Pengamatan Kualitas Cpo Pada Storage Tank Dengan Penambahan Sistem Pengadukan Pada Berbagai Variasi Temperatur

Renjani, Rengga Arnalis; Sugiarto, Riki; Dharmawati, Nuraeni Dwi

doi:10.23960/jtep-l.v9i4.343-352

Cited by 5 publications

(8 citation statements)

References 10 publications

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“…The data in this study were analyzed quantitatively using basic statistical measures such as the mean and standard deviation. Data that has been examined statistically is displayed in graphical form to represent the data distribution for certain descriptions visually (Renjani et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The parameters observed in the sterilizer external condensate include oil losses, moisture content, and Non-Oil Solid (NOS) levels. The extraction method is utilized to determine oil losses, the oven method is employed to determine moisture content, and the extraction thimble cellulose method is utilized to determine NOS (Maulidna & Mawarni, 2019;Pootao & Kanjanapongkul, 2016;Renjani et al, 2020;Wulandari et al, 2011).…”

Section: Figure 1 Research Sampling Point On Sterilizermentioning

confidence: 99%

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Analysis of sterilizer oil losses through variations in pressure and boiling time with dominated fresh fruit bunch overripe fraction

Renjani,

Panjaitan,

Fadhillah

et al. 2024

JRPB

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The problem is that not all FFBs processed daily are more than 90% ripe fruit, causing the yield not to reach the target. This study aims to analyze condensate oil losses from non-standard FFB quality (FFB overripe as much as 25-26%) against time and pressure variations in the sterilizer. The observed indicators include oil losses, moisture content, and non-oil solids (NOS). The study was conducted in 2 stages; the first stage was to test the length of boiling time for each peak stew. The second stage is divided into two pressure variations treatments at each stew's peak. The quantitative presented data is analyzed using simple statistics. All data analyzed statistically is presented in graphical form to visualize the data distribution. In overripe FFB conditions, as much as 25-26% shows that the three best times for peak 1 are 10 minutes with a pressure of 1.0 kg/cm2, peak 2 is 15 minutes with a pressure of 1.5 kg/cm2, and peak 3 is 65 minutes with pressure 3.1 kg/cm2. he best boiling based on the right boiling time to achieve the lowest oil losses is 90–100 minutes in one boiling cycle. If a boiling cycle of 90-100 minutes is carried out, the oil losses achieved are 0.78-0.98%. The longer the boiling process is under FFB overripe, the more oil comes out of the mesocarp and finally comes out mixed with condensate water.

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Section: Discussionmentioning

confidence: 99%

Section: Figure 1 Research Sampling Point On Sterilizermentioning

confidence: 99%

Analysis of sterilizer oil losses through variations in pressure and boiling time with dominated fresh fruit bunch overripe fraction

Renjani,

Panjaitan,

Fadhillah

et al. 2024

JRPB

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“…Sudah memenuhi kapasitas maksimal maka pabrik harus stop produksi. Hal ini menjadi sebuah masalah serius dalam memprediksi Crude Palm Oil berdasarkan kapasitas tangki [5] agar tidak terjadi danger pada storage tank. Data mining dapat dijadikan sebagai solusi untuk menyelesaikan permasalahan danger pada storage tank.…”

Section: Pendahuluanunclassified

Implementasi Data Mining Memprediksi Penjualan Crude Palm Oil Berdasarkan Kapasitas Tangki Menggunakan Multiple Linear Regression

Baskara,

Nazir,

Irsyad

et al. 2023

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Data mining is a process of discovering information from data that can be used to improve business, product development, and other decision-making processes. One application of data mining is in PT. Kerry Sawit Indonesia, which is an agribusiness company in the Wilmar Group that deals with processing crude palm oil (CPO). Sales of CPO are crucial for palm oil plantation companies. To increase efficiency and profitability, palm oil plantation companies can predict CPO sales to optimize sales and CPO inventory. One method that can be used to predict CPO sales is through data mining techniques. In this study, the data mining technique used is multiple linear regression. Multiple linear regression is used to determine the relationship between the tank capacity variable and CPO sales. The data used in this study are CPO production data, CPO sales data, and tank capacity data obtained from palm oil plantation companies over the last five years. The results of the Multiple Linear Regression calculation in this case study show that the coefficient of determination (R-squared) value is 0.9546, indicating that 95.46% of the CPO delivery variability can be explained by the independent variables. Additionally, the MAPE and RMSE tests show that the regression model obtained has good accuracy in predicting CPO deliveries. Therefore, this regression model can be used to predict CPO deliveries in the future, considering the predetermined independent variable values.

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“…Tingginya kadar air pada CPO dapat disebabkan oleh suhu penyimpanan pada storage tank yang tidak sesuai. Hal ini diperkuat dengan hasil penelitian Renjani et al, (2020), suhu pada storage tank sangat mempengaruhi kadar air CPO. Semakin meningkat suhu yang diberikan maka semakin cepat penurunan kadar air pada CPO.…”

Section: Gambar 5 I-mr Chart Kadar Air Cpo Februari 2021unclassified

Pengendalian Mutu Crude Palm Oil (CPO) Dengan Metode Control Chart dan Failure Mode and Effect Analysis (FMEA) Pada Pabrik Kelapa Sawit PT.XYZ

Syafira

Anwar

Rozali

2022

J. Tek. Ind. Pert. Ind.

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The purpose of this research is to analyze the consistency of daily CPO quality at the palm factory PT. XYZ for the last 3 months, that is January, February and March 2021. Based on three quality parameters, that is free fatty acids (FFA), water content and dirt content. The data is evaluated by the I-MR chart method and then compared with the quality specifications of the company and the buyer. Meanwhile, critical points and critical conditions that most influence the quality of palm oil were identified using the FMEA method. The results showed that FFA and water content of CPO were still not statistically controlled, which was indicated by the presence of data points that were outside the control limits. The parameter of FFA CPO quality in January 2021 is the highest with an average of 3.91%. The highest water content quality parameter is in March 2021 with an average 0.398%. And the highest dirt quality parameter was in February 2021 with an average 0.039%. The cause of the variation in the quality CPO was identified from 5 critical conditions where the highest RPN value is the use of restant fresh fruit bunch in the palm oil processing process. The proposed improvement that can be given to palm factory PT.XYZ is to implement a fast processing system using the FIFO (First In First Out) system so that the raw materials that is fresh fruit bunch are not too long and pile up at the loading ramp.

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Pengamatan Kualitas Cpo Pada Storage Tank Dengan Penambahan Sistem Pengadukan Pada Berbagai Variasi Temperatur

Cited by 5 publications

References 10 publications

Analysis of sterilizer oil losses through variations in pressure and boiling time with dominated fresh fruit bunch overripe fraction

Analysis of sterilizer oil losses through variations in pressure and boiling time with dominated fresh fruit bunch overripe fraction

Implementasi Data Mining Memprediksi Penjualan Crude Palm Oil Berdasarkan Kapasitas Tangki Menggunakan Multiple Linear Regression

Pengendalian Mutu Crude Palm Oil (CPO) Dengan Metode Control Chart dan Failure Mode and Effect Analysis (FMEA) Pada Pabrik Kelapa Sawit PT.XYZ

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