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All Journal Techno.Com: Jurnal Teknologi Informasi ELINVO (Electronics, Informatics, and Vocational Education) JURNAL NASIONAL TEKNIK ELEKTRO BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teori dan Aplikasi Fisika Jurnal Teknokes Jurnal Riset Rekayasa Elektro Madani : Indonesian Journal of Civil Society JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Journal of Telecommunication, Electronics and Control Engineering (JTECE) eProceedings of Engineering Jurnal Rekayasa elektrika
Sevia Indah Purnama
Institut Teknologi Telkom Purwokerto
Humanities Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Analisis dan Implementasi Perangkat Elektrokardiogram (EKG) Berbasis Internet of Things Novianto, Arif Indras; Purnama, Sevia Indah; Hikmah, Irmayatul
Journal of Telecommunication Electronics and Control Engineering (JTECE) Vol 7 No 2 (2025): Journal of Telecommunication, Electronics, and Control Engineering (JTECE)
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/jtece.v7i2.1874

Abstract

Berdasarkan informasi Infodatin diketahui lebih dari 36 juta orang didunia meninggal dunia dikarenakan penyakit pada jantung. Kondisi in mendorong kebutuhan perangkat monitoring kondisi jantung. Kondisi jantung dapat diketahui melalui sinyal jantung yang diukur menggunakan Elektrokardiogram. Elektrokardiogram membutuhkan pengolahan sinyal yang baik agar dapat membaca pola sinyal jantung. Penelitian ini berfokus pada pembuatan perangkat monitoring kondisi jantung yang memiliki performa bagus dalam mengolah sinyal jantung, menganalisis kondisi jantung, dan mengirimkan hasil visualisasi sinyal jantung ke telegram. Perangkat yang dikembangkan memanfaatkan digital Butterworth low pass filter untuk mengolah sinyal jantung. Hasil penelitian menunjukkan bahwa filter Butterworth mempu menghasilkan sinyal PQRS dan T jantung dengan riak minimal pada frekwensi cut off 15hz. Perangkat memiliki nilai persentase akurasi sebesar 97,96% dalam membaca detak jantung per menit. Hasil visualsisasi sinyal beserta analisis kondisi sinyal juga dapat terkirim ke Telegram. Hasil penelitian menunjukkan bahwa perangkat dapat digunakan untuk menjawab kebutuhan Elektrokardiogram yang akurat dan mampu mengirim visualisasi sinyal serta analisis kondisi jantung.
Analysis of Odor and Color Parameters in the Meat Freshness Detection System Using Gas Sensor and Reaction Kinetics Methods Arifani, Erlina Nur; Purnama, Sevia Indah; Afandy, Mas Aly; Kurnianto, Danny Kurnianto; Latifasari, Nurul Latifasari
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 10 No. 1 (2025): May 2025 (In Press)
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v10i1.77601

Abstract

The degradation of beef is typically indicated by the presence of   NH3 as ammonia and H2S as hydrogen sulfide. The NH3 and H2S level will increase in line with the meat spoilage. This research is aims to develop the new meat storage with NH3 and H2S level measurement to detect spoilage in beef. This measurement is needed to make sure the meat that are store is still in good condition or already spoil. Kinetic model of NH3 and H2S gas is used to determine the correlation between meat spoilage with time. This equipment has main parts that consist of sensor system microcontroller and computer. The MQ 137 works as detector of NH3 gas which are emitted by sample of beefs during observation. The MQ – 136 sensor works as detector of H2S gas. This research also analyzes the color change in beef spoilage. The data of meat storage develop in this research shows that it can properly measure NH3 and H2S gases that occur during the gas evolution process. The color of the meat also changes while the meat spoilage starts. The rate constants of change of H2S and NH3 follow the zero-order kinetics of H2S and NH3 with constant rates of 0.90 and 0.95, respectively. This result shows that time highly correlated with the spoilage meat.
OPTIMASI PEMBACAAN SUHU KAMERA TERMAL MENGGUNAKAN REGRESI LINIER Purnama, Sevia Indah; Hikmah, Irmayatul; Afandi, Mas Aly; Mulyani, Elsa Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 1 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (432.791 KB) | DOI: 10.30598/barekengvol15iss1pp127-136

Abstract

Fever is one of the symptoms of a person with Covid-19. Body temperature must be checked e before entering crowded areas such as schools, offices, shops, and hospitals. It is a mandatory protocol that must be done. One of the tools that can be used to check body temperature is a thermal camera. Thermal cameras have the disadvantage of a high temperature reading error. This is because the thermal camera used has a low resolution. This study aims to reduce the value of the temperature reading error on the thermal camera using the linear regression method. The linear regression method is able to reduce the error rate of temperature readings by 5.27% at 36 ° C reading. The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. Based on the results obtained, this study shows that linear regression can be applied to thermal cameras and provides a decrease in the error rate of temperature readings on thermal cameras
Pelatihan Penggunaan Perangkat Pembelajaran Huruf Braille untuk Siswa Tuna Netra Purnama, Sevia Indah; Afandi, Mas Aly; Hikmah, Irmayatul; Arifani, Erlina Nur; Puteri, Keyza Nuralifa; Elsalami, Puspa Maudi; Setiawan, Andri Juli
Madani : Indonesian Journal of Civil Society Vol. 7 No. 1 (2025): Madani : Februari 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v7i1.2363

Abstract

Visually impaired children have limitations in learning Braille due to limited resources and improper facilities. These limitations mean that independent learning activities at home cannot be carried out because they require a teacher who understands Braille. This service activity is carried out to provide training to blind children on the use of Braille learning tools. This service aims to enable blind children to learn Braille letters independently without needing a teacher. Training activities consist of an introduction to Braille letters, an explanation of Braille learning devices, and training on the use of devices for self-learning. The results of the service show that Braille learning technology devices help students in learning independently. There are 6 students and 1 blind teacher who became respondents who agreed that the learning device can be used independently without the help of a companion teacher. Respondents also agreed that the use of assistive technology in learning devices is easy to use. Students have been able to use learning tools independently without the help of a companion teacher to study outside of school.
Pemberdayaan Pelaku Usaha Hidroponik Desa Berkoh Melalui Peningkatan Efektifitas Pembibitan Afandi, Mas Aly; Purnama, Sevia Indah; Wibisono, Gunawan; Adriansyah, Bagas; Oktaviana, Lutvi Tri
Madani : Indonesian Journal of Civil Society Vol. 7 No. 1 (2025): Madani : Februari 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v7i1.2484

Abstract

Hydroponic entrepreneurs are one of the business sectors affected by extreme climate change in Indonesia. The main problem caused by extreme climate change is the uncertain seeding time. Buyers such as restaurants need a supply of fresh vegetables at a specific time. Uncertain seeding due to extreme weather makes farmers unable to supply fresh vegetables at the specified time. The community service that has been carried out aims to apply artificial lighting technology to speed up the 2-5 day seeding process by vegetable farmers. The community service carried out uses an empowerment method to utilize artificial lighting technology during the seeding process. Before using this technology, farmers needed 10-15 days depending on the sunlight conditions during that period. Based on the activities that have been carried out, artificial lighting technology can provide a consistent seeding time of 8-10 days. The results of the community service show that there has been an increase in empowerment among farmers in Berkoh village.
Multi-Sensor Internet of Things System for Monitoring Wastewater in Healthcare Facility Purnama, Sevia Indah; Afandi, Mas Aly; Hikmah, Irmayatul
Jurnal Rekayasa Elektrika Vol 21, No 3 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i3.41646

Abstract

Wastewater produced by healthcare facilities must meet the parameter criteria set by the Ministry of Environment and Forestry. These criteria ensure that the discharged wastewater does not harm the environment. The numerous healthcare facilities in an area and irregular monitoring can lead to inaccuracies in recording wastewater content. Technology that can be used for periodic monitoring of wastewater content in healthcare facilities is multi-sensor technology and the internet of things (IoT). This paper aims to develop the devices utilizing multi-sensor technology and IoT for monitoring wastewater parameter criteria in healthcare facilities. The developed device measures pH, turbidity, oxidation reduction potential (ORP), and temperature parameters in the wastewater. The sensor data test results showed an accuracy of 98.77% with a precision of 10.03 0.13 for the pH parameter. The ORP parameter showed an average accuracy of 97.56% with a precision range of 241.20 5.65. The turbidity parameter showed an average accuracy of 96.20% with a precision range of 101,67 3,11. The temperature parameter showed an average accuracy of 97.80% with a precision range of 39.23 0.73. Data transmission to the platform had an average delay of 88.02 ms with an average jitter 0.23 ms. Based on the performance measurement data for sensor and data transmission categories, the proposed device met the research aim in monitoring wastewater conditions in healthcare facilities. The device improve the documentation process in monitoring watewater parameter in healthcare facility. The monitoring results using the device showed that the three healthcare facilities met the criteria required by Indonesian Ministry of Environment and Forestry.
Desain Perangkat Pengukuran Hemoglobin Secara Non-Invasif Berbasis Machine Learning Nuralifa Kalyana Puteri, Keyza; Indah Purnama, Sevia; Aly Afandi, Mas
eProceedings of Engineering Vol. 12 No. 4 (2025): Agustus 2025
Publisher : eProceedings of Engineering

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Abstract

Hemoglobin (Hb) merupakan indikator penting untuk menilai kondisi kesehatan karena berperan dalam transportasi oksigen dan karbon dioksida dalam tubuh. Metode pengukuran Hb yang umum digunakan saat ini bersifat invasif, membutuhkan pengambilan sampel darah yang dapat menimbulkan ketidaknyamanan, risiko infeksi, serta memerlukan waktu dan biaya tambahan. Penelitian ini bertujuanmengembangkan perangkat pengukur kadar hemoglobin secara non-invasif menggunakan sensor MAX30102 dan algoritma machine learning regresi linier. Sensor mendeteksi intensitas cahaya merah (Red) dan inframerah (IR) pada ujung jari, yang selanjutnya digunakan sebagai input dalam model prediksi kadar Hb. Model regresi linier yang digunakan memiliki persamaan: Hb = 0,19118 + 0,02011 × IR – 0,0030 × Red. Hasil evaluasi menunjukkan kombinasi sinyal rata-rata IR dan Red memberikan performa terbaik dengan MAE sebesar 0,939, MSE 1,325, RMSE 1,151, serta koefisien korelasi sebesar 0,643. Rata-rata galat antara hasil prediksi perangkat non-invasif terhadap metode invasif adalah 2,66%. Hasil ini menunjukkan bahwa perangkat non-invasif berbasis regresi linier dapat menjadi alternatif yang akurat, nyaman, dan efisien untuk pemantauan kadar hemoglobin.Kata kunci— hemoglobin, machine learning, non invasif, regresi linier.
Implementasi Arsitektur U-Net Untuk Segmentasi Tumor Otak Otomatis Pada Citra MRI Dengan Data Pengujian Asli Shidqi Dhamara, Ammar; Indah Purnama , Sevia; Aly Afandi, Mas
eProceedings of Engineering Vol. 12 No. 4 (2025): Agustus 2025
Publisher : eProceedings of Engineering

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Abstract

Tumor otak merupakan pertumbuhan selabnormal yang mengganggu fungsi otak. Deteksi dini pentinguntuk meningkatkan akurasi diagnosis, namun segmentasimanual citra MRI memerlukan keahlian tinggi. Penelitian inimengimplementasikan arsitektur U-Net sebagai metodesegmentasi otomatis pada citra MRI menggunakan data aslidari Rumah Sakit Islam Jakarta Cempaka Putih. Eksperimendilakukan dengan variasi epoch (20–100) dan Learning rate(1e-3 dan 1e-4). Konfigurasi terbaik diperoleh pada Learningrate 1e-4 dan 100 epoch dengan Dice Coefficient 0,88 dan IoU0,78. Sistem U-Net ini dapat meningkatkan efisiensi danakurasi diagnosis tumor otak.Kata kunci : Tumor otak, MRI, Segmentasi, U-Net, DeepLearning
Penerapan Sistem Monitoring Dengan Konsep Wearable Device Untuk Simulasi Pemantauan Tanda Vital Pada Pasien Menggunakan BlYNK Wulan Sari, Hesti; Titan Syifa, Fikra; Indah Purnama, Sevia
eProceedings of Engineering Vol. 12 No. 4 (2025): Agustus 2025
Publisher : eProceedings of Engineering

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Abstract

Pemantauan tanda vital secara real-time menjadi aspek krusial dalam pelayanan kesehatan modern untuk mendeteksi dini gangguan seperti demam, takikardia, atau penurunan kadar oksigen dalam darah. Penelitian ini bertujuan mengembangkan sistem monitoring kesehatan berbasis wearable device yang terintegrasi dengan Internet of Things (IoT) melalui platform Blynk. Sistem ini dirancangmenggunakan mikrokontroler Wemos D1 Mini serta sensor MLX90614 untuk suhu tubuh, dan MAX30100 untuk detak jantung (BPM) dan kadar oksigen darah (SpO₂). Parameter yang dipantau meliputi suhu tubuh normal (36,5–37,5°C), BPM normal (60–100 bpm), serta SpO₂ normal (95–100%). Datadikategorikan sebagai gejala gangguan jika suhu ≥38°C, BPM >100 bpm, atau SpO₂ <95%. Hasil pengujian menunjukkan akurasi rata-rata pengukuran sebesar 97,53% untuk suhu tubuh, 97,62% untuk detak jantung, dan 99,07% untuk SpO₂ jika dibandingkan dengan alat medis pembanding. Dengankemampuan mengirim dan menampilkan data secara langsung ke smartphone, sistem ini dapat digunakan sebagai solusi pemantauan pasien secara efisien dan minim kontak fisik, sehingga berpotensi mendukung respons cepat dalam penanganan kondisi kesehatan pasien.Kata kunci— Blynk, Tanda Vital, Wearable Device
Perbandingan Kinerja Model Transfer Learning VGG16 dan ResNet50 Dalam Klasifikasi Tumor Otak Pada Citra MRI Yosef Mnaku Gawen, Baltasar; Indah Purnama, Sevia; Hikmah, Irmayatul
eProceedings of Engineering Vol. 12 No. 4 (2025): Agustus 2025
Publisher : eProceedings of Engineering

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Abstract

Tingginya prevalensi tumor otak dan pentingnyadeteksi dini mendorong pengembangan sistem diagnosisotomatis berbasis kecerdasan buatan. Penelitian ini bertujuanmembandingkan kinerja dua arsitektur deep learning, yaituVGG16 dan ResNet50, dalam mengklasifikasi empat jenis citraMRI tumor otak yakni glioma, meningioma, pituitary, dan notumor. Pendekatan yang digunakan adalah transfer learningdengan dua skenario perbandingan yakni sebelum dan sesudahfine-tuning. Transfer learning memungkinkan pemanfaatanmodel yang telah dilatih sebelumnya, sedangkan fine-tuningdilakukan untuk menyesuaikan parameter model terhadapkarakteristik data baru. Seluruh proses penelitian mengikutitahapan Knowledge Discovery in Database (KDD), yang meliputipengumpulan data, preprocessing, pelatihan model, danevaluasi. Hasil evaluasi menunjukkan bahwa ResNet50menghasilkan akurasi sebesar 94,80% sebelum fine-tuning danmeningkat menjadi 97,54% setelah fine-tuning. Sementara itu,VGG16 memperoleh akurasi sebesar 91,39% sebelum finetuning dan meningkat signifikan menjadi 98,68% setelah finetuning. Berdasarkan hasil tersebut, dapat disimpulkan bahwamodel VGG16 dengan fine-tuning menunjukkan kinerja terbaikdalam klasifikasi tumor otak pada citra MRI. Temuan inimengindikasikan bahwa pendekatan deep learning berbasistransfer learning berpotensi meningkatkan efektivitas danefisiensi diagnosis tumor otak secara otomatis.Kata Kunci: fine-tuning, transfer learning, VGG16, ResNet50,klasifikasi tumor, citra MRI
Co-Authors Adanti Wido Paramadini Adiputra, Dimas Aditya Prayugo Hariyanto Adriansyah, Bagas Afandi, Mas Aly Afandy, Mas Aly Alfataniah Nur Fajrina Alfin Andi Aqsha Ramadana Lubis Azhar Alfarisi, Fadhil Crisianti, Risa Farid Dwika Pangestu, Septiana Elsalami, Puspa Maudi Erlina Nur Arifani Fadhila Karin Purnomo Fajritama, Reza Fikra Titan Syifa Fitriawan, Taufiq Ghifar Rachman Nugraha Gunawan Wibisono Irmayatul Hikmah Jalil Faza Kevin Dwi Andika Hendarta Kevin Pratama Woy, Mario Kirani Lubis, Liza Kurnianto, Danny Kurnianto Latifasari, Nurul Latifasari Makhdhori, Muhammad Muhammad Nur Al-Majid Muhammad Panji Kusuma Praja Muhammad Yusro Mulyani, Elsa Sri Nasya Mauldi, Meyke Novianto, Arif Indras Nuralifa Kalyana Puteri, Keyza Oktaviana, Lutvi Tri Pangestu, Gusti Angga Paskah Saroengoe, Michael Pradana, Zein Hanni Puteri, Keyza Nuralifa Putri Intan Anggiarti Rachel Dwi Laura Br Sigalingging, Sonia Rangga Saputra Risa Farid Crisianti Rochmanto, Raditya Artha Rohan Hiskia Saragih, Aldo Selamet, Sheila Shelvia Setiawan, Andri Juli Shidqi Dhamara, Ammar Shinta Romadhona Witri Arsyada, Rifalia Wulan Sari, Hesti Yosef Mnaku Gawen, Baltasar Zen, Nur Afifah