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All Journal IPTEK The Journal for Technology and Science JSI: Jurnal Sistem Informasi (E-Journal) JURNAL E-DUMATH Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Science and Technology Indonesia Indonesian Journal of Artificial Intelligence and Data Mining Prosiding Seminar Nasional Teknoka Education and Human Development Journal JURNAL PENELITIAN PERAWAT PROFESIONAL
Warsono Warsono
Universitas Lampung
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Health Professions Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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KARAKTERISTIK FUNGSI DISTRIBUSI FOUR-PARAMETER GENERALIZED-t Cahyadi, Rahman; ., Warsono; Usman, Mustofa; Kurniasari, Dian
JURNAL E-DUMATH Vol 2, No 1 (2016)
Publisher : JURNAL E-DUMATH

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research is about the characteristic function of four-parameter generalized tdistribution. Four-parameter generalized t distribution has four parameters whichare μ as a location parameter, σ as a scale parameter, p and q as a shapeparameter, and B as a function of beta. The characteristic function are retrievedfrom the expectation of e itx , where i as a imaginary number. Then, the characteristicfunction of four-parameter generalized t distribution was able to be determined byusing definition and trigonometric expansions. Based on those two methods thisstudy got the same results and then will be continued proving the fundamentalproperties of the characteristic function of four-parameter generalized t distribution.Furthermore, it needs graph simulation on a characteristic function of four-parameter generalized t distribution. Graph simulation result on the characteristicfunction of four- parameter generalized t distribution was formed a closed curve(circle) are smooth.Keywords: four-parameter generalized t distribution, characteristic function,graph simulation
SINERGITAS PENGGIATAN EKONOMI KERAJINAN BATIK LAMPUNG, EKSPLORASI BUDAYA DAN EDUKASI KONSERVASI: ANDANAN BATIK TULIS, NEGERI SAKTI, PESAWARAN, LAMPUNG Elly Lestari Rusitati; Erdi Suroso; Warsono Warsono; Junaidi Junaidi; Favorisen Rosyking Lumbanraja; Priyambodo Priyambodo
Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Vol 3 No 2 (2019)
Publisher : Lembaga Penelitian dan Pengabdian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jss.v3i2.146

Abstract

Batik Lampung merupakan salah budaya yang khas dengan motifnya dan menjadi salah satu kegiatan ekonomi yang kuat di Provinsi Lampung, termasuk kerajinan Andanan Batik Tulis, yang mencirikan keunikan budaya Lampung. Saat ini selain sebagai kegiatan kebutuhan ekonomi, kerajinan Andanan Batik Tulis sekaligus menjadi media edukasi budaya dan konservasi melalui pengkayaan motif berbasis budaya Lampung, konservasi dan penyediaan media belajar membatik. Penerapan edukasi budaya dan konservasi dilakukan melalui paket eduwisata yang disediakan bagi wisatawan baik lokal maupun asing. Program eduwisata ini mendapat tanggapan positif. Kata Kunci: Andanan Batik Tulis, eduwisata, budaya, konservasi, Lampung
On the Moments, Cumulants, and Characteristic Function of the Log-Logistic Distribution Dian Ekawati; Warsono Warsono; Dian Kurniasari
IPTEK The Journal for Technology and Science Vol 25, No 3 (2014)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v25i3.574

Abstract

This research examine about the moments, cumulants, and characteristic function of the log-logistic distribution. Therefore, the purposes of this article are (1) finding moments of the log-logistic distribution by using moment generating function and by definition of expected values of the log-logistic random variable and (2) finding the cumulants and characteristic function of the log-logistic distribution. Log-logistic distribution has two parameters: the shape parameter α and β as a parameter scale. Moments of the log-logistic distribution can be determined by using the moment generating function or the definition of expected value. Cumulants determined by the moments that have been found previously. Furthermore, skewness and kurtosis can be determined from the log-logistic distribution. While the characteristic function is the expected value of e^itx, which I as an imaginary number
Perbedaan Solusi Masalah Instalasi Jaringan Multi Tahap Dalam Proses Koneksi Menggunakan Algoritma Modifikasi Prim dan GNU Octave Wamiliana Wamiliana; Warsono Warsono; Mas Dafri Maulana
Prosiding Seminar Nasional Teknoka Vol 2 (2017): Prosiding Seminar Nasional Teknoka ke - 2
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (271.083 KB)

Abstract

Desain jaringan merupakan salah satu bidang yang banyak terapannya dalam optimisasi kombinatorik. Masalah Instalasi Jaringan Multi Tahap atau Multiperiod Degree Constrained Minimum Spanning Tree (MPDCMST) merupakan salah satu masalah desain jaringan dimana akan ditentukan biaya minimum untuk menghubungkan titik-titik yang dipertimbangkan pada tahap-tahap tertentu, dan tidak melanggar syarat atau kendala yang diberikan . Kendala yang diberikan adalah interkoneksi pada tiap titik tidak melebihi b, b= integer nonnegatif. Selain itu, ada skala prioritas titik-titik yang harus terhubung pada tahap tahap tertentu. Pada penelitian ini akan didiskusikan proses instalasi/koneksi tiap titik pada masing-masing tahap yang menggunakan Modifikasi Algoritma Prim untuk menyelesaikannya. Ada dua algoritma (WWM1 dan WWM2) yang akan dibandingkan proses instalasinya. Hasil penelitian menunjukkan bahwa algoritma WWM2 memberikan solusi yang lebih baik dari algoritma WWM1.
Pendugaan Parameter Model Produksi Constant Elasticity of Subtitutions (CES) dengan Metode Kuadrat Terkecil Nonlinear Dian Kurniasari; Noferdis Setiawan; Warsono Warsono; Yeftanus Antonio
Prosiding Seminar Nasional Teknoka Vol 2 (2017): Prosiding Seminar Nasional Teknoka ke - 2
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (261.463 KB)

Abstract

Tujuan dari penelitian ini adalah memperoleh nilai dugaan dari model produksi Constant Elasticity Subtitutions (CES) secara intrinsik nonlinear. Model produksi CES didefinisikan dengan -. Metode kuadrat terkecil nonlinear digunakan untuk menduga model produksi CES. Persamaan yang diperoleh dengan metode kuadrat terkecil nonlinear tidak dapat diselesaikan secara analitik. Untuk menyelesaikan masalah tersebut digunakan metode iteratif Newton Raphson. Model produksi CES yang diperoleh dari hasil studi dengan menggunakan data adalah - . Simulasi yang dilakukan dengan metode ini menunjukan bias untuk masing-masing parameter adalah =-1.021, = -0.0054, = 0.0675 dan = 0.0955. Hasil tersebut menunjukan metode kuadrat terkecil nonlinear cekup baik untuk menduga parameter pada model produksi CES.
Dynamic Modeling and Forecasting Data Energy Used and Carbon Dioxide (CO2) Edwin Russel; Wamiliana; Nairobi Saibi; Warsono; Mustofa Usman; Jamal I. Daoud
Science and Technology Indonesia Vol. 7 No. 2 (2022): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1425.261 KB) | DOI: 10.26554/sti.2022.7.2.228-237

Abstract

The model of Vector Autoregressive (VAR) with cointegration is able to be modified by Vector Error Correction Model (VECM). Because of its simpilicity and less restrictions the VECM is applied in many studies. The correlation among variables of multivariate time series also can be explained by VECM model, which can explain the effect of a variable or set of variables on others using Granger Causality, Impulse Response Function (IRF), and Forecasting. In this study, the relationship of Energy Used and CO2 will be discussed. The data used here were collected over the year 1971 to 2018. Based on the comparison of some criteria: Akaike Information Criterion Corrected (AICC), Hannan-Quin Information Criterion (HQC), Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) for some VAR(p) model with p= 1,2,3,4,5, the best model with smallest values of AICC, HQC, AIC and SBC is at lag 2 (p= 2). Then the best model found is VECM (2) and further analysis such as Granger Causality, IRF, and Forecasting will be based on this model.
Analysis Multivariate Time Series Using State Space Model for Forecasting Inflation in Some Sectors of Economy in Indonesia Edwin Russel; Wamiliana Wamiliana; Warsono; Nairobi; Mustofa Usman; Faiz AM Elfaki
Science and Technology Indonesia Vol. 8 No. 1 (2023): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2023.8.1.144-150

Abstract

Many analytical methods can be utilized for multivariate time series modeling. One of the analytical models for modeling time series data with multiple variables is the State Space Model. The data to be analyzed in this study is inflation data from expenditure groups such as processed foods, beverages, cigarettes, and tobacco; and housing inflation for water, electricity, gas, and fuel from January 2001 to December 2021. The aim is to determine the best State Space Model that fits the data for forecasting. In this study, the State Space method will be utilized further with multivariate time series data and represent State Space in Vector Autoregressive (VAR) to determine the relationship between groups of observed variables.
IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK (ANN) USING BACKPROPAGATION ALGORITHM BY COMPARING FOUR ACTIVATION FUNCTIONS IN PREDICTING GOLD PRICES Dian Kurniasari; Ranti Vidia Mahyunis; Warsono Warsono; Aang Nuryaman
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 1 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i1.587

Abstract

The trend in global currency values is speedy and fluctuating due to the recession caused by the Covid-19 pandemic. That causes investors to flock to buy gold assets. Therefore, it is necessary to predict the price of gold from a business and academic perspective to obtain a reasonable gold price prediction model. This study applies the Backpropagation Algorithm by determining the best ANN model structure based on four activation functions: Sigmoid, Tanh, ReLU, and Linear, as well as learning rate values, namely 0.01 and 0.001. The results are the best ANN model structure with four nodes in the input layer, four nodes in the hidden layer and the output layer using the Linear activation function and a learning rate of 0.01. Based on the structure of the model, the MSE value is 0.00051, the MAPE value is 1.9798%, and the accuracy is 98%.Keywords: Artificial Neural Network, Backpropagation, Gold Price Prediction, Activation Function, Model Structure Trend nilai mata uang global sangat cepat dan fluktuatif akibat terjadinya resesi yang disebabkan oleh pandemi Covid-19. Hal ini menyebabkan, para investor berbondong-bondong untuk membeli aset emas. Oleh sebab itu, perlu dilakukan prediksi harga emas, baik dari perspektif bisnis maupun akademis agar memperoleh model prediksi harga emas yang baik. Penelitian ini menerapkan Algoritma Backpropagation dengan menentukan struktur model ANN terbaik berdasarkan empat fungsi aktivasi yaitu, Sigmoid, Tanh, ReLU, dan Linear serta nilai learning rate, yaitu 0,01 dan 0,001. Hasil yang diperoleh berupa struktur model ANN terbaik dengan empat node pada input layer, empat node pada hidden layer dan output layer dengan menggunakan fungsi aktivasi Linear dan learning rate sebesar 0,01. Berdasarkan struktur model tersebut, diperoleh nilai MSE sebesar 0.00051, nilai MAPE sebesar 1,9798% dan akurasi sebesar 98%.Kata Kunci: Artificial Neural Network, Backpropagation, Prediksi Harga Emas, Fungsi Aktivasi, Struktur Model
Faktor yang Berhubungan dengan Pencegahan Penularan Covid-19 Yuni Nirmala; Dyah Wulan Sumekar RW; Warsono Warsono
Jurnal Penelitian Perawat Profesional Vol 4 No 4 (2022): November 2022, Jurnal Penelitian Perawat Profesional
Publisher : Global Health Science Group

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Abstract

Angka kejadian Covid-19 masih tinggi baik di dunia dan Indonesia. Covid-19 disebabkan oleh virus SARS-CoV-2 dan berdampak pada berbagai sektor. Factor risiko terjadinya Covid-19 dapat berasal dari faktor internal dan faktor eksternal. Studi literatur ini bertujuan untuk mengetahui factor yang berhubungan dengan pencegahan Covid-19 di Indonesia menggunakan artikel dari berbagai jurnal nasional dan internasional. Artikel yang digunakan adalah artikel tahun 2012-2022 dari database Pubmed, NCBI dan Google Scholar sebanyak 70 artikel dan artikel yang memenuhi syarat sebanyak 30 artikel. Artikel terpilih dilakukan analisis dan interpretasi berdasarkan hasil yang didapatkan. Hasil penelitian mendapatkan bahwa faktor risiko yang berhubungan dengan kejadian Covid-19 antara lain adalah pengetahuan, sikap, penerapan protokol kesehatan, keyakinan akan kesehatan, dukungan sosial perilaku dan paparan media. Simpulan penelitian ini adalah faktor pengetahuan, sikap, penerapan protokol kesehatan, keyakinan akan kesehatan, dukungan sosial perilaku dan paparan media berhubungan dengan kejadian Covid-19.
Application of Artificial Neural Network Method using Hyperparameter Tuning for Predicting of Euro Exchange Rupiah Dian Kurniasari; Amelia Fallizia Putri; Warsono Warsono; Notiragayu Notiragayu
Jurnal Sistem Informasi Vol 15, No 1 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v15i1.19867

Abstract

The Covid-19 pandemic has significantly impacted the economic decline in many countries, such as Italy, the United States and the European Union. Indonesia, also affected by Covid-19, was not spared from economic turmoil, especially in the foreign exchange market, where the rupiah exchange rate against the Euro experienced significant fluctuations in early 2020, hampering international trade and investment activities. Therefore, an appropriate method is needed to predict changes in the rupiah exchange rate against the Euro to minimize the obstacles. This study uses the ANN model to predict the Rupiah (Rp) exchange rate against the Euro (€). The best model is obtained through the hyper-tuning process. The optimal parameter values obtained are the input layer with 10 nodes, 2 hidden layers with 19 nodes and 13 nodes, the output layer, dropout of 0.2, 32 batch sizes, 100 epochs, and the Tanh activation function in the distribution scheme of 90% training data and 10 % testing data. Based on the MAPE value of 0.0042% and 0.0041% obtained, the prediction results on the selling and buying rates of the Rupiah against the Euro, it can be concluded that the model has good predictive ability with an accuracy value of 99.996%.Keywords: Currency Exchange Rates, Data Mining, Machine Learning, Artificial Neural Networks 
Co-Authors . Wamiliana Aang Nuryaman Agus Wahyudi Amelia Fallizia Putri Dian Ekawati Dian Kurniasari Dyah Wulan Sumekar Rengganis Wardani Edwin Russel Edwin Russel Elly Lestari Rusitati Erdi Suroso Faiz AM Elfaki Favorisen R. Lumbanraja Jamal I. Daoud Junaidi Junaidi Mas Dafri Maulana Mustofa Usman Mustofa Usman Mustofa Usman Nairobi Noferdis Setiawan Notiragayu Notiragayu Priyambodo Priyambodo Rahman Cahyadi, Rahman Ranti Vidia Mahyunis Sulistian Oskavina Yeftanus Antonio Yuni Nirmala