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Surtono, Arif
Jurusan Fisika, Universitas Lampung, Bandar Lampung, Indonesia, 35141
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Sistem Akuisisi Data Pengukuran Kadar Oksigen Terlarut Pada Air Tambak Udang Menggunakan Sensor Dissolved Oxygen (DO) Inda Robbihi Mardhiya; Arif Surtono; Sri Wahyu Suciyati
Jurnal Teori dan Aplikasi Fisika Vol. 6 No. 1 (2018): 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.v6i1.175

Abstract

Analisis Karakteristik Elektrik Limbah Kulit Singkong Berbentuk Pasta Sebagai Sumber Energi Listrik Alternatif Terbarukan Tri Sutanto; Amir Supriyanto; Arif Surtono
Jurnal Teori dan Aplikasi Fisika Vol. 6 No. 2 (2018): 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.v6i2.176

Abstract

The electrical characteristics of cassava peel and cassava can be determined by using a pair of electrode copper (Cu) and zinc (Zn). The measurement of the electrical characteristics of cassava peel had been done using a 5 watt LED load and when the load is released. Cassava peel and cassava are used without fermentation and with fermentation. Electrolyte cell that used consists of 20 cells, which were arranged in series and parallel, with volume + 200 ml for one cell. The maximum power generated cassava peel 5.8597 mW, and 14.1052 mW on cassava. Zn2 electrode (zinc battery used) produces a larger power, which is 5.8597 mW compared with Zn1 (ordinary zinc) is 1.9902 mW. Cassava peel without fermentation produces a larger voltage of 20.76 volts, compared with cassava peel 19.17 volts of fermentation. In cassava peel, circuit cell power in series a larger of 5.8597 volts, compared with circuit power in parallel is 5.7078 volts
Studi Awal Analisator Perubahan Sifat Elektrik Materi Cair yang Berinteraksi dengan Cahaya untuk Aplikasi Spektrometri angga wahyu pratama; Arif Surtono; Junaidi Junaidi
Jurnal Teori dan Aplikasi Fisika Vol. 7 No. 1 (2019): 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.v7i1.200

Abstract

An initial study research has been carried out on the realization of electrical properties analyzer of liquids that interact with light to be applied to spectrometry. This study aims to develop a spectrometry method based on changes in electrical resistance in liquids when interacting with laser. Methylene blue solution was used as a sample that illuminated by a laser with 650 nm wavelength.The laser beam causes a change in electrical resistance in the methylene blue solution detected by Arduino Nano and converted to a concentration quantity. The conversion equation for changes in electrical resistance to concentration was obtained from the measurement of the change in electrical resistance of methylene blue solutions at concentration of 100 ppm, 200 ppm, 400 ppm, 600 ppm, 800 ppm, 1000 ppm. The equation was obtained based on the exponential regression approach with error value of 15,70 %. The analyzer test was carried out by measuring the concentration of methylene blur solution at a concentration of 500 ppm, 600 ppm, and 700 ppm. The test results show an error value of 9,83 %.
Desain dan Realisasi Alat Ukur Massa (Neraca Digital) Menggunakan Sensor Load Cell Berbasis Arduino Aditia Saputra; Junaidi Junaidi; Amir Supriyanto; Arif Surtono
Jurnal Teori dan Aplikasi Fisika Vol. 10 No. 2 (2022): 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.v10i2.297

Abstract

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
Rancang Bangun Alat Ukur Tingkat Manis Buah Jeruk Menggunakan Sensor Kapasitor Semi Silinder Berbasis Arduino Grace Pricilya Michiko; Arif Surtono; Humairoh Ratu Ayu; Junaidi Junaidi
Jurnal Teori dan Aplikasi Fisika Vol. 12 No. 1 (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.v12i1.340

Abstract

Abstract. It has been realized the design of the orange based sweet level measuring device using an arduino based semi cylinder capacitor sensor. This study was conducted by providing input to the capacitor plates using an oscillator with a variety of frequency values of 10 KHz, 100 KHz, and 1 MHz. The oscillator used is the IC XR-2206 type. The sweet level of orange fruit is measured using a pocket refractometer otago pal-?. Semi cylinder capacitor sensor testing is carried out on 16 oranges. The most optimal measurement results are obtained in a 100 KHz frequency variation because the graph of the measurement results drops linearly. The voltage range at a frequency of 100 KHz is 200 - 2000 mV, with a brix value obtained between 13.8 - 16.7%. The higher the orange voltage, the lower the Brix value contained in oranges. Brix value 13.8 - 15.6% states the sweet level of orange fruit is sour, while the Brix value 16.7% states the sweet level of orange fruit is sweet. The results of testing the tool obtained an average error value of 0,004% and a tool accuracy value of 99,6%.
Aplikasi Sensor TGS2620 dan MQ138 untuk Mendeteksi Kematangan Buah Durian Berbasis Raspberry Pi 3B Dewi Puspitasari; Arif Surtono; Sri Wahyu Suciyati; Gurum Ahmad Pauzi
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.v9i2.359

Abstract

Telah dilakukan penelitian dengan pengaplikasian sensor gas TGS 2620 dan MQ 138 untuk mendeteksi kematangan buah durian berbasis Raspberry Pi 3b. Penelitian ini dilakukan untuk menghasilkan alat deteksi tingkat kematangan buah durian. Durian diletakkan ke dalam ruang sampel yang berisi sensor gas. Metode klasifikasi yang digunakan untuk menentukan kematangan buah menggunakan K-Nearest Neighbor (KNN). Pengujian KNN dalam klasifikasi kematangan durian menggunakan sensor gas memiliki akurasi keseluruhan 91,07%.
Beyond the Canopy: Resolving Topographic and Acoustic Complexities with Machine Learning for Karst Avifauna Monitoring Fitryan, Anggyta; Abdurrahman, Ahmad Faruq; Nuryani; Prihanto, Surya; Al Fath, Yusril; Aprilia, Ayu; Junaidi; Surtono, Arif
Journal of Innovation in Applied Natural Science Vol. 1 No. 1 (2025): Journal of Innovation in Applied Natural Science
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jinas.v1i1.52

Abstract

Background of study: Tropical karst landscapes harbor exceptional avian biodiversity but pose unique monitoring challenges due to complex topography, cave reverberation, and humidity-driven sound distortion. Conventional ecoacoustic methods fail in these environments, with indices showing weak correlations (r=0.20-0.43) for avian diversity due to insect masking and abiotic interference. Over 83% of karst-endemic birds lack standardized monitoring protocols despite escalating extinction risks.Aims and scope of paper: This review aims to: (1) quantify limitations of current ecoacoustic methods in karst ecosystems, (2) develop a machine learning-enhanced framework addressing topographic and reverberation effects, and (3) establish conservation-ready protocols for endangered karst avifauna. The study synthesizes evidence from 29 studies across hardware innovation, signal processing, and policy applications.Methods: We systematically analyzed 29 studies on acoustic monitoring in karst ecosystems, focusing on machine learning innovations, topographic adaptations, and conservation applications.Result: Topography drives 47% of soundscape variation, surpassing vegetation effects. Machine learning (CNNs/MFCCs) boosts detection accuracy by 22-80% in reverberant caves. Hybrid protocols enable 25-m resolution habitat mapping and precise disturbance monitoring, overcoming tropical "latitude paradox" limitations.Conclusion: This review establishes the first karst-adapted ecoacoustic framework, integrating machine learning with topographic variables to transform monitoring from biodiversity proxy to precision tool. Critical next steps include developing species-specific call libraries, wind-reverberation filters, and policy integration of acoustic baselines for IUCN assessments. The proposed protocols address urgent conservation needs for Earth's most threatened avian sanctuaries.
Co-Authors , Agustiansyah A Agustiawan A Amanto Abdan Sakura Abdurrahman, Ahmad Faruq Abidin, Ramadhani Adi Saputra Aditia Saputra Aewaditha, Randha Kentama Agung Gumelar Agus Riyanto Agus Riyanto Agustiansyah Agustiansyah Ahmad Badrus Soleh Ahmad Saudi Samosir Ahmad Syaifudin Ahmad Syaifudin Al Fath, Yusril Amir Supriyanto Amir Supriyanto Amir Supriyanto Amir Supriyanto Amir Supriyanto angga wahyu pratama Aprilia, Ayu Ardian Ardian Ardian Ardian Arta Bayti Bonita Ayu Aprilia Danu Setiawan Denny Irfan Dewi Puspitasari Diana Margarini Diana Rahma Dina Mauliyani Qoriah Dwi Vaolina Sari Dwina Nurizky Syahputri E Edison EKO YULIANTO Elisabhet Yori Vitariasni Eva Sasmita Fitri Anggraini Fitri Yeli Fitri Yelli Fitryan, Anggyta Friska Tiara Desy Grace Pricilya Michiko Grace Pricilya Michiko Gurum A P Gurum A P, Gurum A P Gurum Ahmad Pauzi Gurum Ahmad Pauzi Gurum Ahmad Pauzi Gurum Ahmad Pauzi Gurum Akhmad Pauzi Humairoh Ratu Ayu I Irsan Ilfa Yuni Arta Imam Nasiqin Inda Robbihi Mardhiya Irvana, Raihan J Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi Junaidi, J Karo , Pulung Karo Kukuh Setiawan Kukuh Setiawan Luh Ari Anjarsari M Mujiono Maesadji Tjokronagoro Maesadji Tjokronagoro Mahfudz Al-Huda Marjunus, Roniyus Muhammad Nur Muhammad Wahyudi Mutiara Amalia Syafira N Nurkholis Nabila, Zhara Nevalen Aginda Prasetyo Nida Lidya Susanti Nita Suliyani Novia Puspasari Nuryani Pauzi, Gurum Ahmad Prihanto, Surya Prima Aprilliana Puji Siamatun Putra, Rio Adhitya Putri, Risa Amelia Randha Kentama Aewaditha Rifqah, Raden Ayu Nurfadhillah Rio Adhitya Putra Rizki Afriliyanti Rizki Yara Narvinda Runiyus Marjunus Sakura, Abdan Sammi Rizki Taufik Sanjaya, Purba Sari, Dwi Vaolina Setyo Dwi Utomo SITI KHOLIFAH Siti Kholifah Situmorang, Elfrina Sri Ratna Sulistiyanti Sri Wahyu Suciyati Sri Wahyu Suciyati Sri Wahyu Suciyati Sri Wahyu Suciyati Sri Wahyu Suciyati Sungkono Sungkono Sungkono Sungkono Supriatin Supriatin Supriyanto, Amir Supriyanto, Amir Supriyanto, Amir Sutopo Hadi Syafriadi Syafriadi Thomas Sri Widodo Thomas Sri Widodo Tri Sutanto W Warsito Warsito Warsito Warsito Warsito Warsito Warsito Warsito, W Wasinton Simanjuntak Yanti Yulianti Yeli, Fitri