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Yogyakarta, Indonesia

Heriana O.,Indonesian Institute of Sciences | Soesanti I.,University of Technology, Yogyakarta
Proceeding - 2015 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2015 | Year: 2015

Breast cancer was a disease with the condition of the breast tissue became abnormal due to the development of cancer cells in the breast area. One method of breast cancer nondestructive detection was by through shooting the indicated breast cancer by using an infrared camera. The emission variations of infrared radiation on the image captured showed the level of cancer. The results of infrared camera imaging called as thermography image was processed in computing algorithm to classify the cancer in breast areas according to the characteristics of each image. The image feature extraction was obtained through the calculation of fractal dimension of the image by using the box counting algorithm. Image classification process was done by using the Fuzzy C-Means algorithm to determine the level of the breast cancer size based on the T component of the TNM system, namely T0, T1, T2 and T3 to the 22 image data to obtain the value of parameter cluster centers in Fuzzy C-Means. The test results showed that the feature extraction of breast thermography image using box counting fractal method gave the different value between normal breast and inflammatory cancer breast tissues. Normal breast tissue (T0) had a fractal dimension average less than T1, there was 1.161525 with deviation standard value was 0.593625. Breast with tumor T1 had a fractal dimension average less than T2, there was 1.45455 with deviation standard value was 0.4645. Breast with tumor T2 had a fractal dimension average less than T3, there was 1.6596 with deviation standard value was 0.2925, and breast with tumor T3 had a fractal dimension average 1.81294 with deviation standard value was 0.20199. The classification of tumor size using Fuzzy C-Means in 3 and 4 clusters with the use of 64×64 pixel box size in box counting process was more consistent than the use of 32×32 pixels box size. © 2015 IEEE.

Suyitno,University of Technology, Yogyakarta | Sutiyoko,Manufacturing Polytechnic of Ceper
Procedia Engineering | Year: 2012

The objective of this research is to investigate the characteristics of gray cast iron in lost foam casting with the pouring temperature and the thickness variation. The Observed characteristics are fluidity, porosity and surface roughness. The pouring temperatures were 1300 - 1400 °C. The pattern was made from a polystyrene foam with 9 kg/m3of density. The pattern was designed with 10 mm of width and the thickness variation are 2 - 6.5 mm. A quartz sand with 50 of AFS was vibrated with an amplitude of 0.5 mm and a frequency of 23 Hz. The composition of the gray cast iron is 3.35 %C, 2.29 %Si, 0.449 %Mn and 0.189 %P. The Fluidity of gray cast iron increases with the pouring temperature. Normalizatied of the fluidity can estimate the fluidity at the different of the thickness. The porosity and surface roughness increase with the pouring temperature. © 2012 Elsevier B.V.

Marlina E.,University of Technology, Yogyakarta
International Journal of Smart Home | Year: 2016

The enactment of the region of Mount Sewu as a Global Geopark Network (GNN) on 19 September 2015 has given a responsibility for governments and communities to develop this region with a proper concept. The karst of Mount Sewu surrounding the Gunungkidul Regency, Wonogiri Regency and Pacitan Regency is one of the most well-known karst regions in Java Island for its uniqueness. Geoheritage and social-cultural wealth in this region becomes the base of its enactment as GGN. This study presents geotourism as a strategy of geosite empowerment towards the tourism sustainability in Gunungkidul regency. It is found that the Geotourism development comes to be an appropriate strategy in developing 13 geosites in Gunungkidul for fulfilling the directive of the policy on the local and national tourism development, demands of the development trend towards the tourism interest among community and the directive of GGN in accordance with the concept as outlined in UNESCO. The directive of the development of this geotourism has been formulated through a synthesis of various analyses including the analysis of government, analysis of potential tourist attraction, and SWOT analysis. The dialogue from a variety of analyses required to produce the formula of geotourism development of various analyses is needed to guarantee the production of a formulation of the proper and synergic directive for the geotourism development analysis necessary to guarantee the formulation of appropriate and synergic Geotourism development with various existing development guidelines. © 2016 SERSC.

Abdullah Z.,University of Malaysia, Terengganu | Herawan T.,University of Technology, Yogyakarta | Deris M.M.,University Tun Hussein Onn Malaysia
Lecture Notes in Electrical Engineering | Year: 2014

Indirect pattern can be considered as one of the interesting information that is hiding in transactional database. It corresponds to the property of high dependencies between two items that are rarely appeared together but indirectly occurred through another items. Therefore, we propose an algorithm for Mining Indirect Least Association Rule (MILAR) from the real dataset. MILAR is embedded with a scalable least measure called Critical Relative Support (CRS). The experimental results indicate that MILAR is capable in generating the indirect least association rules from the given dataset. © Springer Science+Business Media Singapore 2014.

Abdullah Z.,University of Malaysia, Terengganu | Herawan T.,University of Technology, Yogyakarta | Deris M.M.,University Tun Hussein Onn Malaysia
Lecture Notes in Electrical Engineering | Year: 2014

Least association rule refers to the rule that only rarely occur in database but they might reveal some interesting knowledge in certain domain applications. In certain medical datasets, finding these rules is very important and required further analysis. In this paper we applied our novel measure known as Definite Factor (DF) with SLP-Growth algorithm to mining the Definite Least Association Rule (DELAR) from a benchmarked medical datasets. DELAR is also highly correlated and evaluated based on standard Lift measure. The result shows that DF can be used as alternative measure in capturing the interesting rules and thus verify its scalability. © Springer Science+Business Media Singapore 2014.

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