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PERBANDINGAN MODEL ARIMA PADA DATA SPASIAL TRAFIK INTERNET AGREGAT Soesetijo, Sis; Budimulyono, Febrianto; Purnama, Lukas Hadi; Santoso, Welly Wellandow; Setiawan, Hendrik
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 3 (2011): Network And Security
Publisher : Jurusan Teknik Informatika

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Abstract

Pengukuran data spasial trafik internet dilakukan secara agregat selama 46 hari dengan mengambil 4 lokasi pengukuran trafik internet di kampus Universitas Surabaya yaitu Fakultas Bisnis dan Ekonomika, Fakultas Teknik, Perpustakaan dan Kampus Ubaya Ngagel. Pemodelan trafik ini merupakan model trafik internet harian menggunakan model ARIMA (Auto Regressive Integrated Moving Average) dengan validasi model menggunakan qqplot dan uji distribusi normal pada residu model. Oleh karena trafiknya merupakan trafik harian, maka terdapat 184 model ARIMA pada ke-empat lokasi pengukuran trafik tersebut. Hasil pertama yang diperoleh bahwa model ARIMA(1,1,2) merupakan model ARIMA yang umum (sering muncul) pada pemodelan di empat lokasi traf
Lanthanum and Nickel Recovery from Spent Catalyst using Citric Acid: Quantitative Performance Assessment using Response Surface Method Petrus, Himawan Tri Bayu Murti; Wijaya, Ardyanto; Iskandar, Yusuf; Bratakusuma, Danu; Setiawan, Hendrik; Wiratni, Wiratni; Astuti, Widi
Metalurgi Vol 33, No 2 (2018): Metalurgi Vol. 33 No. 2 Agustus 2018
Publisher : Pusat Penelitian Metalurgi dan Material - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (523.642 KB) | DOI: 10.14203/metalurgi.v33i2.437

Abstract

Heavy metals and Rare earth elements (REEs) are nowadays being used widely in many industries from electronics to petroleum industries as catalysts. However, their disposal caused serious problems to the environment. With the sharp growth in its usage, there is a better way to use and utilize valuable metals from secondary sources such as their disposal rather than using new raw materials. The aim of this work is to study the potential of citric acid as a leaching agent to extract lanthanum and nickel in various acid concentration and leaching temperature. The raw material used in this work is spent catalyst from Pertamina Refinery Unit VI, Balongan, Indonesia. The spent catalyst is decarbonized with a heat treatment at 725°C for 10 minutes before the leaching process. The leaching process used 0.1; 1; and 2 M of citric acid with a varied temperature of 30, 60, and 80°C. The lanthanum recovery was calculated by comparing the mass percentage of lanthanum before leaching process and after leaching process using Energy Dispersive X-Ray Spectroscopy (EDX). The results were analyzed by response surface methodology (RSM) and are proved to be a reliable method to depict and analyze the leaching characteristics. The molarity of the citric acid is the most significant independent variables used in the research for lanthanum recovery response. However, based on the Pareto analysis result there are no significant variables that affect the recovery of nickel. The second order polynomial fitting model is also proved to be compatible with the response of lanthanum recovery but is less compatible with nickel recovery.
Natural Colorants from Cosmos Sulphureus Cav. and Tagetes Erecta L.: Extraction And Characterization Rahayuningsih, Edia; Wikansari, Dyah A; Setiawan, Hendrik
ASEAN Journal of Chemical Engineering Vol 16, No 2 (2016)
Publisher : Department of Chemical Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1365.714 KB) | DOI: 10.22146/ajche.49893

Abstract

Ionic liquids demonstrated successful potential applications in the industry most specifically as the new generation of solvents for catalysis and synthesis in chemical processes, thus knowledge of their physico-chemical properties is of great advantage. The present work presents a mathematical correlation that predicts density of binary mixtures of ionic liquids with various alcohols (ethanol/methanol/1-propanol). The artificial neural network algorithm was used to predict these properties based on the variations in temperature, mole fraction, number of carbon atoms in the cation, number of atoms in the anion, number of hydrogen atoms in the anion and number of carbon atoms in the alcohol. The data used for the calculations were taken from ILThermo Database. Total experimental data points of 1946 for the considered binaries were used to train the algorithm and to test the network obtained. The best neural network architecture determined was found to be 6-6-10-1 with a mean absolute error of 48.74 kg/m3. The resulting correlation satisfactorily represents the considered binary systems and can be used accurately for solvent related calculations requiring properties of these systems.
SISTEM PAKAR IDENTIFIKASI JENIS VIRUS PADA KOMPUTER MENGGUNAKAN METODE DEMPSTER SHAFER BERBASIS ANDROID Setiawan, Hendrik
Ubiquitous: Computers and its Applications Journal Vol 2, No 2 (2019): Desember 2019
Publisher : LPPM

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Abstract

Untuk mendapatkan kesimpulan dari suatu masalah kerusakan pada komputer yang disebabkan oleh virus dapat dilakukan dengan mengklasifikasikan suatu gejala ke dalam beberapa kelas. Klasifikasi merupakan pengelompokan atau identifikasi suatu gejala yang disebabkan virus komputer. Dalam melakukan klasifikasi pada suatu gejala terdapat berbagai macam metode diantaranya adalah metode forward chaining, backward chaining, certainty faktor, dan dempster shafer. Dalam penelitian ini mengunakan metode dempster shafer karena metode dempster shafer memiliki perhitungan untuk menentukan besar nilai kebenaran bahwa komputer telah disisipi oleh virus. Dalam klasifikasi ada dua teknik yang digunakan oleh penulis yaitu klasifikasi berdasarkan gejala dan klasifikasi berdasarkan jenis virus. Klasifikasi berdasarkan gejala adalah mengumpulkan semua gejala yang disebabkan virus dan kemudian diklasifikasikan berdasarkan jenis virus yang menginfeksi. Klasifikasi berdasarkan jenis virus adalah mengumpulkan semua nama virus yang ada di dalam dunia komputer dan kemudian diklasifikasikan berdasarkan jenis virus yang ada. Selanjutnya akan dibahas mengenai sistem pakar yang mampu untuk melakukan proses identifikasi jenis virus pada komputer dengan menggunakan salah satu metode matematika yaitu metode dempster shafer, sehingga akan dapat dihitung nilai dari setiap gejala yang ditimbulkan menggunakan perhitungan pada dempster shafer. Hasil perhitungan ini akan menentukan besar nilai kebenaran bahwa suatu komputer telah terinfeksi oleh sebuah virus.