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All Journal Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer AGRIVITA, Journal of Agricultural Science Jurnal Teknologi dan Sistem Komputer Journal of Information Technology and Computer Science Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Electrical Engineering and Computer Science
Ahmad Afif Supianto
University of Brawijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Spectral Characteristics of High-Yielding Varieties of Rice Plants Using Landsat 8 Data Dewi, Candra; Supianto, Ahmad Afif; Sutrisno, Sutrisno
AGRIVITA, Journal of Agricultural Science Vol 35, No 3 (2013)
Publisher : Faculty of Agriculture University of Brawijaya and Indonesian Agronomic Assossiation

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In applying remote sensing technology for inventory, evaluation and estimation of rice crop production, required the data of spectral characteristics changing of the plants during its growth phase. By identifying spectral characteristics, it will be recognized the objects in the images. This study identifies the spectral characteristics of high-yielding varieties of rice plants during their growth in Malang regency. Based on the results of field survey, the high yielding varieties that are commonly planted consist of IR64, Ciherang and Membramo. Then, from the identification of vegetation index is known that all these three varieties have different growth patterns, where the most distinct pattern found in IR64.
Implementasi Teknik Watershed Dan Morfologi Pada Citra Satelit Untuk Segmentasi Area Universitas Brawijaya ., Sutrisno; Supianto, Ahmad Afif; Cholissodin, Imam
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 1, No 1 (2014)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2057.225 KB)

Abstract

AbstrakPenelitian di bidang segmentasi citra telah banyak dilakukan, terutama di bidang citra satelit. Proses segmentasi ini dilakukan untuk melakukan deteksi terhadap objek-objek yang terdapat di dalam citra. Pada penelitian ini, diimplementasikan sebuah metode segmentasi citra dengan menggunakan teknik watershed dan morfologi. Pertama, citra diubah ke dalam format citra grayscale.Kemudian, citra grayscale tersebut diolah dengan metode watershed untuk mendapatkan segmentasi awal. Selanjutnya, citra segmentasi tersebut diperbaiki menggunakan metode morfologi untuk mengurangi segmentasi berlebih yang dihasilkan oleh proses sebelumnya. Uji coba dilakukan terhadap 5dataset citra satelitarea Universitas Brawijaya dengan tingkat skala yang berbeda-beda. Skala yang digunakan dalam penelitian ini meliputi 20m, 50m, 100m, 200m, dan 500m. Uji coba menunjukkan bahwa metode yang diusulkan berhasil melakukan segmentasi citra dengan skala kurang dari 100 meter.Semakin rendah nilai skala yang digunakan sebagai uji coba, segmentasi yang dihasilkan semakin baik.Kata kunci: Watershed, Morfologi Citra, Citra SatelitAbstractResearch in the field of image segmentation has been widely applied , especially in the field of satellite imagery. The segmentation process is performed to detect the objects present in the image. In this study, implemented a method of image segmentation using watershed and morphological techniques. First, the image is converted into grayscale format. Then the grayscale image is processed by the watershed method to get initial segmentation. Furthermore, the improved image segmentation using morphological methods to reduce the excessive segmentation generated by the previous process. Tests performed on 5 satellite imagery dataset UB area with levels varying scales. The scale used in this study include the 20 meters , 50 meters, 100 meters, 200 meters, and 500 meters. The trials showed that the proposed method successfully to segment the image with the scale of less than 100 meters . The lower the scale value is used as a test , the better the resulting segmentation .Keywords: Watershed, Morphological Image, Satellite Imagery
SPECTRAL CHARACTERISTICS OF HIGH-YIELDING VARIETIES OF RICE PLANTS USING LANDSAT 8 DATA Dewi, Candra; Supianto, Ahmad Afif; Sutrisno, Sutrisno
AGRIVITA, Journal of Agricultural Science Vol 35, No 3 (2013)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v35i3.340

Abstract

In applying remote sensing technology for inventory, evaluation and estimation of rice crop production, required the data of spectral characteristics changing of the plants during its growth phase. By identifying spectral characteristics, it will be recognized the objects in the images. This study identifies the spectral characteristics of high-yielding varieties of rice plants during their growth in Malang regency. Based on the results of field survey, the high yielding varieties that are commonly planted consist of IR64, Ciherang and Membramo. Then, from the identification of vegetation index is known that all these three varieties have different growth patterns, where the most distinct pattern found in IR64.
Educational Media Design for Learning Basic Programming in Branching Control Structure Material Using Problem-Posing Learning Model Syahidi, Aulia Akhrian; Tolle, Herman; Supianto, Ahmad Afif; Hirashima, Tsukasa
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 4, November 2019
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (63.172 KB) | DOI: 10.22219/kinetik.v4i4.803

Abstract

Basic programming is one subject that tends to be difficult for students to learn. Along with the development of technology, several researchers have provided solutions to solve this problem, by developing educational games, educational media, interactive learning media, and other auxiliary media. However, on average they have not used or adhered to the syntax of various existing learning models. This study focuses on designing educational media that uses the problem-posing learning model to study the material of branching control structures in basic programming learning which is recommended as a learning medium for vocational high school students. Educational media named TOLSYASUPI-EduMed. We use the highest type of research and development (R&D), the level 4 that we adopted to be adapted into a number of steps that are in line with the needs of this research area. Observation techniques are used as a form of generative research which is a type of user experience research, to explore information before designing a product/application. The side that we highlight here is how the form of educational media design by following the syntax of the problem-posing learning model. Then do an A/B testing which is assessed by experts to choose the best design with results that are type B designs with a percentage of 90.9%. We also state the analysis of the functional aspects of educational media to strengthen the validity of this design idea.
Design and Implementation of Earth Image Classification Using Unmanned Aerial Vehicle Barlian Henryranu Prasetio; Ahmad Afif Supianto; Gembong Edhi Setiawan; Budi Darma Setiawan; Imam Cholissodin; Sabriansyah Rizkiqa Akbar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1786

Abstract

Research in the field of image classification has been widely applied and developed, especially in the field of satellite imagery. Image classification is the process of grouping the pixels in an image into a number of classes, so that each class can describe an entity with certain characteristics. The research aims to build software that can perform the classification of earth image results from UAV (Unmanned Aerial Vehicle) monitoring. The Image converted into YUV format then classified using Fuzzy Support Vector Machine (FSVM). This research designed elements that UAVs will be used for monitoring as follows: (1) the control station, which designed the software on a computer that is used to send or receive data, and display the data in graphical form, (2) payload, using the camera to capture images and send to the control station, (3) communication system using TCP/IP protocol, and (4) UAV, using X650 quadcopter products from xaircraft. All of data can be received if it is sent by several segmented package into smaller parts. The results of image classification, the image of the monitoring carried out on the UAV sized 256 x 256 pixels with a total number of 450 training data size. It is 16x16 pixel image data. Tests performed to classify the image into 3 classes, namely agricultural area, residential area, and water area. The highest accuracy value of 77.69% obtained by the number of training data as much as 375.
Prediksi Siswa Putus Sekolah Swasta Menggunakan Algoritma Bayesian Network (Studi Pada : SMA Islam Al Wahid Kepung) Krisnabayu, Rifky Yunus; Supianto, Ahmad Afif; Wicaksono, Satrio Agung
Jurnal Teknologi dan Sistem Komputer Volume 10, Issue 2, Year 2022 (April 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14121

Abstract

Masalah siswa putus sekolah di SMA Islam Al Wahidmembawa dampak kepada sekolah antara lain berkurangnya bantuan operasional yang diterima, berkurangnya jumlah rombongan belajar, dan hutang biaya siswa. Mempertimbangkan dampaknya bagi sekolah, penelitian ini bertujuan mengembangkan sistem prediksi dini siswa putus sekolah. Penelitian menggunakan Bayesian Network (BN) dengan tujuan mengetahui faktor yang paling berpengaruh, di mana tugas tersebut tidak dapat diselesaikan menggunakan naive bayes. Jumlah data yang digunakan dalam penelitian ini berjumlah 77 siswa dengan 18 siswa berlabel putus sekolah. Hasil dari penelitian ini menghasilakn sebuah model dengan akurasi bernilai 0,935 dan nilai area under curve sebesar 0,948. Struktur BN memperlihatkan bahwa faktor nilai rerata, mengikuti ekstrakurikuler, dan penghasilan ayah merupakan faktor yang paling berpengaruh terhadap siswa putus sekolah. Struktur BN memperlihatkan bahwa faktor nilai rerata, mengikuti ekstrakurikuler, dan penghasilan ayah merupakan faktor yang paling berpengaruh terhadap siswa putus sekolah.
Automatic detection of crop diseases using gamma transformation for feature learning with a deep convolutional autoencoder Zilvan, Vicky; Ramdan, Ade; Supianto, Ahmad Afif; Heryana, Ana; Arisal, Andria; Yuliani, Asri Rizki; Krisnandi, Dikdik; Suryawati, Endang; Suryo Kusumo, Raden Budiarianto; Yuawana, Raden Sandra; Kadar, Jimmy Abdel; Pardede, Hilman F.
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 10, Issue 3, Year 2022 (July 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14250

Abstract

Precision agriculture is a management strategy for sustaining and increasing the production of agricultural commodities. One of its implementations is for crop disease detection. Currently, deep learning methods have become widespread methods for the automatic detection of crop diseases. Most deep learning methods showed better performance when using an original image in raw form as inputs. However, the original image of crop diseases may appear similar between one disease to another.  Therefore, the deep learning methods may misclassify the data. To deal with these, we propose the gamma transformation with a deep convolutional autoencoder to extract good features from the original image data. We use the output of the gamma transformation with a deep convolutional autoencoder as inputs to a classifier for the automatic detection of crop diseases. Our experiments show that the average accuracies of our method improve the performance of crop disease detection compared to only using raw data as inputs.
Distracted driver behavior recognition using modified capsule networks Kadar, Jimmy Abdel; Dewi, Margareta Aprilia Kusuma; Suryawati, Endang; Heryana, Ana; Zilfan, Vicky; Kusumo, Budiarianto Suryo; Yuwana, Raden Sandra; Supianto, Ahmad Afif; Pratiwi, Hasih; Pardede, Hilman Ferdinandus
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.177-185

Abstract

Human activity recognition (HAR) is an increasingly active study field within the computer vision community. In HAR, driver behavior can be detected to ensure safe travel. Detect driver behaviors using a capsule network with leave-one-subject-out validation. The study was done using CapsNet with leave-one-subject-out validation to identify driving habits. The proposed method in this study consists of two parts, namely encoder and decoder. The encoder used in this study modifies Sabour’s capsule network architecture by adding a convolution layer before going to the primary capsule layer. The proposed method is evaluated using a primary dataset with 10 classes and 300 images for each class. The dataset is split based on hold-out validation and leave-one-subject-out validation. The resulting models were then compared to conventional CNN architecture. The objective of the research is to identify driving behavior. In this study, the proposed method results an accuracy rate of 97.83 % in the split dataset using hold-out validation. However, the accuracy decreased by 53.11 % when the proposed method was used on a split dataset using leave-one-subject-out validation. This is because the proposed method extracts all features including the attributes of each participant contained in the input image (user-independent). Thus, the resulting model in this study tends to overfit.
Educational Media Development using Guided Discovery Learning Approach in Chemical Element Subject Renavitasari, Ivenulut Rizki Diaz; Tolle, Herman; Bachtiar, Fitra A.; Supianto, Ahmad Afif
Journal of Information Technology and Computer Science Vol. 8 No. 2: August 2023
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202382448

Abstract

A chemical element is one of the materials in high school for chemistry subject. Students have difficulties in studying chemical elements due to ample theories that must be memorized. In addition, conventional learning models that tend to be one-way create boredom feeling towards students. The use of interactive educational media can be a solution to the learning process. This study tries to provide a solution by developing mobile-based educational media combined with guided discovery learning models to help the learning process of chemical elements in high school. The use of appropriate educational media can be used as an independent learning tool. This study uses Research & Development (R&D) combined with SAM Model to develop this educational media. Testing is using an expert validation approach for the prototype of educational media. This study adapted the Computer System Usability Questionnaire (CSUQ) to assess an aspect of the usability of educational media. To assess the content of the material in this educational media, this study uses an evaluation questionnaire from the subject matter and media experts. The development process is carried out in three iterations, namely the preparation stage, iterative stage, and iterative development stage. The results of this study show that the assessment of chemical elements in educational media has a score of 86.8% on its system usability according to media experts and a score of 90.5% on educational media content according to material experts. So, this educational media is feasible to be applied to high school students. Overall, this educational media got a good score on the pretest-posttest, where the effectiveness of using this educational media increased student learning outcomes with an N-Gain value of 80.62%.
A conceptual approach of optimization in federated learning Mar’i, Farhanna; Supianto, Ahmad Afif
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp288-299

Abstract

Federated learning (FL) is an emerging approach to distributed learning from decentralized data, designed with privacy concerns in mind. FL has been successfully applied in several fields, such as the internet of things (IoT), human activity recognition (HAR), and natural language processing (NLP), showing remarkable results. However, the development of FL in real-world applications still faces several challenges. Recent optimizations of FL have been made to address these issues and enhance the FL settings. In this paper, we categorize the optimization of FL into five main challenges: Communication Efficiency, Heterogeneity, Privacy and Security, Scalability, and Convergence Rate. We provide an overview of various optimization frameworks for FL proposed in previous research, illustrated with concrete examples and applications based on these five optimization goals. Additionally, we propose two optional integrated conceptual frameworks (CFs) for optimizing FL by combining several optimization methods to achieve the best implementation of FL that addresses the five challenges.
Co-Authors Ade Ramdan Admaja Dwi Herlambang, Admaja Dwi Andria Arisal, Andria Azpiranda, Novira Bahtiar, Fitra Abdurrahman Barlian Henryranu Prasetio Bawono, Aditya Hari Budi Darma Setiawan Candra Dewi Candra Dewi Dewi, Margareta Aprilia Kusuma Febriandirza, Arafat Fitra Abdurrachman Bachtiar Gembong Edhi Setiawan Gultom, Dito William Hamonangan Hafis, Muhammad Hayashi, Yusuke Herman Tolle Heryana, Ana Hirashima, Tsukasa Imam Cholissodin Imam Cholissodin Kadar, Jimmy Abdel Krisnabayu, Rifky Yunus Krisnandi, Dikdik Kusumo, Budiarianto Suryo Kusumo, R. Budiarianto Suryo Mar'i, Farhanna Mochamad Anshori MUHAMMAD HASBI Nanang Yudi Setiawan Pardede, Hilman F. Pardede, Hilman Ferdinandus pratiwi, hasih Renavitasari, Ivenulut Rizki Diaz Sabriansyah Rizkiqa Akbar Satrio Agung Wicaksono Selvi Marcellia Suryawati, Endang Suryo Kusumo, Raden Budiarianto Sutrisno . Sutrisno Sutrisno Syahidi, Aulia Akhrian Vicky Zilvan, Vicky Wahyu Tejakusuma, Wahyu Wayan Firdaus Mahmudy Yuawana, Raden Sandra Yuliani, Asri Rizki Yuwana, R. Sandra Yuwana, Raden Sandra Zilfan, Vicky