Rambutan (Nephelium lappaceum L.) is a tropical fruit widely cultivated in Southeast Asia, including Indonesia. Manual classification of rambutan types and ripeness levels remains a challenge due to the high subjectivity and time-intensive nature of the process, particularly in large-scale agricultural operations. Convolutional Neural Network (CNN), a deep learning approach, offers significant potential in automating and improving the accuracy of fruit classification tasks by extracting complex visual features such as color and texture. This study employs a Systematic Literature Review (SLR) to evaluate the application of CNN in rambutan classification. Relevant research from 2019 to 2024 was analyzed to identify trends, accuracy levels, and challenges in utilizing CNN for this purpose. Results demonstrate that CNN achieves superior accuracy (>90%) compared to traditional methods like K-Nearest Neighbor (KNN). However, limitations include restricted dataset diversity and insufficient testing under real-world conditions. Recommendations for future research emphasize the need for larger, more diverse datasets and integration of additional media, such as spectral data and video, to enhance model robustness
| Word | TW | HV | Detail |
|---|---|---|---|
| 1. status | 130 words | 0.76 | systematic : 0.68, literature : 0.69, review : 0, on : 0, the : 0.5, application : 0.51, of : 0, convolutional : 0.33, neural : 0.39, networks : 0.53, for : 0, rambutan : 0.51, fruit : 0.41, classification : 0.46, advances : 0.53, challenges : 0.51, and : 0.5, future : 0.56, directions : 0.51, nephelium : 0.43, lappaceum : 0.52, l : 0, is : 0.56, a : 0.72, tropical : 0.43, widely : 0, cultivated : 0.52, in : 0, southeast : 0.66, asia : 0.44, including : 0.43, indonesia : 0.43, manual : 0.56, types : 0.58, ripeness : 0.43, levels : 0.44, remains : 0.54, challenge : 0.43, due : 0, to : 0.56, high : 0, subjectivity : 0.52, time : 0.47, intensive : 0.52, nature : 0.56, process : 0.44, particularly : 0.47, large : 0.46, scale : 0.62, agricultural : 0.47, operations : 0.49, network : 0.44, cnn : 0, deep : 0, learning : 0.43, approach : 0.43, offers : 0.44, significant : 0.48, potential : 0.52, automating : 0.56, improving : 0, accuracy : 0.53, tasks : 0.7, by : 0, extracting : 0.6, complex : 0, visual : 0.56, features : 0.64, such : 0.52, as : 0.61, color : 0, texture : 0.64, this : 0.61, study : 0.76, employs : 0.44, slr : 0.55, evaluate : 0.51, relevant : 0.43, research : 0.53, from : 0, 2019 : 0, 2024 : 0, was : 0.5, analyzed : 0.43, identify : 0.43, trends : 0.56, utilizing : 0.43, purpose : 0.44, results : 0.66, demonstrate : 0.34, that : 0.75, achieves : 0.53, superior : 0.58, 90 : 0, compared : 0.43, traditional : 0.59, methods : 0.54, like : 0, k : 0, nearest : 0.54, neighbor : 0, knn : 0, however : 0, limitations : 0.59, include : 0.44, restricted : 0.6, dataset : 0.53, diversity : 0.43, insufficient : 0.5, testing : 0.53, under : 0, real : 0.47, world : 0, conditions : 0.51, recommendations : 0, emphasize : 0.52, need : 0, larger : 0.44, more : 0, diverse : 0.44, datasets : 0.56, integration : 0.59, additional : 0.34, media : 0.46, spectral : 0.58, data : 0.44, video : 0, enhance : 0.44, model : 0, robustness : 0.56 |
| 2. gizi | 130 words | 0.58 | systematic : 0, literature : 0.45, review : 0.47, on : 0, the : 0, application : 0.45, of : 0, convolutional : 0.44, neural : 0, networks : 0, for : 0, rambutan : 0, fruit : 0.48, classification : 0.55, advances : 0, challenges : 0, and : 0, future : 0, directions : 0.57, nephelium : 0.45, lappaceum : 0, l : 0, is : 0.58, a : 0, tropical : 0.46, widely : 0.47, cultivated : 0.45, in : 0.58, southeast : 0, asia : 0.5, including : 0.57, indonesia : 0.45, manual : 0, types : 0, ripeness : 0.46, levels : 0, remains : 0.46, challenge : 0, due : 0, to : 0, high : 0.5, subjectivity : 0.44, time : 0.5, intensive : 0.57, nature : 0, process : 0, particularly : 0.44, large : 0, scale : 0, agricultural : 0.56, operations : 0.45, network : 0, cnn : 0, deep : 0, learning : 0.46, approach : 0, offers : 0, significant : 0.56, potential : 0.45, automating : 0.45, improving : 0.57, accuracy : 0, tasks : 0, by : 0, extracting : 0.45, complex : 0, visual : 0.47, features : 0, such : 0, as : 0, color : 0, texture : 0, this : 0.5, study : 0, employs : 0, slr : 0, evaluate : 0, relevant : 0, research : 0, from : 0, 2019 : 0, 2024 : 0, was : 0, analyzed : 0.46, identify : 0.58, trends : 0, utilizing : 0.58, purpose : 0, results : 0, demonstrate : 0, that : 0, achieves : 0.46, superior : 0.46, 90 : 0, compared : 0, traditional : 0.56, methods : 0, like : 0.5, k : 0, nearest : 0, neighbor : 0.42, knn : 0, however : 0, limitations : 0.56, include : 0.46, restricted : 0.45, dataset : 0, diversity : 0.57, insufficient : 0.56, testing : 0.46, under : 0, real : 0, world : 0, conditions : 0.57, recommendations : 0, emphasize : 0.45, need : 0, larger : 0, more : 0, diverse : 0.46, datasets : 0, integration : 0.39, additional : 0.57, media : 0.48, spectral : 0, data : 0, video : 0.48, enhance : 0, model : 0, robustness : 0 |
| 3. mahsiswa | 130 words | 0.75 | systematic : 0.51, literature : 0.32, review : 0.53, on : 0, the : 0.49, application : 0.55, of : 0, convolutional : 0.47, neural : 0.43, networks : 0.33, for : 0, rambutan : 0.47, fruit : 0.44, classification : 0.59, advances : 0.5, challenges : 0.45, and : 0.49, future : 0, directions : 0.48, nephelium : 0.49, lappaceum : 0.49, l : 0, is : 0.54, a : 0.71, tropical : 0.5, widely : 0.43, cultivated : 0.48, in : 0, southeast : 0.48, asia : 0.71, including : 0.41, indonesia : 0.57, manual : 0.7, types : 0.44, ripeness : 0.47, levels : 0.43, remains : 0.61, challenge : 0.32, due : 0, to : 0, high : 0.58, subjectivity : 0.47, time : 0.42, intensive : 0.49, nature : 0.43, process : 0.51, particularly : 0.54, large : 0.44, scale : 0.38, agricultural : 0.54, operations : 0.56, network : 0.42, cnn : 0, deep : 0, learning : 0.5, approach : 0.5, offers : 0.43, significant : 0.55, potential : 0.49, automating : 0.47, improving : 0.49, accuracy : 0.5, tasks : 0.66, by : 0, extracting : 0.48, complex : 0.42, visual : 0.51, features : 0.5, such : 0.42, as : 0.75, color : 0, texture : 0, this : 0.6, study : 0.44, employs : 0.51, slr : 0.49, evaluate : 0.5, relevant : 0.42, research : 0.33, from : 0.46, 2019 : 0, 2024 : 0, was : 0.64, analyzed : 0.42, identify : 0.42, trends : 0.43, utilizing : 0.41, purpose : 0.42, results : 0.51, demonstrate : 0.55, that : 0.42, achieves : 0.67, superior : 0.5, 90 : 0, compared : 0.5, traditional : 0.55, methods : 0.64, like : 0.46, k : 0, nearest : 0.51, neighbor : 0.33, knn : 0, however : 0.42, limitations : 0.38, include : 0, restricted : 0.48, dataset : 0.51, diversity : 0.32, insufficient : 0.31, testing : 0.51, under : 0, real : 0.46, world : 0, conditions : 0.48, recommendations : 0.46, emphasize : 0.66, need : 0, larger : 0.43, more : 0.51, diverse : 0.35, datasets : 0.58, integration : 0.48, additional : 0.56, media : 0.59, spectral : 0.5, data : 0.46, video : 0.44, enhance : 0.35, model : 0.5, robustness : 0.48 |
| 4. program | 130 words | 0.73 | systematic : 0.33, literature : 0.47, review : 0.44, on : 0.55, the : 0, application : 0.49, of : 0.55, convolutional : 0.41, neural : 0.54, networks : 0.51, for : 0.48, rambutan : 0.51, fruit : 0.45, classification : 0.4, advances : 0.42, challenges : 0.33, and : 0, future : 0.44, directions : 0.41, nephelium : 0.5, lappaceum : 0.59, l : 0, is : 0, a : 0, tropical : 0.57, widely : 0, cultivated : 0.41, in : 0, southeast : 0.5, asia : 0.46, including : 0, indonesia : 0.5, manual : 0.44, types : 0.45, ripeness : 0.35, levels : 0, remains : 0.52, challenge : 0.42, due : 0, to : 0.55, high : 0.46, subjectivity : 0, time : 0, intensive : 0, nature : 0.44, process : 0.73, particularly : 0.6, large : 0.56, scale : 0, agricultural : 0.55, operations : 0.53, network : 0.52, cnn : 0, deep : 0, learning : 0.35, approach : 0.69, offers : 0.54, significant : 0.49, potential : 0.63, automating : 0.47, improving : 0.59, accuracy : 0.51, tasks : 0, by : 0, extracting : 0.5, complex : 0.43, visual : 0.44, features : 0.35, such : 0, as : 0, color : 0.56, texture : 0.43, this : 0, study : 0, employs : 0.52, slr : 0.49, evaluate : 0.42, relevant : 0.51, research : 0.49, from : 0.6, 2019 : 0, 2024 : 0, was : 0, analyzed : 0.42, identify : 0, trends : 0.44, utilizing : 0, purpose : 0.66, results : 0.43, demonstrate : 0.48, that : 0, achieves : 0, superior : 0.6, 90 : 0, compared : 0.52, traditional : 0.49, methods : 0.43, like : 0, k : 0, nearest : 0.43, neighbor : 0.51, knn : 0, however : 0.52, limitations : 0.32, include : 0, restricted : 0.5, dataset : 0.43, diversity : 0.42, insufficient : 0, testing : 0, under : 0.45, real : 0.46, world : 0.4, conditions : 0.41, recommendations : 0.53, emphasize : 0.5, need : 0, larger : 0.64, more : 0.43, diverse : 0.43, datasets : 0.42, integration : 0.46, additional : 0.5, media : 0.45, spectral : 0.6, data : 0.46, video : 0.45, enhance : 0.43, model : 0.45, robustness : 0.5 |
| 5. studi | 130 words | 0.92 | systematic : 0.67, literature : 0.37, review : 0.46, on : 0, the : 0.51, application : 0.43, of : 0, convolutional : 0.52, neural : 0.46, networks : 0.44, for : 0, rambutan : 0.44, fruit : 0.6, classification : 0.51, advances : 0.44, challenges : 0, and : 0.51, future : 0.41, directions : 0.47, nephelium : 0.44, lappaceum : 0, l : 0, is : 0.57, a : 0, tropical : 0.55, widely : 0.46, cultivated : 0.52, in : 0, southeast : 0.58, asia : 0.48, including : 0.64, indonesia : 0.54, manual : 0.46, types : 0.47, ripeness : 0.44, levels : 0, remains : 0.45, challenge : 0, due : 0.51, to : 0.57, high : 0, subjectivity : 0.67, time : 0.48, intensive : 0.54, nature : 0.58, process : 0, particularly : 0.51, large : 0, scale : 0.52, agricultural : 0.36, operations : 0.53, network : 0.45, cnn : 0, deep : 0, learning : 0.44, approach : 0, offers : 0, significant : 0.57, potential : 0.54, automating : 0.52, improving : 0.44, accuracy : 0.44, tasks : 0.47, by : 0, extracting : 0.53, complex : 0, visual : 0.58, features : 0.55, such : 0.67, as : 0.57, color : 0, texture : 0.56, this : 0.48, study : 0.92, employs : 0, slr : 0.56, evaluate : 0.44, relevant : 0, research : 0.44, from : 0, 2019 : 0, 2024 : 0, was : 0, analyzed : 0, identify : 0.55, trends : 0.58, utilizing : 0.53, purpose : 0.45, results : 0.56, demonstrate : 0.43, that : 0.48, achieves : 0.44, superior : 0.69, 90 : 0, compared : 0, traditional : 0.62, methods : 0.56, like : 0, k : 0, nearest : 0, neighbor : 0.44, knn : 0, however : 0, limitations : 0.36, include : 0.56, restricted : 0.63, dataset : 0.45, diversity : 0.54, insufficient : 0.45, testing : 0.57, under : 0.47, real : 0, world : 0.47, conditions : 0.47, recommendations : 0.42, emphasize : 0.44, need : 0.48, larger : 0, more : 0, diverse : 0, datasets : 0.38, integration : 0.36, additional : 0.47, media : 0.6, spectral : 0.6, data : 0.48, video : 0.47, enhance : 0, model : 0.47, robustness : 0.47 |
| 6. penndidikan | 130 words | 0.7 | systematic : 0.41, literature : 0.41, review : 0.51, on : 0.53, the : 0.47, application : 0.57, of : 0, convolutional : 0.47, neural : 0.34, networks : 0.44, for : 0, rambutan : 0.31, fruit : 0.43, classification : 0.55, advances : 0.31, challenges : 0.46, and : 0.62, future : 0.42, directions : 0.55, nephelium : 0.52, lappaceum : 0.4, l : 0, is : 0, a : 0, tropical : 0.55, widely : 0.48, cultivated : 0.41, in : 0.53, southeast : 0.47, asia : 0.45, including : 0.48, indonesia : 0.65, manual : 0.42, types : 0.53, ripeness : 0.45, levels : 0.42, remains : 0.46, challenge : 0.47, due : 0.45, to : 0, high : 0.45, subjectivity : 0.51, time : 0.39, intensive : 0.52, nature : 0.34, process : 0.54, particularly : 0.56, large : 0.43, scale : 0.43, agricultural : 0.45, operations : 0.59, network : 0.46, cnn : 0.62, deep : 0.56, learning : 0.54, approach : 0.48, offers : 0.42, significant : 0.57, potential : 0.7, automating : 0.41, improving : 0.42, accuracy : 0.41, tasks : 0, by : 0, extracting : 0.52, complex : 0.49, visual : 0.42, features : 0.41, such : 0, as : 0, color : 0, texture : 0.41, this : 0.45, study : 0.43, employs : 0.32, slr : 0, evaluate : 0.48, relevant : 0.44, research : 0.41, from : 0, 2019 : 0, 2024 : 0, was : 0, analyzed : 0.48, identify : 0.5, trends : 0.59, utilizing : 0.42, purpose : 0.47, results : 0.41, demonstrate : 0.45, that : 0, achieves : 0.31, superior : 0.55, 90 : 0, compared : 0.48, traditional : 0.57, methods : 0.49, like : 0.39, k : 0, nearest : 0.32, neighbor : 0.44, knn : 0.62, however : 0.41, limitations : 0.58, include : 0.49, restricted : 0.52, dataset : 0.32, diversity : 0.48, insufficient : 0.48, testing : 0.46, under : 0.46, real : 0.45, world : 0.43, conditions : 0.65, recommendations : 0.59, emphasize : 0.42, need : 0.56, larger : 0.42, more : 0.45, diverse : 0.4, datasets : 0.31, integration : 0.5, additional : 0.63, media : 0.62, spectral : 0.55, data : 0.45, video : 0.51, enhance : 0.57, model : 0.36, robustness : 0.4 |
| 7. jasmani | 130 words | 0.76 | systematic : 0.66, literature : 0.41, review : 0, on : 0, the : 0, application : 0.46, of : 0, convolutional : 0.48, neural : 0.44, networks : 0, for : 0, rambutan : 0.69, fruit : 0, classification : 0.54, advances : 0.6, challenges : 0.5, and : 0.49, future : 0, directions : 0.33, nephelium : 0.42, lappaceum : 0.5, l : 0, is : 0.55, a : 0.71, tropical : 0.35, widely : 0, cultivated : 0.33, in : 0, southeast : 0.5, asia : 0.73, including : 0.34, indonesia : 0.5, manual : 0.54, types : 0.45, ripeness : 0.42, levels : 0, remains : 0.55, challenge : 0.5, due : 0, to : 0, high : 0, subjectivity : 0.45, time : 0.46, intensive : 0.48, nature : 0.44, process : 0, particularly : 0.45, large : 0.45, scale : 0.4, agricultural : 0.48, operations : 0.47, network : 0, cnn : 0, deep : 0, learning : 0.6, approach : 0.51, offers : 0, significant : 0.52, potential : 0.42, automating : 0.67, improving : 0.48, accuracy : 0.51, tasks : 0.56, by : 0, extracting : 0.47, complex : 0.43, visual : 0.54, features : 0.42, such : 0.46, as : 0.76, color : 0, texture : 0, this : 0.46, study : 0.45, employs : 0.43, slr : 0.49, evaluate : 0.51, relevant : 0.51, research : 0.35, from : 0.46, 2019 : 0, 2024 : 0, was : 0.65, analyzed : 0.51, identify : 0.51, trends : 0.44, utilizing : 0.34, purpose : 0, results : 0.43, demonstrate : 0.48, that : 0.46, achieves : 0.51, superior : 0.51, 90 : 0, compared : 0.35, traditional : 0.46, methods : 0, like : 0, k : 0, nearest : 0.43, neighbor : 0, knn : 0, however : 0, limitations : 0.48, include : 0, restricted : 0.5, dataset : 0.51, diversity : 0.5, insufficient : 0.45, testing : 0.51, under : 0, real : 0.46, world : 0, conditions : 0.5, recommendations : 0.53, emphasize : 0.55, need : 0, larger : 0.44, more : 0, diverse : 0, datasets : 0.49, integration : 0.46, additional : 0.57, media : 0.45, spectral : 0.51, data : 0.6, video : 0, enhance : 0.52, model : 0, robustness : 0.5 |
| 8. kesehatan | 130 words | 0.73 | systematic : 0.45, literature : 0.38, review : 0.52, on : 0, the : 0.46, application : 0.54, of : 0, convolutional : 0.41, neural : 0.52, networks : 0.41, for : 0, rambutan : 0.46, fruit : 0.44, classification : 0.5, advances : 0.32, challenges : 0.49, and : 0, future : 0.43, directions : 0.54, nephelium : 0.44, lappaceum : 0.31, l : 0, is : 0.54, a : 0, tropical : 0.41, widely : 0.43, cultivated : 0.31, in : 0, southeast : 0.6, asia : 0.57, including : 0.41, indonesia : 0.48, manual : 0.43, types : 0.54, ripeness : 0.49, levels : 0.5, remains : 0.59, challenge : 0.5, due : 0.48, to : 0, high : 0.45, subjectivity : 0.42, time : 0.45, intensive : 0.48, nature : 0.43, process : 0.5, particularly : 0.53, large : 0.44, scale : 0.48, agricultural : 0.53, operations : 0.61, network : 0.42, cnn : 0, deep : 0.57, learning : 0.57, approach : 0.32, offers : 0.52, significant : 0.52, potential : 0.44, automating : 0.43, improving : 0.41, accuracy : 0.41, tasks : 0.37, by : 0, extracting : 0.53, complex : 0.42, visual : 0.52, features : 0.52, such : 0.57, as : 0.54, color : 0, texture : 0.48, this : 0.41, study : 0.44, employs : 0.42, slr : 0.48, evaluate : 0.56, relevant : 0.66, research : 0.66, from : 0, 2019 : 0, 2024 : 0, was : 0.48, analyzed : 0.32, identify : 0.49, trends : 0.52, utilizing : 0.41, purpose : 0.5, results : 0.59, demonstrate : 0.57, that : 0.69, achieves : 0.46, superior : 0.32, 90 : 0, compared : 0.32, traditional : 0.52, methods : 0.5, like : 0.57, k : 0.73, nearest : 0.69, neighbor : 0.49, knn : 0.53, however : 0.5, limitations : 0.42, include : 0.42, restricted : 0.54, dataset : 0.55, diversity : 0.56, insufficient : 0.42, testing : 0.67, under : 0.44, real : 0.57, world : 0, conditions : 0.47, recommendations : 0.53, emphasize : 0.5, need : 0.57, larger : 0.43, more : 0.45, diverse : 0.59, datasets : 0.52, integration : 0.48, additional : 0.38, media : 0.54, spectral : 0.48, data : 0.45, video : 0.44, enhance : 0.55, model : 0.44, robustness : 0.49 |
| 9. rekreasi | 130 words | 0.77 | systematic : 0.51, literature : 0.45, review : 0.7, on : 0, the : 0.49, application : 0.31, of : 0, convolutional : 0.4, neural : 0.51, networks : 0.58, for : 0.49, rambutan : 0.55, fruit : 0.44, classification : 0.53, advances : 0.47, challenges : 0.55, and : 0, future : 0.53, directions : 0.55, nephelium : 0.57, lappaceum : 0.32, l : 0, is : 0, a : 0, tropical : 0.47, widely : 0.43, cultivated : 0.45, in : 0, southeast : 0.57, asia : 0.46, including : 0.41, indonesia : 0.52, manual : 0.43, types : 0.55, ripeness : 0.7, levels : 0.63, remains : 0.77, challenge : 0.32, due : 0.49, to : 0, high : 0, subjectivity : 0.47, time : 0.46, intensive : 0.57, nature : 0.53, process : 0.6, particularly : 0.43, large : 0.55, scale : 0.38, agricultural : 0.43, operations : 0.58, network : 0.51, cnn : 0, deep : 0.58, learning : 0.54, approach : 0.5, offers : 0.63, significant : 0.31, potential : 0.46, automating : 0.48, improving : 0.49, accuracy : 0.5, tasks : 0.55, by : 0, extracting : 0.55, complex : 0.42, visual : 0.43, features : 0.65, such : 0, as : 0, color : 0.44, texture : 0.6, this : 0.46, study : 0, employs : 0.51, slr : 0.49, evaluate : 0.47, relevant : 0.73, research : 0.72, from : 0.46, 2019 : 0, 2024 : 0, was : 0, analyzed : 0.33, identify : 0.5, trends : 0.63, utilizing : 0.41, purpose : 0.49, results : 0.68, demonstrate : 0.5, that : 0.46, achieves : 0.58, superior : 0.58, 90 : 0, compared : 0.42, traditional : 0.55, methods : 0.51, like : 0.42, k : 0.71, nearest : 0.65, neighbor : 0.42, knn : 0.49, however : 0.49, limitations : 0.38, include : 0.42, restricted : 0.74, dataset : 0.43, diversity : 0.65, insufficient : 0.38, testing : 0.51, under : 0.55, real : 0.77, world : 0.44, conditions : 0.32, recommendations : 0.72, emphasize : 0.65, need : 0.58, larger : 0.63, more : 0.58, diverse : 0.61, datasets : 0.42, integration : 0.62, additional : 0.32, media : 0.55, spectral : 0.58, data : 0.46, video : 0.44, enhance : 0.49, model : 0.44, robustness : 0.5 |
| 10. universitas | 130 words | 0.8 | systematic : 0.52, literature : 0.58, review : 0.48, on : 0.53, the : 0.47, application : 0.49, of : 0, convolutional : 0.55, neural : 0.55, networks : 0.62, for : 0.47, rambutan : 0.55, fruit : 0.6, classification : 0.57, advances : 0.54, challenges : 0.46, and : 0.47, future : 0.48, directions : 0.6, nephelium : 0.42, lappaceum : 0.4, l : 0, is : 0.53, a : 0, tropical : 0.44, widely : 0.51, cultivated : 0.66, in : 0.56, southeast : 0.57, asia : 0.45, including : 0.52, indonesia : 0.68, manual : 0.34, types : 0.53, ripeness : 0.59, levels : 0.48, remains : 0.56, challenge : 0.4, due : 0.62, to : 0, high : 0.45, subjectivity : 0.54, time : 0.56, intensive : 0.57, nature : 0.51, process : 0.56, particularly : 0.44, large : 0.36, scale : 0.43, agricultural : 0.56, operations : 0.48, network : 0.57, cnn : 0.47, deep : 0.45, learning : 0.45, approach : 0.48, offers : 0.59, significant : 0.5, potential : 0.54, automating : 0.5, improving : 0.52, accuracy : 0.55, tasks : 0.43, by : 0, extracting : 0.5, complex : 0.41, visual : 0.55, features : 0.54, such : 0.45, as : 0, color : 0.43, texture : 0.46, this : 0.56, study : 0.43, employs : 0.49, slr : 0.47, evaluate : 0.56, relevant : 0.45, research : 0.44, from : 0.45, 2019 : 0, 2024 : 0, was : 0.47, analyzed : 0.48, identify : 0.53, trends : 0.59, utilizing : 0.58, purpose : 0.52, results : 0.62, demonstrate : 0.56, that : 0, achieves : 0.54, superior : 0.5, 90 : 0, compared : 0.31, traditional : 0.5, methods : 0.49, like : 0.56, k : 0, nearest : 0.72, neighbor : 0.54, knn : 0.47, however : 0.46, limitations : 0.5, include : 0.56, restricted : 0.55, dataset : 0.46, diversity : 0.8, insufficient : 0.62, testing : 0.48, under : 0.78, real : 0.45, world : 0.43, conditions : 0.58, recommendations : 0.61, emphasize : 0.37, need : 0.56, larger : 0.34, more : 0.39, diverse : 0.72, datasets : 0.54, integration : 0.66, additional : 0.5, media : 0.36, spectral : 0.54, data : 0, video : 0.51, enhance : 0.32, model : 0.43, robustness : 0.55 |
| 11. rokania | 130 words | 0.71 | systematic : 0.5, literature : 0.41, review : 0.59, on : 0.55, the : 0, application : 0.57, of : 0.55, convolutional : 0.63, neural : 0.44, networks : 0.42, for : 0.48, rambutan : 0.65, fruit : 0.56, classification : 0.55, advances : 0.49, challenges : 0.5, and : 0, future : 0, directions : 0.41, nephelium : 0.42, lappaceum : 0.5, l : 0, is : 0, a : 0, tropical : 0.61, widely : 0, cultivated : 0.33, in : 0, southeast : 0.5, asia : 0.46, including : 0.5, indonesia : 0.59, manual : 0.64, types : 0, ripeness : 0.56, levels : 0, remains : 0.67, challenge : 0.5, due : 0, to : 0.55, high : 0, subjectivity : 0.41, time : 0, intensive : 0.5, nature : 0.44, process : 0.52, particularly : 0.55, large : 0.4, scale : 0.45, agricultural : 0.55, operations : 0.6, network : 0, cnn : 0.49, deep : 0, learning : 0.61, approach : 0.57, offers : 0.44, significant : 0.46, potential : 0.67, automating : 0.6, improving : 0.59, accuracy : 0.51, tasks : 0.4, by : 0, extracting : 0.57, complex : 0.43, visual : 0.44, features : 0.42, such : 0, as : 0, color : 0.45, texture : 0, this : 0, study : 0, employs : 0, slr : 0.49, evaluate : 0.51, relevant : 0.64, research : 0.56, from : 0.6, 2019 : 0, 2024 : 0, was : 0.49, analyzed : 0.51, identify : 0.51, trends : 0.54, utilizing : 0.34, purpose : 0.43, results : 0.49, demonstrate : 0.57, that : 0.46, achieves : 0.51, superior : 0.42, 90 : 0, compared : 0.51, traditional : 0.66, methods : 0, like : 0.46, k : 0.71, nearest : 0.43, neighbor : 0.42, knn : 0.65, however : 0.43, limitations : 0.32, include : 0, restricted : 0.55, dataset : 0.43, diversity : 0.42, insufficient : 0.32, testing : 0.36, under : 0, real : 0.64, world : 0.4, conditions : 0.58, recommendations : 0.65, emphasize : 0.5, need : 0, larger : 0.37, more : 0.43, diverse : 0, datasets : 0.51, integration : 0.46, additional : 0.57, media : 0.4, spectral : 0.42, data : 0.46, video : 0, enhance : 0.52, model : 0.45, robustness : 0.66 |
| 12. semester | 130 words | 0.71 | systematic : 0.62, literature : 0.47, review : 0.53, on : 0, the : 0.49, application : 0.41, of : 0, convolutional : 0.4, neural : 0.43, networks : 0.54, for : 0, rambutan : 0.5, fruit : 0.44, classification : 0.53, advances : 0.5, challenges : 0.48, and : 0, future : 0.46, directions : 0.48, nephelium : 0.49, lappaceum : 0.41, l : 0, is : 0.54, a : 0, tropical : 0, widely : 0.43, cultivated : 0.48, in : 0, southeast : 0.57, asia : 0.46, including : 0, indonesia : 0.49, manual : 0.43, types : 0.55, ripeness : 0.58, levels : 0.63, remains : 0.6, challenge : 0.49, due : 0.49, to : 0, high : 0, subjectivity : 0.59, time : 0.42, intensive : 0.52, nature : 0.46, process : 0.51, particularly : 0.31, large : 0.44, scale : 0.6, agricultural : 0.31, operations : 0.45, network : 0.6, cnn : 0, deep : 0.58, learning : 0.42, approach : 0, offers : 0.51, significant : 0.46, potential : 0.32, automating : 0.32, improving : 0.41, accuracy : 0.42, tasks : 0.55, by : 0, extracting : 0.56, complex : 0.51, visual : 0.43, features : 0.62, such : 0.51, as : 0.54, color : 0.44, texture : 0.57, this : 0.46, study : 0.5, employs : 0.6, slr : 0.54, evaluate : 0.58, relevant : 0.58, research : 0.58, from : 0.46, 2019 : 0, 2024 : 0, was : 0.49, analyzed : 0.42, identify : 0.5, trends : 0.53, utilizing : 0, purpose : 0.35, results : 0.52, demonstrate : 0.71, that : 0.46, achieves : 0.58, superior : 0.63, 90 : 0, compared : 0.47, traditional : 0.41, methods : 0.52, like : 0.46, k : 0, nearest : 0.69, neighbor : 0.5, knn : 0, however : 0.6, limitations : 0.48, include : 0.42, restricted : 0.58, dataset : 0.49, diversity : 0.52, insufficient : 0.47, testing : 0.49, under : 0.55, real : 0.46, world : 0, conditions : 0.41, recommendations : 0.59, emphasize : 0.65, need : 0.58, larger : 0.53, more : 0.42, diverse : 0.61, datasets : 0.47, integration : 0.44, additional : 0.41, media : 0.38, spectral : 0.7, data : 0.46, video : 0.44, enhance : 0.51, model : 0.38, robustness : 0.51 |
| 13. pendek | 130 words | 0.72 | systematic : 0.42, literature : 0.42, review : 0.56, on : 0.56, the : 0.5, application : 0.42, of : 0, convolutional : 0.41, neural : 0.39, networks : 0.51, for : 0, rambutan : 0, fruit : 0, classification : 0, advances : 0.51, challenges : 0.6, and : 0.67, future : 0.44, directions : 0.34, nephelium : 0.62, lappaceum : 0.52, l : 0, is : 0, a : 0, tropical : 0.43, widely : 0.39, cultivated : 0.42, in : 0.56, southeast : 0.43, asia : 0, including : 0.52, indonesia : 0.61, manual : 0.44, types : 0.58, ripeness : 0.72, levels : 0.56, remains : 0.44, challenge : 0.43, due : 0.5, to : 0, high : 0, subjectivity : 0.42, time : 0.47, intensive : 0.35, nature : 0.56, process : 0.59, particularly : 0.48, large : 0.46, scale : 0.46, agricultural : 0, operations : 0.51, network : 0.53, cnn : 0.5, deep : 0.61, learning : 0.53, approach : 0.43, offers : 0.44, significant : 0.42, potential : 0.65, automating : 0, improving : 0.43, accuracy : 0, tasks : 0.46, by : 0, extracting : 0.42, complex : 0.44, visual : 0, features : 0.53, such : 0, as : 0, color : 0, texture : 0.54, this : 0, study : 0.46, employs : 0.37, slr : 0, evaluate : 0.53, relevant : 0.53, research : 0.53, from : 0, 2019 : 0, 2024 : 0, was : 0, analyzed : 0.53, identify : 0.46, trends : 0.67, utilizing : 0, purpose : 0.59, results : 0.44, demonstrate : 0.42, that : 0, achieves : 0.53, superior : 0.53, 90 : 0, compared : 0.53, traditional : 0.42, methods : 0.54, like : 0.47, k : 0, nearest : 0.53, neighbor : 0.36, knn : 0.5, however : 0.54, limitations : 0, include : 0.64, restricted : 0.51, dataset : 0.44, diversity : 0.35, insufficient : 0.5, testing : 0.44, under : 0.53, real : 0.47, world : 0.46, conditions : 0.51, recommendations : 0.52, emphasize : 0.35, need : 0.72, larger : 0.44, more : 0.47, diverse : 0.54, datasets : 0.53, integration : 0.34, additional : 0.42, media : 0.58, spectral : 0.53, data : 0, video : 0.41, enhance : 0.64, model : 0.41, robustness : 0.51 |
| 14. tahun | 130 words | 0.73 | systematic : 0.43, literature : 0.63, review : 0, on : 0, the : 0.72, application : 0.43, of : 0, convolutional : 0.35, neural : 0.46, networks : 0.44, for : 0, rambutan : 0.66, fruit : 0.47, classification : 0.42, advances : 0.55, challenges : 0.52, and : 0.51, future : 0.41, directions : 0.43, nephelium : 0.44, lappaceum : 0.44, l : 0, is : 0, a : 0.73, tropical : 0.5, widely : 0, cultivated : 0.37, in : 0, southeast : 0.48, asia : 0.48, including : 0.37, indonesia : 0.44, manual : 0.59, types : 0.52, ripeness : 0.44, levels : 0, remains : 0.56, challenge : 0.53, due : 0, to : 0.61, high : 0.48, subjectivity : 0.43, time : 0.54, intensive : 0.37, nature : 0.59, process : 0, particularly : 0.51, large : 0.47, scale : 0.47, agricultural : 0.52, operations : 0.53, network : 0.45, cnn : 0, deep : 0, learning : 0.55, approach : 0.44, offers : 0, significant : 0.43, potential : 0.54, automating : 0.61, improving : 0.44, accuracy : 0.55, tasks : 0.68, by : 0, extracting : 0.63, complex : 0, visual : 0.46, features : 0.55, such : 0.48, as : 0.57, color : 0, texture : 0.61, this : 0.67, study : 0.6, employs : 0, slr : 0, evaluate : 0.55, relevant : 0.44, research : 0.44, from : 0, 2019 : 0, 2024 : 0, was : 0.51, analyzed : 0.55, identify : 0.44, trends : 0.62, utilizing : 0.53, purpose : 0.45, results : 0.45, demonstrate : 0.43, that : 0.71, achieves : 0.55, superior : 0.44, 90 : 0, compared : 0.44, traditional : 0.66, methods : 0.56, like : 0, k : 0, nearest : 0.45, neighbor : 0.44, knn : 0, however : 0.45, limitations : 0.53, include : 0.45, restricted : 0.43, dataset : 0.4, diversity : 0, insufficient : 0.36, testing : 0.61, under : 0, real : 0.48, world : 0, conditions : 0.43, recommendations : 0.42, emphasize : 0.37, need : 0, larger : 0.46, more : 0, diverse : 0, datasets : 0.38, integration : 0.36, additional : 0.52, media : 0, spectral : 0, data : 0.48, video : 0, enhance : 0.57, model : 0, robustness : 0.53 |
| 15. akademik | 130 words | 0.74 | systematic : 0.51, literature : 0.32, review : 0.53, on : 0, the : 0.49, application : 0.49, of : 0, convolutional : 0.4, neural : 0.36, networks : 0.5, for : 0, rambutan : 0.5, fruit : 0.44, classification : 0.46, advances : 0.63, challenges : 0.48, and : 0.67, future : 0.43, directions : 0.56, nephelium : 0.46, lappaceum : 0.65, l : 0, is : 0, a : 0.74, tropical : 0.42, widely : 0.53, cultivated : 0.39, in : 0, southeast : 0.41, asia : 0.63, including : 0.49, indonesia : 0.57, manual : 0.53, types : 0.44, ripeness : 0.42, levels : 0.43, remains : 0.57, challenge : 0.49, due : 0.64, to : 0, high : 0, subjectivity : 0.47, time : 0.42, intensive : 0.49, nature : 0.53, process : 0.42, particularly : 0.47, large : 0.55, scale : 0.55, agricultural : 0.52, operations : 0.45, network : 0.51, cnn : 0, deep : 0.58, learning : 0.47, approach : 0.55, offers : 0.43, significant : 0.41, potential : 0.49, automating : 0.6, improving : 0.41, accuracy : 0.55, tasks : 0.55, by : 0, extracting : 0.45, complex : 0.35, visual : 0.43, features : 0.33, such : 0, as : 0.59, color : 0, texture : 0.42, this : 0, study : 0.44, employs : 0, slr : 0, evaluate : 0.58, relevant : 0.33, research : 0.33, from : 0.46, 2019 : 0, 2024 : 0, was : 0.49, analyzed : 0.63, identify : 0.58, trends : 0.36, utilizing : 0.41, purpose : 0.42, results : 0.42, demonstrate : 0.55, that : 0.46, achieves : 0.52, superior : 0.5, 90 : 0, compared : 0.42, traditional : 0.55, methods : 0.35, like : 0.58, k : 0.71, nearest : 0.35, neighbor : 0.42, knn : 0.49, however : 0.42, limitations : 0.38, include : 0.51, restricted : 0.48, dataset : 0.61, diversity : 0.57, insufficient : 0.31, testing : 0.51, under : 0.55, real : 0.42, world : 0.44, conditions : 0.48, recommendations : 0.46, emphasize : 0.49, need : 0.42, larger : 0.53, more : 0.46, diverse : 0.51, datasets : 0.58, integration : 0.44, additional : 0.6, media : 0.64, spectral : 0.42, data : 0.6, video : 0.55, enhance : 0.51, model : 0.55, robustness : 0.41 |
| 16. 2023 | 130 words | 0.88 | systematic : 0, literature : 0, review : 0, on : 0, the : 0, application : 0, of : 0, convolutional : 0, neural : 0, networks : 0, for : 0, rambutan : 0, fruit : 0, classification : 0, advances : 0, challenges : 0, and : 0, future : 0, directions : 0, nephelium : 0, lappaceum : 0, l : 0, is : 0, a : 0, tropical : 0, widely : 0, cultivated : 0, in : 0, southeast : 0, asia : 0, including : 0, indonesia : 0, manual : 0, types : 0, ripeness : 0, levels : 0, remains : 0, challenge : 0, due : 0, to : 0, high : 0, subjectivity : 0, time : 0, intensive : 0, nature : 0, process : 0, particularly : 0, large : 0, scale : 0, agricultural : 0, operations : 0, network : 0, cnn : 0, deep : 0, learning : 0, approach : 0, offers : 0, significant : 0, potential : 0, automating : 0, improving : 0, accuracy : 0, tasks : 0, by : 0, extracting : 0, complex : 0, visual : 0, features : 0, such : 0, as : 0, color : 0, texture : 0, this : 0, study : 0, employs : 0, slr : 0, evaluate : 0, relevant : 0, research : 0, from : 0, 2019 : 0.73, 2024 : 0.88, was : 0, analyzed : 0, identify : 0, trends : 0, utilizing : 0, purpose : 0, results : 0, demonstrate : 0, that : 0, achieves : 0, superior : 0, 90 : 0.58, compared : 0, traditional : 0, methods : 0, like : 0, k : 0, nearest : 0, neighbor : 0, knn : 0, however : 0, limitations : 0, include : 0, restricted : 0, dataset : 0, diversity : 0, insufficient : 0, testing : 0, under : 0, real : 0, world : 0, conditions : 0, recommendations : 0, emphasize : 0, need : 0, larger : 0, more : 0, diverse : 0, datasets : 0, integration : 0, additional : 0, media : 0, spectral : 0, data : 0, video : 0, enhance : 0, model : 0, robustness : 0 |
| 17. 2024 | 130 words | 1 | systematic : 0, literature : 0, review : 0, on : 0, the : 0, application : 0, of : 0, convolutional : 0, neural : 0, networks : 0, for : 0, rambutan : 0, fruit : 0, classification : 0, advances : 0, challenges : 0, and : 0, future : 0, directions : 0, nephelium : 0, lappaceum : 0, l : 0, is : 0, a : 0, tropical : 0, widely : 0, cultivated : 0, in : 0, southeast : 0, asia : 0, including : 0, indonesia : 0, manual : 0, types : 0, ripeness : 0, levels : 0, remains : 0, challenge : 0, due : 0, to : 0, high : 0, subjectivity : 0, time : 0, intensive : 0, nature : 0, process : 0, particularly : 0, large : 0, scale : 0, agricultural : 0, operations : 0, network : 0, cnn : 0, deep : 0, learning : 0, approach : 0, offers : 0, significant : 0, potential : 0, automating : 0, improving : 0, accuracy : 0, tasks : 0, by : 0, extracting : 0, complex : 0, visual : 0, features : 0, such : 0, as : 0, color : 0, texture : 0, this : 0, study : 0, employs : 0, slr : 0, evaluate : 0, relevant : 0, research : 0, from : 0, 2019 : 0.73, 2024 : 1, was : 0, analyzed : 0, identify : 0, trends : 0, utilizing : 0, purpose : 0, results : 0, demonstrate : 0, that : 0, achieves : 0, superior : 0, 90 : 0.58, compared : 0, traditional : 0, methods : 0, like : 0, k : 0, nearest : 0, neighbor : 0, knn : 0, however : 0, limitations : 0, include : 0, restricted : 0, dataset : 0, diversity : 0, insufficient : 0, testing : 0, under : 0, real : 0, world : 0, conditions : 0, recommendations : 0, emphasize : 0, need : 0, larger : 0, more : 0, diverse : 0, datasets : 0, integration : 0, additional : 0, media : 0, spectral : 0, data : 0, video : 0, enhance : 0, model : 0, robustness : 0 |
| 18. subtitlestatus | 130 words | 0.72 | systematic : 0.63, literature : 0.57, review : 0.33, on : 0, the : 0.6, application : 0.42, of : 0, convolutional : 0.45, neural : 0.48, networks : 0.42, for : 0, rambutan : 0.51, fruit : 0.49, classification : 0.45, advances : 0.46, challenges : 0.5, and : 0, future : 0.57, directions : 0.44, nephelium : 0.41, lappaceum : 0.45, l : 0.69, is : 0.55, a : 0, tropical : 0.51, widely : 0.46, cultivated : 0.59, in : 0.52, southeast : 0.72, asia : 0.55, including : 0.35, indonesia : 0.45, manual : 0.46, types : 0.44, ripeness : 0.47, levels : 0.4, remains : 0.44, challenge : 0.46, due : 0.6, to : 0.52, high : 0.44, subjectivity : 0.72, time : 0.65, intensive : 0.45, nature : 0.46, process : 0.44, particularly : 0.49, large : 0.51, scale : 0.64, agricultural : 0.48, operations : 0.45, network : 0.31, cnn : 0, deep : 0.44, learning : 0.36, approach : 0.4, offers : 0.33, significant : 0.52, potential : 0.59, automating : 0.55, improving : 0.39, accuracy : 0.46, tasks : 0.49, by : 0.52, extracting : 0.48, complex : 0.48, visual : 0.56, features : 0.51, such : 0.64, as : 0.52, color : 0.42, texture : 0.49, this : 0.49, study : 0.54, employs : 0.31, slr : 0.64, evaluate : 0.49, relevant : 0.47, research : 0.42, from : 0, 2019 : 0, 2024 : 0, was : 0.47, analyzed : 0.46, identify : 0.36, trends : 0.4, utilizing : 0.58, purpose : 0.44, results : 0.65, demonstrate : 0.47, that : 0.55, achieves : 0.53, superior : 0.61, 90 : 0, compared : 0.3, traditional : 0.54, methods : 0.44, like : 0.54, k : 0, nearest : 0.38, neighbor : 0.42, knn : 0, however : 0.4, limitations : 0.55, include : 0.49, restricted : 0.45, dataset : 0.45, diversity : 0.41, insufficient : 0.42, testing : 0.56, under : 0.51, real : 0.38, world : 0.42, conditions : 0.39, recommendations : 0.35, emphasize : 0.41, need : 0.44, larger : 0.49, more : 0.44, diverse : 0.38, datasets : 0.53, integration : 0.44, additional : 0.4, media : 0.49, spectral : 0.57, data : 0.44, video : 0.51, enhance : 0.4, model : 0.35, robustness : 0.69 |