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All Journal Indonesian Journal of Electronics and Instrumentation Systems Transmisi: Jurnal Ilmiah Teknik Elektro Techno.Com: Jurnal Teknologi Informasi ELINVO (Electronics, Informatics, and Vocational Education) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO JETT (Jurnal Elektro dan Telekomunikasi Terapan) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTERA (Jurnal Teknologi Rekayasa) BAREKENG: Jurnal Ilmu Matematika dan Terapan JRST (Jurnal Riset Sains dan Teknologi) Madani : Indonesian Journal of Civil Society Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Journal of Telecommunication, Electronics and Control Engineering (JTECE) Jurnal Ekonomika Dan Bisnis JURNAL TEKNIK INDUSTRI eProceedings of Engineering Jurnal Rekayasa elektrika Jurnal INFOTEL
Afandi, Mas Aly
Institut Teknologi Telkom Purwokerto
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Implementasi SMOTE Untuk Mengatasi Imbalance Class Pada Berita Online Menggunakan Metode K-Nearest Neighbor (KNN) Sitanggang, Andreas; Rhomandhona, Shinta; Aly Afandi, Mas
eProceedings of Engineering Vol. 12 No. 3 (2025): Juni 2025
Publisher : eProceedings of Engineering

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Abstract

Berdasarkan survei Asosiasi Penyelenggara JasaInternet Indonesia (APJII), jumlah pengguna internet diIndonesia mencapai 215,63 juta orang pada periode 2022-2023,meningkat sebesar 2,67% dibandingkan periode sebelumnya.Peningkatan ini menyebabkan lonjakan jumlah berita onlineyang memerlukan pengelolaan data yang lebih baik, terutamadalam menangani ketidakseimbangan kelas data set padaklasifikasi data. Penelitian ini bertujuan untuk mengatasimasalah tersebut dengan menerapkan teknik SMOTE, yangmenghasilkan sampel baru untuk kelas data set minoritas gunameningkatkan representasi data. Selain itu, algoritma KNNdigunakan untuk mengevaluasi pengaruh kombinasi SMOTEdan KNN terhadap performa model klasifikasi. Evaluasidilakukan menggunakan metrik akurasi, presisi, recall, dan F1-Score. Hasil penelitian menunjukkan bahwa penerapanSMOTE berhasil meningkatkan performa model klasifikasi.Kombinasi terbaik diperoleh pada nilai parameter k=1, denganakurasi sebesar 62,50%, presisi 58,39%, recall 86,96%, dan F1-Score 69,87%. Dibandingkan dengan model sebelum penerapanSMOTE, terjadi peningkatan performa akurasi dari 58,33%,presisi dari 49,56%, dan F1-Score dari 63,28%, sambilmempertahankan recall 87,50%. Penelitian ini membuktikanbahwa SMOTE efektif dalam menangani ketidakseimbangankelas data set, menghasilkan prediksi model yang lebih akuratdan seimbang. Hasil penelitian memberikan kontribusi dalampengelolaan data berita online untuk mendukung kualitasklasifikasi yang lebih baik.Kata kunci— AI, KNN, SMOTE, Berita Online
Klasifikasi Penyakit Daun Kelapa Sawit Menggunakan Metode Convolutional Neural Network (CNN) Abimanyu, Arya; Aly Afandi, Mas; Indah, Sevia
eProceedings of Engineering Vol. 12 No. 3 (2025): Juni 2025
Publisher : eProceedings of Engineering

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Abstract

Kelapa sawit merupakan salah satu komoditasperkebunan yang memiliki peran strategis dalam pembangunanekonomi Indonesia. Sebagai tulang punggung ekonomi bagijutaan penduduk, perkembangan sektor ini menekankanpemenuhan persyaratan guna menjamin hasil produksi yangberkualitas. Tantangan utama yang dihadapi petani adalahpenyakit pada tanaman kelapa sawit yang disebabkan olehhama dan kekurangan unsur hara, yang dapat menghambatpertumbuhan dan mengurangi hasil panen. Kurangnyapengetahuan petani mengenai jenis penyakit daun kelapa sawitsering kali mengakibatkan kesalahan dalam penanganannya.Penelitian ini berfokus pada klasifikasi penyakit daun kelapasawit menggunakan pengolahan citra berbasis kecerdasanbuatan (Artificial Intelligence), dengan tujuan membantupetani dalam mengidentifikasi daun sehat dan berpenyakitsecara akurat. Metode Convolutional Neural Network (CNN)digunakan untuk mengenali pola dan fitur kompleks pada citradaun kelapa sawit. Hasil menunjukkan bahwa akurasipelatihan meningkat cepat hingga hampir 1 pada epoch 1–20,dengan loss turun signifikan. Namun, akurasi validasi stabil disekitar 0,95, menandakan adanya overfitting. Epoch terbaiktercatat pada epoch 20 dengan akurasi pelatihan 1 dan loss0,001, sementara akurasi validasi tertinggi terjadi pada epoch80 sebesar 0,975. Berdasarkan confusion matrix, model berhasilmengklasifikasikan daun berpenyakit sebanyak 66 kali dandaun sehat sebanyak 80 kali, dengan 14 kesalahan false positivedan tanpa false negative. Akurasi model mencapai 91,25%,dengan presisi 82,5% dan recall 100%, menunjukkan performayang baik dalam mengidentifikasi daun sehat dan berpenyakit.Harapannya, penelitian ini dapat menjadi solusi praktis bagipetani dalam mendeteksi penyakit daun kelapa sawit secaracepat dan akurat, meminimalkan kesalahan, dan meningkatkanhasil pertanian secara keseluruhan.Kata kunci— AI, CNN, Daun Sawit, Klasifikasi
Prototype Implementasi Pencatatan Pengisian Bahan Bakar Otomatis Berbasis Internet Of Things Dwi Cahyani, Puput; Aly Afandi, Mas; Permatasari, Indah
eProceedings of Engineering Vol. 12 No. 3 (2025): Juni 2025
Publisher : eProceedings of Engineering

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Abstract

Pencatatan pengisian bahan bakar secara manual memiliki risiko kesalahan manusia, kurang efisien, dan sulit diakses secara real-time, yang dapat menyebabkan ketidaktepatan dalam pengelolaan bahan bakar. Untuk mengatasi permasalahan ini, dikembangkan prototipe sistem pencatatan pengisian bahan bakar berbasis Internet of Things yang menggunakan ESP32 sebagai kontrol utama. Sistem ini mengintegrasikan sensor flowmeter untuk mengukur volume bahan bakar, sensor ultrasonik untuk mendeteksi level cairan dalam tangki, serta buzzer sebagai indikator peringatan saatstok bahan bakar menipis. Data pencatatan dikirim secara real-time ke Google Spreadsheet melalui koneksi WiFi, sehingga dapat diakses dengan mudah dan menghilangkan kebutuhan pencatatan manual. Hasil pengujian menunjukkan bahwa sensor flowmeter mencatat rata-rata 408 pulsa per liter, dengan tingkat error 1,73% pada volume per 1000 ml. Sistem ini mampu mencatat data pengisian bahan bakar secara otomatis, akurat, dan real-time, serta meningkatkan efisiensi dalam pemantauan penggunaan bahan bakar.Kata kunci— Bahan bakar solar, ESP32, IoT, Flowmeter, Ultrasonic, Google Spreadsheet
Rekayasa Budidaya Melon Hidroponik dalam Greenhouse untuk Meningkatkan Pendapatan Masyarakat Desa Purwojati Murdiantoro, Randi Adzin; Nur, Ivan Akmal; Isnawati, Anggun Fitrian; Afandi, Mas Aly; Rumestri, Agatha Dinarah Sri; Purwanti, Eri Nanda Dewi; Nurmeilinda, Kharisma; Anjani, Mia; Saputra, Sahrul; Arsiandro, Fadzly Haris; Nurkholis, Rizki; Prasetio, Angga Ari; Utari, Tria; Fadillah, Siti; Sutarmin, Sutarmin
Jurnal Ekonomika Dan Bisnis (JEBS) Vol. 4 No. 6 (2024): November - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jebs.v4i6.2237

Abstract

Agriculture is still the main sector in rural economy in Indonesia, including in Purwojati Village. This village is one of the extreme poor areas in Purwojati Subdistrict, Kabupaten Banyumas, where most of the area is dry land. Banyumas whose area is mostly dry land. Based on this condition, it is necessary to modify the technology on commodities in the based on these conditions, it is necessary to modify the existing commodities in the area, namely hydroponic melon cultivation engineering in greenhouses. The purpose of this activity is to increase cultivation productivity to increase community income. The results of the use of greenhouses in the use of greenhouses in golden melon cultivation in Purwojati Village increases productivity up to 4-5 times per year for 1 unit of greenhouse. harvest per year for 1 greenhouse unit, better fruit quality, and increased community knowledge in the field of hydroponic melon cultivation. better fruit quality, and increased community knowledge in the field of business management and modern agriculture. This has the potential to increase community income significantly, thus supporting economic empowerment and income significantly, thus supporting economic empowerment and improving welfare of farmers in the area.
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
Co-Authors Abi Hakim Amanullah Abimanyu, Arya Adelia Kencana Putri Adiputra, Dimas Adriansyah, Bagas Afifah Dwi Ramadhani Agatha Dinarah Sri Rumestri Agung Wicaksono Agung Wicaksono Agustinah, Chandra Aisyah Ayu Wulandari Aisyah Alfin Anantia Prakasa Andi Aqsha Ramadana Lubis Andri Juli Setiawan Angga Bagus Prawira Anggun Fitrian Isnawati Anjani, Mia Arfianto Fahmi Arsiandro, Fadzly Haris Azhar Alfarisi, Fadhil Brayan Raynaldi Caesar Sabani Chandra Agustinah Crisianti, Risa Farid Dadan Nur Ramadan Dania Anggraeni Dhany Maulana Supriadi Dicky Revan Pangestu Dwi Cahyani, Puput DWI SURYANTO Dwika Pangestu, Septiana Eka Setia Nugraha Elsalami, Puspa Maudi Erlina Nur Arifani Ezi Rohmat Fadhila Karin Purnomo FADHLAN, FATHURROZAQ Fadillah, Siti Fairuz Azmi Fikra Titan Syifa Fikri Nizar Gustiyana Filbert H. Juwono Goran, Petrus Kerowe Gunawan Wibisono Hanif Aditya Permana Hanin Latif Fuadi hazia rifka maulida Hedi Krishna Helmy Widyantara Herryawan Pujiharsono I Ketut Agung Enriko Ibrohim Huzaimi Indah Permatasari Indah Permatasari Indah, Sevia Indrarini Dyah Irawati Irmayatul Hikmah Isa Hafidz Kevin Dwi Andika Hendarta Khulqi Rasyid kinanti, Alicia Kirani Lubis, Liza Lukman Priyambodo M. Raihan Muzzaki Makhdhori, Muhammad Marina, Prieska Montolalu, Billy Muhammad Aulia Baihaqy Muhammad Nur Al-Majid Mulyani, Elsa Sri Nabila, Nisrina Hania Nada Febiola Nur Azizah Natasya Nur Khalika Naura Nazhifah Nur, Ivan Akmal Nuralifa Kalyana Puteri, Keyza Nurcahyani Wulandari Nurkholis, Rizki Nurmeilinda, Kharisma Octavian Ery Pamungkas Oktaviana, Lutvi Tri Pangestu, Gusti Angga Prasetio, Angga Ari Prieska Marina Purwanti, Eri Nanda Dewi Puspa Rahmawati Puteri, Keyza Nuralifa Randi Adzin Murdiantoro Raynaldi, Brayan Reni Dyah Wahyuningrum Rhomandhona, Shinta Risa Fareid Christianti Risa Farid Crisianti Ristanti Akseptori Rochmanto, Raditya Artha Rohan Hiskia Saragih, Aldo Salsabila, Unik Hanifah Saputra, Sahrul Selamet, Sheila Shelvia Setiawan, Andri Juli Sevia Indah Purnama Shidqi Dhamara, Ammar Silvi Nurandi Sitanggang, Andreas Sugondo Hadiyoso Sutarmin Sutarmin, Sutarmin Tarigan, Nicolas Yonara Tasya Enjelika Saputri Thofan Maliyano Ubaidilah Umar Utari, Tria Wahyu Andy Prastyabudi Yudha Purwanto