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All Journal Jurnal Pendidikan Vokasional Teknik Elektronika (JVoTE) Journal of Electrical Engineering and Computer (JEECOM) Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Inventor: Jurnal Inovasi dan Tren Pendidikan Teknologi Informasi
Mochammad Rifki Ulil Albaab
Politeknik Negeri Jember
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Other

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Pengembangan Digi Ecosmart, Ekosistem Ekonomi Digital Cerdas Berbasis Immersive Technology PT Nuswantoro Informasi Teknologi Denny Trias Utomo; Mochammad Rifki Ulil Albaab; Ahmad Fahriyannur Rosyady; Adi Sucipto; Sholihah Ayu Wulandari
Journal of Electrical Engineering and Computer (JEECOM) Vol 5, No 1 (2023)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v5i1.5141

Abstract

Sidoarjo Regency is a Delta Plain with an altitude between 0 to 25 m, a height of 0-3m with an area of 19,006 Ha, covering 29.99%, is a fishpond area located in the eastern part of the Central Region which has fresh water with an altitude of 3-10 meters above sea level is a residential area, trade and government. Covering 40.81%. The western region with an altitude of 10-25 meters above sea level is an agricultural area. [1],[2]The Matching Fund Program is a program funded by the Ministry of Education and Culture, Ministry of Research and Technology to strengthen cooperation between PTs and DUDI to jointly form the Merdeka Learning Ecosystem - Merdeka Campus. At the end of the program, a better and sustainable working relationship will be established between PT and DUDI, which is expected to contribute to solving real problems in the field or carrying out national strategic actions. [3]The method used on this project is prototyping, which is a system development method in which prototypes are built, tested and then reworked as necessary until acceptable results are achieved of the system or a complete product can be developed.
Website Monitoring Pintar Terintegrasi Berbasis IoT pada Budidaya Lobster Air Tawar mochammad rifki Ulil Albaab; rani purbanigtyas; Muhammad Ferdiansyah Aulia Kusuma; junia vitasari; Daffa Agung Nugroho; Adisty Pramudita Putri Rudi
Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Vol 4 No 1 (2023): Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) April 2023
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/jatim.v4iNo.1.1978

Abstract

Menurut Dinas Tenaga Kerja (Disnaker) Sidoarjo angka pengangguran di Sidoarjo mencapai 10,97% dari keseluruhan angkatan kerja. Pandemi merupakan penyebab utama tingginya pengangguran di Sidoarjo. Budidaya lobster air tawar merupakan peluang usaha yang memiliki omset tinggi dan menjanjikan serta dapat menjadi jawaban dari permasalahan tingginya tingkat pengangguran di Sidoarjo. Untuk membantu keberhasilan budidaya crawfish, beberapa hal harus diperhatikan seperti suhu, pH dan jenis pakan crawfish. Aspek penting adalah kualitas air. Pada tambak udang air tawar yang ideal suhu air 26-30℃ dan jika suhu tidak stabil maka lobster tidak dapat hidup dan tumbuh dengan baik. Teknologi dengan inovasi terbaru yang diciptakan diharapkan dapat membantu mendeteksi tingkat suhu dan dapat mengontrol suhu air kolam lobster untuk tetap stabil. Hasil deteksi suhu air pada kolam lobster menggunakan sensor suhu DS18B20 akan ditampilkan secara real-time pada layar LCD I2C.
Sistem BIMA: Integrasi IoT dan Deep Learning untuk Penyortiran Kualitas Telur Ayam Mochammad Rifki Ulil Albaab; Muhammad Hafidh Firmansyah; Reza Putra Pradana; Agung Muliawan; Bima Wahyu Maulana
Inventor: Jurnal Inovasi dan Tren Pendidikan Teknologi Informasi Vol. 4 No. 3 (2026): Edisi Oktober
Publisher : STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/inventor.v4i3.5121

Abstract

Proses penyortiran telur ayam di peternakan masih umumnya dilakukan secara manual sehingga berisiko menghasilkan penilaian subjektif, kesalahan manusia, dan ketidakkonsistenan. Penelitian ini merancang BIMA, sebuah sistem cerdas berbasis Internet of Things (IoT) yang ditujukan untuk mengintegrasikan proses identifikasi mutu dan penyortiran telur secara otomatis. Metode Convolutional Neural Network (CNN) dengan arsitektur MobileNetV2 digunakan untuk mengenali dan menentukan kategori kualitas telur berdasarkan citra. Dalam implementasinya, ESP32 sebagai pengendali utama, sedangkan ESP32-CAM digunakan untuk menangkap citra telur. Pengukuran bobot dilakukan menggunakan Load Cell yang terintegrasi dengan HX711, sementara IR Obstacle Sensor berfungsi mendeteksi keberadaan telur pada jalur konveyor. Mekanisme pemindahan dan pengelompokan telur didukung oleh mini conveyor dan robot arm. Berdasarkan hasil klasifikasi, telur dikelompokkan ke dalam empat kelas mutu, yakni Grade A, Grade B, Grade C, dan Tidak Layak (TL). Model dilatih menggunakan 2.436 citra melalui transfer learning dan menghasilkan akurasi validasi 94,40% serta rata-rata F1-score 95,3%. Pengujian sistem terhadap 100 telur dalam lima sesi memperoleh akurasi 72,0%. Sensor Load Cell menghasilkan MAPE 2,02%, sedangkan sensor IR Obstacle mampu mendeteksi keberadaan telur dengan baik. Hasil menunjukkan bahwa integrasi CNN-MobileNetV2 dan IoT berpotensi mendukung otomatisasi penyortiran telur secara real-time.
Two-Stage Adaptive Normalization Based on Exponential Moving Average for DC Offset and Variance Non-Stationarity Compensation in Real-Time Volcanic Seismic Signal Preconditioning Radimas Putra Muhammad Davi Labib; Ratri Andinisari; Mochammad Rifki Ulil Albaab; Ferty Lanisa Putri; Fernanda Sucitra Murti; Agam Nizar Dwi Nur Fahmi
JURNAL PENDIDIKAN VOKASIONAL TEKNIK ELEKTRONIKA (JVoTE) Vol. 8 No. 2 (2025): Vol 8 No 2 (2025): JURNAL PENDIDIKAN VOKASIONAL TEKNIK ELEKTRONIKA (JVoTE) Volu
Publisher : PENDIDIKAN VOKASIONAL TEKNIK ELEKTRONIKA FAKULTAS TEKNIK UNIVERSITAS NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jvote.v8i2.71692

Abstract

Volcanic seismic signals output by digitizers as raw counts carry the accumulated imperfections of the entire acquisition chain—specifically, significant DC offset and large-scale variability—thereby violating the stationarity assumption underpinning downstream estimation blocks. This study proposes a two-stage adaptive normalization architecture based on the Exponential Moving Average (EMA) to serve as a statistical pre-conditioning block prior to the Kalman Filter. The first stage removes the DC offset using a recursive mean estimator—analytically equivalent to a first-order high-pass filter—while the second stage performs Z-Score standardization based on a running estimate of the standard deviation. Testing was conducted on a 386.48-second vertical-channel recording from the Leker (LKR) station at Mount Semeru (sampled at 100 Hz; 38,649 samples), characterized by a DC offset of −7,292.4 counts and a variance dynamic ratio of 10.42. With an adaptation constant of 0.005, the effective cutoff frequency of 0.0796 Hz lies approximately eighteen times below the 1.42 Hz fundamental frequency of the harmonic tremor, resulting in a passband attenuation of only −0.035 dB. Results demonstrate that the estimator locks onto the bias with a discrepancy of 7.72 counts (0.070% of the signal's standard deviation), reduces the dynamic ratio to 1.52, and yields an output where 99.989% of samples fall within the ±3 range. The Normalized Innovation Squared test confirms that the static covariance parameters of the Kalman Filter remain consistent with the normalized input, yielding a ratio of 1.17 compared to 17.10 for the raw input—an improvement factor of 14.6. The algorithm requires 8 bytes of state memory and 0.0104% processor utilization on an ARM Cortex-M4F at 48 MHz, whereas static normalization of the same recording requires 151.0 kB and cannot be implemented on that platform.
Co-Authors Adi Sucipto Adisty Pramudita Putri Rudi Agam Nizar Dwi Nur Fahmi Agung Muliawan Ahmad Fahriyannur Rosyady Bima Wahyu Maulana Daffa Agung Nugroho Denny Trias Utomo, Denny Trias Fernanda Sucitra Murti Ferty Lanisa Putri junia vitasari Muhammad Ferdiansyah Aulia Kusuma MUHAMMAD HAFIDH FIRMANSYAH Radimas Putra Muhammad Davi Labib rani purbanigtyas Ratri Andinisari Reza Putra Pradana Wulandari, Sholihah Ayu