Judul: Graphology Analysis Based on Letter a and t Using Perceptron.
Abstrak: Graphology or handwriting analysis is a method of identifying, analyzing, evaluating, and understanding personality through the strokes and patterns revealed by handwriting. A person who can analyze handwriting is called a graphologist. A graphologists can be subjective in their assesments different graphologist can have different analysis of the same handwriting. Therefore, a computer technology may help to minimize the subjectivity. This research used perceptron to analyze personality based on handwriting. Perceptron is one method of neural network. This research analyze two letters to letter a and t image. Letter a are represented by 135 images, consisting of 81 images as training data and 54 images as testing data. There are 150 images used for t images, consisting of 90 images as training data and 60 images as testing data.There are 5 experiments consisting of 2 experiments for letter a and 3 experiments for letter t. The result is the character of each class letter a and t where each parameters there are 3 classes. The accuracy of letter t and letter a was 55% and 88.89% respectively.
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Judul: Analisis Grafologi Berdasarkan Huruf a dan t Menggunakan Jaringan Syaraf Tiruan Propagasi Balik Standar
Abstrak: Graphology or handwriting analysis is a method of identifying, analysing, evaluating, and understanding personality through the strokes and patterns revealed by handwriting. People who can analyze handwriting called graphologist. Graphologist can have a subjective assesment. Different graphologist can analyze the same handwriting but give different results. In addition, the accuracy of handwriting analysis depend on the graphologists ability. A system that can recognize handwrititng patterns is required to overcome these problems. Identification system which is implemented in this research uses Backpropagation Neural Network (BPNN). This research used 135 images of letter a and 150 images of letter t. This research is divided into three parts which are determining optimal combination of BPNN parameter, identifying personality based on letter a, and identifying personality based on letter t then classifies them into one of three character classes available. The results of this research is that the system has 98.15% accuracy for letter a and 73.33% for letter t. The result shows that Backpropagation Neural Network can be used to classify the personality
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Judul: Penentuan Kondisi Simpan untuk Mempertahankan Viabilitas dan Vigor Benih Kenikir (Cosmos caudatus Kunth.).
Abstrak: Kenikir (Cosmos caudatus Kunth.) merupakan salah satu jenis sayuran indigenos di Indonesia yang dikonsumsi dalam bentuk segar sehingga perlu ditanam terus-menerus. Benih harus tersedia secara kontinyu. Kondisi simpan yang efisien untuk mempertahankan viabilitas dan vigor benih kenikir belum banyak diteliti, oleh karena itu penelitian dilakukan. Penelitian ini dilakukan di Laboratorium Penyimpanan dan Pengujian Mutu Benih, IPB, dari Januari sampai Juli 2016. Penelitian ini dilaksanakan dalam rancangan petak tersarang dua faktor dengan empat ulangan. Faktor pertama adalah suhu ruang simpan yang terdiri atas 4 taraf, yaitu suhu 27 ºC-30 ºC (suhu kamar); 17-21 ºC (suhu ruang ber-AC); 2-12 ºC (refrigerator), dan -5-(-13) ºC (freezer). Faktor kedua adalah jenis kemasan yang terdiri dari 3 taraf, yaitu plastik polietilen, alluminium foil, dan botol kaca, tersarang dalam faktor suhu ruang simpan. Hasil penelitian menunjukkan penyimpanan benih kenikir pada suhu 17-21˚C (ruang ber-AC), 2-12˚C (refrigerator) dan -13˚C-(-5˚C) (freezer) menggunakan kemasan plastik polietilen, alluminium foil, dan botol kaca dapat mempertahankan kadar air, viabilitas, dan vigor selama 24 minggu. Penyimpanan pada suhu 27-31˚C (kamar) harus menggunakan alluminium foil dan botol kaca untuk mempertahankan kadar air, viabilitas, dan vigor. Penyimpanan pada suhu 27-31˚C (kamar) dalam kemasan alluminium foil merupakan penyimpanan yang paling efisien.
Keyword: Asteraceae, daya berkecambah, sayuran indigenos, suhu kamar