Classification and identification of synthetic flavor become routine activities in the flavor and food industry due to its application. As a modern olfactory technology, electronic nose (e-nose) has the possibility to be applied in these activities. This study aimed to evaluate an e-nose for classifying synthetic flavors. In this study, an e-nose was designed with an array of gases sensors as the main sensing component and principal component analysis (PCA) for the pattern recognition software. This research was started with preparation of the hardware, continued with preparation of sample, data collection, and analysis. There were nine samples of synthetic flavors with different aroma, namely: grapes, strawberry, mocha, pandanus, mango, jackfruit, orange, melon, and durian. The data collection process includes three stages, i.e. flushing, collecting, and purging of 2 min, 3 min, 2 min respectively. These sensor responses were then analyzed for forming aroma patterns. Four pre-treatment methods were applied for the aroma pattern formation: absolute data, normalize of absolute data, relative data, and normalize of relative data. With the PCA for evaluation, the results showed that the absolute data treatment provided the best results, indicated from the distribution of aroma patterns that were grouped according to the type of samples.

The real data support the “seriousness” of the serious game and give more authentic situations, which can make players feel immersed in scenarios, and gain a real experience. Therefore, the modeler must be able to recognize whether a model reflects reality to identify and deal with divergences between theory and data. In this paper, we present a model for design a basis of immersive in serious games. The studied case is the tillage using a moldboard plow, by taking real data through an experiment use a device called soil bin. It aims to determine the effect of angle, depth, and speed on the soil porosity; by comparing the value of the smallest error using the polynomial function of the use of different orders. The result of an average smallest error with the polynomial approach is 1.10E-07 in the 3rd order, closer to the experimental value. Therefore, the model can be used for designing immersive serious game.

Proses pemupukan merupakan salah satu tahapan yang sangat penting dalam meningkatkan kualitas dan kuatitas tanaman. Penggunaan pupuk kimia secara terus-menerus dengan dosis yang meningkat setiap tahunnya dapat mengganggu keseimbangan hara tanah. Oleh sebab itu dibutuhkan alat pemupuk berbasis variable rate application yang dapat mengatur dosis pupuk yang dibutuhkan oleh tanaman. Tujuan dari penelitian ini yaitu menguji kinerja alat pemupuk berbasis variable rate pada budidaya tanaman kedelai. Bahan yang digunakan adalah pupuk urea, SP-36, KCl, kacang kedelai (Glycine max) varietas Grobogan. Alat yang digunakan pada penelitian ini berupa rol meter, stopwatch, timbangan, multitester, penggaris, jangka sorong dan aplikator pemupuk. Kinerja alat dan dampaknya terhadap pertumbuhan kedelai diobservasi pada demplot seluas 36 x 8 m 2 yang dibagi menjadi 6 petak seluas 12 x 4 m 2 dan tiap petaknya diberikan kode petak A1 hingga A6. Hasil pengujian alat pemupuk di lapangan diperoleh kapasitas lapang efektif (KLE), kapasitas lapang teoritis (KLT), dan efisiensi lapang (Ef) berturut-turut sebesar 624 m 2 /jam, 864 m 2 /jam, dan 72,27%. Dari hasil analisis pertumbuhan tanaman menunjukkan bahwa secara statistik pemberian pupuk menggunakan aplikator tidak secara signifikan mempengaruhi parameter tinggi tanaman tetapi secara signifikan berpengaruh nyata terhadap diameter batang, jumlah daun dan coverage area. Meskipun demikian masih dijumpai ketidakseragaman produktivitas tanaman kedelai yang ditunjukkan dengan nilai signifikansi sebesar 0,028. Analisis regresi dengan variabel SP-36 (X2) terhadap produktivitas didapatkan fungsi Y = -1,405.10 -4 + 0,12X 2 -0,001X 2 2 dengan nilai R 2 sebesar 0,581. Analisis regresi dengan variabel KCl (X3) terhadap produktivitas didapatkan fungsi Y = -2,546.10 -16 + 0,053X 3 -2,063.10 -4 X 3 2 dengan nilai R 2 sebesar 0,701.

This study evaluates an e-nose based on gas sensors to measure the freshness of tilapia. The device consists of a series of semiconductor sensors as detector, a combination of valve-vial-oxygen as sample delivery system, a microcontroller as interface and controller, and a computer for data recording and processing. The e-nose was firstly used to classify the fresh and non-fresh tilapia. A total of 48 samples of fresh tilapia and 50 samples of non-fresh tilapia were prepared and measured using the e-nose through three stages, namely: flushing, collecting, and purging. The sensor responses were processed into aroma patterns, then classified by two pattern classification softwares of principal component analysis (PCA) and neural network (NN). There were four methods for aroma patterns formation being evaluated: absolute data, normalized absolute data, relative data, normalized relative data. The results showed that the normalized absolute data method provides the best classification with the accuracy level of 93.88%. With this method, the trained NN was used to predict the freshness of 15 tilapia samples collected from a traditional market. The result showed that 60.0% of the samples are classified into fresh category, 33.3% are in the non-fresh category, and 6.7% are not included in both categories.

Blora and Grobogan are regions with higher production capacity of corn commodity compared to other regions in Central Java province. However, low number of technical irrigation and el-nino phenomenon have become the main threat for the sustainability of corn farming in both regions. During dry session, the top soil of the land are solidified which lead to higher difficulty for planting the corn seed using traditional tool. An improved design of the traditional seeder is then required to solve this problem to enable farmers plant corn seed during dry session. The objective of this research was to develop seeder prototype with “Tugal Dalam” type in Blora and Grobogan regions where the land have been categorized as marginal land during dry session. The proposed design is based on technical, ergonomic, economical, and social aspect. The qualitative approach was used to obtain the technical, ergonomical, economical and social aspect required by the farmer. Kansei Engineering is used to translate and evaluate the proposed design through some tests conducted on several group of farmers where they were requested to use 4 seeder design options and write their preference on each design option based on the mentioned aspects. Tests confirmed that the proposed design can be used to plant a corn seed at farmers desired characteristics. Kansei engineering also confirmed that ‘high speed’, ‘easy to operate’, ‘low price’, ‘easy to handle’ and ‘has a watering system’ were preferred by the farmers and determined their decision on buying and using the seeder tool. Keywords: kansei engineering,  marginal land, seeder development, tugal dalam