2 research outputs found
PERAN PENYELENGGARAAN PEMELIHARAAN RUTIN JALAN PROVINSI JAWA TENGAH TERHADAP PENURUNAN ANGKA KEMISKINAN DAN PEMANFAATAN TEKNOLOGI GAWAI ANDROID
No full textAbstract In managing the roads, the Bina Marga and Cipta Karya Public Works Office in Central Java Province organizes the Bina Marga Community Group, which consists of poor and healthy people, which are located around provincial roads. Public expectations of road conditions are often conveyed through social media and mass media. Road handling is then accommodated through the use of easy-to-use technology, the Aplikasi Jalan Cantik, which is operated with an Android Device. This study uses descriptive method, describing the object under study through the collected data, performing a simple analysis, and making general conclusions. The analysis showed that, as of August 2019, 577 reports of public complaints that entered the Aplikasi Jalan Cantik, had been responded quickly within 1 x 24 hours. The condition of the Provincial Roads in Central Java was maintained well, and gradually exceeded the performance target of the 2019 Regional Work Plan, which was 90.20%. There is 1,018 Bina Marga community group member spread over 9 Road Management Centers, which means that the Bina Marga and Cipta Karya Public Works Office in Central Java Province participated in reducing poverty by 0.109% of the Central Java population\u27s poverty rate. Keywords: road routine maintenance, provincial roads, Aplikasi Jalan Cantik, poverty rates Abstrak Dalam penyelenggaraan jalan, Dinas Pekerjaan Umum Bina Marga dan Cipta Karya Provinsi Jawa Tengah menggandeng Kelompok Masyarakat Bina Marga, yang terdiri atas masyarakat miskin dan sehat, yang berada di sekitar jalan provinsi. Ekspektasi masyarakat terhadap kondisi jalan sering kali disampaikan melalui media sosial dan media massa. Penanganan jalan kemudian diakomodasikan melalui pemanfaatan teknologi yang mudah digunakan, yaitu Aplikasi Jalan Cantik, yang dioperasikan dengan Gawai Android. Penelitian ini menggunakan metode deskriptif, yaitu mendeskripsikan objek yang diteliti melalui data yang telah terkumpul, melakukan analisis sederhana, dan membuat kesimpulan yang berlaku untuk umum. Hasil analisis menunjukkan bahwa, sampai dengan Agustus 2019, laporan aduan masyarakat yang masuk ke Aplikasi Jalan Cantik sebanyak 577 telah direspons cepat dalam waktu 1 x 24 jam. Kondisi Jalan Provinsi di Jawa Tengah dipertahankan baik, dan berangsur-angsur melebihi target kinerja Rencana Kerja Perangkat Daerah 2019, yaitu sebesar 90,20%. Tercatat 1.018 orang Masyarakat Bina Marga yang tersebar di 9 Balai Pengelolaan Jalan, yang berarti Dinas Pekerjaan Umum Bina Marga dan Cipta Karya Provinsi Jawa Tengah ikut serta dalam penurunan angka kemiskinan sebesar 0,109% terhadap angka kemiskinan penduduk Jawa Tengah. Kata-kata kunci: pemeliharaan rutin jalan, jalan provinsi, Aplikasi Jalan Cantik, angka kemiskina
Plasmodium Parasite Detection Using Combination of Image Processing and Deep Learning Approach
No full textThe development of an intelligent system for automated malaria detection became the one of challenges since its application supported the examination process which was conducted manually by the doctor or medical personnel. Some previous studies have been done to overcome those problems. However, most of them still have problem in detecting parasite candidates. Hence, their proposed methods did not successfully detect all parasite candidates and remains a large number of false-negative. Actually, the misdetection problem occurred since the characteristic of parasites seems unclear. To overcome these problems, we applied image processing technique and deep learning architecture to detect and to ensure whether the detected candidate is a parasite or not. Our proposed method was applied to 46 digital microscopic images provided by the Department of Parasitology, Universitas Gadjah Mada and Eijkman Institute for Molecular Biology. The proposed method comprised of four steps which are normalization process using GGB (green, green, blue) color transformation, segmentation process using Otsu followed by some morphological operations, object labelling using BLOB analysis, and classification using deep learning. Our detection process successfully detected all parasites and the classification process achieved an accuracy, sensitivity, specificity, PPV and NPV of 98.97, 100, 98.08, 97.85, and 100 respectively. This result shows that our proposed method achieved outstanding performance in both detection and classification process which indicates that our proposed method had the potential to be implemented as an intelligent system for supporting the parasitologist in conducting rapid assessment of plasmodium parasite infection. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd
