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All Journal Bulletin of Electrical Engineering and Informatics Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Eksos LPPM Techno LPPM Seminar Nasional Informatika (SEMNASIF) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Mineral, Energi dan Lingkungan Compiler Jurnal Ilmiah Lingkungan Kebumian Jurnal Mineral, Energi dan Lingkungan Teknika IEJST (Industrial Engineering Journal of the University of Sarjanawiyata Tamansiswa) Science in Information Technology Letters Industrial Research Workshop and National Seminar Jurnal Pengabdian Literasi Digital Indonesia Jurnal Pendidikan Geosfer Bulletin of Social Informatics Theory and Application Indonesian Journal of Environment and Disaster Globe: Publikasi Ilmu Teknik, Teknologi Kebumian, Ilmu Perkapalan
Awang Hendrianto Pratomo
(SCOPUS ID 35174983600, Universitas Pembangunan Nasional Veteran Yogyakarta), Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Optimizing CNN hyperparameters with genetic algorithms for face mask usage classification Awang Hendrianto Pratomo; Nur Heri Cahyana; Septi Nur Indrawati
Science in Information Technology Letters Vol 4, No 1 (2023): May 2023
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v4i1.1182

Abstract

Convolutional Neural Networks (CNNs) have gained significant traction in the field of image categorization, particularly in the domains of health and safety. This study aims to categorize the utilization of face masks, which is a vital determinant of respiratory health. Convolutional neural networks (CNNs) possess a high level of complexity, making it crucial to execute hyperparameter adjustment in order to optimize the performance of the model. The conventional approach of trial-and-error hyperparameter configuration often yields suboptimal outcomes and is time-consuming. Genetic Algorithms (GA), an optimization technique grounded in the principles of natural selection, were employed to identify the optimal hyperparameters for Convolutional Neural Networks (CNNs). The objective was to enhance the performance of the model, namely in the classification of photographs into two categories: those with face masks and those without face masks. The convolutional neural network (CNN) model, which was enhanced by the utilization of hyperparameters adjusted by a genetic algorithm (GA), demonstrated a commendable accuracy rate of 94.82% following rigorous testing and validation procedures. The observed outcome exhibited a 2.04% improvement compared to models that employed a trial and error approach for hyperparameter tuning. Our research exhibits exceptional quality in the domain of investigations utilizing Convolutional Neural Networks (CNNs). Our research integrates the resilience of Genetic Algorithms (GA), in contrast to previous studies that employed Convolutional Neural Networks (CNN) or conventional machine learning models without adjusting hyperparameters. This unique approach enhances the accuracy and methodology of hyperparameter tuning in Convolutional Neural Networks (CNNs). 
Pengelolaan Risiko Banjir Lahar Hujan Gunungapi Semeru Sektor Tenggara, Lumajang, Jawa Timur Eko Teguh Paripurno; Awang Hendrianto Pratomo; Nandra Eko Nugroho; Wahyu Sugeng Triadi; Wiratama Putra
Jurnal Ilmiah Lingkungan Kebumian Vol 5, No 2 (2023): March
Publisher : Jurusan Teknik Lingkungan, FTM, Universitas Pembangunan Nasional “Veteran” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jilk.v5i2.7762

Abstract

Sabtu, 4 Desember 2021, Gunungapi Semeru mengalami erupsi memuntahkan material awan panas guguran dan banjir lahar hujan ke sekitar Sungai Besuk Kobokan di Kecamatan Pronojiwo dan Candipuro. Banyaknya korban yang jatuh pada erupsi Gunungapi Semeru 2021 diakibatkan karena adanya pusat aktivitas masyarakat di sekitar Sungai Besuk Kobokan serta kurangnya peringatan dan pengetahuan masyarakat akan pengurangan risiko bencana. Penelitian ini dilakukan untuk mengupayakan pengelolaan risiko bencana di sub urusan sistem peringatan dini banjir lahar hujan Gunungapi Semeru. Fokus penelitian ini ada pada layanan pemantauan bahaya pada beberapa parameter yang mempengaruhi terjadinya banjir lahar hujan berbasis infrastruktur Internet of Things dan cloud computing yang akurat dan real-time.
Peranan Kegiatan Kuliah Kerja Nyata (KKN) UPNVYK Dalam Media Literasi Digital Pada Masyarakat Pedesaan Awang Hendrianto Pratomo
Jurnal Pengabdian Literasi Digital Indonesia Vol. 2 No. 2 (2023): December
Publisher : Puslitbang Akademi Relawan TIK Indonesia (ARTIKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/abdimas.v2i2.44

Abstract

Increasing digital literacy is crucial in the age of digital transformation, especially in rural communities. Data from the Ministry of Communication and Informatics (KOMINFO) shows that Indonesia's Digital Literacy Index has seen improvement, but challenges persist, particularly in marginalized rural areas. To address this, the 77th batch of Kuliah Kerja Nyata (KKN) at UPN "Veteran" Yogyakarta has taken a strategic step towards empowering digital literacy in rural communities. This initiative focuses on four pillars of digital literacy: digital skills development, fostering a positive culture related to technology, promoting digital ethics, and ensuring digital safety. The KKN project involves college students who not only provide access to technology but also create an environment that encourages community participation in the digital era. In collaboration with UPN "Veteran" Yogyakarta, KOMINFO, and the Regent of Bantul, the KKN successfully implemented a digital literacy program in Karang Tengah Village, Bantul Regency, with the participation of 1,000 individuals. The program included activities such as socialization, door-to-door digital literacy, workshops, and a closing ceremony. The program effectively improved the community's digital skills, fostered a positive culture surrounding technology, instilled digital ethics, and promoted digital safety on social media platforms.
Pengembangan Sistem Peringatan Dini Bencana Banjir Lahar Hujan Merapi di Sungai Blongkeng Kabupaten Magelang Agung Yulianto Nugroho; Awang Hendrianto Pratomo; Eko Teguh Paripurno; Johan Danu Prasetya; Arif Rianto Budi Nugroho; Ficky Adi Kurniawan
Globe: Publikasi Ilmu Teknik, Teknologi Kebumian, Ilmu Perkapalan Vol. 2 No. 1 (2024): Publikasi Ilmu Teknik, Teknologi Kebumian, Ilmu Perkapalan
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/globe.v2i1.98

Abstract

Mount Merapi is one of the most active volcanoes in Indonesia and is located in the Sleman Regency area of the Special Region of Yogyakarta Province and the Magelang, Klaten and Boyolali Regencies in Central Java Province. There are tools to support the early warning system located at stations or posts around the Blongkeng River. This tool is still active and is needed to notify you if a rain lava flood disaster will occur with a water level sensor. Therefore, a warning system model is needed that can be utilized by the community around Blongkeng. This research was conducted using qualitative methods with data obtained through FGD/Interviews, Observation and documentation studies. The subjects of this research were 15 residents living around the Blongkeng River. The research results show that the existing device developed can provide information to the people around Blongkeng if the water level is dangerous and has the potential for lava flooding. From the results of interviews, observations and documentation studies, it shows that the community needs tools and systems to receive early warnings when a rain lava flood disaster occurs. Furthermore, as a means of information for villages located on the top/slopes of Mount Merapi to be able to provide information to villages located below it when lava floods will occur. Existing devices can provide information to people living around the Blongkeng River if the water level is dangerous and has the potential for rain lava flooding, although there are still several obstacles because there are tools at the Salamsari Station/Post that need to be calibrated.
Dynamic path planning using a modified genetic algorithm Pratomo, Awang Hendrianto; Wahyunggoro, Oyas; Triharminto, Hendri Himawan
International Journal of Advances in Intelligent Informatics Vol 10, No 3 (2024): August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v10i3.699

Abstract

Genetic algorithm (GA) is well-known algorithm to find a feasible path planning which can be defined as global optimum problem. The drawback of GA is the high computation due to random process on each operator.  In this research, the new initial population integrating with new crossover operator strategy was proposed. The parameter is the length of distance travelled of the robot. Before employing the crossover operator, generating a c-obstacle have been done. The c-obstacle is used  as a filter to reduce unnecessary nodes to decrease time computation. After that, the initial population has been determined. The initial population is divided into two parents which parent’s chromosome contains an initial and goal position. The second parents are fulfilled with nodes from each obstacle. The genes of chromosome will add with c-obstacle nodes. Crossover operator is applied after filtering and c-obstacle of possible hopping is determined. Filtering method is used to remove unnecessary nodes that are part of c-obstacle. Fitness function considers the distance from  the last to next position. Optimum value is the shortest distance of path planning which avoids the obstacle in front.  The aim of the proposed method is to reduce the random population and random operating in GA. By using a similar data set of previous researches, the modified GA can reduce the total of generation and yield an adaptive generation number. This means that the modified GA converges faster than the other GA methods.
Comparison of K-Nearest Neighbor and Naïve Bayes algorithms for hoax classification in Indonesian health news Pratomo, Awang Hendrianto; Rachmad, Faiz; Kodong, Frans Richard
Bulletin of Social Informatics Theory and Application Vol. 8 No. 2 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i2.796

Abstract

The categorization of health-related hoaxes is paramount in determining if they report facts. This paper analyzes the accuracy of the K-Nearest Neighbor (KNN) and the Naïve Bayes Classifier as two algorithms for health news hoaxes classification. Text mining was employed by feature extraction employing the TF-IDF method from the news headlines to classify the clusters. A prototype model was used to develop the system. Models assessment included confusion matrices and k-fold cross-validation. K=3 KNN model attained an average accuracy of 82.91%, precision of 85.3% and recall of 79.38% with no predictors included. The best performance was recorded for using the Naive Bayes model at fixation of K=3 KNN model at an average accuracy of 86.42%, precision level of 88.10% and recall high of 84.05%. These findings suggest that the KNN surfaces in the last model level rather than in the absence of the Naive Bayes model concerning classifying the hoax position of health news visible through the confusion evaluative matrix. Although related studies have been conducted in the past, this study is dissimilar in terms of its preprocessing methods, size of the data, and outcomes. The dataset consists of 1219 hoaxes labelled and 1227 facts labelled news headlines
Efektivitas Diseminasi Informasi Kebencanaan Melalui Media Massa Purwoto, Purwoto; Susilastuti, Susilastuti; Pratomo, Awang Hendrianto
Jurnal Pendidikan Geosfer Vol 10, No 1 (2025): Jurnal Pendidikan Geosfer
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jpg.v10i1.44981

Abstract

Diseminasi informasi kebencanaan melalui media massa memiliki peran penting dalam meningkatkan kesiapsiagaan masyarakat terhadap bencana. Indonesia sebagai negara yang rawan bencana memerlukan sistem penyebaran informasi yang cepat, akurat, dan mudah diakses oleh seluruh lapisan masyarakat. Penelitian ini bertujuan untuk menganalisis efektivitas media massa dalam menyebarkan informasi kebencanaan serta faktor-faktor yang mempengaruhi keberhasilannya. Metode yang digunakan dalam penelitian ini adalah studi literatur dengan pendekatan kualitatif, yang menganalisis berbagai sumber seperti jurnal ilmiah dan berita dari media online. Hasil penelitian menunjukkan bahwa media massa berkontribusi dalam menyebarkan peringatan dini, memberikan edukasi, dan membangun kesadaran masyarakat terhadap risiko bencana. Namun, tantangan seperti aksesibilitas informasi di daerah terpencil dan validitas data masih menjadi kendala. Oleh karena itu, diperlukan sinergi antara pemerintah, media, dan masyarakat dalam meningkatkan efektivitas komunikasi kebencanaan.
Implementation DeLone & McLean IS Success Model for Research and Community Service Management Information System Evaluation Pratomo, Awang Hendrianto; Agusdin, Riza Prapascatama; Tahalea, Sylvert Prian; Cahyana, Nur Heri
Journal TECHNO Vol. 7 No. 2 (2021): November
Publisher : Universitas Pembangunan Nasional Veteran Yogayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/journal techno.v7i2.6298

Abstract

SRIKANDI is an information system managed by LPPM that manages research and lecturer service within the UPN "Veteran" Yogyakarta. SRKANDI in its implementation has never been evaluated, therefore in this reserach SRIKANDI was evaluated. The evaluation was carried out using the DeLone & McLean IS Success Model with 150 data obtained from distributing questionnaires to lecturers who had used SRIKANDI. The approach used in this research is quantitative by using regression analysis to test the twelve hypotheses that exist with the successful implementation of SRIKANDI as an information system.
ANALISIS KERUSAKAN LINGKUNGAN AKIBAT PERTAMBANGAN PASIR DI SUNGAI PROGO Paripurno, Eko Teguh; Awang Hendrianto Pratomo; Purbudi Wahyuni; Nandra Eko Nugroho; Wahyu Sugeng Triadi; Gigih Aditya Pratama; Sukiyani; Wana Kristanto; Gandar Mahojwala
Indonesian Journal of Environment and Disaster Vol. 4 No. 2 (2025): Indonesian Journal of Environment and Disaster
Publisher : Disaster Research Center, Universitas Sebelas Maret, Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijed.v4i2.1920

Abstract

Kegiatan penambangan dapat berdampak signifikan terhadap lingkungan fisik, terutama di area yang dekat dengan infrastruktur penting seperti sungai dan bangunan tempat tinggal. Penelitian ini secara sengaja memilih kegiatan penambangan suatu perusahaan di Sungai Progo untuk dievaluasi dalam konteks kerusakan lingkungan. Studi ini bertujuan untuk menilai sejauh mana kerusakan lingkungan di dalam dan sekitar area konsesi penambangan perusahaan, dengan fokus khusus pada degradasi sungai, erosi, dan ketidakstabilan struktural. Tujuannya adalah untuk mengklasifikasikan kerusakan sesuai dengan kriteria lingkungan yang telah ditetapkan dan menentukan tingkat keparahan dampaknya. Penelitian ini menggunakan foto udara, citra satelit dari Google Earth, dan pengukuran di lokasi untuk menganalisis perubahan morfologi sungai, pola erosi, dan stabilitas tanah. Penilaian dilakukan dengan menggunakan kriteria dan tolok ukur yang diberikan oleh Keputusan Gubernur Daerah Istimewa Yogyakarta No. 63 tahun 2003. Temuan menunjukkan adanya kerusakan lingkungan yang signifikan akibat kegiatan penambangan PT A. Perubahan aliran sungai teridentifikasi, dengan pergeseran ke pola berkelok-kelok dan pembentukan cekungan dalam di dasar sungai. Berdasarkan analisis, kerusakan lingkungan yang disebabkan oleh kegiatan penambangan PT A tergolong dalam kategori kerusakan berat. Degradasi sungai, erosi tanah, dan ketidakstabilan infrastruktur di sekitarnya memerlukan perhatian mendesak dan upaya mitigasi untuk mencegah kerusakan lingkungan lebih lanjut.
Implementasi Algoritma Region of Interest (ROI) untuk Meningkatkan Performa Algoritma Deteksi dan Klasifikasi Kendaraan Pratomo, Awang Hendrianto; Kaswidjanti, Wilis; Mu'arifah, Siti
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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

Abstract

Semakin tinggi kualitas suatu citra maka semakin detail informasi yang akan di peroleh. Tetapi, tidak semua wilayah citra memungkinkan untuk dilakukan analisis dengan kecepatan proses yang tinggi. Pemilihan algoritma yang tepat berpengaruh terhadap kecepatan waktu pemrosesan. Apabila tidak ada pembatasan untuk area yang akan di proses mengakibatkan waktu pemrosesan secara realtime melebihi waktu pemrosesan maksimal yang seharusnya. Tingginya waktu pemrosesan yang terjadi mengakibatkan aliran data menjadi kurang cepat. Sarana/processor yang digunakan juga mampu mempengaruhi kecepatan pemrosesan. Region Of Interest (ROI) adalah cara yang tepat untuk mengurangi tingginya waktu pemrosesan tersebut. ROI mampu menandai area tertentu sehingga dapat digunakan untuk mengoptimalisasikan kinerja sistem untuk mendeteksi, menghitung dan mengklasifikasi kendaraan secara realtime. Tanpa adanya ROI, pemrosesan dilakukan pada seluruh piksel citra tanpa terkecuali. Terdapat beberapa tahapan yang dilakukan di dalam penelitian yaitu menganalisis masalah yang ada, penentuan wilayah ROI, aplikasi ROI sebelum proses pengolahan citra dan menganalisis hasil yang di dapatkan.  Hasil yang diperoleh adalah dengan menggunakan ROI waktu pemrosesan citra menggunakan metode segmentasi MOG2 dan tracking dapat lebih cepat dibandingkan dengan waktu pemrosesan ketika tidak menggunakan ROI dengan selisih 0,026 s atau setara dengan 26 ms/frame. AbstractIncreasing resolution of an image is more detailed information will be obtained especially in the image used to detect vehicles. But, every singles areas are not allow to analize with higher speed process. If there are no restrictions for the area to be processed, the processing time in real time exceeds the maximum processing time that should be. The high processing time that occurs make less rapid data flow. The high processing time can affect to processing speed. Region Of Interest (ROI) is the right way to reduce the high processing time. ROI is able to mark certain areas so that it can be used to optimize system performance to detect, calculate and classify vehicles in realtime. Without ROI, processing is carried out on all pixels without exception. There are several steps taken in the research, namely analyzing existing problems, determining the ROI area, application of ROI before the image processing and analyzing the results obtained. The results obtained are by using ROI image processing time can be faster than the processing time when not using ROI. 
Co-Authors Abdur Rahman, Hafidz Fajar Agung Yulianto Nugroho Agung Yulianto Nugroho Agus Ristono Agusdin, Riza Prapascatama Alamin, Duta Alek Setiyo Nugroho Anak Agung Istri Sri Wiadnyani Andiko Putro Suryotomo Anton Satria Prabuwono Anton Satria Prabuwono Arif Rianto Budi Nugroho Arif Rianto Budi Nugroho Augyeris Lioga Seandrio B Ihsan Balza Ahmad Bambang Yuwono Danang Arif Rahmanda Dessyanto Boedi Prasetyo Dimas Candra Nugraha Putra Eko Teguh Paripurno Eko Teguh Paripurno Ficky Adi Kurniawan Ficky Adi Kurniawan Frans Richard Kodong Gandar Mahojwala Gigih Aditya Pratama Granitia Septirina Junaedi H H Triharminto Hafidz Fajar Abdur Rahman Hafidz Fajar Abdur Rahman, Hafidz Fajar Abdur Heru Cahya Rustamaji Heru Cahya Rustamaji Heru Cahya Rustamaji Hidayatulah Himawan Indra Aprillinfanteri Army Johan Danu Prasetya Kahiruddin Omar Khairuddin Omar Kusmendar, Kusmendar Leonel Hernandez Mangaras Yanu F Mochammad Assofa Indera Jati Mohd Shanudin Zakaria Mohd Shanudin Zakaria Mu'arifah, Siti Muhadjir Fachrurradjie Muhammad Arif Wijaya Muhammad Rifai Samekta Adi Nandra Eko Nugroho Nandra Eko Nugroho Nidya Indah Sari Nur Heri Cahyana Nur Heri Cahyana Nur Heri Cahyana Nur Heri Cahyana Nuryono Satya Widodo Nuryono Setya Widodo Nuryono Setyo Widodo Oliver Samuel Simanjuntak Oyas Wahyunggoro Prasetya, Johan Danu Puji Pratiknyo Purbudi Wahyuni Purwoto Purwoto Putra, Dimas Candra Nugraha Rachmad, Faiz Rafly Pradana Putra Rifki Indra Perwira Sabihaini Sabihaini Saifullah, Shoffan Septi Nur Indrawati Setiyo Hartato Setiyo Hartato M Siti Norul Huda Seikh Abdullah Siti Norul Huda Syeikh Abdullah Sudaryatie Sudaryatie SUKIYANI Susilastuti Dwi Nugraha Jati Tahalea, Sylvert Prian Tejo Pramono Triharminto, Hendri Himawan Wahyu Sugeng Triadi Wahyu Sugeng Triadi Wana Kristanto Wilis Kaswidjanti Wilis Kaswidjanti Wilis Kaswidjanti Wiratama Putra Y I Sania Yenni Sri Utami Yuli Fauziah