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All Journal Publikasi Pendidikan JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Simantec Scan : Jurnal Teknologi Informasi dan Komunikasi Proceeding International Conference on Information Technology and Business Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sistem Informasi dan Bisnis Cerdas Format : Jurnal Imiah Teknik Informatika Sistemasi: Jurnal Sistem Informasi InComTech: Jurnal Telekomunikasi dan Komputer J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Journal of Information Systems and Informatics bit-Tech Journal of Robotics and Control (JRC) JATI (Jurnal Mahasiswa Teknik Informatika) Jifosi Indonesian Journal of Data and Science Nusantara Science and Technology Proceedings Jurnal Pengabdian Masyarakat Indonesia Jurnal Manajemen Informatika Jayakarta International Journal Of Computer, Network Security and Information System (IJCONSIST) Algoritme Jurnal Mahasiswa Teknik Informatika Literasi Nusantara Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Kohesi: Jurnal Sains dan Teknologi Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Router : Jurnal Teknik Informatika dan Terapan Modem : Jurnal Informatika dan Sains Teknologi Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Router : Jurnal Teknik Informatika dan Terapan
Eva Yulia Puspaningrum
Universitas Pembangunan Nasional “Veteran” Jawa Timur
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Other

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IMPLEMENTASI MODEL HYBRID CNN-SVM PADA KLASIFIKASI KONDISI KESEGARAN DAGING AYAM Agung Mujiono, Alfinas; Kartini, Kartini; Yulia Puspaningrum, Eva
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 1 (2024): JATI Vol. 8 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i1.8855

Abstract

Perkembangan media internet memiliki manfaat yang dapat dirasakan pada kegiatan jual beli yang dibuktikan dengan banyaknya e-commerce yang tersedia saat ini. Jual beli bahan makanan seperti daging ayam juga turut dilakukan pada berbagai platform e-commerce. Tingginya penjualan daging ayam membuat stok yang disediakan oleh penjual semakin banyak sehingga stok tersebut tidak sepenuhnya laku di tangan konsumen. Permasalahan akan muncul ketika penjual terpaksa menjual lagi daging ayam dengan kondisi yang tidak sepenuhnya segar sehingga pembeli harus mempunyai kesadaran akan kondisi kesegaran daging ayam. Dalam penelitian ini, dilakukan proses klasifikasi kondisi kesegaran daging ayam dengan menerapkan penggabungan dua algoritma pembelajaran mesin, yaitu algoritma CNN sebagai pengekstraksi fitur dan algoritma SVM sebagai pengklasifikasi. Tujuannya adalah untuk membuat sebuah model hybrid yang dapat mengklasifikasikan dua label berdasarkan pra-pemrosesan gambar, ekstraksi fitur, dan klasifikasi dari data citra daging ayam. Nilai akurasi tertinggi mampu dihasilkan oleh model yang menggunakan learning rate 0.00001 dengan nilai akurasi 95%, presisi 95%, recall 94.8%, dan f1-score 94.9%. Hasil yang paling seimbang didapatkan pada model yang menggunakan learning rate 0.000001 dengan nilai akurasi sebesar 90%, presisi 90.1%, recall 90.1%, dan f1-score 90.1%.
ANALISIS HUBUNGAN ANTARA PARAMETER METEOROLOGI DAN KONSUMSI ENERGI LISTRIK MENGGUNAKAN ALGORITMA HDD Wafiqotul Azizah, Nabila; Yulia Puspaningrum, Eva; Mas Diyasa, I Gede Susrama
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 3 (2024): JATI Vol. 8 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i3.9749

Abstract

Listrik menjadi satu diantara elemen yang bersifat krusial dalam kehidupan, mengingat sebagian besar aktivitas manusia bergantung kepada listrik. Sehingga tidak heran, apabila listrik mengalami peningkatan yang pesat khususnya pada era globalisasi seperti saat ini. Peningkatan ini juga dipengaruhi oleh faktor meteorologi. Beberapa penelitian telah dilakukan untuk mengetahui kecenderungan penggunaan listrik yang dipengaruhi oleh parameter meteorologi. Penelitian ini bertujuan untuk mengetahui pemakaian listrik pada kehidupan sehari-hari yang dipengaruhi oleh faktor meteorologi. Pemilihan faktor ini disebabkan faktor meteorologi menjadi faktor yang mempunyai keterikatan yang sangat erat dengan kehidupan manusia. Sejalan dengan hal tersebut, penelitian ini menggunakan dataset yang diperoleh dari BMKG dan PLN. Pada kesempatan kali ini, peneliti menggunakan CRISP-DM dan algoritma HDD. Metode CRISP-DM berguna untuk menggambarkan siklus data mining sehingga prosesnya bisa lebih teratur, sedangkan metode HDD berguna untuk mengetahui korelasi parameter meteorologi terhadap konsumsi listrik pada musim kemarau. Sejalan dengan itu, penelitian ini menghasilkan proyeksi konsumsi listrik selama periode 2023-2030 dengan menggunakan algoritma HDD, serta menghasilkan prediksi konsumsi listrik pada bulan Desember 2023. Prediksi tersebut menghasilkan nilai MAPE sebesar 1,3%, nilai tersebut menyatakan bahwa akurasi dari hasil relative tinggi
KLASIFIKASI PENYAKIT GINJAL MENGGUNAKAN ALGORITMA HIBRIDA CNN-ELM Hasby Bik, Ahmad; Tri Anggraeny , Fetty; Yulia Puspaningrum, Eva
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 3 (2024): JATI Vol. 8 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i3.9807

Abstract

Penyakit ginjal adalah masalah serius yang memerlukan deteksi dini. Studi ini menjelajahi model hybrid CNN-ELM untuk mengklasifikasikan gambar CT penyakit ginjal, menyoroti pentingnya pemilihan fungsi aktivasi. Dengan fokus pada gambar CT, pendekatan ini menjanjikan diagnosis yang akurat dengan akurasi tinggi, mendukung praktik klinis sehari-hari. Melalui percobaan jumlah filter dalam CNN dan neuron tersembunyi dalam ELM, performa model dapat ditingkatkan. ReLU mencapai akurasi tertinggi (0.9963), sedangkan Tanh (0.8419). Hasil ini memberikan panduan penting untuk mengoptimalkan konfigurasi model dalam mendiagnosis penyakit ginjal secara efisien. Dengan akurasi yang memuaskan, pendekatan ini berpotensi menjadi alat bantu berharga dalam praktik medis, membantu praktisi dalam membuat keputusan yang lebih baik
Optimasi Pengenalan Posisi Plat Nomor Kendaraan Menggunakan Kombinasi Metode MSER Dan Harris Corner Bagus Sutikno Putra; Eva Yulia Puspaningrum; Hendra Maulana
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 2 No. 2 (2024): Maret : Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v2i2.165

Abstract

The research proposes an innovative approach to identifying and positioning vehicle number plates using a combination of Maximally Stable Extremal Regions (MSER) and Harris Corner methods. The MSER method is used to detect stable regions on the vehicle number plate image. MSER has the ability to recognize areas that have significant contrast intensity, which often represents the characteristic of the number plate. After identifying the potential regions, the Harris Corner method was applied to determine the characteristic angles. The cross points on the number plate. The combination of these two methods allows for more accurate and reliable identification of the position of the number plate. In this study the author performs optimization by changing the preprocessing part and the part of the MSER method. In the preprosessing the author changes the morphological part of a filter, in the section of the method MSER adds input arguments such as ThresholdDelta, RegionAreaRange, and MaxAreaVariation. The results of this study are 99.27% accuracy, 82.73% precision and 83.14% recall. Previous studies were 98.85%, 67.61% and 79.66% recalls. Based on the results of these values, the study has successfully optimized previous studies.
Perbandingan Algoritma Deep Q-Network dan Local Outlier Factor Untuk Deteksi Anomali Konsumsi Air Minum Pelanggan PUDAM Kabupaten Banyuwangi Andhika Ahnaf Daniswara; Basuki Rahmat; Eva Yulia Puspaningrum
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 4 (2024): Agustus : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i4.243

Abstract

Adequate provision of drinking water in quantity, quality, and continuity is needed to realize a healthy and productive society. A well-managed Drinking Water Supply System (SPAM) is essential to meet this need. Based on Government Regulation Number 122 of 2015, the implementation of SPAM involves the development and management of drinking water which is the responsibility of the local government and PUDAM as the implementer. The main challenges faced by PUDAM include the high level of water loss or Non-Revenue Water (NRW), which reaches 40% in Indonesia. One of the efforts to reduce the NRW level at PUDAM Banyuwangi Regency in the Kalipuro District area is to detect abnormal consumption in customer drinking water consumption. This study uses the Deep Q Network and Local Outlier Factor algorithms to detect anomalies in drinking water consumption, with the aim of comparing the performance of the two algorithms in identifying abnormal consumption patterns at PUDAM Banyuwangi Regency. The results of the study indicate that the Local Outlier Factor algorithm is more suitable for anomaly detection as evidenced by the absence of detection errors and an F1-Score value of 36%.
Perbandingan Kinerja Arsitektur Resnet-50 Dan Googlenet Pada Klasifikasi Penyakit Alzheimer Dan Parkinson Berbasis Data MRI Shawn Hafizh Adefrid Pietersz; Basuki Rahmat; Eva Yulia Puspaningrum
Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 2 (2024): Juni: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v1i2.110

Abstract

Alzheimer's and Parkinson's diseases are neurodegenerative conditions that affect the brain, with Alzheimer's causing cognitive and behavioral decline, while Parkinson's leads to motor and non-motor impairments. Both diseases have significant impacts on the health and quality of life of patients, with prevalence increasing in recent years. Although the exact causes of these diseases are still unknown, MRI (Magnetic Resonance Imaging) is widely used to detect brain activity and serves as one of the diagnostic methods. With technological advancements, intelligent systems in image processing for image classification have been extensively used and have become a popular field due to their ability to replicate human visual capabilities. Image classification is performed using various supervised learning machine learning algorithms based on the shape, texture, and color of the images. This study employs two Convolutional Neural Network (CNN) architectures, ResNet50 and GoogLeNet, to compare the performance of these models in classifying MRI scans of patients with Alzheimer's and Parkinson's diseases. The results show that the ResNet50 model outperforms the GoogLeNet model, with parameters set to 100 epochs, a batch size of 128, a learning rate of 0.0001, and the Adam optimizer, achieving an accuracy rate of 90%.
SIMAPA System Testing Using Alpha and Beta Tests Eva Yulia Puspaningrum; Dhian Satria Yudha K.; Hapsari Wiji Utami; Yisti Vita Via; Eka Prakarsa Mandyartha; Hendra Maulana
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4133

Abstract

The SIMAPA system is a system for monitoring children's activities and development which is implemented at KB-TK Agripina Surabaya. The SIMAPA system has been designed using system development, namely SDLC (System Development Life Cycle). The system can be declared valid and by what is expected if testing has been carried out. An application can be tested using collaborative alpha and beta testing using the black box method. Alpha testing is carried out to see whether all systems can run well and is carried out by the system manufacturer. Meanwhile, in beta testing, the party who will assess the system is the user or people who are not involved in creating the system. This testing is carried out by distributing questionnaires to several users to assess the application that has been built. The questionnaire contains questions about the system being built so that it can be concluded whether the application is by the objectives. The results of the Beta test with 6 questions about the system obtained good results with an average score of 92%. so that the system built is by what is expected.
Testing of the Monitoring and Evaluation System for Subsidized Fertilizer using the Black Box Method Agung Mustika Rizki; Eva Yulia Puspaningrum; Annisaa Sri Indrawanti; Firza Prima Adityawan
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4163

Abstract

Evaluation and monitoring of subsidized fertilizer is needed by the Food and Agriculture Security Service to control the distribution of subsidized fertilizer. To make it easier to monitor fertilizer distribution, an information system was created that can control and monitor fertilizer supplies and distribution. At the system needs analysis stage there are several procedures related to users in the system including farmers, distributors, extension workers, and the department itself. The evaluation and monitoring system was built using the waterfall method with needs analysis, design, implementation, testing, and maintenance. At the trial stage, system testing will be carried out using the black box testing method. Testing using black box testing aims to find out errors that occur when the system is used by the end user. From the results of testing using the black box method, it was found that the functionality of the system was running well.
Community Services on Website Development for Agripina Kindergarten Surabaya as a School Profiling Media Eka Prakarsa Mandyartha; Eva Yulia Puspaningrum
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.33101

Abstract

Agripina Kindergarten Surabaya, located in Rungkut District, Surabaya City, is an educational institution for pre-school education for early childhood and kindergarten. Agripina Kindergarten as an educational institution must be active in advancing the institution. The progress of educational institutions can be seen from the effectiveness in promoting schools to the community so that they can attract public interest in schools to these educational institutions. The rapid development of technology can be utilized by institutions in building relationships with the community and providing various information and facilities related to schools. This can be realized through the school website. The school website serves as a school profiling media. for that required the ability of human resources or teachers there in creating and managing web applications. Through the website as a school profiling medium, the identity of the school, the school's vision and mission, curriculum, teachers, student activities, and school facilities and infrastructure can be displayed. Through community service activities carried out by a team of lecturers from UPN veterans of East Java, they will provide training in the field of web creation and management for teachers there. Creating a basic school website through WordPress is taught through this activity, which serves as a type of training. WordPress is a website-based Content Management System (CMS) platform that can be operated by the public, without having special skills in the field of information technology such as programming. This community service activity aims to provide training to Agripina Kindergarten teachers to have the insight and skills to build a simple school website, it is hoped that teachers can use the website to build school profiling media to present themselves in the world of online portals.
Studi Performa TF-IDF dan Word2Vec Pada Analisis Sentimen Cyberbullying Ahmad Hilman Dani; Eva Yulia Puspaningrum; Retno Mumpuni
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 2 (2024): Juni : Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i2.76

Abstract

On August 14, 2023, Indonesia had approximately 228 million social media users, a number that is expected to continue growing to reach 267 million by 2028. Social media can be used to spread both positive and negative information, and one of the various negative effects is cyberbullying. Consequently, much research is conducted in the field of machine learning to develop sentiment analysis. One crucial step in sentiment analysis is word weighting. The two most common word weighting methods are TF-IDF and Word2Vec. These methods can be compared to determine which one produces better classification results, allowing cyberbullying sentiments on social media to be detected more accurately. Based on nine test scenarios, the final results showed that TF-IDF performed better than Word2Vec in this study, with an accuracy of 84%.
Co-Authors Abiyan Naufal Hilmi Achmad Junaidi Adityawan, Firza Prima Adyani, Adelia Putri Agung Mujiono, Alfinas Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Ahmad Fahry Hamidy Ahmad Hilman Dani Akbar, Fawwaz Ali Al Danny Rian Wibisono Ali Muhhamad Saleh Baaboud Andhika Ahnaf Daniswara Andreas Nugroho Sihananto Annisaa Sri Indrawanti Anny Yuniarti Aqsa Prima Cahya Ariani, Dian Dwi Ariyono Setiawan Aryananda, Rangga Laksana Aswan Aswan Attaqwa, Syukur Iman Az-Zahro', Syaikhhanun Nabila Azizah, Nabila Wafiqotul Bagus Sutikno Putra Basuki Rahmat Basuki Rahmat Basuki Rahmat Masdi Siduppa Bimantara, Candra Kusuma Muhammad Budi Nugroho Budi Nugroho Budi Nugroho Budi Nugroho Chafid, M Putih Devan Cakra Mudra Wijaya Dewi, Deshinta Arrova Dhian Satria Yudha K. Dimas Saputra Diyasa, I Gede Susrama Mas Dwi Anggraeni, Shinta Dwiki Aditama Supangkat Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha, Eka Elzandy, Imeldha Etniko Siagian, Pangestu Sandya Fahmi Al Hafidz, Achmad Fara Disa Durry Faris Syaifulloh Farkhan, Farkhan Fetty Tri Anggraeny Firza Prima Adityawan Fitri Rahmawati Hapsari Wiji Utami Hasby Bik, Ahmad Henni Endah Wahanani Humairah, Sayyidah Humam Maulana Tsubasanofa Ramadhan I Gede Susrama Mas Diyasa I Gede Susrama Mas Diyasa I Nyoman Sujana I Wayan Alston Argodi Idhana, Ilham Ainur indrawanti, annisaa sri Karim, Mohammad Daniel Sulthonul Kartini Kartini Lestari, Kusmiyati Lina Nurlaili, Afina M. Syahrul Munir, M. Syahrul Mada Lazuardi Nazilly Made Hanindia Prami Swari Manggala, Herwantoro Arya Marchel Adias Pradana Mas Diyasa, I Gede Susrama Mas Diyasa, I Gede Susrama Susrama Maulana, Hendra Merdin Risalul Abrori Moch. Hatta Mohammad Idhom Muhammad Asyraf Muhammad Fernanda Naufal Fathoni Muhammad Misbachuddin Muhammad Muharrom Al Haromainy Muhammad Syafril Hidayat Nabilah, Qonitah Jihan Nanik Suciati Noor Fitria Azzahra Nugroho, Budi Nugroho, Budi Nugroho, Budi Nurcahyo, Syai'in Bayu Nurul Taukid, Mochamad Pallawabonang, Mahabintang Pratama Wirya Atmaja Pratama, Gede Ardi Prisheila Dharmawan, Diaz Putra, Chrystia Aji Putra, Riza Satria Putri, Desya Ristya Retno Mumpuni Rizqi Mar'atus Sholiihah, Eka Royan Fajar Sultoni S J Saputra, Wahyu Safira, Dwi Putri Salsabilah, Andini Fitriyah Samuel Krispama Lumbantoruan Saputra, Raka Aji Saputra, Wahyu S J Saputra, Wahyu S J Saputra, Wahyu S. J. Saputra, Wahyu S.J. Satria Yudha Kartika , Dhian Shawn Hafizh Adefrid Pietersz Shofiya Syidada Sukendah, Sukendah Surjohadi, Surjohadi Susrama Mas Diyasa, I Gede Syahrul Hidayat Syaifullah JS, Wahyu Taruna Ardianto Tataq Distasianto Utami, Hapsari Wiji Vita Via, Yisti Wafiqotul Azizah, Nabila Wahyu Caesarendra Wahyu Dwi Lestari Wahyu S.J. Saputra Wahyu Syaifullah Jauharis Saputra Wan Awang, Wan Suryani Wan Suryani Wan Awang Wiji Utami, Hapsari Yisti Vita Via Yisti Vita Via Yogie Wilvren Saragih Yudha K., Dhian Satria Yudhistira Nanda Kumala YUSMI NUR AINI Zacky Yaser Malik Gumiwang ZAMAZANI, ZAIN MUZADID Zuhriyah, Sitti