Judul: Development of Mangosteen Maturity Classification Model on Color Based Using Fuzzy Neural Network.
Abstrak: Fuzzy Neural Network (FNN) has a capability to classify a pattern located within two different classes where a classical Neural Network (NN) is failed to do so. The fuzzy pattern classification is using membership degree on output of neuron as learning target. Objective of this research is to develop an artificial intelligence system model for non-destructive classification of fresh mangosteen using Fuzzy Neural Network. Component of color result in from image processing that influential against level of mangosteen’s maturity is used as input parameter. Percentage accuracy ratio of FNN model compare to NN for five, three, and two classification classes is 70:40, 86:65 and 90:90 respectively. The best result of FNN modeling is achieved on three class target classification (unripe, export and local) with green color index, value, a* u*, v*, entropy, contrast, energy and homogeinity as predictor parameters and 15 neurons hidden layer. Comparison of percentage capability of FNN against NN to identify the class is 100:0, 100:87 and 63:75.
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Judul: Pengembangan Model Probabilistic Neural Networks untuk Sortasi Belimbing Manis Berdasarkan Citra RGB
Abstrak: Starfruits (Averrhoa Carambola L.) is one of agroproducts which is liked by most society. Typically it is seen like a star when sliced athwartly. The characteristics of starfruits type which pre-eminent are size big, colour draw, smooth fibre, water containment, and fresh sweet. One of the vital process in post-harvest treatment is sortation. Fruits are grouped according to size measure and ripe phase. Starfruits which marketed have to fulfill the standard which accepted by consumer widely, either in domestic market and also global market. This matter in order to give best quality and also improve product competitiveness by farmer. Determination of starftruits sweetness is generally based on fruit colour visually. But, change of colour gradually complicated determination the taste of fruit. This needs more intelligent sortation methods and tools that overcome the sortcomings of manual process. Probabilistic Neural Network (PNN) is one of Artificial Neural Network (ANN) variants that can be used to develop a computer-based sortation engine for starfruits. This research aim is to develop PNN model for starfruits sortation based on RGB image value. Conclusion at this research indicates that PNN can be used to classify starfruits with high accuration reach 92%.
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Judul: Kerusakan bantalan rel kereta api di wilaya inspeksi 2 jalan dan bangunan perusahaan jawatan kereta api (pjka),cirebon
Abstrak: Kereta api merupakan salah satu sarana angkutan yang murah, cepat dan aman serta dapat mengangkut barang dalam jumlah besar. Kelancaran operasi sarana angkutan tersebut banyak ditentukan oleh kondisi jalan rel, termasuk kondisi bantalannya. Dalam hal ini bantalan rel kereta api dapat dibuat dari kayu, logam, atau beton. Namun demikian kayu merupakan bahan yang paling banyak digunakan sebagai pembuat bantalan rel kereta api di berbagai negara. Kenyataan menunjukkan bahwa kayu yang digunakan sebagai bantalan rel kereta api sering mengalami berbagai macam kerusakan yang menyebabkan bantalan tidak berfungsi lagi atau menurun fungsinya. Di Indonesia, informasi mengenai jenis dan tingkat kerusakan bantalan kayu masih sangat kurang, pada- hal informasi tersebut sangat penting sebagai dasar pertimbangan dalam rangka pemeliharaan jalan kereta api, agar umur pakainya (service life) lebih lama.
Keyword: bantalan rel