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Imam Mukhlash
Contact Email
imamm@matematika.its.ac.id
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+6285648721814
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ijcsam.matematika@its.ac.id
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Departemen Matematika, Gedung F Lantai II, Kampus ITS, Keputih, Sukolilo-Surabaya 60111 Jawa Timur, Indonesia Phone: +62 31-5943354 Email:ijcsam.matematika@its.ac.id
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Kota surabaya,
Jawa timur
INDONESIA
International Journal of Computing Science and Applied Mathematics-IJCSAM
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 24775401     DOI : -
Core Subject : Education,
Mathematics
IJCSAM (International Journal of Computing Science and Applied Mathematics) is an open access journal publishing advanced results in the fields of computations, science and applied mathematics, as mentioned explicitly in the scope of the journal. The journal is geared towards dissemination of original research and practical contributions by both scientists and engineers, from both academia and industry. IJCSAM (International Journal of Computing Science and Applied Mathematics) is a journal published by Pusat Publikasi Ilmiah LPPM, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
Arjuna Subject : Matematika - Matematika Terapan
Articles 3 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2016)" : 3 Documents clear
Quality Control Analysis of The Water Meter Tools Using Decision-On-Belief Control Chart in PDAM Surya Sembada Surabaya Farida Agustini Widjajati; Nuri Wahyuningsih; Lisda Septi Hasofah
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 2 No. 1 (2016)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

Efforts to maintain and improve the quality of the resulting product can be done by using statistical quality control. One of the methods used in quality control is DOB (Decision On Belief) control chart. DOB control chart is a controller diagram which is used in quality control of univariate data. In this paper, we discuss quality control of the water meter tools using DOB control chart. The case study is in PDAM Surya Sembada Surabaya. Production quality control can also be applied to the c univariate control chart to compute the sensitivity of DOB control chart. Implementation of c control chart and DOB control chart indicates that the data of water meter tools have not been statistically controlled. Application of DOB control chart provides results that are more sensitive by 23.33% than c control chart based on the amount of data that is out of control.
Classification of Poverty Levels Using k-Nearest Neighbor And Learning Vector Quantization Methods Santoso Santoso; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 2 No. 1 (2016)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

Poverty is the inability of individuals to fulfill the minimum basic needs for a decent life. The problem of poverty is one of the fundamental problems that become the central attention of the local government. One of the government efforts to overcome poverty is using the alleviation programs. Government often faces some difficulties to sort out of the poverty levels in the society. Therefore it is necessary to conduct a study that helps the government to identify the poverty level so that the aid did not miss the targets. In order to tackle this problem, this paper leverages two classification methods: k-nearest neighbor (k-NN) and learning vector quantization (LVQ). The purpose of this study is to compare the accuracy of the value of both methods for classifying poverty levels. The data attributes that are used to characterize poverty among others include: aspects of housing, health, education, economics and income. From the testing results using both methods, the accuracy of k-NN is 93.52%, and the accuracy of LVQ is 75.93%. It can be concluded that the classification of poverty levels using k-NN method gives better performance than using LVQ method.
Auto Floodgate Control Using EnKf-NMPC Method Evita Purnaningrum; Erna Apriliani
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 2 No. 1 (2016)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

One of the flood controls, especially in the downstream areas are barrage. Those are optimized using Ensemble Kalman filter based non linear predictive control. Ensemble Kalman Filter is used to predict water levels and flow of waters when it reaches the barrage. The results obtained from this method is then used as input for controlling the floodgates. Simulations are performed in three circumstances, namely the normal flow, flooding and drought. For normal flow, using optimum quantities are obtained from NMPC by opening the floodgates. Simulations were performed for 100 hours, with a gap of 5 per hour of observation. EnKf fulfilled with RMSE yields accuracy of the system and estimates of less than 1, RMSE debit is 0.5346 and RMSE water level is 0.2716. Furthermore the operation of the opening gate achieves optimum value, with the movement of between 40 - 65 per cent, with an average difference of movement is 0.10065 percent. Flood conditions, the water flow 2.000 m3/s and the water level 10 m operation of opening gate ranging between 98 - 100 per cent and the amount of the difference opening gate is 0.028835. RMSE to estimate the flow rate of 1.5835, while for the water level of 0.3145. While the flow conditions dry, with water flow 10 m3/s and the water level 1 m operation of opening gate ranging between 0 - 1 percent and the amount of the difference opening gate is 0.41289 percent. RMSE to estimate the flow rate of 0.0826, while for the water level of 0.0677.

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