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ANALISA DATA CURAH HUJAN STASIUN KLIMATOLOGI SEMARANG DENGAN MODEL JARINGAN SYARAF TIRUAN Arif, F M; Gernowo, Rahmat; Setyawan, Agus; Febrianty, D
BERKALA FISIKA Vol 15, No 1 (2012): Berkala Fisika
Publisher : BERKALA FISIKA

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The major purpose of this research was to applying artificial neural network to predicting rainfall in Semarang climatology station and occurs its accuration. One ofartificial neural network method is back propagation artificial neural network. Withheuristic technique its optimizing to train algorithmic faster and improving net works. Weused rainfall data in 2000-2009 from Semarang climatology station. Artificial neuralnetwork modelling planned in MATLAB R2008b programme. The best model or net viewsfrom correlation level between net’s output, observation data and RMSE point whichproduced by the net. The results shown the best network has 5 neurons in input’s layer, 10in hidden layer and 1 neuron in output layer. Its performance has learning data 66,7%,testing data 33,3%, learning rate 0,7 and momentum 0,4 which has correlated around70,72% to observation data with RMSE point 141,55. The best network will use topredicting rainfalls in 2010, its correlation is 88,43% and its RMSE points is 83,76 tillJuly. Its better than what BMKG has which only reach 84,63% correlation points and87,21 RMSE points.Keywords:  Artificial neural network, optimizing, correlation, RMSE
Prediksi Variabilitas Nilai Tukar Rupiah Indonesia Terhadap Dollar Amerika Serikat Berbasis Sistem Inferensi Fuzzy Jaringan Saraf Adaptif sebagai Analisis Tingkat Perekonomian Gernowo, Rahmat; Ernitawati, Yenny
JURNAL SAINS DAN MATEMATIKA Volume 21 Issue 2 Year 2013
Publisher : JURNAL SAINS DAN MATEMATIKA

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The purpose of this paper to predict the variability of exchange rate (Rp/ US $) based Adaptif Neuro-Fuzzy Inference Systems (ANFIS)  analysis of the economic level. The data is secondary data obtained from the movement of the exchange rate (Rp / US $) in Bank Indonesia from January 2003 to December 2013 . The software is used among others of ANFIS system. The results obtained with the Neuro-Fuzzy system shows the range of estimates for all data were obtained at 89.51% for treatment with ANFIS. Dollar exchange rate variability index, showed a pattern that tends to stabilize after years in which Indonesia was hit by the financial crisis of 1998..   Keywords: Prediction, dollar exchange rate index, ANFIS.
Data-Based Fuzzy TOPSIS for Alternative Ranking Utomo, Victor; Gernowo, Rahmat; Sugiharto, Aris
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 3, No 2 (2013): Volume 3 Nomor 2 Tahun 2013
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.098 KB) | DOI: 10.21456/vol3iss2pp104-108

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Technique for Order Preference by Similarity (TOPSIS) solves multi-criteria decision making (MCDM) by ranking the alternatives. When the attributes are not deterministic, a Fuzzy TOPSIS method is applied. The traditional fuzzy TOPSIS depends on decision makers to determine alternative’s value which considered subjective. A new method named data-based fuzzy TOPSIS proposed to diminish the dependency to decision maker. The proposed algorithm use data to determine alternative’s values objectively. Subtractive Clustering (SC) and Fuzzy C-Mean (FCM) selected to transform crisp value data to fuzzy value data. Some modification applied to SC and FCM to obtain fuzzy triangular value needed by fuzzy TOPSIS.  Keyword : Index Terms—Decision support systems,  fuzzy TOPSIS, fuzzy C-mean, subtractive clustering
The Prediction of Bandwidth On Need Computer Network Through Artificial Neural Network Method of Backpropagation Mekongga, Ikhthison; Gernowo, Rahmat; Sugiharto, Aris
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 2 (2012): Volume 2 Nomor 2 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (971.992 KB) | DOI: 10.21456/vol2iss2pp098-107

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The need for bandwidth has been increasing recently. This is because the development of internet infrastructure is also increasing so that we need an economic and efficient provider system. This can be achieved through good planning and a proper system. The prediction of the bandwidth consumption is one of the factors that support the planning for an efficient internet service provider system. Bandwidth consumption is predicted using ANN. ANN is an information processing system which has similar characteristics as the biologic al neural network.  ANN  is  chosen  to  predict  the  consumption  of  the  bandwidth  because  ANN  has  good  approachability  to  non-linearity.  The variable used in ANN is the historical load data. A bandwidth consumption information system was built using neural networks  with a backpropagation algorithm to make the use of bandwidth more efficient in the future both in the rental rate of the bandwidth and in the usage of the bandwidth.Keywords: Forecasting, Bandwidth, Backpropagation
Penerapan Model Certainty Factor Untuk Mendeteksi Gejala Kanker Mulut Rahim Mariana, Novita; Gernowo, Rahmat; Noranita, Beta
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 3 (2012): Volume 2 Nomor 3 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol2iss3pp152-159

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An expert system is a system that seeks to adopt human expertise so that computers can do things that can be done by an expert to solve specific problems. Experts in this case is an expert in the field to address the problem under on detecting cervical cancer. Cervical cancer is a disease that is very afraid of all women because it attacks the reproductive organs caused by the virus Human Papilloma Virus (HPV). The system is made to detect cervical cancer using the certainty factor with a forward chaining inference engine. Certainty factor method used in cervical cancer detection system to give certainty to the disease. As a result of this information system is to provide information regarding the statement of cervical cancer and cancer treatment solution according to the stage.   Kata kunci : Certainty Factor; Forward Chaining; Kanker Mulut Rahim
Rancang Bangun Sistem Peramalan Konsumsi Daya Listrik dengan Artificial Neural Network Backpropagation Sinta, Radini; Gernowo, Rahmat; Suryono, Suryono
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 3, No 1 (2013): Volume 3 Nomor 1 Tahun 2013
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (6289.735 KB) | DOI: 10.21456/vol3iss1pp48-58

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Jaringan saraf tiruan model jaringan layar jamak yang diimplementasikan dengan menggunakan program komputasi untuk menyelesaikan masalah yang kompleks melalui proses perhitungan dengan algoritma Backpropagation. Salah satu masalah yang dapat dipecahkan adalah sistem peramalan berdasarkan data time series, data time series untuk data masukan adalah data konsumsi daya listrik dalam satuan kWh pada LWBP dan WBP, data okupansi tahun 2011. Jaringan yang sudah dilatih menghasilkan akurasi peramalan MSE pada LWBP     7,48738e-12, MSE pada WBP 1,11035e-10, dan MAPE pada LWBP 1,6141e-9%, MAPE pada WBP 2,50e-8%, untuk jaringan yang tidak dilatih dapat meramalkan konsumsi daya listrik dengan uji validitas pada LWBP R = 0,837, dan pada WBP R = 0,835. Pada pelatihan dan pengujian sistem optimal dengan 8 neuron pada lapisan tersembunyi.   Katakunci: Jaringan Saraf Tiruan; algoritma Backpropagation; data time series; sistem peramalan.  
Kombinasi Steganografi Berbasis Bit Matching dan Kriptografi DES untuk Pengamanan Data Prasetiyo, Budi; Gernowo, Rahmat; Noranita, Beta
Scientific Journal of Informatics Vol 1, No 1 (2014): May 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i1.3643

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Pada penelitian ini dilakukan kombinasi steganografi dan kriptografi untuk pengamanan data dengan tidak mengubah kualitas media cover. Metode steganografi yang digunakan dengan melakukan pencocokan bit pesan pada bit MSB citra. Proses pencocokan dilakukan secara divide and conquer. Hasil indeks posisi bit kemudian dienkripsi menggunakan algoritma kriptografi Data Encryption Standard (DES). Masukkan data berupa pesan teks, citra, dan kunci. Output yang dihasilkan berupa chiperteks posisi bit yang dapat digunakan untuk merahasiakan data. Untuk mengetahui isi pesan semula diperlukan kunci dan citra yang sama. Kombinasi yang dihasilkan dapat digunakan untuk pengamanan data. Kelebihan metode tersebut citra tidak mengalami perubahan kualitas dan kapasitas pesan yang disimpan dapat lebih besar dari citra. Hasil pengujian menunjukkan citra hitam putih maupun color dapat digunakan sebagai cover, kecuali citra 100% hitam dan 100% putih. Proses pencocokan pada warna citra yang bervariasi lebih cepat. Kerusakan pesan dengan penambahan noise salt and peper mulai terjadi pada nilai MSE 0,0067 dan gaussian mulai terjadi pada nilai MSE 0,00234. 
Fuzzy-AHP MOORA approach for vendor selection applications Al Khoiry, I’tishom; Gernowo, Rahmat; Surarso, Bayu
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8, No 1 (2022): In progress (January)
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2356

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Vendor selection is a critical activity in order to support the achievement of company success and competitiveness. Significantly, the company has some specific standards in the selection. Therefore, an evaluation is needed to see which vendors match the company's criteria. The purpose of this study is to evaluate and select the proposed vendor in a web-based decision support system (DSS) by using the fuzzy-AHP MOORA approach. The fuzzy-AHP method is used to determine the importance level of the criteria, while the MOORA method is used for alternative ranking. The results showed that vendor 4 has the highest score than other alternatives with a value of 0.2536. Sensitivity analysis showed that the proposed DSS fuzzy-AHP MOORA concept was already solid and suitable for this problem, with a low rate of change.
PERANCANGAN SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN TARUNA BARU MENGGUNAKAN BASIS DATA FUZZY - STUDI KASUS DI AKPELNI SEMARANG Eko Nur Hidayat; Rahmat Gernowo; Aris Sugiharto
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2013): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 4 2013
Publisher : Prosiding SNST Fakultas Teknik

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Proses  seleksi  penerimaan  taruna  baru  di  Akademi  Pelayaran  Niaga  Indonesia (AKPELNI)  terdapat beberapa ketidakpastian, antara  lain nilai ujian seleksi potensi akademik,  nilai  kesamaptaan,  kesehatan,  tinggi  badan  serta  wawancara  setiap periode tidak pasti, tergantung dari jumlah pendaftar dan daya tampung. Logika fuzzy merupakan  salah  satu metode  penyelesaian masalah  yang mulai  berkembang  pada tahun  1965.  Logika  fuzzy  menggunakan  dasar  teori  himpunan  fuzzy  dimana keberadaan  suatu  elemen  dalam  himpunan  ditentukan  oleh  derajat  keanggotaan elemen  tersebut.    Dengan  sifat  keanggotaan  himpunan  fuzzy  tersebut  maka  logika fuzzy menjadi  lebih  fleksibel  (mampu beradaptasi dengan perubahan-perubahan dan ketidakpastian yang menyertai permasalahan) serta memiliki  toleransi  terhadap data yang  tidak  tepat.  Penelitian  ini  bertujuan  membangun  sebuah  sistem  pendukung keputusan  untuk  menentukan  calon  taruna  yang  diterima  dan  tidak  diterima menggunakan  basis  data  fuzzy  menyesuaikan  dengan  jumlah  pendaftar  dan kapasitas/kuota.    Dengan  memberikan  input  berapa  kapasitas/kuota    yang  akan diterima serta standar nilai  maka panitia penerimaan taruna baru dapat memutuskan siapa yang diterima dan yang tidak diterima.  Kata Kunci :Logika Fuzzy, penerimaan taruna baru, system pendukung keputusan
The Implementations of K-medoids Clustering for Higher Education Accreditation by Evaluation of Davies Bouldin Index Clustering Ghufron Ghufron; Bayu Surarso; Rahmat Gernowo
Jurnal Ilmiah Kursor Vol 10 No 3 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i3.232

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The need for data analysis in tertiary education every semester is needed, this is due to the increasingly large and uncontrolled data, on the other hand generally higher education does not yet have a data warehouse and big data analysis to maintain data quality at tertiary institutions is not easy, especially to estimate the results of university accreditation high, because the data continues to grow and is not controlled, the purpose of this study is to apply k-medoids clustering by applying the calculation of the weighting matrix of higher education accreditation with the data of the last 3 years namely length of study, average GPA, student and lecturer ratio and the number of lecturers according to the study program, so that it can predict accurate cluster results, the results of this study indicate that k-medoid clustering produces good cluster data results with an evaluation value of the Bouldin index davies cluster index of 0.407029478 and is said to be a good cluster result.
Co-Authors Adi Wibowo Adiyono, Soni Agus Setyawan Agus Sutejo Ahmad Lubis Ghozali Aldi Setiawan, Aldi Andi Setiabudi, Nur Andryani, Ria Annisa Luthfianti Panular Ardima, Muhammad Basyier Arfriandi, Arief Ari Bawono Putranto Aria Hendrawan, Aria Aries Dwi Indriyanti, Aries Dwi Aris Sugiharto Atik Zilziana Muflihati Noor Bayong Tjasyono H. Kasih Bayu Surarso Beta Noranita Budi Prasetiyo, Budi Budi Warsito Budi Warsito Catur Edi Widodo Cholil, Saifur Rohman Christine Dewi D Febrianty Dafiz Adi Nugroho Dedy Kurniadi Edi Surya Negara Eko Nur Hidayat Eko Sediyono F M Arif Faliha Muthmainah Fauzan Ishlakhuddin Frysca Putti Muviana Ghufron Ghufron Gumay, Naretha Kawadha Pasemah Hengki Hengki Heri Mulyanti Hidayat, Agung Rahmad I. Istadi Ikhthison Mekongga Iryanto Iryanto Ismi Dian Kusumawardhani Isnain Gunadi Istadi I’tishom Al Khoiry Khusnah, Miftakhul Koesuma, Sorja Kuresih, Kuresih Kurnia Adi Cahyanto Kusworo Adi M. Solehuddin Mahrus Ali Michael Andreas Purwoadi Moh Ali Fikri Muchammad A Rofik Mulyani, Esti Munengsih Sari Bunga Munji Hanafi Novita Mariana Nuriyana Muthia Sani Nuriyana Muthia Sani Nursamsiah Nursamsiah Oky Dwi Nurhayati Pinem, Agusta Praba Ristadi Prayitno R. Rizal Isnanto Radini Sinta, Radini Ratih Rundri Utami Rosyalia, Syofi Sakhina, Friska Ayu Shahmirul Hafizullah Imanuddin Siti Yuniar Pangestu Slamet, Vincencius Gunawan Suryono Suryono Syibli, Mohammad Tri Mulyono Triyono, Liliek Victor Gayuh Utomo Wahyu Jatmiko Wahyul Amien Syafei Wicaksana, Hilman Singgih Widagdo, Krisan Aprian Widiyatmoko, Carolus Borromeus Wulandari, Rosita Ayu Yenny Ernitawati Zaenal Arifin