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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Advances in Applied Sciences TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Jurnal EECCIS Jurnal Informatika dan Teknik Elektro Terapan JURNAL PENGABDIAN KEPADA MASYARAKAT Science and Technology Indonesia Matrix : Jurnal Manajemen Teknologi dan Informatika Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Teknoinfo JCRS (Journal of Community Research and Service) Jurnal Teori dan Aplikasi Fisika Journal of Engineering and Scientific Research (JESR) Journal of Applied Data Sciences TEKTAN Journal of Innovation and Technology Journal of Multidisciplinary Applied Natural Science Prosiding Seminar Nasional Hasil Penelitian Sains, Teknik dan Aplikasi Industri Fakultas Teknik Universitas Lampung Electrician : Jurnal Rekayasa dan Teknologi Elektro SNTE Journal of Digital Market and Digital Currency Nemui Nyimah Analit: Analytical And Environmental Chemistry
Sri Ratna Sulistiyanti
[Scopus ID: 36606902600] Department Of Electrical Engineering Faculty Of Engineering University Of Lampung Jl. Sumantri Brojonegoro 1, Bandar Lampung
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Penerapan Jaringan Saraf Tiruan / JST (Backpropagation) untuk Prakiraan Cuaca di Bandar Udara Radin Inten II Lampung Adi Saputra; Sri Ratna Sulistiyanti; Roniyus Marjunus; Yanti Yulianti; Junaidi Junaidi; Arif Surtono
Jurnal Teori dan Aplikasi Fisika Vol. 11 No. 1 (2023): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v11i1.331

Abstract

Prediksi cuaca diperlukan dalam perencanaan kehidupan sehari-hari, salah satunya untuk membuat keputusan. Keberhasilan dari suatu prediksi cuaca akan berdampak pada pengambilan keputusan di berbagai bidang, antara lain pada bidang pertanian dan penerbangan. Pada bidang penerbangan, prediksi cuaca penting untuk menentukan waktu, lokasi, arah gerak, ketinggian serta merencanakan pergerakan pesawat untuk memperhitungkan gangguan operasi yang dapat disebabkan jika cuaca sedang buruk dan juga untuk mempertimbangkan dalam menentukan rute penerbangan atau menentukan dalam membawa tambahan bahan bakar jika dalam suatu kasus pesawat harus kembali dikarenakan kondisi cuaca yang tidak memungkinkan. Oleh karena itu perlunya sebuah metode prediksi cuaca yang baik sehingga dapat mengurangi kerugian dan kerusakan. Parameter maksimum dalam pengembangan perancangan informasi prakiraan cuaca berbasis Jaringan Saraf Tiruan / JST (Backpropagation) dengan menambah inputan data curah hujan, suhu, kelembaban, penyinaran matahari, tekanan udara, arah angin dan kecepatan angin. Penelitian ini dilakukan di wilayah Bandar Udara Radin Inten II Lampung. Data yang digunakan dalam penelitian ini adalah berupa data harian kondisi meteorologi di wilayah Bandar Udara Radin Inten II Lampung dari Stasiun Meteorologi Radin Inten II selama 3 tahun terakhir yaitu dari tahun 2017 hingga tahun 2019. Data tersebut dibutuhkan sebagai data masukan untuk algoritma yang akan digunakan dalam penelitian. Berdasarkan pada hasil penelitian, diperoleh akurasi pelatihan terbaik sebesar 100% pada arsitektur jaringan syaraf tiruan dengan parameter fungsi pelatihan levenberg-marquardt (trainlm) dan scaled conjugate gradient (trainscg), fungsi aktivasi sigmoid biner dan sigmoid bipolar, dan jumlah neuron 20, 40, 60, 80, dan 100. Sedangkan akurasi pengujian terbaik sebesar 74.359% pada arsitektur jaringan syaraf tiruan dengan parameter fungsi pelatihan gradient descent wit momentum and adaptive learning rate (traingdx) dan fungsi aktivasi sigmoid biner (logsig) dan jumlah neuron 20 dan 80.Kata kunci: Penerapan Jaringan Saraf Tiruan, Prakiraan Cuaca, Bandar Udara Radin Inten II Lampung.Weather prediction is needed in planning daily life, one of which is to make decisions. The success of a weather prediction will have an impact on decision making in various fields, including agriculture and aviation. In the field of aviation, weather prediction is important to determine the time, location, direction of motion, altitude and plan the movement of aircraft to take into account operational disturbances that can be caused if the weather is bad and also to consider in determining flight routes or determining in carrying additional fuel if in an emergency. In the case of the aircraft having to return due to unfavorable weather conditions. Therefore the need for a good weather prediction method so as to reduce losses and damage. In this case the author tries to focus on the maximum parameters in the development of weather forecasting information design based on Artificial Neural Networks / Backpropagation by adding input data of rainfall, temperature, humidity, sunlight, air pressure, wind direction and wind speed. This research was conducted in the area of Radin Inten II Airport, Lampung. The material used in this study is in the form of daily data on meteorological conditions in the Radin Inten II Lampung Airport area from the Radin Inten II Meteorological Station for the last 3 years, from 2017 to 2019. This data is needed as input data for the algorithm that will be used in study. Based on the research results, the best training accuracy is 100% on the artificial neural network architecture with levenberg-marquardt training function parameters (trainlm) and scaled conjugate gradient (trainscg), binary sigmoid and bipolar sigmoid activation functions, and the number of neurons 20, 40, 60, 80, and 100. Meanwhile, the best test accuracy is 74,359% on the artificial neural network architecture with the training function parameters gradient descent wit momentum and adaptive learning rate (trainingdx) and binary sigmoid activation function (logsig) and the number of neurons 20 and 80. Keywords: Application of Artificial Neural Networks, Weather Forecast, Radin Inten II Airport Lampung
Design of an Earthquake Intensity Estimation System for Early Warning Trismahargyono Trismahargyono; Sri Ratna Sulistiyanti; Roniyus Marjunus
Jurnal Teori dan Aplikasi Fisika Vol. 9 No. 2 (2021): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v9i2.362

Abstract

Penggunaan Interpolasi Bilinier Pada Akuisisi Data Massa Muhammad Ifan Saputra; Sri Ratna Sulistiyanti; F.X. Arinto Setyawan
Jurnal Teori dan Aplikasi Fisika Vol. 12 No. 02 (2024): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v12i02.376

Abstract

The bilinear interpolation method is generally used to improve images that have noise. However, in this research the bilinear interpolation method will be used to determine the weight value of a digital scale designed with four load cell sensors. Data collection was carried out by placing loads at nine different points. The loads used are 2kg and 5kg. The results of this research are that the value of the point in the center or on the axis of the four load cells, namely points B, D, E, F, and H, has the same voltage as the actual value, namely for a 2kg weight of 4.31 mV. and for a weight of 5 kg it is 5.87 mV. Meanwhile, the other points, namely points A, C, G and I, have values ​​that deviate from the actual value by 0.36 mV or an error of 36%.   Keywords: Bilinear Interpolation, Digital Scales, Load Cell Sensors.
Rancang Bangun Mesin CNC Laser 4 Axis menggunakan Motor Stepper Tipe Nema 23 Terintergrasi Mach3 USB untuk Aplikasi Mesin Cutting Otomatis Hesti Wahyu Handani; Sri Ratna Sulistiyanti; Yanti Yulianti; Posman Manurung; Junaidi
Jurnal Teori dan Aplikasi Fisika Vol. 13 No. 02 (2025): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v13i02.413

Abstract

Perancangan dan pembuatan mesin CNC Laser 4 Axis menggunakan motor stepper tipe nema 23 terintegrasi Mach3 USB untuk aplikasi mesin cutting otomatis telah dilakukan. Alat ini merupakan suatu alat laboratorium bidang manufaktur yang digunakan untuk memotong material berbahan akrilik secara otomatis dengan dimensi pemotongan mencapai 1000 mm x 2000 mm. Alat ini memiliki mata potong berupa laser dioda ukuran 40 watt yang mampu memotong lembaran akrilik dengan ketebalan 3 mm. Alat ini dikontrol menggunakan kontroler Mach3 board dan dikomunikasikan dengan software Mach3 menggunakan perintah berupa G-code. Alat ini mampu memotong lembaran akrilik ketebalan 3 mm dengan kecepatan maksimum 55 mm/menit. Untuk hasil pemotongan optimal, proses pemotongan akrilik dilakukan pada jarak laser terhadap akrilik yaitu sejauh 15 mm. Alat ini memiliki kesalahan relatif yaitu 0,27% dan deviasi sebesar 0,25 mm. Berdasarkan spesifikasi tersebut, mesin CNC Laser ini dapat diaplikasikan untuk mesin cutting otomatis untuk material berbahan dasar akrilik.
Artificial Neural Network Backpropagation Method for Predicting Soil Nutrient Content: Artificial Neural Network Backpropagation Method for Predicting Soil Nutrient Content Witaningsih Witaningsih; Sri Ratna Sulistiyanti; Mareli Telaumbanua; F X Arinto Setyawan; Helmy Fitriawan; Rita Anggraini
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 6 (2025): December 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i6.2424-2438

Abstract

Monitoring soil nutrient levels such as nitrogen (N), phosphorus (P), and potassium (K) is essential to support fertilizer efficiency and sustainable agricultural land management. However, commonly used laboratory-based analytical methods are time-consuming and costly. Therefore, alternative approaches that are more practical and efficient are needed. This study aimed to develop an Artificial Neural Network (ANN)-based system for predicting soil nutrient levels using soil physical parameters, namely pH, temperature, moisture content, and electrical resistance, as input variables. Data were collected from red-yellow podzolic soil subjected to different fertilization treatments. After normalization, the data were trained using an ANN model with four input nodes, two hidden layers (each consisting of five nodes), and one output node, employing the backpropagation algorithm and evaluating 27 combinations of activation functions. The training results showed coefficients of determination (R²) of 0.9642 for nitrogen, 1.0000 for phosphorus, and 0.9996 for potassium, with RMSE values of 0.0107, 10.5386, and 0.016457 and RRMSE values of 8.5048%, 0.79786%, and 1.581111%, respectively. During validation, R² values of 0.7218 (nitrogen), 0.6479 (phosphorus), and 0.6137 (potassium) were obtained. Nitrogen prediction exhibited good accuracy (RMSE 0.0222; RRMSE 15.54%), potassium prediction showed moderate accuracy (RMSE 0.2963; RRMSE 28.46%), while phosphorus prediction resulted in relatively high errors (RMSE 1066.77; RRMSE 80.98%), indicating the need for further model development.
Design and Implementation of an Artificial Neural Network Model for Soil Nitrogen Prediction Rita Anggraini; Sri Ratna Sulistiyanti; Helmy Fitriawan; FX Arinto Setyawan; Mareli Telaumbanua; Witaningsih Witaningsih
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 2 (2026): April 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i2.732-742

Abstract

The availability of nitrogen in soil is a crucial factor determining crop productivity. However, the measurement of total nitrogen (N-total) content requires considerable time and cost. Therefore, a fast, accurate, and easy prediction method is needed to support the agricultural development. This study aims to develop an Artificial Neural Network (ANN) model based on the backpropagation algorithm to identify soil N-total content using soil pH, moisture content, and soil resistance as input parameters. The model was trained using the trainbr training function with variations of logsig and tansig activation functions and hidden layer structures of 5–5, 8–8, and 12–12 to obtain the best configuration. The training results indicate that the tansig–tansig combination with 8–8 hidden layer structure achieved the highest performance, with a R2 training of 0.953 and a R2 testing of 0.911. The model was implemented in the form of a Graphical User Interface (GUI) application to facilitate field-level prediction. Validation using 40 testing data samples showed a classification accuracy of 70% and an R² value of 0.932 for nitrogen prediction. The model correctly classified 28 data samples out of the total 40 tested data. These results indicate that the proposed model is capable of predicting soil nitrogen content accurately and reliably.
ANALISIS PEMANFAATAN JEMBATAN GARAM KCl DAN NaCl TERHADAP LAJU KOROSI ELEKTRODA Zn PADA SEL VOLTA MENGGUNAKAN AIR LAUT SEBAGAI ELEKTROLIT Gurum Ahmad Pauzi; Arie Anjarwati; Ahmad Saudi Samosir; Sri Ratna Sulistiyanti; Wasinton Simanjuntak
Analit : Analytical and Environmental Chemistry Vol. 4, No. 02 October (2019) Analit : Analytical and Environmental Chemistry
Publisher : Jurusan Kimia FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/aec.v4i2.2019.p50-58

Abstract

Penelitian ini dilakukan untuk menganalisis pengaruh jembatan garam terhadap laju korosi elektroda Zn pada Sel volta. Pasang elektroda Cu (Ag)-Zn digunakan untuk menghasilkan tegangan dan arus dalam sel dengan elektrolit air laut. Variasi jembatan garam menggunakan agar yang dilarutkan dengan 0,1 mol NaCl, 0,1 mol KCl, 1 mol NaCl, dan 1 mol KCl. Sel volta terdiri dari 20 sel yang tersusun secara seri, masing-masing sel diisi ± 300 ml air laut. Sel volta terhubung ke beban LED 3 watt 12 volt selama satu hari, dan 30 hari. Hasil penelitian menunjukkan bahwa jembatan garam NaCl 1 mol menghasilkan karakteristik listrik yang lebih tinggi dan laju korosi yang lebih tinggi pada elektroda Zn.http://dx.doi.org/10.23960/aec.v4.i2.2019.p50-58
Co-Authors A S Samosir Achmad Yahya Teguh Panuju Adi Saputra Admi Syarif Afri Yudamson Afri Yudamson Ageng Sadnowo Ageng Sadnowo Repelianto Agus Trisanto Agus Wantoro Ahmad Pauzi, Gurum Ahmad Saudi Samosir Ahmad Saudi Samosir Anjarwati, Arie Arie Anjarwati Arie Setya Putra Arief, Khollaqul Dedyk Erryyanto dhika, eduar Dyah Indriana Kusumastuti Eko Efendi Eko Rismawan Endro Prasetyo Wahono F X Arinto Setyawan F.X. Arinto F.X. Arinto Setyawan Ferika Shaumi, Rahma Fitria Yunita Fitriwan, Helmy Frisky Volino Andreas Gurum Ahmad Pauzi Gurum Ahmad Pauzi Gusri Akhyar Ibrahim Haris Murwadi Helmy Fitriawan Helmy Fitriawan Helmy Fitriawan Hendro Utomo Herlinawati -, Herlinawati Herlinawati Herlinawati Herlinawati Herlinawati Herri Gusmedi Herti Utami Herti Utami Hesti Wahyu Handani Junaidi Junaidi Junaidi Junaidi Junaidi Khairudin Khairudin Khairun Nisa Khollaqul Arief Komalasari, Agrianti Komarudin, M. Kris Sivam Kurnia Muludi Kurniawan, Dendi Luh Putu Ratna Sundari Lukita, Jimmy M Jerry Juliandr Suja M Said Hasibuan M Yusuf Tamtomi M. Dyan Susila Madi Hartono Mahfut Mardiana Mardiana Mardiyah, Luthfiyyatun Mareli Telaumbanua Marjunus, Roniyus Meizano Ardhi Muhammad Minhajjul Abidin Jaya Muhamad Komarudin Muhamad Komarudin Muhamad Komarudin Muhammad David Muhammad Ifan Saputra Muthia, Tiya Nadia Muthiati Nisa, Mia Abi Noer Sudjarwanto Nurul Hudayani Okta Ainita Pami Ruli Setiawan Pauzi, Gurum Ahmad Posman Manurung Quart Ferrina Rahmat, Rafli Dwi Rakhmat, Riko Ranny Dwidayanti Rita Anggraini Riza Muhida Rudi Darmawan Setyawan, F X Arinto Setyawan, FX Arinto Sony Ferbangkara Sri Purwiyanti Sri Purwiyanti Sri Purwiyanti Sri Wahyu Suciyati Sumadi Sumadi SUMADI SUMADI Surtono, Arif Suryadiwansa Harun Sutyarso Sutyarso Syafriadi Syafriadi Syaiful Alam Syaiful Alam Syaiful Alam Titin Yulianti Tiya Muthia Tiya Muthia Trismahargyono Trismahargyono ubaidah ubaidah Ubaidah, Ubaidah Umi Murdika Wahyu Eko Sulistiono Warsito Warsito Warsono Warsono Wasinton Simanjuntak Wasinton Simanjuntak Wasinton Simanjuntak Wijaya, Agung Kusuma Winanti, Diki Danar Tri Winarto Winarto Witaningsih Witaningsih Y E Putra Yanti Yulianti Yanti Yulianti Yogi Aldino Yudi Eka Putra Yudi Eka Putra Yuli Darni Yuli Darni Yuli Darni