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INDONESIA
Journal of Enviromental Engineering and Sustainable Technology
Published by Universitas Brawijaya
ISSN : 23563117     EISSN : 23563109     DOI : -
Core Subject : Social,
Environmental Science
JEEST is an interdisciplinary and refereed journal, addresses matters related to environmental engineering and sustainable technology. Its range of themes encompasses ecological studies, field research, empirical work and descriptive analyses on topics such as environmental systems, environmental policies and politics, environmental legislation, environmental impact assessment, air, water and land pollution, water and energy related issues, engineering innovations, development, technical solutions and sustainability technology. Other matters related to or which influence the international debate on sustainability will be also considered.
Arjuna Subject : -
Articles 8 Documents
 1 
Search results for , issue "Vol 2, No 1 (2015)" : 8 Documents clear
PEMILIHAN ALTERNATIF SIMPLISIA MENGGUNAKAN METODE WEIGHTED PRODUCT (WP) DAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) Febrianita Indah Perwitasari; Arief Andy Soebroto; Nurul Hidayat
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (114.94 KB) | DOI: 10.21776/ub.jeest.2015.002.01.4

Abstract

Nowadays, people tend to consume organic stuff for meal and medication because of its condition of being secure and inexpensive price. Simplisia is organic material which is not yet processed in order to cure the illness. The part that is used from the whole part to the each piece of simplisia, such as leaves, flowers, fruits, and so on. Simplisia has been being used for solution to the illness, especially at Poli Obat Tradisional RSUD Dr. Soetomo. There are many variants of illness that can be cured by simplisia and there are many variants of simplisia than can be used to cure the illness, which are all usually made the people confused which one is the best variant to cure. Regarding of choosing the alternatives, there is more than one method in Decision Support System that can be used to solve the problem. In this research, there will be two methods that aim at finding the best alternative of simplisia, which are Weighted Product (WP) and Simple Additive Weighting (SAW). Comparison research is used to decide which method as the best method on giving simplisia for the illness. The test scenario is comparing between the result which is given by the system and by the doctor. The accuracy of the result for WP method is 89% and SAW method is 89%.
OPTIMASI FUZZY INFERENCE SYSTEM SUGENO DENGAN ALGORITMA HILL CLIMBING UNTUK PENENTUAN HARGA JUAL RUMAH Arinda Hapsari Achnas; Imam Cholissodin; Wayan Firdaus Mahmudy
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (101.587 KB) | DOI: 10.21776/ub.jeest.2015.002.01.5

Abstract

A house selling price can be determined by two methods, financially and technically. Hovewer, the selling price that determined by the methods are often different. It makes the manager having a problem when determining the house final selling price accurately. This paper proposes Sugeno Fuzzy Inference System (FIS) to calculate an accurate price. To get better result, Hill Climbing Algorithms is used to optimize the membership function of Sugeno FIS. A series of computational experimens prove that the approach is effective. Hill Climbing Algorithms can improve the accuracy of results.
PENGEMBANGAN SISTEM PAKAR DIAGNOSA PENYAKIT SAPI POTONG DENGAN METODE FUZZY K-NEAREST NEIGHBOUR Restia Dwi Oktavianing Tyas; Arief Andy Soebroto; Muhammad Tanzil Furqon
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (104.109 KB) | DOI: 10.21776/ub.jeest.2015.002.01.8

Abstract

Early detection and treatment of cow disease is an important thing for increasing productivity of beef. The dependence of the existence of an expert or veterinarian is too high. It is caused by a lack of knowledge of the breeder about cow disease. This is a condition in which an expert is needed. However, An expert or veterinarian is not always there every encountered, especially in country areas. Those problems can be solved by expert systems. This expert system using fuzzy K-Nearest Neighbour method to process the diagnosis. The results show the functional validation testing and system expertise by 100% and accuracy test variation k, variations training data and m by 97.56%.
EVALUASI PENGOPTIMALAN INSTALASI PENGOLAHAN AIR LIMBAH TERHADAP PENCEMARAN SUNGAI WANGI DI PASURUAN Mochamad Awaludin Adam; Maftuch .
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (259.29 KB) | DOI: 10.21776/ub.jeest.2015.002.01.1

Abstract

Water pollution that occurred 2014 in Wangi river flow caused by many things, such as household waste, industrial waste disposal and the market as well as the erosion process. The sourcesed of river stream that comes from the river Prigen and empties into the river flow Bangil Pasuruan. Pollution in rivers Wangi had a negative effect on the environment. Streams that previously could be used by residents for everyday activities began to change in recent times. The activities necessary to manage liquid waste so that the effluent that discharged into the environment does not exceed effluent quality standards have been set. The activity will be successful if any commitment and control as well as the cooperation of all parties.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN ALGORITMA SIMPLIIFIED SEQUENTIAL MINIMAL OPTIMIZATION (SSMO) PADA SUPPPORT VECTOR MACHINE (SVM) Eugenius Yosep Korsan N; Arief Andy Soebroto; Imam Cholissodin
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (338.686 KB) | DOI: 10.21776/ub.jeest.2015.002.01.6

Abstract

Balai Pembibitan Ternak Unggul (BPTU) Sapi Bali di Jembrana, Bali merupakan sebuah tempat pembudidayaan Sapi Bali yang memiliki kualitas unggul.Sapi Bali merupakan jenis sapi yang memiliki ciri khas yang unik. Ciri khas tersebut terletak pada warna kulit Sapi Bali yang mengalami perubahan sesuai dengan jenis kelamin dan usianya. Pemilihan bibit unggul Sapi Bali di BPTU dilakukan dengan berbagai macam cara. Salah satunya melihat pola warna kulit secara langsung yang terdapat pada tubuh Sapi Bali. Proses pemilihan bibit unggul Sapi Bali rentan terjadinya kesalahan yang dilakukan oleh para peternak (human error) dikarenakan jumlah Sapi Bali yang banyak di BPTU Sapi Bali. Pemilihan bibit unggul diklasifikasikan ke dalam tiga kelas yaitu Baik (Bibit Unggul), Sedang, Buruk. Untuk itu, perlu dibutuhkan suatu sistemyang mampu menghasilkan klasifikasi bibit unggul Sapi Bali berdasarkan warna kulit yang diambil menggunakan citra digital.Pada sistem tersebut, akan menerapkan algoritma SimplifiedSequential Minimal Optimization (SSMO)dengan kernel Radial Basis Function (RBF)  untuk proses training data dan metode One-Against-All untuk proses klasifikasi berdasarkan fitur rata-rata dari nilai red, green dan blue (RGB). Hasil dari skenario pengujian didapatkan rata-rata tingkat akurasi untuk empat skenario pengujian Sapi Bali Jantan dan Betina sebesar 97.50% dan 67.50%.
PENERAPAN ALGORITMA GENETIKA UNTUK MEMAKSIMALKAN LABA PRODUKSI JILBAB Samaher .; Wayan Firdaus Mahmudy
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (72.037 KB) | DOI: 10.21776/ub.jeest.2015.002.01.2

Abstract

A maximum profit is the main goal of each production processes in industry. However, the profit is limited by the availability of production material and investment fund. The producer should determine the volume of each product types (hijab) to get a maximum profit while considering various production constraints. This study proposes genetic algorithm to obtain an appropriate production volume. Computational experiments are conducted to get the best parameters for the genetic algorithm. By using the best parameters, the proposed algorithm results the combination of product types that should be produced with maximum profit and lowest constraints violation.
PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN METODE K-NEAREST NEIGHBOR Indra Ekaristio P; Arief Andy Soebroto; Ahmad Afif Supianto
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.329 KB) | DOI: 10.21776/ub.jeest.2015.002.01.7

Abstract

Bali cattle is an Indonesian native cattle that have a characteristic of the color of his skin. Bali cattle skin color can indicate the quality of the Bali cattle. The classification of the quality of Bali cattle directly is difficult because the human eye has a limited ability to see colors. A decision support system that is able to classify the quality of Bali cattle is based on a digital image of the skin color can help to overcome these limitations. The system will classify Bali cattle into three classes, namely Good (Seeds Superior), Average and Poor. System applying the K-Nearest Neighbor algorithm for the classification process is based on the average features and standard deviation of the red, green, and blue (RGB). This research tested a method to obtain the best value of K, the best image size, and the amount of training data best that will be used. Male Bali cattle using a value of K = 3, image size = 128×128 pixel, and the amount of training data = 45. While the female Bali cattle using a value of K = 6, image size = 64×64 pixel, and the amount of training data = 30. The results of testing the accuracy of the system for male Bali cattle is 100%, while the results of testing the accuracy of the system for female Bali cattle is 66.67%.
PENGARUH ARSITEKTUR ANFIS PADA PERAMALAN CUACA Candra Dewi
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (165.935 KB) | DOI: 10.21776/ub.jeest.2015.002.01.3

Abstract

Dalam proses pembelajaran dengan Adaptive Neuro Fuzzy Inference System (ANFIS), selain parameter laju pembelajaran dan error harap, jumlah neuron dalam tiap lapisan juga sangat mempengaruhi hasil pembelajaran. Dengan demikian, pengujian untuk mendapatkan arsitektur jaringan yang optimal perlu untuk dilakukan. Adapun dalam arsitektur  ANFIS, bagian lapisan yang memegang peranan adalah lapisan pertama dan lapisan kedua, dimana lapisan pertama yang merupakan fuzzyfikasi dari input dan lapisan kedua mewakili jumlah aturan fuzzy dalam proses inferensi. Pada penelitian ini diimplementasikan pengujian arsitektur ANFIS untuk peramalan cuaca, terutama untuk mengetahui jumlah neuron yang paling baik pada lapisan pertama dan kedua.Hasil uji coba menunjukkan bahwa kombinasi persentase 40%, 50% dan 60% data latih menghasilkan nilai akurasi dan RMSE yang cukup stabil pada beberapa kombinasi neuron (antara 2 sampai 6) pada lapisan pertama dan kedua. Disamping itu dapat diketahui bahwa kombinasi jumlah neuron yang optimal adalah antara 2 sampai 4.

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