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All Journal International Journal of Public Health Science (IJPHS) Jurnal Teknoin Jurnal Teknologi Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Jurnal Pengabdian Dharma Bakti Respati Jurnal Computer Science and Information Technology (CoSciTech)
Ikhwan Mustiadi
Universitas Respati Yogyakarta
Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health

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Pemanfaatan Energi Surya sebagai Energi Alternatif Pengganti Listrik untuk Memenuhi Kebutuhan Penerangan Jalan di Dusun Nglinggo Kelurahan Pagerharjo Kecamatan Samigaluh Kabupaten Kulon Progo Utari, Evrita Lusiana; Mustiadi, Ikhwan; Yudianingsih, Yudianingsih
Jurnal Pengabdian Dharma Bakti VOL 1, NO 2 (2018): AGUSTUS 2018
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1103.223 KB) | DOI: 10.35842/jpdb.v1i2.53

Abstract

Potensi wisata sebagai modal pembangunan dari lingkup kota, kabupaten, hingga yang terkecil yaitu desa, mulai dipasarkan demi meningkatkan lapangan kerja, meningkatkan pendapatan, serta mendukung perkembangan usaha kecil di daerah masing – masing. Wilayah yang memiliki potensi wisata yang cukup besar salah satunya adalah Kabupaten Kulonprogo Propinsi Daerah Istimewa Yogyakarta. Salah satu Desa  yang memiliki keistimewaan wisata alam, budaya, dan agro adalah Desa Pagerharjo yang terletak di Kecamatan Samigaluh. Sebagai daerah tujuan  wisata harus memiliki daya tarik wisata antara lain memiliki fasilitas atau objek yang menarik, mudah  dicapai  dengan  kendaraan, menyediakan tempat hunian sementara atau homestay bagi para wisatawan. Salah satu dusun didesa Pagerharjo yaitu Dusun Nglinggo. Dusun Nglinggo Pagerharjo Samigaluh Kulonprogo terletak di daerah perkebunan teh Nglinggo yang berada pada ketinggian 800 m dpl yang membentang cukup luas di daerah Pegunungan Menoreh. Di pegunungan ini dapat menikmati indahnya panorama delapan puncak gunung yaitu Merapi, Merbabu, Slamet, Prau, Ungaran, Sumbing, Telomoyo, dan Sindoro. Apabila kondisi cuaca berkabut dan gelap, pencahayaan sangat kurang sehingga menyulitkan bagi wisatawan untuk menuju maupun meninggalkan daerah perkebunan tersebut. Hal ini dikarenakan sumber energi yang ada didaerah perkebunan tersebut masih terbatas dan masih membutuhkan tambahan fasilitas utamanya adalah energi listrik.Dari keterbatasan energi listrik tersebut memunculkan gagasan untuk memberikan penyuluhan pemanfaatan energi matahari sebagai energi alternatif sebagai sumber listrik. Pemanfaat energi matahari tersebut nantinya, hasilnya dapat digunakan untuk penerangan jalan. Sehingga mempermudah akses masyarakat menuju kawasan kebun teh yang masih minim penerangan. Oleh karena itu energi alternatif yang nantinya dapat digunakan untuk mempermudah akses jalan menuju daerah yang masih minim energi listrik dan pemanfaatan energi terbarukan ini juga dapat membantu meningkatkan perekonomian masyarakat utamanya Dusun Nglinggo Pagerharjo Samigaluh Kulonprogo.Keyword: Solar Panel, Dusun Nglinggo, Samigaluh, Desa Wisata, Kebun Teh
IMPLEMENTASI TEKNOLOGI SOLAR PANEL UNTUK PARIWISATA DAN PENGAIRAN DI TANGGULANGSI KULON PROGO Utari, Evrita Lusiana; Mustiadi, Ikhwan; Irawati, Novi
Jurnal Pengabdian Dharma Bakti VOL 4, NO 2 (2021) : AGUSTUS 2021
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/jpdb.v14i2.149

Abstract

The Indonesian government is empowering renewable energy as an alternative energy besides energy produced by natural gas. This is the idea to implement using renewable energy that will be utilized in the tourism area of Tanggulangsi Gate. This area is located in the Sidoharjo Samigaluh Kulon Progo region. Where this area is developing tourism is supported by natural scenery and cool air adds to the atmosphere in interesting tourist places to visit. In addition to the good scenery at Tanggulangsi, it also offers another tourist spot, namely the Vegetable Picking tour which is managed by KWT Tanggulangsi Mekar. Implement renewable energy that will be applied in the tourist area of Tanggulangsi Gate in the form of lighting, and for picking vegetables is implemented to irrigate agricultural land in order to help the community in caring for their plants. Methods of carrying out activities include surveys or field observations, socialization of activities, counseling, training, design and installation of tools.Keywords: Energy, Samigaluh, Solar Panel, Kulon Progo
Sistem Perancangan Robot Pemindah Barang Berbasis Line Follower Yudianingsih, Yudianingsih; Utari, Evrita Lusiana; Mustiadi, Ikhwan
Jurnal Teknologi Informasi RESPATI Vol 17, No 1 (2022)
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/jtir.v17i1.439

Abstract

INTISARIRobot sangat berguna untuk meringankan pekerjaan manusia. Beberapa hal juga akan lebih efektif jika dikerjakan oleh robot. Penelitian ini bertujuan meringankan beban manusia dalam hal pemindahan barang. Mengingat keterbatasan manusia dan resiko yang dapat terjadi selama proses pemindahan barang. Robot pemindah barang ini menggunakan robot line follower dengan menambahkan lengan robot yang berfungsi untuk mengambil dan meletakkan kembali benda yang dipindahkan. Menggunakan modul sensor BFD-1000 yang digunakan untuk mendeteksi jalur dan mikrokontroler Arduino UNO yang digunakan sebagai pengolah perintah yang telah diberikan melalui software Arduino IDE menuju lengan robot dan driver L298N untuk menggerakkan motor.Robot pemindah barang ini dapat mengikuti jalur yang diberikan dengan baik dalam satu tujuan tanpa adanya persimpangan. Robot ini dapat memindahkan barang dari titik pengambilan barang menuju titik tujuan peletakan barang dengan berat barang kurang dari 110gr.Kata kunci— line follower, robot pemindah barang ABSTRACTIn this paper, an analysis of the value of voltage and current will be carried out on the Intensity Robots are very useful to ease human work. Some things will also be more effective if done by robots. This study aims to ease the human burden in terms of moving item. Considering human limitations and the risks that can occur during the process of moving item.This item moving robot uses a line follower robot by adding a robotic arm that functions to pick up and put back the objects being moved. Using the BFD-1000 sensor module which is used to detect the path and the Arduino UNO microcontroller which is used as a processing command that has been given through the Arduino IDE software to the robot arm and the L298N driver to drive the motor.This item moving robot can follow the given path well in one destination without any intersections. This robot can move item from the point of picking up the item to the point of placing the item with a weight of item less than 110gr.Keyword—  line follower, item moving robot
Klasifikasi sinyal EMG berbasis jaringan syaraf tiruan dan discrete wavelet transform Ikhwan Mustiadi
Teknoin Vol. 23 No. 3 (2017)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknoin.vol23.iss3.art4

Abstract

Electromyograph signal (EMG) is a non-stationary biomedical signal, making it difficult todetermine the pattern. The method normally used for signal analysis is Fast Fourier Transform (FFT), but it has some drawbacks because it requires stable signals. To answer this deficiency wavelet transformation is used, especially discrete wavelet transforms that can analyze the signal in both the realm of time and frequency.The method to be used in this research is wavelet transformation for signal analysis withdecomposition up to level 7 using wavelet symlet 8. This feature extraction result is used as input of artificial neural network (ANN) type of propagation backward with architecture of 8 input layer, 5 hidden layer and 3 layers of output.ANN Turnback is able to recognize 3 types of EMG signals namely Normal, Myopathy andNeuropathy. Based on the feature extraction of EMG signal decomposition energy characteristics. Network architecture with 8 input layers. 5 hidden layers and 3 output layers Proven best in the introduction of EMG signals. The highest success rate is the introduction of EMop Myopathy signal pattern reaching 94%, so the network architecture is proposed to regenerate the EMG signal.
ANALISIS EKSTRAKSI CIRI SINYAL EMG MENGGUNAKAN WAVELET DISCRETE TRANSFORM Ikhwan Mustiadi; Thomas Sri Widodo; Indah Soesanti
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 3 (2012): Intelligent System dan Application
Publisher : Jurusan Teknik Informatika

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

Abstract

Sinyal Electromyograph (EMG) adalah salah satu sinyal biomedis yang sangat penting untuk mengetahui aktivitas kontraksi otot, hal ini sangat penting dilakukan karena banyak kelainan aktivitas otot yang terjadi. Pada penelitian ini dilakukan analisis sinyal menggunakan Discrete Wavelet Transfoerm (DWT) jenis Symlet level 8 dengan filter-filter yang dapat menganalisa sinyal EMG sehingga komponen-komponen sinyalnya dapat diketahui sebagai sesuatu yang unik untuk setiap sinyal yang di analisis, dengan 3 sinyal yang berbeda yaitu sinyal EMG Normal, Myopathy dan Neuropathy, dapat ditemukan sesuatu yang unik untuk setiap sinyal tersebut dengan mengukur daya sinyal dan menormalisasinya, pada sinyal normal, daya sinyal maksimum adalah pada koefisien aproksimasinya, pada sinyal EMG Myopathi adala pada koefisien detail 3 dan pada sinyal EMG Neuropathy adalah pada keofisien detail 2.
Conv-Tire: Tire Condition Assessment using Convolutional Neural Networks Latifah Listyalina; Irawadi Buyung; Agus Qomaruddin Munir; Ikhwan Mustiadi; Dhimas Arief Dharmawan
Telematika Vol 19, No 3 (2022): Edisi Oktober 2022
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v19i3.7697

Abstract

Purpose: In this study, the authors designed an algorithm based on convolutional neural networks that can automatically assess tire quality.Design/methodology/approach: The proposed algorithm is built through several stages as follows. In the first stage, the tire images, which are the input of the designed algorithm, are acquired. Further, the acquired images are divided into two sets, namely training and testing sets. The training set contains tire images used in the training phase of several convolutional neural networks (CNN) architectures such as ResNet-50, MobileNetV2, Inception V3, and DenseNet-121. The training phase is carried out in a number of epochs, and at each epoch, the cross entropy loss function will be calculated which expresses the performance of the CNN architecture in classifying tire images. For this reason, the training stage requires a label or reference that shows the feasibility of the tires displayed in each image.Findings/result: In the testing phase, trained CNN architectures are used to classify tire images from the test set. Classification performance in the test set is also expressed in terms of cross-entropy loss function value. In addition, the accuracy value has also been calculated which shows the percentage of the number of tire images that are successfully classified correctly to the total number of tire images in the test set, namely the DenseNet-121 model has the best accuracy of 92.62%.Originality/value/state of the art: Given the high accuracy achieved by our algorithm, this work can be used as a reference by other researchers, specifically to benchmark their tire quality classification methods developed in the future.
Efektifitas Pengisian Baterai Menggunakan Solar Panel 50 WP (Watt Peak) dengan Metode PWM (Pulse Width Modulation) Ikhwan Mustiadi; Evrita Lusiana Utari
Jurnal Teknologi Vol 16 No 1 (2023): Jurnal Teknologi
Publisher : Jurnal Teknologi, Fakultas Teknologi Industri, Institut Sains & Teknologi AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/jurtek.v16i1.4186

Abstract

Electrical energy has become a basic need for humans today, almost all aspects of human life require electrical energy. The electrical energy needed so far has been produced from fossil energy which is not environmentally friendly and has dwindling reserves, alternative energy is needed which is environmentally friendly and sustainable. Energy that can be utilized includes water energy, wind energy, solar energy and so on. The sun is one of the abundant energy, by crossing the equator, Indonesia has enormous energy reserves. This potential is expected to become Indonesia's future energy. Currently solar cell technology is very advanced with increasingly good efficiency, in addition to energy conversion by solar cells with photovoltaic technology, a method is needed to store the results of the conversion into storage (batteries) optimally. One of the battery charging technologies is the Pulse Width Modulation (PWM) method, with this method battery charging is optimal on a 50 WP solar panel. In this study, a 50 WP solar panel was used, a 28 Ah 12 Volt battery, a 10 Watt Dc 12 Volt load and a 10 Ampere PWM Solar Charger Controller (SCC). The system was running for 3 months from September to December, the load was turned on for 12 hours every day with a load absorption current of 0.9 Amperes. Every day the current used is 10.8 Amperes. For 3 months the weather was not always stable, so charging was less than optimal, but until now the system is running well with an average after usage voltage of 12.3 Volts.
AdaBoost Classification for Predicting Residential Habitation Status in Mount Merapi Post-Eruption Rehabilitation NURHADI WIJAYA; MOHAMMAD DIQI; IKHWAN MUSTIADI
Computer Science and Information Technology Vol 4 No 2 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i2.5141

Abstract

This research paper explores the use of the AdaBoost algorithm for predicting residential habitation status in the aftermath of the Mount Merapi eruption. Using a dataset from the Rehabilitation and Reconstruction Task Force, with 2516 instances and 11 attributes, the AdaBoost model was trained and evaluated. The model demonstrated a robust performance with an accuracy of 92%, though it struggled with correctly identifying all 'No Habited' instances. These findings underscore the potential of machine learning algorithms in disaster management, particularly in optimizing resource allocation and expediting recovery times. Future research should aim to improve the model's performance on imbalanced datasets and explore the incorporation of temporal dimensions for more dynamic and accurate predictions.
Innovation in vector control of dengue hemorrhagic fever using portable devices mechanical electric methods Alvira Pascawati, Nur; Baskoro Tunggul Satoto, Tri; Mustiadi, Ikhwan; Lusiana Utari, Evrita
International Journal of Public Health Science (IJPHS) Vol 13, No 3: September 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v13i3.24218

Abstract

This innovation was created to control the dengue hemorrhagic fever (DHF) vector population in the larval cycle because several previous control methods were considered less sensitive, effective, and efficient. To test the effectiveness of portable electrical-mechanical methods in controlling Aedes aegypti larvae. The research design was posttest only which was tested on 80-liter and 90-liter volume containers in light and dark colors. Statistical analysis used the independent samples t-test, and Pearson correlation (α=5%). Laboratory test results show that the average time needed to suck all the larvae in a light-colored container with a volume of 80 liters is 38 seconds (28-57 seconds) and a volume of 90 liters is 99.6 seconds (80-119 seconds). In a dark-colored container, the 80-liter volume is 50.8 seconds (3-89 seconds) and the 90-liter volume is 106.8 seconds (88-122 seconds). This tool sucks larvae faster in containers with a volume of 80 liters compared to a volume of 90 liters. The greater the volume of water and the higher the water surface, the longer it takes to suck the larvae. This tool is effective and efficient in speeding up the process of monitoring, collecting, and controlling larvae in large containers.
Rubber Leaf Image Classification Using Artificial Intelligence Methods as an Effort to Improve Plantation Production Results Buyung, Irawadi; Utari, Evrita Lusiana; Mustiadi, Ikhwan; Winardi, Sugeng; Ariyanto, Ipan; Listyalina, Latifah
Telematika Vol 21 No 3 (2024): Edisi Oktober 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i2.13587

Abstract

Purpose: Rubber is one of the plantation commodities that contributes positively to the trade surplus in the agricultural sector. Seeing the positive trend in global rubber consumption and production, demand is expected to continue increasing in the future. To enhance rubber productivity, rubber processing technology can be used to make it more efficient, thus increasing the amount of latex extracted from the sap and reducing waste materialDesign/methodology/approach: One technology that can be developed to increase the productivity efficiency of rubber plants is by using Artificial Intelligence. This technology is expected to be implemented in the rubber plantation sector, specifically in the automatic recognition of rubber leaves.Findings/result: The measurement and performance analysis of the rubber leaf image classification algorithm based on Artificial Intelligence has also been evaluated, showing near-perfect accuracy on training data (99.86%) and very good performance on validation data (97.43%), with a very low validation loss (0.0873), indicating that the model has learned well by the last epochOriginality/value/state of the art: The population in this study consists of image data from various tree leaves, including 10 types of rubber leaves and non-rubber leaves 
Co-Authors Agus Qomaruddin Munir Alvira Pascawati, Nur Ariyanto, Ipan Dharmawan, Dhimas Arief Evrita Lusiana Utari Evrita Lusiana Utari, Evrita Lusiana Indah Soesanti Irawadi Buyung, Irawadi Latifah Listyalina Listyalina, Latifah Lusiana Utari, Evrita Mohammad Diqi Novi Irawati Sugeng Winardi Thomas Sri Widodo Tri Baskoro Tunggul Satoto Wijaya, Nurhadi Yudianingsih, Yudianingsih