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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 Jurnal Transformatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Science and Technology Indonesia Indonesian Journal of Artificial Intelligence and Data Mining Prosiding Seminar Nasional Teknoka JCRS (Journal of Community Research and Service) JURNAL PENELITIAN PERAWAT PROFESIONAL Jurnal Dedikasi untuk Negeri Sciencestatistics: Journal of Statistics, Probability, and Its Application
Warsono Warsono
Universitas Lampung
Religion 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 Law, Crime, Criminology & Criminal Justice 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
INTRODUCING INTERNET OF THINGS (IOT) FOR A COMMUNITY VILLAGE BASED ON INDUSTRIAL REVOLUTION 4.0 Sri Ratna Sulistiyanti; F.X. Arinto Setyawan; M. Komarudin; Warsono Warsono
Journal of Community Research and Service Vol 2, No 2: July 2018
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jcrs.v2i2.13148

Abstract

AbstractA house is a gathering place for a family, where each family member has a different passion and busyness. If at any time a family member is traveling and wants to monitor and control conditions from a distance, an electronic device is used. One solution to determine the condition of home security at all times, an internet connection is needed by using the concept of the Internet of Things (IoT). IoT is a concept of using an internet network to transfer data or share information with certain applications. The IoT concept is one of the IR 4.0 based systems. In Indonesia, the system has not been widely implemented, especially for village areas. The purpose of this activity is to introduce the concept of IoT in a region as a system of monitoring and controlling homes. The method used is socialization and training of IoT-based smart home models. The system that is introduced is setting lights, monitoring gas (kitchen security), and monitoring using a camera. The results obtained were an increase in knowledge from 45.4% to 79%, and increased skills from 33% to 63%.Keywords: IoT, Village, Industrial Revolution 4.0.
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.
APLIKASI STATISTIKA DESKRIPTIF PADA DATA HASIL PENGABDIAN KEPADA MASYARAKAT: STUDI KASUS DATA HASIL PELATIHAN DISAIN MEDIA PEMBELAJARAN DAN PENGOLAHAN NILAI DENGAN MS WORD BAGI GURU SLTP DI KOTA BANDAR LAMPUNG Dian Kurniasari; Fitri ani; Warsono Warsono
Jurnal Dedikasi untuk Negeri Vol 1, No 1 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat UML

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.686 KB) | DOI: 10.36269/jdn.v1i1.876

Abstract

Abstrak Statistika deskriptif sebagai alat bantu dalam analisis data dan penelitian telah banyak digunakan secara intensif. Analisis statistika deskriptif dalam analisis pelatihan desain media pembelejaran dan pengolahan nilai dengan MS Word merupakan bentuk pengabdian kepada masyarakat oleh institusi Universitas Lampung pada umumnya dan Jurusan Matematika pada khususnya yang bertujuan untuk meningkatkan pengetahuan dan keterampilan guru dalam menggunakan komputer sebagai alat penunjang aktivitas/pekerjaan mereka di sekolah, khususnya dalam mengolah nilai siswa dan menjadikan transparansi sebagai media pembelajaran dalam menghadapi era globalisasi. Berdasarkan pretest dan posttest kegiatan pelatihan ini memberikan hasil yang 'Sangat Baik'. Artinya terjadi peningkatan hasil yang memuaskan dilihat dari hasil ujian akhir (Posttest) peserta pelatihan yang mengalami peningkatan secara signifikan sebesar 95% dari kondisi awal (pretest).   Kata kunci: Statistika Deskriptif, Analisis Data Pelatihan, Desain Media Pembelajaran, Pengolahan Nilai Abstract Descriptive statistics as a tool in data analysis and research has been used intensively. Descriptive statistical analysis in the analysis of learning media design training and value processing with MS Word is a form of community service by the University of Lampung institutions in general and the Department of Mathematics in particular, which aims to improve the knowledge and skills of teachers in using computers as a tool to support their activities/work in schools, especially in processing student values and making transparency as a medium of learning in the face of globalization. This training activity gave 'Very Good' results based on the pretest and posttest. Those means an increase in satisfactory results seen from the trainees' final exam (Posttest), which has increased significantly by 95% from the initial condition (pretest). Keywords: Descriptive Statistics, Data Trainning Anaysis,  Learning Media Design, Value Processing 
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
Co-Authors . Wamiliana Aang Nuryaman Amanto Amanto 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 Ferzy Tryanda Nosa Fitri ani Indah Suciati Jamal I. Daoud Juanda Juanda Junaidi Junaidi Khoirin Nisa M. Komarudin Mas Dafri Maulana Miftahul Irfan Mustofa Usman Mustofa Usman Mustofa Usman Mustofa Usman Nairobi Noferdis Setiawan Notiragayu Notiragayu Priyambodo Priyambodo Rahman Cahyadi, Rahman Ranti Vidia Mahyunis Setyawan, FX Arinto Sri Ratna Sulistiyanti Sulistian Oskavina Wardhani Utami Dewi Wardhani Utami Dewi Yeftanus Antonio Yuni Nirmala