Journal of Enviromental Engineering and Sustainable Technology
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.
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124 Documents
<![CDATA[OPTIMASI FUNGSI KEANGGOTAAN FUZZY TSUKAMOTO MENGGUNAKAN ALGORITMA GENETIKA UNTUK PENENTUAN HARGA JUAL RUMAH ]]>
<![CDATA[Evi Nur Azizah]]>;
<![CDATA[Imam Cholissodin]]>;
<![CDATA[Wayan Firdaus Mahmudy]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.02.3
<![CDATA[Secara umum, penentuan harga jual rumah ditentukan oleh dua bagian yaitu bagian teknik dan bagian keuangan. Namun seringkali harga jual yang didapatkan pada bagian ini berbeda sehingga menyebabkan manager melakukan perhitungan ulang dari kedua hasil tersebut. Untuk menyelesaikan permasalahan tersebut, maka perlu dibuat suatu sistem yang dapat menghitung harga jual secara akurat. Dalam paper ini, harga jual rumah ditentukan menggunakan sistem inferensi fuzzy Tsukamoto. Namun penggunaan logika fuzzy saja masih memungkinkan mendapatkan error yang relative besar. Untuk memperkecil nilai error maka digunakan algoritma genetika untuk menentukan batasan nilai fungsi keanggotaan yang sesuai. Dari pengujian yang dilakukan didapatkan kesimpulan bahwa penggunaan algoritma genetika mampu memperkecil error secara signifikan.]]>
<![CDATA[MULTI GEOPHYSICAL OBSERVATIONS AT BLAWAN - IJEN VOLCANO GEOTHERMAL COMPLEX FOR REGIONAL DEVELOPMENT ]]>
<![CDATA[Sukir Maryanto]]>;
<![CDATA[Agus S Wicaksono]]>;
<![CDATA[Anjar P Azhari]]>;
<![CDATA[Cinantya N Dewi]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.02.7
<![CDATA[Geothermal resource investigation by using multi geophysical observation was accomplished for Blawan-Ijen geothermal system. Geological and surface investigation found about 21 hot springs have been found in Blawan area with the surface temperature ranged from about 40oC-55oC. Based on resistivity and GPR data known that the underground seepage of hot water following the fault direction. This fault structure is identified based on the high distribution of microseismicity and thermal infrared remote sensing (TIR) analysis which associated with high land surface temperature (LST). Meanwhile, the heat source of Blawan - Ijen geothermal system are found in the southwest part based on high magnetic anomaly which represents the igneous rocks. All methods used shows the results indicating that Blawan-Ijen volcano complex is an interesting area for geothermal energy development and suitable for pilot project on regional development of volcano geothermal region.]]>
<![CDATA[EVALUASI PENGOPTIMALAN INSTALASI PENGOLAHAN AIR LIMBAH TERHADAP PENCEMARAN SUNGAI WANGI DI PASURUAN ]]>
<![CDATA[Mochamad Awaludin Adam]]>;
<![CDATA[Maftuch .]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.01.1
<![CDATA[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.]]>
<![CDATA[SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN ALGORITMA SIMPLIIFIED SEQUENTIAL MINIMAL OPTIMIZATION (SSMO) PADA SUPPPORT VECTOR MACHINE (SVM) ]]>
<![CDATA[Eugenius Yosep Korsan N]]>;
<![CDATA[Arief Andy Soebroto]]>;
<![CDATA[Imam Cholissodin]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.01.6
<![CDATA[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%.]]>
<![CDATA[OPTIMASI DISTRIBUSI PUPUK MENGGUNAKAN EVOLUTION STRATEGIES ]]>
<![CDATA[Fauziatul Munawaroh]]>;
<![CDATA[Wayan Firdaus Mahmudy]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.02.5
<![CDATA[The purpose of distribution is accelerating the delivery and equity of goods in various regions. However, the most common problem especially in fertilizer distribution is a high cost distribution in delivery caused by the route and vehicle selection used are less precise and less to maximize the capacity of the vehicle. Several researches have been done using a variety of methods to minimize distribution costs, one of which is the Evolution Strategies algorithm. This research uses permutation representation which is divided into two segments for representate solution. This research using (μ + λ) ES cycle, elitism selection and exchange mutation. Based on this research results, parameters with the best fitness value is the population size of 80, the number of offspring 5, the number of generations of 80, and the composition segments are 30% of segment 1, 20% of segment 2, and 50% for both segments.]]>
<![CDATA[POWER MANAGEMENT CONTROL OF A HYBRID PV-GENSET SYSTEM USING ZELIO LOGIC SMART RELAY ]]>
<![CDATA[Soeprapto Soeprapto]]>;
<![CDATA[Unggul Wibawa]]>;
<![CDATA[Mahfudz Shidiq]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 3, No 1 (2016) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2016.003.01.2
<![CDATA[Power management control using Zelio Logic Smart Relay is applied as a means to make automatic power transition from battery to generator and vice versa. The design of a hybrid system in a laboratory scale is described including the design of software part using Zelio Soft2 (ANONIM 3, 2014). The experiment results show that the values of voltage and power output of the solar cell will increase with the increasing intensity of the sun, while the current will be decreasing. The current sensor used in the system is able to detect the linear changes of current flowing into the load and to respond in a form of voltage to be inputted into Zelio. The automatic operation of genset can be performed properly and the SFC optimum value of the genset of 2.8 kW, 220 V, 50 Hz is 0.67 l/kWh under 72% loading of the generator capacity. Automatic switching of the hybrid system can be realized based on the sensing results of battery voltage and load voltage with the help of Zelio. Load is supplied through the battery inverter when the battery voltage exceeds its voltage, it is supplied directly from the genset and the relay is activated to charge the battery.]]>
<![CDATA[PENERAPAN ALGORITMA GENETIKA UNTUK MEMAKSIMALKAN LABA PRODUKSI JILBAB ]]>
<![CDATA[Samaher .]]>;
<![CDATA[Wayan Firdaus Mahmudy]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.01.2
<![CDATA[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.]]>
<![CDATA[PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN METODE K-NEAREST NEIGHBOR ]]>
<![CDATA[Indra Ekaristio P]]>;
<![CDATA[Arief Andy Soebroto]]>;
<![CDATA[Ahmad Afif Supianto]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.01.7
<![CDATA[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%.]]>
<![CDATA[PENYELESAIAN VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) MENGGUNAKAN ALGORITMA GENETIKA HYBRID ]]>
<![CDATA[Diah Anggraeni Pitaloka]]>;
<![CDATA[Wayan Firdaus Mahmudy]]>;
<![CDATA[Sutrisno .]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 1, No 2 (2014) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2014.001.02.5
<![CDATA[Vehicle Routing Problem with Time Windows (VRPTW) is a combinatorial problem which is used to determine the route of a goods distribution from depots (distribution center) to customers scattered in various points of the site. VRPTW is an extension of the VRP with constraints the limitations on the capacity of goods and every customer have time interval of service [ ] or time windows. In this study, the hybrid genetic algorithm with nearest insertion heuristic is used as one of the search alternative solutions. The implementation for this case, 50% initial solution was generated using nearest insertion heuristic method and 50% rest are generated by randomly. This completion is tested in a set of Solomons problem. The results of this study are compared with the best known solution of Solomon using 2 sets of test data from each data type such as C1, C2, R1, R2, RC1, dan RC2 with 25, 50 and 100 customers. The results show that the implementation of hybrid genetic algorithm and the nearest insertion heuristic gives solutions which is nearly optimal or approaching the best known of Solomon for data type C101, C105, C201, R101, RC101 dan RC102.]]>
<![CDATA[PENGARUH ARSITEKTUR ANFIS PADA PERAMALAN CUACA ]]>
<![CDATA[Candra Dewi]]>
<![CDATA[ Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015) ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya ]]>
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DOI: 10.21776/ub.jeest.2015.002.01.3
<![CDATA[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.]]>
