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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Share : Journal of Service Learning Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Elektro: Ilmu dan Teknologi
Resmana Lim
Petra Christian University
Arts Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Social Sciences

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SISTEM PEMBARUAN STOK BARANG PADA TOKO PAKAIAN MENGGUNAKAN TEKNOLOGI RFID Elysia Levina; Resmana Lim; Petrus Santoso
Jurnal Teknik Elektro Vol. 16 No. 2 (2023): September 2023
Publisher : Institute of Research and Community Outreach

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jte.16.2.30-33

Abstract

Pendataan barang pada toko ritel penting untuk mengetahui status ketersediaan barang, dengan adanya pendataan stok barang, maka pencarian barang akan lebih mudah. Pencatatan keluar juga perlu dilakukan dengan cepat agar tidak mengganggu kegiatan jual beli, sehingga sistem diharapkan dapat mengelola stok barang yang dapat diakses dengan mudah dan dapat dilakukan dengan cepat. Website berfungsi sebagai interface untuk menampilkan data yang ada pada database. USB RFID reader digunakan sebagai alat untuk membaca RFID. Pembuatan website menggunakan node js sebagai framework backend dan vue js sebagai framework frontend. Akses website dibedakan menjadi dua jenis berdasarkan fiturnya, yaitu storage, untuk mencatat barang masuk dan store, untuk mencatat barang keluar. Pengujian dilakukan dengan menguji keberhasilan komunikasi Node js dengan MySQL menggunakan aplikasi Postman, dan menguji keberhasilan komunikasi website dengan database. Dari hasil pengujian tersebut, RFID dapat dibaca oleh USB RFID reader, lalu data barang dapat dibaca, ditulis, diedit dan dihapus melalui web
PERANCANGAN AIR MANCUR OTOMATIS SESUAI TEMPO MUSIK DI URBAN FARMING ALAM SARI PETRA Ezechiel Clifford; Resmana Lim; Handry Khoswanto
Jurnal Teknik Elektro Vol. 16 No. 2 (2023): September 2023
Publisher : Institute of Research and Community Outreach

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jte.16.2.55-61

Abstract

Alam Sari Petra merupakan sarana Urban Farming PPPK (Perhimpunan Pendidikan dan Pengajaran Kristen Petra) Petra yang memiliki tujuan untuk membangun kesadaran para siswa terhadap wawasan lingkungan. Untuk menambah keelokan dari Urban Farming Alam Sari Petra, maka dirancangnya air mancur menari yang dapat menari sesuai tempo musik. Air mancur menari dirancang untuk dapat dikontrol ketinggian pancuran dan bergerak ke kanan kiri sesuai dengan keras suara dan frekuensinya. Hardware yang digunakan adalah Arduino Uno dengan memanfaatkan library ArduinoFFT untuk menentukan ketinggian pancuran dan fungsi AnalogRead untuk menentukan ketinggian pancuran dan gerakan aktuator. Alat diprogram menggunakan software Arduino IDE dengan memanfaatkan pulse timer menggunakan delay dan millis untuk mengatur tinggi pancuran dan gerakan aktuator ke kanan dan kiri. Hasil dari perancangan ini adalah air mancur dapat menari sesuai keras suara dan frekuensi suara yang didapat dari sumber audio berupa Handphone ataupun Laptop. Pengujian dilakukan dengan menghitung berapa waktu yang dibutuhkan untuk membuka valve atau menggerakkan aktuator untuk mencapai suatu ketinggian pancuran dan kemiringan aktuator yang diinginkan. Berdasarkan pengujian pada kolam kanan dan kiri, didapati gerakan aktuator membutuhkan 7 detik untuk mencapai kemiringan maksimum yaitu dengan sudut dalam 65° sedangkan 3 Way Valve perlu 16 detik untuk mencapai ketinggian maksimum yaitu 155 cm.
Indoor positioning system using BLE beacon to improve knowledge about museum visitors Andreas Handojo; Tanti Octavia; Resmana Lim; Jonathan Kurnia Anggita
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14886

Abstract

Generally, a museum has many locations and artifacts collection that display for visitors. Museum manager often have difficulty in obtaining information on visitors behavior such as, is there are particular locations/artifacts in the museum that are frequently/rarely visit by museum visitors, how long visitors spend their time in particular locations/artifacts, etc. The purpose of this study is try to build a suitable system in order to improve knowledge about the behavior of museum visitors by identifying the position of visitors in the museum. This study uses Bluetooth Low Energy (BLE) Beacon that place around the museum. The visitor mobile phone will detect BLE beacon signal, then the mobile phone application will calculated the visitor’s mobile phone position using the signal strength from the BLE beacons that are detected. The application then sends it to the computer server to display it in as museum visitor heat map. From this information, the museum manager could find out the visitors behavior movement and know which areas/artifacts that frequently/rarely visit by museum visitors. According to distance error testing which compare real location and position of the calculation, it is show that the average of distance error is around 140 cm. So, it can be concluded that the information obtained is sufficient enough to represent the position of museum visitors.
Evaluation of hybrid parallelism for scalable training of DenseNet-121 in diabetic retinopathy classification Indar Sugiarto; Djoni Haryadi Setiabudi; Darrell Cornelius Rivaldo; Taweesak Kijkanjanarat; Resmana Lim
Indonesian Journal of Electrical Engineering and Computer Science Vol 43, No 2: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v43.i2.pp662-671

Abstract

Training large and complex deep learning models is often constrained by GPU memory limitations and prolonged training times. While several parallelism strategies have been proposed, this study specifically evaluates hybrid parallelism—a combination of data parallelism and pipeline parallelism—to address both challenges simultaneously. Using a case study on diabetic retinopathy (DR) classification with the DenseNet-121 architecture, we analyze the trade-off between computational efficiency and memory scalability. Results show that although hybrid parallelism does not yet provide speedup compared to a single-GPU setup—due to communication overhead and pipeline fragmentation—it enables training of large models that exceed the memory capacity of a single GPU. The trained model achieved a validation accuracy of 0.737, a quadratic weighted kappa (QWK) of 0.861, and a weighted F1-score of 0.749. In contrast, pure data parallelism showed a potential speedup of up to 1.9× in scenarios where the model still fits within a single GPU. These findings highlight the critical role of hybrid parallelism in overcoming the memory wall in large-scale model training, though optimization to reduce overhead remains a key challenge.
Co-Authors Andreas Handojo Brian Sahuleka Briantono Pryana Darrell Cornelius Rivaldo Djoni Haryadi Setiabudi Elysia Levina Endang Setyati Evan Alfredo Gozali Ezechiel Clifford Geraldi Merkusi Limanta Gregorio Diovani Wahanie Handry Khoswanto Indar Sugiarto Jonathan Kurnia Anggita Petrus Santoso Rafael Bogdan Raymond Sutjiadi Ribut Basuki Samuel Stephanus Chandra Sienny Thio Tanti Octavia Taweesak Kijkanjanarat WONOSEPUTRO Christine