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The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm Arkeman, Yandra; Yusuf, Akhmad; Mushthofa, Mushthofa; Fitri Laxmi, Gibtha; Boro Seminar, Kudang
TELKOMNIKA Telecommunication, Computing, Electronics and Control Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

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Abstract

Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II) technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.
PEMODELAN DOWNSCALING LUARAN GCM DAN ANOMALI SST NINO 3.4 MENGGUNAKAN SUPPORT VECTOR REGRESSION (STUDI KASUS CURAH HUJAN BULANAN INDRAMAYU) Maesya, Aries; Buono, Agus; Mushthofa, Mushthofa
Proceedings of KNASTIK 2012
Publisher : Duta Wacana Christian University

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Abstract

anomaly Nino 3.4 as input in the training to predict a rainfall monthly in Indramayu.The techniques of a downscaling is used for a phenomenon indicators of El Nino andSouthern Oscillation (ENSO) climate anomaly such as a Global Circulation Model(GCM) and Sea Surface Temperature (SST) nino 3.4 are commonly used as a primarystudy learn and understand the climate system. This research propose a method fordeveloping a downscaling model GCM output and SST anomaly Nino 3.4 by usingSupport Vector Regression (SVR). The research result showed that GCM output andSST anomaly Nino 3.4 can be approach the average value of monthly rainfall. The bestresult of prediction is Bondan station which has average correlation that is 0.700.
Perbandingan Metode Ekstraksi Ciri Histogram dan PCA untuk Mendeteksi Stoma pada Citra Penampang Daun Freycinetia Satria, Dony; Mushthofa, Mushthofa
Jurnal Ilmu Komputer dan Agri-Informatika Vol 2, No 1 (2013)
Publisher : Departemen Ilmu Komputer IPB

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Abstract

Ekstraksi fitur adalah proses pengambilan ciri sebuah objek yang dapat menggambarkan karakteristik dari objek tersebut. Pada penelitian ini, dua buah metode ekstraksi fitur digunakan, yaitu Principal Component Analysis (PCA) dan histogram untuk melakukan deteksi stoma pada gambar penampang daun Freycinetia. Penelitian ini menggunakan frame berjalan yang melakukan pengolahan bagian citra dan melakukan deteksi kemunculan stoma pada bagian citra tersebut. Untuk memodelkan kemunculan stoma, dibuat tiga kelas frame, yaitu frame dengan kemunculan stoma penuh, frame dengan kemunculan sebagian stoma, dan frame tanpa kemunculan stoma. Untuk proses klasifikasi, digunakan pemodelan menggunakan Jaringan Saraf Tiruan (JST) Backprogragation. Hasil percobaan menunjukkan bahwa ekstraksi fitur menggunakan PCA menghasilkan akurasi yang lebih baik dibandingkan dengan metode histogram. Nilai F1-measure yang terbaik yang didapatkan menggunakan ekstraksi fitur PCA ialah 0.9091.Kata kunci: deteksi stoma, ekstraksi fitur, Freycinetia, histogram, PCA
STRATEGI MITIGASI RESIKO SUPPLY CHAIN DENGAN METODE HOUSE OF RISK Abryandoko, Eko Wahyu; Mushthofa, Mushthofa
Rekayasa Sipil Vol 14, No 1 (2020)
Publisher : Department of Civil Engineering, Faculty of Engineering, University of Brawijaya

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Abstract

CV. Asri Tehnika is a company engaged in the construction, one of the projects that is now in the work by CV. Asri Tehnika is a project building construction of SDN Tlogoagung in Bojonegoro district. This research aims to identify various risks that occur in CV. Asri Tehnika at the time of construction of the building of SDN Tlogoagung District Kedungadem District Bojonegoro, along with the cause. The method used in this research is House of Risk, this method consists of two phases, namely the first phase to identify risk and risk agent, while the second phase is risk management. This research is expected to assist in the problem of supply chain activities within the company.