific logic. Based on the results of research for authors on a CV. Alkema Deo, the use of Excel in companies is quite good at processing data, but on a CV. Alkema Deo does not yet have land groupings based on productivity levels, so it is difficult to see the level achieved in 6 months based on the set target, and daily production control in terms of area and block area. Data obtained from CV. Alkema Deo is grouped based on area, block, and productivity. Application of data mining for grouping productive oil palm land on a CV. Alkema Deo with 4 variables, namely: land area, length, average production yield, percentage of achievement using the K-Means Algorithm to produce three clusters, namely 8 blocks or 50% including the high productive group (C2), 1 block or 6% blocks including the medium productive plantation group (C1), and 7 blocks or 44% including the small productive plantation group (C0).

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Deteksi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit dengan Algoritme K-Means

Cited by 4 publications

References 0 publications

Keragaman Genetik Varietas Kelapa Sawit (Elaeis guineensis Jacq.)

Keragaman Genetik Varietas Kelapa Sawit (Elaeis guineensis Jacq.)

Sistem Pemilah Otomatis Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Logika Fuzzy Mamdani Dan Sensor TCS3200

Clustering Productive Palm Land using the K- Means Clustering Algorithm

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