Mudjirahardjo, Panca
Jurusan Teknik Elektro Fakultas Teknik Universitas Brawijaya

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Journal : Jurnal INFOTEL

Sistem Layanan Informasi dan Pemesanan Nomor Antrian Menggunakan Media SMS Berbasis Komunikasi Serial Asinkron Multipoint Standar RS-485 Danny Kurnianto; Panca Mudjirahardjo; M. Julius St Julius St
JURNAL INFOTEL Vol 6 No 2 (2014): November 2014
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v6i2.19

Abstract

Sistem layanan informasi dan pemesanan nomor antrian terpusat melalui media handphone dapat dijadikan sebagai  salah satu solusi untuk mempermudah masyarakat dalam melakukan antrian sehingga aktivitas mereka bisa berjalan dengan baik dan waktu mereka tidak terbuang terlalu lama. Dengan menggunakan sistem ini, nasabah dapat dengan mudah melihat kondisi antrian saat ini dan memesan nomor antrian, yaitu dengan mengirimkan SMS berupa kata “daftar” untuk memesan nomor antrian dan kata “info” untuk mengetahui kondisi antrian ke handphone server. Personal komputer digunakan sebagai pusat pengendalian yang berfungsi untuk mengirim dan menerima data dari hanphone dan dari mikrokontroler pada unit slave. Komunikasi data antara komputer sentral dengan mikrokontroler berjalan dengan menggunakan komunikasi serial asinkron multipoint dengan baudrate 57600 bps. Komunikasi serial antara komputer sentral dengan handphone berjalan dengan baudrate 19200 bps. Dari hasil pengujian menunjukkan bahwa sistem layanan informasi dan pemesanan nomor antrian dapat bekerja dengan baik. Informasi yang diberikan saat nasabah mendaftar nomor antrian melalui handphone berupa nomor antrian dan password. Informasi yang diberikan komputer sentral saat nasabah meminta informasi kondisi antrian berupa berupa jumlah nasabah yang terdaftar pada sistem antrian saat ini, nomor antrian yang sedang dilayani pada masing-masing loket, waktu tutup antrian.
Designing an Optimization of Orientation System toward Moving Object in 3-Dimensional Space Using Genetic Algorithm Feishal Reza; Panca Mudjirahardjo; Erni Yudaningtyas
JURNAL INFOTEL Vol 10 No 4 (2018): November 2018
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v10i4.408

Abstract

This research offers a scheme of orientation system toward moving object in 3-dimensional space that using Stereo Vision Camera. The system benefits in giving an alternative solution in projecting practically without manual identification by conventional measuring device. The result of the projection in the system is in the form of coordinate position information (x, y, z), the length, the width, and the height of the object detected. The output displayed in the real-time digital image with 3-dimensional modeling. In the process of the object identification, there was a stage when an image was converted from colored image to binary image. But the conversion used the threshold method which was considered less efficient when an object moved. As consequence, the new adaptive method in solving the problem was needed. Genetic Algorithm was proposed as the optimization method because it was considered suitable with the emerging problems. In the optimization process, genetic algorithm was in a task of searching process and determining the threshold value as the process of creating binary image. The result shows an increased accuracy in the identification process after the system had been optimized by the Genetic Algorithm (GA).
Breast Cancer Detection using Residual Convolutional Neural Network and Weighted Loss Samuel Aji Sena; Panca Mudjirahardjo; Sholeh Hadi Pramono
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.430

Abstract

This research presents a breast cancer detection system using deep learning method. Breast cancer detection in a large slide of biopsy image is a hard task because it needs manual observation by a pathologist to find the malignant region. The deep learning model used in this research is made up of multiple layers of the residual convolutional neural network, and instead of using another type of classifier, a multilayer neural network was used as the classifier and stacked together and trained using end-to-end training approach. The system is trained using invasive ductal carcinoma dataset from the Hospital of the University of Pennsylvania and The Cancer Institute of New Jersey. From this dataset, 80% and 20% were randomly sampled and used as training and testing data respectively. Training a neural network on an imbalanced dataset is quite challenging. Weighted loss function was used as the objective function to tackle this problem. We achieve 78.26% and 78.03% for Recall and F1-Score metrics, respectively which are an improvement compared to the previous approach.
Co-Authors Abdul Goffar Ricky Mahendra Achmad Basuki Adharul Muttaqin Ahmad Syafiq Kanzul Fikri Aiman Muhamad Basymeleh Airlangga, Daniar Putri Aldy, Farouq Akbar Alkafi Dimitri Sukmana Andy Kurnia Santoso Angger Abdul Razak Anthony Wijoyo Arafah, Ghifari Raihan Bagus Esa Pramudya Bidin Yuniar Hamzah Bima Feridhan Nugraha Bimasena, Muhammad Farrel Brahmana, Nigel Shidqy Razendriya Chandra Halim Harahap Dachlan, Hary Soekotjo Danny Kurnianto Doni Juli Wiranata Eka Maulana Erni Yudaningtyas Esa Ilham Akbar Faradisa , Annisa' Illah Farihah Hedar Fatchur Rozi Al Fitrah Fauzi, Maher Feishal Reza Firmansyah, Vicky FX. Arinto Setyawan Gilang Luih Pinandita Haidar Taqy Hartono, Rafendra Ariwardana Hary Soekotjo Dachlan Hasdi Sasandi Ismail Musirin Ismail Musirin Ita Dwi Purnamasari Izanati, Nazuha Juan Mora Michael Marbun Juli Arianes Leonard Dimas Prakoso Lilik J. Awalin Lukman Gumelar M Fauzan Edy Purnomo M. Hanif Azhary M. Julius St Julius St M. Julius St Julius St, M. Julius St Machfud Firmansyah Manerep Luis Fernando Purba Marco Gunawan Maulana, Eka Maulana, Eka Miladina Rizka Aziza Mohammad Alif Robby Gani Mohammad Ilhammudin Toiyib Monifa Arini Muhammad Akbar Muhammad Aziz Muslim Muhammad Ikhsan Muhammad Ivan Fadillah Muhammad Rafi’ Zaidan Maajid n/a Soeprapto Nanang Sulistiyanto Nathanael, Indra Notario Pramudita Nugraha, Dimas Aji Nurus Sa'adah Octarudin Mahendra Oky Risky Dwi Santoso Pangemanan, Christofel Panjaitan, Gian Amadea Pebrianto, Wahyu Permatasari, Alissa Dyah Ayu Ponco Siwindarto Pratolo Rahardjo R. A. Setyawan Rachmawati, Luthfiyah Raden Arief Setyawan Rahmadwati Rahmadwati Rahmadwati, n/a Rahmadwati, n/a Rahmadwati, Rahmadwati Rauf, Daru Adiyatma Reinato Teguh Santoso Reza, Feishal Ricky Insyani Santosa P. P. Ridho Herasmara Rif'an, Mochammad Rifqa Asruroh Efnif Rini Nur Hasanah Riza Hasbi Ash Shiddieqy Rizky Aiman Haniffalah Harijanto Robbith Qosath Al Auhi Rohman, Muhammad Ariefur Samuel Aji Sena Sena, Samuel Aji Septi Uliyani Sholeh Hadi Pramono Sirojul Hadi Sofyan Andika Yusuf Sultoni Sultoni Sultoni, Sultoni Surya Agung Kurnia Suyono, Hadi Syarifah, Naily Tri Nurwati Vira Zafarin Waru Djuriatno Waru Djuriatno Wuri Roro Indraswari yuliana diah pristanti Zainuri, Akhmad