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All Journal Jurnal Teknik ITS IPTEK The Journal of Engineering IPTEK Journal of Proceedings Series Sewagati

Detak Yan Pratama

Departemen Teknik Fisika, Institut Teknologi Sepuluh Nopember, Kampus ITS, Keputih, Sukolilo, Surabaya 60111

Author-ID : 3183775

Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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The Application of Neural Network for Predicting Corrotion Rate in Metal Pipe Installation Abdullah, Zulkifli; Pratama, Detak Yan; Sawitri, Dyah; Risanti, Doty Dewi
IPTEK Journal of Proceedings Series Vol 1, No 1 (2014): International Seminar on Applied Technology, Science, and Arts (APTECS) 2013
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2014i1.349

Corrotion is one of the problems that must be considered in the metal pipe installation because it can disturb the operation of the plant. The possibility of the corrotion occurrence can be predicted using neural network system. The black box system in the neural network can be used to calculate several potential causes the corrotion and to predict the corrotion rate. This study had constructed the prediction system of corrotion rate using neural network. The input of the system are material compositions, pH, flow rate and temperature. The material compositions which are used are Carbon (C), Manganese (Mn), Silicon (Si), Phosphorus (P), Sulphur (S), Chromium (Cr), Molybdenum (Mo), Aluminium (Al), Nickel (Ni) and Iron (Fe). The corrotion rate prediction network is using one hidden layer and lavenberg marquardt for the learning algorithm. The Mean Square Error (MSE) which is used to analyze the network performance indicates that both of training and validation show excellence results. The MSE of training is 0,000338971 and the validation is 0,000493117.

Prediction of Ceramic’s Mechanical Properties Based on Sintering Temperature using Neural Network Zulkifli Zulkifli; Detak Yan Pratama; Dyah Sawitri; Purwadi Agus Darwito
IPTEK Journal of Proceedings Series No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015
Publisher : Institut Teknologi Sepuluh Nopember

Ceramics is one of material which apply in many area. Thus, study of its properties is very important to fulfilled the properties requirement. The mechanical properties of ceramic such as flexural strength and hardness mainly depend on the sintering temperature and additive material. The experiments must be done to determine the best mechanical properties based on proportional sintering temperature and additive materials. Simulation for predicting mechanical properties of ceramics had been developed by using Artificial Neural Network. According to neural network simulation, the graphic of simulation result had same pattern to experimental data as the target. For predicting hardness, the Normalized Root Mean Square Error of network is 0 at training and 0.077 at validation part. This value is in line to its Coefficient Correlation which have value closed to 1. Meanwhile, the network can be used to predict flexural strength of ceramics excellently.

Distortion Inspection System Development of Rearview Mirror using Radial Line Method Based on Image Processing Detak Yan Pratama; Apriani Kusumawardhani; Aulia M T Nasution; Andi Rahmadiansyah; Achmadi Achmadi
IPTEK Journal of Proceedings Series No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015
Publisher : Institut Teknologi Sepuluh Nopember

Quality control is one of the important steps in production process of rearview mirror industry. This activity can be in the form of product inspection. As an essential component of vehicle, rearview mirror must be observed especially in distortion assessment. During this time, the assessment of rearview mirror product is finished by experts. Thus, faults of inspection can be occurred. These faults could be caused by a decrease of accuracy which is an effect of eyes tiredness. The technique of image processing method is observed to solve this inspection problem. This study is proposed to construct the distortion inspection system on rearview mirror by using radial line method based on image processing.

Emission Reduction Study for Eco-Campus Program, Case Study in Sepuluh Nopember Institute of Technology Indonesia Ridho Hantoro; Detak Yan Pratama; Endah Laksmi Nugraha; Rizky Nanda Puspitasari
IPTEK Journal of Proceedings Series No 6 (2017): The 3rd International Conference on Civil Engineering Research (ICCER) 2017
Publisher : Institut Teknologi Sepuluh Nopember

Emission of CO2 in Indonesia is high relatively and have reached 1,55-ton carbon (5,67 ton CO2 – eq) per capita. It is predicted to increase up to 3,22-ton carbon per capita in 2050 as increasing of population growth. Indonesian Government has issued the policy for decreasing greenhouse gasses effect below 26% in 2020. It proposed to all of society not only public and private institutions, but also education institution like campus. This study is aimed to identify the factors which can influence greenhouse gasses effect, including carbon emission in transportation, waste management and electrical consumption in Sepuluh Nopember Institute of Technology (ITS). It is projected to support implementation of ITS eco campus program more effectively. Therefore, this study has formulated local planning and policy which can be implemented by campus community to decrease carbon emission and organize ITS as real eco-campus.

Co-Authors Achmadi Achmadi Agus M Hatta Agus Muhammad Hatta Ahmad Fauzan Adziimaa Andi Rahmadiansyah Andri Haris Setyawan Apriani Kusumawardhani Aulia M.T. Nasution Aulia Muhammad Taufiq Nasution Aulia Siti Aisjah Bambang Lelono Widjiantoro Bangkit Dwijo Saputro Dewi Sugihartati Doty Dewi Risanti Dyah Sawitri Endah Laksmi Nugraha Gunawan Nugroho Hatta, Agus Muhamad Hery Widijanto Ika Puspita Iwan Cony Setiadi, Iwan Cony Katherin Indriawati Luthfansyah Mohammad M Kamalul Wafi Muhammad Khamim Asyari Nabila Widad Dira Sinatrya Ontoseno Penangsang Purwadi Agus Darwito Ridho Hantoro Rizky Nanda Puspitasari Ruri Agung Wahyuono Sekartedjo Sekartedjo Septyaningrum, Erna Suyanto, Suyanto Syamsul Arifin Wahyu Nur Handayani Zulkifli Zulkifli Zulkifli Zulkifli

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