Accurate determination of oil palm fruit ripeness is crucial for optimizing oil yield and enhancing agricultural efficiency. This study utilizes deep learning, specifically Convolutional Neural Networks (CNNs), to classify oil palm fruit ripeness into four stages: raw, under-ripe, ripe, and overripe. The model leverages extensive data preprocessing and augmentation techniques to handle variations in lighting, angles, and fruit orientation, ensuring high classification accuracy. The approach addresses limitations of traditional methods, such as human error and inconsistencies, by providing an automated and reliable solution for real-time ripeness detection. Results demonstrate an overall accuracy of 97%, with robust precision, recall, and F1 scores across all categories. This study highlights the importance of diverse datasets and proposes further integration of contextual factors like environmental conditions to enhance applicability. The system offers a practical tool for precision agriculture, improving harvesting efficiency, reducing waste, and supporting sustainable practices
| Word | TW | HV | Detail |
|---|---|---|---|
| 1. status | 114 words | 0.84 | advanced : 0.43, classification : 0.46, of : 0, oil : 0, palm : 0.47, fruit : 0.41, ripeness : 0.43, deep : 0, learning : 0.43, for : 0, enhanced : 0.43, agricultural : 0.47, efficiency : 0, accurate : 0.51, determination : 0.41, is : 0.56, crucial : 0.44, optimizing : 0.42, yield : 0, and : 0.5, enhancing : 0.43, this : 0.61, study : 0.76, utilizes : 0.53, specifically : 0.48, convolutional : 0.33, neural : 0.39, networks : 0.53, cnns : 0.47, to : 0.56, classify : 0.51, into : 0.47, four : 0.47, stages : 0.84, raw : 0.5, under : 0, ripe : 0, overripe : 0, the : 0.5, model : 0, leverages : 0.52, extensive : 0.52, data : 0.44, preprocessing : 0.41, augmentation : 0.54, techniques : 0.6, handle : 0.44, variations : 0.49, in : 0, lighting : 0.43, angles : 0.56, orientation : 0.59, ensuring : 0.53, high : 0, accuracy : 0.53, approach : 0.43, addresses : 0.52, limitations : 0.59, traditional : 0.59, methods : 0.54, such : 0.52, as : 0.61, human : 0.46, error : 0, inconsistencies : 0.46, by : 0, providing : 0, an : 0.56, automated : 0.58, reliable : 0.43, solution : 0.56, real : 0.47, time : 0.47, detection : 0.52, results : 0.66, demonstrate : 0.34, overall : 0.44, 97 : 0, with : 0.47, robust : 0.5, precision : 0.43, recall : 0.44, f1 : 0, scores : 0.6, across : 0.56, all : 0.5, categories : 0.49, highlights : 0.42, importance : 0.51, diverse : 0.44, datasets : 0.56, proposes : 0.43, further : 0.44, integration : 0.59, contextual : 0.6, factors : 0.53, like : 0, environmental : 0, conditions : 0.51, enhance : 0.44, applicability : 0.41, system : 0.6, offers : 0.44, a : 0.72, practical : 0.35, tool : 0.47, agriculture : 0.48, improving : 0, harvesting : 0.49, reducing : 0.43, waste : 0.53, supporting : 0.54, sustainable : 0.67, practices : 0.5 |
| 2. gizi | 114 words | 0.6 | advanced : 0, classification : 0.55, of : 0, oil : 0.53, palm : 0, fruit : 0.48, ripeness : 0.46, deep : 0, learning : 0.46, for : 0, enhanced : 0, agricultural : 0.56, efficiency : 0.57, accurate : 0, determination : 0.44, is : 0.58, crucial : 0.46, optimizing : 0.57, yield : 0.48, and : 0, enhancing : 0.45, this : 0.5, study : 0, utilizes : 0.6, specifically : 0.56, convolutional : 0.44, neural : 0, networks : 0, cnns : 0, to : 0, classify : 0.46, into : 0.5, four : 0, stages : 0, raw : 0, under : 0, ripe : 0.5, overripe : 0.46, the : 0, model : 0, leverages : 0, extensive : 0.45, data : 0, preprocessing : 0, augmentation : 0.44, techniques : 0.45, handle : 0, variations : 0.57, in : 0.58, lighting : 0.6, angles : 0.47, orientation : 0.45, ensuring : 0.46, high : 0.5, accuracy : 0, approach : 0, addresses : 0, limitations : 0.56, traditional : 0.56, methods : 0, such : 0, as : 0, human : 0, error : 0, inconsistencies : 0.54, by : 0, providing : 0.57, an : 0, automated : 0, reliable : 0.46, solution : 0.46, real : 0, time : 0.5, detection : 0.45, results : 0, demonstrate : 0, overall : 0, 97 : 0, with : 0.5, robust : 0, precision : 0.57, recall : 0, f1 : 0, scores : 0, across : 0, all : 0, categories : 0.57, highlights : 0.57, importance : 0.45, diverse : 0.46, datasets : 0, proposes : 0, further : 0, integration : 0.39, contextual : 0, factors : 0, like : 0.5, environmental : 0.44, conditions : 0.57, enhance : 0, applicability : 0.55, system : 0, offers : 0, a : 0, practical : 0.45, tool : 0, agriculture : 0.56, improving : 0.57, harvesting : 0.45, reducing : 0.46, waste : 0, supporting : 0.45, sustainable : 0.45, practices : 0.45 |
| 3. mahsiswa | 114 words | 0.75 | advanced : 0.42, classification : 0.59, of : 0, oil : 0.49, palm : 0.42, fruit : 0.44, ripeness : 0.47, deep : 0, learning : 0.5, for : 0, enhanced : 0.33, agricultural : 0.54, efficiency : 0.41, accurate : 0.5, determination : 0.54, is : 0.54, crucial : 0.51, optimizing : 0.32, yield : 0.44, and : 0.49, enhancing : 0.46, this : 0.6, study : 0.44, utilizes : 0.5, specifically : 0.54, convolutional : 0.47, neural : 0.43, networks : 0.33, cnns : 0.46, to : 0, classify : 0.58, into : 0, four : 0, stages : 0.51, raw : 0.49, under : 0, ripe : 0.46, overripe : 0.42, the : 0.49, model : 0.5, leverages : 0.32, extensive : 0.49, data : 0.46, preprocessing : 0.47, augmentation : 0.44, techniques : 0.56, handle : 0.36, variations : 0.55, in : 0, lighting : 0.33, angles : 0.53, orientation : 0.48, ensuring : 0.5, high : 0.58, accuracy : 0.5, approach : 0.5, addresses : 0.57, limitations : 0.38, traditional : 0.55, methods : 0.64, such : 0.42, as : 0.75, human : 0.49, error : 0, inconsistencies : 0.41, by : 0, providing : 0.41, an : 0.54, automated : 0.49, reliable : 0.33, solution : 0.5, real : 0.46, time : 0.42, detection : 0.41, results : 0.51, demonstrate : 0.55, overall : 0.42, 97 : 0, with : 0.42, robust : 0.43, precision : 0.32, recall : 0.43, f1 : 0, scores : 0.53, across : 0.63, all : 0.49, categories : 0.56, highlights : 0.56, importance : 0.45, diverse : 0.35, datasets : 0.58, proposes : 0.5, further : 0.42, integration : 0.48, contextual : 0.41, factors : 0.51, like : 0.46, environmental : 0.47, conditions : 0.48, enhance : 0.35, applicability : 0.54, system : 0.53, offers : 0.43, a : 0.71, practical : 0.57, tool : 0, agriculture : 0.48, improving : 0.49, harvesting : 0.55, reducing : 0.42, waste : 0.55, supporting : 0.48, sustainable : 0.59, practices : 0.57 |
| 4. program | 114 words | 0.72 | advanced : 0.42, classification : 0.4, of : 0.55, oil : 0.49, palm : 0.52, fruit : 0.45, ripeness : 0.35, deep : 0, learning : 0.35, for : 0.48, enhanced : 0.42, agricultural : 0.55, efficiency : 0, accurate : 0.51, determination : 0.44, is : 0, crucial : 0.52, optimizing : 0.47, yield : 0, and : 0, enhancing : 0.42, this : 0, study : 0, utilizes : 0, specifically : 0.48, convolutional : 0.41, neural : 0.54, networks : 0.51, cnns : 0, to : 0.55, classify : 0.42, into : 0.46, four : 0.43, stages : 0.44, raw : 0.49, under : 0.45, ripe : 0.43, overripe : 0.49, the : 0, model : 0.45, leverages : 0.48, extensive : 0, data : 0.46, preprocessing : 0.63, augmentation : 0.45, techniques : 0, handle : 0, variations : 0.33, in : 0, lighting : 0.42, angles : 0.44, orientation : 0.46, ensuring : 0.42, high : 0.46, accuracy : 0.51, approach : 0.69, addresses : 0.42, limitations : 0.32, traditional : 0.49, methods : 0.43, such : 0, as : 0, human : 0.45, error : 0.57, inconsistencies : 0.4, by : 0, providing : 0.71, an : 0, automated : 0.48, reliable : 0.51, solution : 0.42, real : 0.46, time : 0, detection : 0, results : 0.43, demonstrate : 0.48, overall : 0.51, 97 : 0, with : 0, robust : 0.54, precision : 0.6, recall : 0.54, f1 : 0, scores : 0.37, across : 0.54, all : 0, categories : 0.53, highlights : 0.41, importance : 0.57, diverse : 0.43, datasets : 0.42, proposes : 0.72, further : 0.52, integration : 0.46, contextual : 0.5, factors : 0.52, like : 0, environmental : 0.55, conditions : 0.41, enhance : 0.43, applicability : 0.31, system : 0.44, offers : 0.54, a : 0, practical : 0.67, tool : 0.46, agriculture : 0.32, improving : 0.59, harvesting : 0.33, reducing : 0.42, waste : 0, supporting : 0.47, sustainable : 0.41, practices : 0.67 |
| 5. studi | 114 words | 0.92 | advanced : 0.44, classification : 0.51, of : 0, oil : 0, palm : 0, fruit : 0.6, ripeness : 0.44, deep : 0, learning : 0.44, for : 0, enhanced : 0, agricultural : 0.36, efficiency : 0.43, accurate : 0.44, determination : 0.5, is : 0.57, crucial : 0.56, optimizing : 0.53, yield : 0.47, and : 0.51, enhancing : 0.44, this : 0.48, study : 0.92, utilizes : 0.55, specifically : 0.57, convolutional : 0.52, neural : 0.46, networks : 0.44, cnns : 0, to : 0.57, classify : 0.55, into : 0.48, four : 0.48, stages : 0.66, raw : 0, under : 0.47, ripe : 0, overripe : 0.44, the : 0.51, model : 0.47, leverages : 0, extensive : 0.54, data : 0.48, preprocessing : 0, augmentation : 0.51, techniques : 0.53, handle : 0.46, variations : 0.37, in : 0, lighting : 0.38, angles : 0, orientation : 0.36, ensuring : 0.66, high : 0, accuracy : 0.44, approach : 0, addresses : 0.44, limitations : 0.36, traditional : 0.62, methods : 0.56, such : 0.67, as : 0.57, human : 0.47, error : 0, inconsistencies : 0.34, by : 0, providing : 0.37, an : 0, automated : 0.37, reliable : 0.44, solution : 0.71, real : 0, time : 0.48, detection : 0.53, results : 0.56, demonstrate : 0.43, overall : 0, 97 : 0, with : 0.48, robust : 0.46, precision : 0.44, recall : 0, f1 : 0, scores : 0.51, across : 0, all : 0, categories : 0.53, highlights : 0.43, importance : 0.37, diverse : 0, datasets : 0.38, proposes : 0, further : 0.4, integration : 0.36, contextual : 0.43, factors : 0.45, like : 0, environmental : 0.43, conditions : 0.47, enhance : 0, applicability : 0.43, system : 0.62, offers : 0, a : 0, practical : 0.54, tool : 0.48, agriculture : 0.36, improving : 0.44, harvesting : 0.43, reducing : 0.55, waste : 0, supporting : 0.67, sustainable : 0.67, practices : 0.54 |
| 6. penndidikan | 114 words | 0.7 | advanced : 0.44, classification : 0.55, of : 0, oil : 0.47, palm : 0.5, fruit : 0.43, ripeness : 0.45, deep : 0.56, learning : 0.54, for : 0, enhanced : 0.62, agricultural : 0.45, efficiency : 0.5, accurate : 0.41, determination : 0.58, is : 0, crucial : 0.49, optimizing : 0.59, yield : 0.46, and : 0.62, enhancing : 0.67, this : 0.45, study : 0.43, utilizes : 0.48, specifically : 0.62, convolutional : 0.47, neural : 0.34, networks : 0.44, cnns : 0.56, to : 0, classify : 0.41, into : 0.45, four : 0, stages : 0.42, raw : 0, under : 0.46, ripe : 0.51, overripe : 0.48, the : 0.47, model : 0.36, leverages : 0.47, extensive : 0.54, data : 0.45, preprocessing : 0.6, augmentation : 0.56, techniques : 0.52, handle : 0.42, variations : 0.52, in : 0.53, lighting : 0.44, angles : 0.34, orientation : 0.56, ensuring : 0.54, high : 0.45, accuracy : 0.41, approach : 0.48, addresses : 0.42, limitations : 0.58, traditional : 0.57, methods : 0.49, such : 0, as : 0, human : 0.43, error : 0.43, inconsistencies : 0.53, by : 0, providing : 0.64, an : 0.53, automated : 0.3, reliable : 0.48, solution : 0.31, real : 0.45, time : 0.39, detection : 0.52, results : 0.41, demonstrate : 0.45, overall : 0.41, 97 : 0, with : 0.45, robust : 0, precision : 0.7, recall : 0.42, f1 : 0, scores : 0.42, across : 0, all : 0, categories : 0.46, highlights : 0.46, importance : 0.41, diverse : 0.4, datasets : 0.31, proposes : 0.46, further : 0.41, integration : 0.5, contextual : 0.41, factors : 0, like : 0.39, environmental : 0.56, conditions : 0.65, enhance : 0.57, applicability : 0.47, system : 0.42, offers : 0.42, a : 0, practical : 0.58, tool : 0, agriculture : 0.39, improving : 0.42, harvesting : 0.52, reducing : 0.5, waste : 0.43, supporting : 0.52, sustainable : 0.4, practices : 0.52 |
| 7. jasmani | 114 words | 0.76 | advanced : 0.6, classification : 0.54, of : 0, oil : 0, palm : 0.6, fruit : 0, ripeness : 0.42, deep : 0, learning : 0.6, for : 0, enhanced : 0.51, agricultural : 0.48, efficiency : 0.33, accurate : 0.51, determination : 0.54, is : 0.55, crucial : 0.36, optimizing : 0.41, yield : 0, and : 0.49, enhancing : 0.59, this : 0.46, study : 0.45, utilizes : 0.42, specifically : 0.45, convolutional : 0.48, neural : 0.44, networks : 0, cnns : 0.46, to : 0, classify : 0.6, into : 0, four : 0, stages : 0.37, raw : 0.49, under : 0, ripe : 0, overripe : 0.42, the : 0, model : 0, leverages : 0.42, extensive : 0.48, data : 0.6, preprocessing : 0.41, augmentation : 0.64, techniques : 0.5, handle : 0.44, variations : 0.53, in : 0, lighting : 0.35, angles : 0.44, orientation : 0.46, ensuring : 0.49, high : 0, accuracy : 0.51, approach : 0.51, addresses : 0.5, limitations : 0.48, traditional : 0.46, methods : 0, such : 0.46, as : 0.76, human : 0.57, error : 0, inconsistencies : 0.43, by : 0, providing : 0.34, an : 0.55, automated : 0.59, reliable : 0.35, solution : 0.49, real : 0.46, time : 0.46, detection : 0.34, results : 0.43, demonstrate : 0.48, overall : 0.43, 97 : 0, with : 0, robust : 0.44, precision : 0.42, recall : 0.44, f1 : 0, scores : 0.44, across : 0.54, all : 0.49, categories : 0.5, highlights : 0.41, importance : 0.58, diverse : 0, datasets : 0.49, proposes : 0.42, further : 0, integration : 0.46, contextual : 0.33, factors : 0.43, like : 0, environmental : 0.39, conditions : 0.5, enhance : 0.52, applicability : 0.44, system : 0.54, offers : 0, a : 0.71, practical : 0.48, tool : 0, agriculture : 0.49, improving : 0.48, harvesting : 0.57, reducing : 0.35, waste : 0.56, supporting : 0.47, sustainable : 0.59, practices : 0.5 |
| 8. kesehatan | 114 words | 0.64 | advanced : 0.32, classification : 0.5, of : 0, oil : 0, palm : 0, fruit : 0.44, ripeness : 0.49, deep : 0.57, learning : 0.57, for : 0, enhanced : 0.52, agricultural : 0.53, efficiency : 0.54, accurate : 0.49, determination : 0.51, is : 0.54, crucial : 0.42, optimizing : 0.47, yield : 0.44, and : 0, enhancing : 0.63, this : 0.41, study : 0.44, utilizes : 0.41, specifically : 0.42, convolutional : 0.41, neural : 0.52, networks : 0.41, cnns : 0.45, to : 0, classify : 0.32, into : 0, four : 0, stages : 0.44, raw : 0, under : 0.44, ripe : 0.45, overripe : 0.41, the : 0.46, model : 0.44, leverages : 0.56, extensive : 0.44, data : 0.45, preprocessing : 0.52, augmentation : 0.49, techniques : 0.54, handle : 0.43, variations : 0.53, in : 0, lighting : 0.57, angles : 0.52, orientation : 0.52, ensuring : 0.57, high : 0.45, accuracy : 0.41, approach : 0.32, addresses : 0.48, limitations : 0.42, traditional : 0.52, methods : 0.5, such : 0.57, as : 0.54, human : 0.44, error : 0.44, inconsistencies : 0.45, by : 0, providing : 0.41, an : 0, automated : 0.48, reliable : 0.49, solution : 0.57, real : 0.57, time : 0.45, detection : 0.63, results : 0.59, demonstrate : 0.57, overall : 0.5, 97 : 0, with : 0.45, robust : 0.52, precision : 0.56, recall : 0.52, f1 : 0, scores : 0.35, across : 0.43, all : 0, categories : 0.38, highlights : 0.47, importance : 0.43, diverse : 0.59, datasets : 0.52, proposes : 0.49, further : 0.48, integration : 0.48, contextual : 0.38, factors : 0.42, like : 0.57, environmental : 0.51, conditions : 0.47, enhance : 0.55, applicability : 0.41, system : 0.44, offers : 0.52, a : 0, practical : 0.56, tool : 0, agriculture : 0.4, improving : 0.41, harvesting : 0.64, reducing : 0.49, waste : 0.48, supporting : 0.54, sustainable : 0.54, practices : 0.48 |
| 9. rekreasi | 114 words | 0.77 | advanced : 0.33, classification : 0.53, of : 0, oil : 0, palm : 0, fruit : 0.44, ripeness : 0.7, deep : 0.58, learning : 0.54, for : 0.49, enhanced : 0.47, agricultural : 0.43, efficiency : 0.45, accurate : 0.47, determination : 0.54, is : 0, crucial : 0.49, optimizing : 0.41, yield : 0.44, and : 0, enhancing : 0.57, this : 0.46, study : 0, utilizes : 0.42, specifically : 0.43, convolutional : 0.4, neural : 0.51, networks : 0.58, cnns : 0.46, to : 0, classify : 0.58, into : 0, four : 0.46, stages : 0.51, raw : 0.54, under : 0.55, ripe : 0.63, overripe : 0.62, the : 0.49, model : 0.44, leverages : 0.66, extensive : 0.65, data : 0.46, preprocessing : 0.74, augmentation : 0.43, techniques : 0.51, handle : 0.43, variations : 0.47, in : 0, lighting : 0.42, angles : 0.53, orientation : 0.62, ensuring : 0.58, high : 0, accuracy : 0.5, approach : 0.5, addresses : 0.56, limitations : 0.38, traditional : 0.55, methods : 0.51, such : 0, as : 0, human : 0.44, error : 0.55, inconsistencies : 0.36, by : 0, providing : 0.49, an : 0, automated : 0.32, reliable : 0.67, solution : 0.42, real : 0.77, time : 0.46, detection : 0.57, results : 0.68, demonstrate : 0.5, overall : 0.49, 97 : 0, with : 0, robust : 0.58, precision : 0.56, recall : 0.7, f1 : 0, scores : 0.63, across : 0.53, all : 0, categories : 0.62, highlights : 0.32, importance : 0.48, diverse : 0.61, datasets : 0.42, proposes : 0.47, further : 0.49, integration : 0.62, contextual : 0.48, factors : 0.51, like : 0.42, environmental : 0.44, conditions : 0.32, enhance : 0.49, applicability : 0.47, system : 0.43, offers : 0.63, a : 0, practical : 0.57, tool : 0, agriculture : 0.48, improving : 0.49, harvesting : 0.61, reducing : 0.67, waste : 0.44, supporting : 0.48, sustainable : 0.44, practices : 0.59 |
| 10. universitas | 114 words | 0.78 | advanced : 0.44, classification : 0.57, of : 0, oil : 0.47, palm : 0, fruit : 0.6, ripeness : 0.59, deep : 0.45, learning : 0.45, for : 0.47, enhanced : 0.31, agricultural : 0.56, efficiency : 0.41, accurate : 0.59, determination : 0.53, is : 0.53, crucial : 0.52, optimizing : 0.46, yield : 0.53, and : 0.47, enhancing : 0.37, this : 0.56, study : 0.43, utilizes : 0.63, specifically : 0.48, convolutional : 0.55, neural : 0.55, networks : 0.62, cnns : 0.56, to : 0, classify : 0.31, into : 0.39, four : 0.56, stages : 0.51, raw : 0, under : 0.78, ripe : 0.56, overripe : 0.45, the : 0.47, model : 0.43, leverages : 0.54, extensive : 0.5, data : 0, preprocessing : 0.48, augmentation : 0.54, techniques : 0.46, handle : 0.51, variations : 0.58, in : 0.56, lighting : 0.44, angles : 0.59, orientation : 0.64, ensuring : 0.65, high : 0.45, accuracy : 0.55, approach : 0.48, addresses : 0.52, limitations : 0.5, traditional : 0.5, methods : 0.49, such : 0.45, as : 0, human : 0.53, error : 0.53, inconsistencies : 0.56, by : 0, providing : 0.52, an : 0.53, automated : 0.52, reliable : 0.31, solution : 0.44, real : 0.45, time : 0.56, detection : 0.37, results : 0.62, demonstrate : 0.56, overall : 0.57, 97 : 0, with : 0.45, robust : 0.59, precision : 0.6, recall : 0.42, f1 : 0, scores : 0.48, across : 0.51, all : 0, categories : 0.5, highlights : 0.46, importance : 0.59, diverse : 0.72, datasets : 0.54, proposes : 0.5, further : 0.46, integration : 0.66, contextual : 0.59, factors : 0.49, like : 0.56, environmental : 0.65, conditions : 0.58, enhance : 0.32, applicability : 0.43, system : 0.34, offers : 0.59, a : 0, practical : 0.48, tool : 0, agriculture : 0.4, improving : 0.52, harvesting : 0.58, reducing : 0.38, waste : 0.36, supporting : 0.5, sustainable : 0.49, practices : 0.5 |
| 11. rokania | 114 words | 0.69 | advanced : 0.49, classification : 0.55, of : 0.55, oil : 0.49, palm : 0.46, fruit : 0.56, ripeness : 0.56, deep : 0, learning : 0.61, for : 0.48, enhanced : 0.35, agricultural : 0.55, efficiency : 0.33, accurate : 0.51, determination : 0.54, is : 0, crucial : 0.51, optimizing : 0.47, yield : 0, and : 0, enhancing : 0.48, this : 0, study : 0, utilizes : 0.42, specifically : 0.32, convolutional : 0.63, neural : 0.44, networks : 0.42, cnns : 0.46, to : 0.55, classify : 0.51, into : 0.46, four : 0.46, stages : 0.44, raw : 0.69, under : 0, ripe : 0.52, overripe : 0.49, the : 0, model : 0.45, leverages : 0.42, extensive : 0.5, data : 0.46, preprocessing : 0.55, augmentation : 0.55, techniques : 0.5, handle : 0.54, variations : 0.57, in : 0, lighting : 0.35, angles : 0, orientation : 0.59, ensuring : 0.51, high : 0, accuracy : 0.51, approach : 0.57, addresses : 0.34, limitations : 0.32, traditional : 0.66, methods : 0, such : 0, as : 0, human : 0.56, error : 0.56, inconsistencies : 0.43, by : 0, providing : 0.59, an : 0, automated : 0.48, reliable : 0.54, solution : 0.49, real : 0.64, time : 0, detection : 0.42, results : 0.49, demonstrate : 0.57, overall : 0.52, 97 : 0, with : 0, robust : 0.63, precision : 0.5, recall : 0.59, f1 : 0, scores : 0.44, across : 0.54, all : 0, categories : 0.47, highlights : 0.41, importance : 0.57, diverse : 0, datasets : 0.51, proposes : 0.51, further : 0.43, integration : 0.46, contextual : 0.58, factors : 0.43, like : 0.46, environmental : 0.57, conditions : 0.58, enhance : 0.52, applicability : 0.55, system : 0, offers : 0.44, a : 0, practical : 0.67, tool : 0.46, agriculture : 0.46, improving : 0.59, harvesting : 0.49, reducing : 0.54, waste : 0.45, supporting : 0.47, sustainable : 0.56, practices : 0.59 |
| 12. semester | 114 words | 0.72 | advanced : 0.42, classification : 0.53, of : 0, oil : 0, palm : 0.46, fruit : 0.44, ripeness : 0.58, deep : 0.58, learning : 0.42, for : 0, enhanced : 0.5, agricultural : 0.31, efficiency : 0.48, accurate : 0.42, determination : 0.57, is : 0.54, crucial : 0, optimizing : 0.32, yield : 0.44, and : 0, enhancing : 0.41, this : 0.46, study : 0.5, utilizes : 0.5, specifically : 0.52, convolutional : 0.4, neural : 0.43, networks : 0.54, cnns : 0.46, to : 0, classify : 0.5, into : 0.46, four : 0, stages : 0.66, raw : 0, under : 0.55, ripe : 0.46, overripe : 0.47, the : 0.49, model : 0.38, leverages : 0.56, extensive : 0.63, data : 0.46, preprocessing : 0.48, augmentation : 0.43, techniques : 0.48, handle : 0.43, variations : 0.41, in : 0, lighting : 0.42, angles : 0.53, orientation : 0.48, ensuring : 0.47, high : 0, accuracy : 0.42, approach : 0, addresses : 0.57, limitations : 0.48, traditional : 0.41, methods : 0.52, such : 0.51, as : 0.54, human : 0.44, error : 0.55, inconsistencies : 0.46, by : 0, providing : 0, an : 0, automated : 0.46, reliable : 0.5, solution : 0.55, real : 0.46, time : 0.42, detection : 0.46, results : 0.52, demonstrate : 0.71, overall : 0.42, 97 : 0, with : 0.46, robust : 0.53, precision : 0.49, recall : 0.43, f1 : 0, scores : 0.66, across : 0.43, all : 0, categories : 0.47, highlights : 0.41, importance : 0.51, diverse : 0.61, datasets : 0.47, proposes : 0.33, further : 0.49, integration : 0.44, contextual : 0.32, factors : 0.43, like : 0.46, environmental : 0.54, conditions : 0.41, enhance : 0.51, applicability : 0, system : 0.72, offers : 0.51, a : 0, practical : 0.41, tool : 0, agriculture : 0.44, improving : 0.41, harvesting : 0.56, reducing : 0.42, waste : 0.55, supporting : 0.5, sustainable : 0.66, practices : 0.49 |
| 13. pendek | 114 words | 0.72 | advanced : 0.51, classification : 0, of : 0, oil : 0, palm : 0.52, fruit : 0, ripeness : 0.72, deep : 0.61, learning : 0.53, for : 0, enhanced : 0.63, agricultural : 0, efficiency : 0.51, accurate : 0.43, determination : 0.49, is : 0, crucial : 0, optimizing : 0.42, yield : 0.58, and : 0.67, enhancing : 0.52, this : 0, study : 0.46, utilizes : 0.43, specifically : 0.5, convolutional : 0.41, neural : 0.39, networks : 0.51, cnns : 0.47, to : 0, classify : 0, into : 0.47, four : 0, stages : 0.44, raw : 0, under : 0.53, ripe : 0.61, overripe : 0.53, the : 0.5, model : 0.41, leverages : 0.52, extensive : 0.5, data : 0, preprocessing : 0.62, augmentation : 0.5, techniques : 0.6, handle : 0.67, variations : 0, in : 0.56, lighting : 0, angles : 0.56, orientation : 0.51, ensuring : 0.53, high : 0, accuracy : 0, approach : 0.43, addresses : 0.5, limitations : 0, traditional : 0.42, methods : 0.54, such : 0, as : 0, human : 0.46, error : 0.46, inconsistencies : 0.49, by : 0, providing : 0.57, an : 0.56, automated : 0.43, reliable : 0.53, solution : 0, real : 0.47, time : 0.47, detection : 0.5, results : 0.44, demonstrate : 0.42, overall : 0.44, 97 : 0, with : 0, robust : 0, precision : 0.57, recall : 0.44, f1 : 0, scores : 0.44, across : 0, all : 0, categories : 0.51, highlights : 0, importance : 0.42, diverse : 0.54, datasets : 0.53, proposes : 0.58, further : 0.44, integration : 0.34, contextual : 0.34, factors : 0, like : 0.47, environmental : 0.58, conditions : 0.51, enhance : 0.64, applicability : 0.41, system : 0.44, offers : 0.44, a : 0, practical : 0.48, tool : 0, agriculture : 0, improving : 0.43, harvesting : 0.42, reducing : 0.53, waste : 0.46, supporting : 0.42, sustainable : 0.42, practices : 0.57 |
| 14. tahun | 114 words | 0.73 | advanced : 0.55, classification : 0.42, of : 0, oil : 0, palm : 0.48, fruit : 0.47, ripeness : 0.44, deep : 0, learning : 0.55, for : 0, enhanced : 0.55, agricultural : 0.52, efficiency : 0.43, accurate : 0.55, determination : 0.52, is : 0, crucial : 0.45, optimizing : 0.53, yield : 0, and : 0.51, enhancing : 0.53, this : 0.67, study : 0.6, utilizes : 0.38, specifically : 0, convolutional : 0.35, neural : 0.46, networks : 0.44, cnns : 0, to : 0.61, classify : 0.44, into : 0, four : 0.48, stages : 0.58, raw : 0.51, under : 0, ripe : 0, overripe : 0, the : 0.72, model : 0, leverages : 0, extensive : 0.54, data : 0.48, preprocessing : 0, augmentation : 0.62, techniques : 0.69, handle : 0.59, variations : 0.53, in : 0, lighting : 0.55, angles : 0.46, orientation : 0.43, ensuring : 0.38, high : 0.48, accuracy : 0.55, approach : 0.44, addresses : 0.44, limitations : 0.53, traditional : 0.66, methods : 0.56, such : 0.48, as : 0.57, human : 0.47, error : 0, inconsistencies : 0.42, by : 0, providing : 0.44, an : 0.57, automated : 0.48, reliable : 0.44, solution : 0.55, real : 0.48, time : 0.54, detection : 0.44, results : 0.45, demonstrate : 0.43, overall : 0, 97 : 0, with : 0.48, robust : 0.46, precision : 0, recall : 0.46, f1 : 0, scores : 0, across : 0.46, all : 0.51, categories : 0.37, highlights : 0.43, importance : 0.43, diverse : 0, datasets : 0.38, proposes : 0, further : 0.4, integration : 0.36, contextual : 0.47, factors : 0.45, like : 0, environmental : 0.43, conditions : 0.43, enhance : 0.57, applicability : 0.43, system : 0, offers : 0, a : 0.73, practical : 0.44, tool : 0.54, agriculture : 0.53, improving : 0.44, harvesting : 0.52, reducing : 0.55, waste : 0.47, supporting : 0.53, sustainable : 0.6, practices : 0.44 |
| 15. akademik | 114 words | 0.74 | advanced : 0.63, classification : 0.46, of : 0, oil : 0, palm : 0.58, fruit : 0.44, ripeness : 0.42, deep : 0.58, learning : 0.47, for : 0, enhanced : 0.5, agricultural : 0.52, efficiency : 0.48, accurate : 0.63, determination : 0.6, is : 0, crucial : 0.35, optimizing : 0.32, yield : 0.38, and : 0.67, enhancing : 0.49, this : 0, study : 0.44, utilizes : 0.33, specifically : 0.47, convolutional : 0.4, neural : 0.36, networks : 0.5, cnns : 0, to : 0, classify : 0.5, into : 0, four : 0, stages : 0.53, raw : 0.49, under : 0.55, ripe : 0.46, overripe : 0.5, the : 0.49, model : 0.55, leverages : 0.32, extensive : 0.49, data : 0.6, preprocessing : 0.47, augmentation : 0.65, techniques : 0.48, handle : 0.63, variations : 0.45, in : 0, lighting : 0.42, angles : 0.58, orientation : 0.44, ensuring : 0.42, high : 0, accuracy : 0.55, approach : 0.55, addresses : 0.61, limitations : 0.38, traditional : 0.55, methods : 0.35, such : 0, as : 0.59, human : 0.38, error : 0, inconsistencies : 0.29, by : 0, providing : 0.32, an : 0.59, automated : 0.57, reliable : 0.42, solution : 0.42, real : 0.42, time : 0.42, detection : 0.57, results : 0.42, demonstrate : 0.55, overall : 0.35, 97 : 0, with : 0, robust : 0, precision : 0.49, recall : 0.36, f1 : 0, scores : 0.43, across : 0.49, all : 0.54, categories : 0.56, highlights : 0.41, importance : 0.32, diverse : 0.51, datasets : 0.58, proposes : 0.42, further : 0.42, integration : 0.44, contextual : 0.41, factors : 0.42, like : 0.58, environmental : 0.42, conditions : 0.48, enhance : 0.51, applicability : 0.48, system : 0.53, offers : 0.43, a : 0.74, practical : 0.49, tool : 0, agriculture : 0.53, improving : 0.41, harvesting : 0.56, reducing : 0.47, waste : 0.55, supporting : 0.41, sustainable : 0.48, practices : 0.46 |
| 16. 2023 | 114 words | 0 | advanced : 0, classification : 0, of : 0, oil : 0, palm : 0, fruit : 0, ripeness : 0, deep : 0, learning : 0, for : 0, enhanced : 0, agricultural : 0, efficiency : 0, accurate : 0, determination : 0, is : 0, crucial : 0, optimizing : 0, yield : 0, and : 0, enhancing : 0, this : 0, study : 0, utilizes : 0, specifically : 0, convolutional : 0, neural : 0, networks : 0, cnns : 0, to : 0, classify : 0, into : 0, four : 0, stages : 0, raw : 0, under : 0, ripe : 0, overripe : 0, the : 0, model : 0, leverages : 0, extensive : 0, data : 0, preprocessing : 0, augmentation : 0, techniques : 0, handle : 0, variations : 0, in : 0, lighting : 0, angles : 0, orientation : 0, ensuring : 0, high : 0, accuracy : 0, approach : 0, addresses : 0, limitations : 0, traditional : 0, methods : 0, such : 0, as : 0, human : 0, error : 0, inconsistencies : 0, by : 0, providing : 0, an : 0, automated : 0, reliable : 0, solution : 0, real : 0, time : 0, detection : 0, results : 0, demonstrate : 0, overall : 0, 97 : 0, with : 0, robust : 0, precision : 0, recall : 0, f1 : 0, scores : 0, across : 0, all : 0, categories : 0, highlights : 0, importance : 0, diverse : 0, datasets : 0, proposes : 0, further : 0, integration : 0, contextual : 0, factors : 0, like : 0, environmental : 0, conditions : 0, enhance : 0, applicability : 0, system : 0, offers : 0, a : 0, practical : 0, tool : 0, agriculture : 0, improving : 0, harvesting : 0, reducing : 0, waste : 0, supporting : 0, sustainable : 0, practices : 0 |
| 17. 2024 | 114 words | 0 | advanced : 0, classification : 0, of : 0, oil : 0, palm : 0, fruit : 0, ripeness : 0, deep : 0, learning : 0, for : 0, enhanced : 0, agricultural : 0, efficiency : 0, accurate : 0, determination : 0, is : 0, crucial : 0, optimizing : 0, yield : 0, and : 0, enhancing : 0, this : 0, study : 0, utilizes : 0, specifically : 0, convolutional : 0, neural : 0, networks : 0, cnns : 0, to : 0, classify : 0, into : 0, four : 0, stages : 0, raw : 0, under : 0, ripe : 0, overripe : 0, the : 0, model : 0, leverages : 0, extensive : 0, data : 0, preprocessing : 0, augmentation : 0, techniques : 0, handle : 0, variations : 0, in : 0, lighting : 0, angles : 0, orientation : 0, ensuring : 0, high : 0, accuracy : 0, approach : 0, addresses : 0, limitations : 0, traditional : 0, methods : 0, such : 0, as : 0, human : 0, error : 0, inconsistencies : 0, by : 0, providing : 0, an : 0, automated : 0, reliable : 0, solution : 0, real : 0, time : 0, detection : 0, results : 0, demonstrate : 0, overall : 0, 97 : 0, with : 0, robust : 0, precision : 0, recall : 0, f1 : 0, scores : 0, across : 0, all : 0, categories : 0, highlights : 0, importance : 0, diverse : 0, datasets : 0, proposes : 0, further : 0, integration : 0, contextual : 0, factors : 0, like : 0, environmental : 0, conditions : 0, enhance : 0, applicability : 0, system : 0, offers : 0, a : 0, practical : 0, tool : 0, agriculture : 0, improving : 0, harvesting : 0, reducing : 0, waste : 0, supporting : 0, sustainable : 0, practices : 0 |
| 18. subtitlestatus | 114 words | 0.77 | advanced : 0.4, classification : 0.45, of : 0, oil : 0.6, palm : 0.44, fruit : 0.49, ripeness : 0.47, deep : 0.44, learning : 0.36, for : 0, enhanced : 0.4, agricultural : 0.48, efficiency : 0.45, accurate : 0.47, determination : 0.41, is : 0.55, crucial : 0.54, optimizing : 0.45, yield : 0.49, and : 0, enhancing : 0.39, this : 0.49, study : 0.54, utilizes : 0.73, specifically : 0.51, convolutional : 0.45, neural : 0.48, networks : 0.42, cnns : 0.44, to : 0.52, classify : 0.43, into : 0.38, four : 0.44, stages : 0.69, raw : 0, under : 0.51, ripe : 0.55, overripe : 0.3, the : 0.6, model : 0.35, leverages : 0.49, extensive : 0.41, data : 0.44, preprocessing : 0.41, augmentation : 0.5, techniques : 0.52, handle : 0.49, variations : 0.4, in : 0.52, lighting : 0.42, angles : 0.4, orientation : 0.47, ensuring : 0.53, high : 0.44, accuracy : 0.46, approach : 0.4, addresses : 0.49, limitations : 0.55, traditional : 0.54, methods : 0.44, such : 0.64, as : 0.52, human : 0.42, error : 0, inconsistencies : 0.47, by : 0.52, providing : 0.39, an : 0, automated : 0.54, reliable : 0.49, solution : 0.57, real : 0.38, time : 0.65, detection : 0.45, results : 0.65, demonstrate : 0.47, overall : 0.38, 97 : 0, with : 0.38, robust : 0.57, precision : 0.4, recall : 0.33, f1 : 0, scores : 0.61, across : 0.49, all : 0.47, categories : 0.48, highlights : 0.44, importance : 0.4, diverse : 0.38, datasets : 0.53, proposes : 0.53, further : 0.55, integration : 0.44, contextual : 0.54, factors : 0.31, like : 0.54, environmental : 0.45, conditions : 0.39, enhance : 0.4, applicability : 0.45, system : 0.57, offers : 0.33, a : 0, practical : 0.49, tool : 0.55, agriculture : 0.49, improving : 0.39, harvesting : 0.4, reducing : 0.36, waste : 0.6, supporting : 0.65, sustainable : 0.77, practices : 0.58 |