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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Rekayasa Sipil Building of Informatics, Technology and Science
Rossi, Farli
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Engineering Transportation

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Penerapan Convolutional Neural Network (CNN) pada Pengenalan Aksara Lampung Berbasis Optical Character Recognition (OCR) Mulyanto, Agus; Susanti, Erlina; Rossi, Farli; Wajiran, Wajiran; Borman, Rohmat Indra
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 7, No 1 (2021): Volume 7 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v7i1.44133

Abstract

Provinsi Lampung memiliki bahasa dan aksara daerah yang disebut juga dengan Had Lampung atau KaGaNga yang merupakan aksara asli lampung. Melihat bagaimana pentingnya nilai akan eksistensi sebuah budaya dan pentingnya pelestarian aksara lampung maka dibutuhkan teknologi yang membantu dalam mengenalkan aksara lampung, salah satunya dengan teknologi optical character recognition (OCR) yang digunakan untuk merubah citra kedalam teks. Untuk mengenali pola citra Aksara Lampung dan klasifikasi model maka digunakan Convolutional Neural Network (CNN). CNN memiliki lapisan convolution yang terbentuk dari beberapa gabungan lapisan konvolusi, lapisan pooling dan lapisan fully connected. Pada peneilitian yang dilakukan dataset dikembangkan dengan pengumpulan hasil tulis tangan dari sampel responden yang telah ditentukan, kemudian dilakukan scanning gambar. Selanjutnya, dilakukan proses pelabelan dan disimpan dengan format YOLO yaitu TXT. Dari asitektur CNN yang dibangun berdasarkan hasil evaluasi menunjukan loss, accuracy menghasilkan nilai training accuracy mendapatkan nilai sebesar 0.57 dan precision mendapatkan nilai sebesar 0.87. Dari hasil nilai accuracy dan precision menunjukkan bahwa model training sudah baik karena mendekati angka 1.
Classification of Character Types of Wayang Kulit Using Extreme Learning Machine Algorithm Fatmayati, Fryda; Nugraheni, Murien; Nuraini, Rini; Rossi, Farli
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3568

Abstract

Wayang Kulit, which is an original Indonesian culture, is conditioned by the meaning of life in every performance. However, Wayang Kulit is currently less popular among young people due to a lack of understanding of the art of Wayang Kulit performance. To be able to provide knowledge to the younger generation about Wayang Kulit, one of which is by introducing the characters that exist in Wayang Kulit performances. This study aims to build an image classification system for Wayang Kulit characters by applying the neural network method using Extreme Learning Machine (ELM) and morphological feature extraction. Morphological feature extraction provides information about the shape characteristics of objects present in the image which are then used for input in the classification process. The Extreme Learning Machine (ELM) method may arbitrarily establish the weight value between the input neurons and the hidden layer during the classification step, resulting in a quicker learning pattern. Based on the test results using the confusion matrix, the accuracy value is calculated to get a value of 81%.
Trend Of Water Quality Status In Kelantan River Downstream, Peninsular Malaysia Fitri, Arniza; Abdul Maulud, Khairul Nizam; Pratiwi, Dian; Phelia, Arlina; Rossi, Farli; Zuhairi, Nur Zukrina
Jurnal Rekayasa Sipil (JRS-Unand) Vol. 16 No. 3 (2020)
Publisher : Civil Engineering Departement, Andalas University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jrs.16.3.178-184.2020

Abstract

The issues of freshwater pollutions and the high demand of clean freshwater for daily human activities have forced developing countries such as Malaysia to continuously monitor the quality of the freshwater. The present study objective is to present the trend of water quality status in the Kelantan River downstream, Peninsular Malaysia from 2005 to 2018. Water samples were collected during dry and monsoon seasons from a sampling station located at downstream of the Kelantan River. Water quality parameters such as temperature, pH and dissolved oxygen (DO) were measured in situ while other parameters were analysed in the laboratory based on retrieved water samples. Water quality status was determined based on National Water Quality Standard (NWQS) for River in Malaysia by calculating the water quality index (WQI) according to the concentration of six water quality parameters involving pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (TSS) and Ammonia Nitrogen (AN). The results showed that Kelantan River had good water quality during the dry season classified in Class II at 2005. The water quality was found to be slightly lower during the monsoon season in year 2006. In addition, increasing the number of construction, human activities in the land use areas, land use changes and the sewage water from domestic, industrial, wet market and food outlets in the Kelantan State have declined the water quality in Kelantan River from Class II (in 2005) to Class III (in 2010 and 2011) and to become Class IV in 2017 to 2018. The results of the present study are expected to give valuable information for the water managers in order to deal with better strategies in controlling the quality of freshwater at the Kelantan River and minimize the incidence of pollution-oriented problems, thus the water can be utilized for various water uses with appropriate quality.
Co-Authors Abdul Maulud, Khairul Nizam Agus Mulyanto Dian Pratiwi Erlina Susanti Fitri, Arniza Fryda Fatmayati Heni Pujiastuti Murien Nugraheni Phelia, Arlina Rini Nuraini, Rini Rohmat Indra Borman Zuhairi, Nur Zukrina