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All Journal International Journal of Electrical and Computer Engineering Jurnal Sistem Komputer Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Bulletin of Electrical Engineering and Informatics Telematika : Jurnal Informatika dan Teknologi Informasi Sinergi Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Register: Jurnal Ilmiah Teknologi Sistem Informasi JURNAL NASIONAL TEKNIK ELEKTRO Bulletin of Electrical Engineering and Informatics Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JIKO (Jurnal Informatika dan Komputer) Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Compiler MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) GERVASI: Jurnal Pengabdian kepada Masyarakat Systemic: Information System and Informatics Journal Journal of Information Systems and Informatics Buletin Ilmiah Sarjana Teknik Elektro International Journal of Engineering, Technology and Natural Sciences (IJETS) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advances in Data and Information Systems Journal of Innovation Information Technology and Application (JINITA) Science in Information Technology Letters Jurnal INFOTEL Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Saifullah, Shoffan

Universitas Pembangunan Nasional Veteran Yogyakarta

Author-ID : 607862

Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Chicken Egg Fertility Identification using FOS and BP-Neural Networks on Image Processing Shoffan Saifullah; Andiko Putro Suryotomo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

This article aims to test FOS (first-order statistical) in extracting features of embryonated eggs. This test uses the initial step of image processing to get the best input image in feature extraction. The image processing method starts from the image acquisition process, then improves with image preprocessing and segmentation. Image acquisition in this study uses the concept of egg candling in a dark place captured with a smartphone camera. The acquisition results are improved by image preprocessing using gray scaling, image enhancement (by Histogram Equalization), and segmentation of chicken egg image. The segmentation results were extracted using FOS with five parameters: mean, entropy, variance, skewness, and kurtosis. Based on the calculation of these parameters, it is graphed and shows the difference in patterns between fertile and infertile eggs. However, some eggs have a similar pattern, thus affecting the identification process. The identification process used neural networks by the backpropagation method for training and testing. The training results provide an accuracy value of 100% of all training data; however, 80% of the new test data obtained test results at testing. This test is carried out with 100 data, 50 each for training and test data. Based on the test results, which significantly affect the level of accuracy is the feature extraction method. FOS pattern in detecting the fertility of chicken eggs by BP Neural Network is still categorized as low, so it is necessary to improve methods to get maximum results.

Detection of Chicken Egg Embryos using BW Image Segmentation and Edge Detection Methods Shoffan Saifullah; Andiko Putro Suryotomo; Yuhefizar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

This study aims to identify chicken egg embryos with the concept of image processing. This concept uses input and output in images. Thus the identification process, which was originally carried out using manual observation, was developed by computerization. Digital images are applied in identification by various image preprocessing, image segmentation, and edge detection methods. Based on these three methods, image processing has three processes: image grayscaling (convert to a grayscale image), image adjustment, and image enhancement. Image adjustment aims to clarify the image based on color correction. Meanwhile, image enhancement improves image quality, using histogram equalization (HE) and Contrast Limited Adaptive Histogram Equalization methods (CLAHE). Specifically for the image enhancement method, the CLAHE-HE combination is used for the improvement process. At the end of the process, the method used is edge detection. In this method, there is a comparison of various edge detection operators such as Roberts, Prewitt, Sobel, and canny. The results of edge detection using these four methods have the SSIM value respectively 0.9403; 0.9392; 0.9394; 0.9402. These results indicate that the SSIM values of the four operators have the same or nearly the same value. Thus, the edge detection method can provide good edge detection results and be implemented because the SSIM value is close to 1.00 (more than 0.93). Image segmentation detected object (egg and embryo), and the continued process by edge detection showed clearly edge of egg and embryo.

Knowledge representation of drug using ontology alignment and mapping techniques Herlina Jayadianti; Alisya Amalia Putri Hasanah; Yuli Fauziah; Shoffan Saifullah
Science in Information Technology Letters Vol 2, No 1: May 2021
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v2i1.561

Drug searches are still based on drug names and brands, making it difficult for patients to come looking for a cure by saying that they feel sick. Likewise, when looking for drugs and information about their content to avoid overdose errors when changing drugs when drugs are supposed to be unavailable. Based on the issues raised, a study was conducted on applying semantic web ontology to search for drugs that can appear based on patients’ names, compositions, or complaints of diseases. Protégé 5.5 serves to represent drug information based on knowledge. The application uses Netbeans with Jena API as a library and creates data and drug information on the semantic web. Drug search also uses similar in-formation meaning based on user knowledge. By representing knowledge on the search for drug and disease information with semantic web ontology technology, it can meet the purpose of research, namely to improve drug and disease information search following the user’s wishes.

PELATIHAN E-LEARNING MENGGUNAKAN GOOGLE CLASSROOM BAGI GURU MA RADEN FATAH PRAMBANAN Shoffan Saifullah; Bagus Muhammad Akbar
GERVASI: Jurnal Pengabdian kepada Masyarakat Vol 4, No 1 (2020): GERVASI: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM IKIP PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/gervasi.v4i1.1680

Pendidikan adalah proses untuk meningkatkan kecerdasan siswa. Proses ini menggunakan kegiatan pelatihan dan pengajaran. Seiring dengan perkembangan teknologi dan komunikasi, proses pelatihan dan pembelajaran menggunakan berbagai metode, salah satunya adalah e-learning. Prosesnya menggunakan internet, yang dapat diakses dan diproses kapan saja dan di mana saja. Proses ini mendukung kebijakan Kementerian Pendidikan dan Kebudayaan Indonesia terkait proses pembelajaran dan mendeka belajar. Proses ini dapat meningkatkan pendidikan aktif, terencana, dan efektif. Selain itu, inovasi layanan dan pembelajaran meningkat sehingga tidak hanya menggunakan pembelajaran konvensional. Tujuan dari pengabdian masyarakat ini adalah untuk melatih para guru di MA Raden Fatah dalam mengimplementasikan e-learning menggunakan Google Classroom. Metode pelaksanaannya menggunakan teori dan praktik. Hasil dari proses pelatihan dapat memberikan inovasi pembelajaran online dengan Google Classroom, dan kemampuan guru untuk mengimplementasikannya dapat meningkatkan proses belajar mandiri. Para guru dapat melakukan pembelajaran dengan kelas virtual mengikuti kondisi pembelajaran di kelas. Kelas yang dibangun dengan Google Classroom dapat digunakan untuk berbagi materi, memberikan tugas, kuis, menetapkan nilai, dan menjadwalkan kegiatan. Selain itu, proses video conference menyesuaikan jadwal di classroom dan calendar dan kalender menggunakan meet.

The Development of Website on Management Information System for E-commerce and Services Ahmad Tri Hidayat; Andi Muhammad Dirham Dewantara; Shoffan Saifullah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 9, No 3 (2020): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v9i3.992

Currently, the sales system is overgrowing. The concept of selling that was done manually (which is still less than optimal) becomes electronic (e-commerce). System development requires a digital platform. This platform must be able to carry out all activities that were carried out before (manually), such as collecting documents, recording transactions, and reporting. Besides, the e-commerce platform can provide support and increased performance in the sales process, both in checking stock items, transaction reports, and services. Besides, this optimization can provide services precisely and quickly to consumers. A management information system concept is needed to carry out e-commerce and services with integrated data and be stored in its development database. This prototype concept requires a method for website development. The method used is a waterfall. Website design uses the Hypertext PreProcessor (PHP) programming language and MySQL database. The design model uses two concepts: entity-relationship diagrams (ERD) and data flow diagrams (DFD). The result is a website and e-commerce services that can be accepted by users and e-commerce organizers with tests that have been carried out. System testing uses Blackbox and Whitebox testing, each of which results can be used to implement e-commerce sites and services. The website can assist officers in service and e-commerce and make it easier for officers to determine the target and service status.

PERBANDINGAN SEGMENTASI PADA CITRA ASLI DAN CITRA KOMPRESI WAVELET UNTUK IDENTIFIKASI TELUR Shoffan Saifullah; Sunardi Sunardi; Anton Yudhana
ILKOM Jurnal Ilmiah Vol 8, No 3 (2016)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v8i3.75.190-196

Citra digital merupakan gambaran yang jelas dari objek yang dapat diolah dengan komputer. Semakin besar ukuran (pixel) citra akan membutuhkan tempat penyimpanan yang besar pula. Dasar pengolahan citra yang dilakukan dalam penelitian ini terletak pada proses segmentasi pengolahan citra. Hal yang perlu dipertimbangkan adalah objek dari citra telur ayam yang akan diidentifikasi. Proses pengolahan citra melibatkan beberapa proses mulai dari akuisisi citra, preprocessing dan proses pengolahan citra sampai hasilnya. Preprocessing dilakukan untuk proses segmentasi yaitu dengan mengubah citra menjadi citra grayscale, dan kemudian diubah menjadi citra hitam putih. Dalam setiap proses dilakukan padding haar untuk mengurangi ukuran (size on disk) dengan matrik haar 8x8. Dan juga dilakukan proses dilasi dan opening untuk membuat objek terlihat jelas serta menghaluskan permukaan untuk menghilangkan noise. Pada proses pengolahannya dilakukan dengan menggunakan segmentasi dan pelabelan dengan didahului dengan perhitungan centroid dan penentuan bounding box untuk mengidentifikasi telur ayam. Perbandingan hasil pengolahan citra asli dengan hasil kompresi dari citra asli menunjukkan bahwa proses segmentasi citra telur ayam memberikan hasil 100% sama (baik citra asli maupun citra kompresi wavelet). Dengan kompresi akan menghemat penyimpanan (disk) dan hasil yang sama diperoleh dalam proses perhitungan objek, luas area, dan penentuan titik centroid.

Identification of chicken egg fertility using SVM classifier based on first-order statistical feature extraction Shoffan Saifullah; Andiko Putro Suryotomo
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.937.285-293

This study aims to identify chicken eggs fertility using the support vector machine (SVM) classifier method. The classification basis used the first-order statistical (FOS) parameters as feature extraction in the identification process. This research was developed based on the processs identification process, which is still manual (conventional). Although currently there are many technologies in the identification process, they still need development. Thus, this research is one of the developments in the field of image processing technology. The sample data uses datasets from previous studies with a total of 100 egg images. The egg object in the image is a single object. From these data, the classification of each fertile and infertile egg is 50 image data. Chicken egg image data became input in image processing, with the initial process is segmentation. This initial segmentation aims to get the cropped image according to the object. The cropped image is repaired using image preprocessing with grayscaling and image enhancement methods. This method (image enhancement) used two combination methods: contrast limited adaptive histogram equalization (CLAHE) and histogram equalization (HE). The improved image becomes the input for feature extraction using the FOS method. The FOS uses five parameters, namely mean, entropy, variance, skewness, and kurtosis. The five parameters entered into the SVM classifier method to identify the fertility of chicken eggs. The results of these experiments, the method proposed in the identification process has a success percentage of 84.57%. Thus, the implementation of this method can be used as a reference for future research improvements. In addition, it may be possible to use a second-order feature extraction method to improve its accuracy and improve supervised learning for classification.

Image Segmentation Using Watershed Transform Method Based on Image Enhancement in Detection of Egg Embryos Shoffan Saifullah
Systemic: Information System and Informatics Journal Vol. 5 No. 2 (2019): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Image processing dapat diterapkan dalam proses deteksi embrio telur. Proses deteksi embrio telur dilakukan dengan menggunakan proses segmentasi, yang membagi citra sesuai dengan daerah yang dibagi. Proses ini memerlukan perbaikan citra yang diproses untuk memperoleh hasil optimal. Penelitian ini akan menganalisis deteksi embrio telur berdasarkan image processing dengan image enhancement dan konsep segmentasi menggunakan metode watershed transform. Image enhacement pada preprocessing dalam perbaikan citra menggunakan kombinasi metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dan Histogram Equalization (HE). Citra grayscale telur diperbaiki dengan menggunakan metode CLAHE, dan hasilnya diproses kembali dengan menggunakan HE. Hasil perbaikan citra menunjukkan bahwa metode kombinasi CLAHE-HE memberikan gambar secara jelas daerah objek citra telur yang memiliki embrio. Proses segmentasi dengan menggunakan konversi citra ke citra hitam putih dan segmentasi watershed mampu menunjukkan secara jelas objek telur ayam yang memiliki embrio. Hasil segmentasi mampu membagi daerah telur memiliki embrio secara nyata dan akurat dengan persentase sebesar » 98%.

Fish detection using morphological approach based on K means segmentation Shoffan Saifullah; Andiko Putro Suryotomo; Bambang Yuwono
Compiler Vol 10, No 1 (2021): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Image segmentation is a concept that is often used for object detection. This detection has difficulty detecting objects with backgrounds that have many colors and even have a color similar to the object being detected. This study aims to detect fish using segmentation, namely segmenting fish images using k-means clustering. The segmentation process is processed by improving the image first. The initial process is preprocessing to improve the image. Preprocessing is done twice, before segmentation using k-means and after. Preprocessing stage 1 using resize and reshape. Whereas after k-means is the contrast-limited adaptive histogram equalization. Preprocessing results are segmented using k-means clustering. The K-means concept classifies images using segments between the object and the background (using k = 8). The final step is the morphological process with open and close operations to obtain fish contours using black and white images based on grayscale images from color images. Based on the experimental results, the process can run well, with the ssim value close to 1, which means that image information does not change. Processed objects provide a clear picture of fish objects so that this k-means segmentation can help detect fish objects.

ANALISIS PERBANDINGAN HE DAN CLAHE PADA IMAGE ENHANCEMENT DALAM PROSES SEGMENASI CITRA UNTUK DETEKSI FERTILITAS TELUR Shoffan Saifullah
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 9 No. 1 (2020)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v9i1.23013

Perkembangan teknologi di bidang peternakan mampu memberikan kemudahan dalam proses penetasan ayam. Namun, proses deteksi fertilitas telur telah diperiksa secara manual oleh pekerja yang menyortir telur yang fertil dan infertil. Penelitian ini bertujuan untuk mempermudah proses pendeteksian gambar fertilitas telur menggunakan sistem komputerisasi secara otomatis. Deteksi fertilitas telur dilakukan preprocessing dengan metode Image Enhancement. Dalam metode ini, metode Histogram Equalization (HE) dan metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dibandingkan satu sama lain pada proses peningkatan citra (Image Enhancement). HE memberikan hasil yang dapat mengidentifikasi fertilitas telur. Namun, ada satu faktor penting dalam pemrosesan gambar, yaitu pengambilan telur (proses akuisisi). Proses deteksi fertilitas telur menggunakan segmentasi dengan metode morfologi. Proses pengujian yang dilakukan menggunakan metode kekauratan pada metode HE dan CLAHE yang masing-masing adalah sebesar 96% dan 79%. Hasil menunjukkan bahwa hasil HE lebih jelas terlihat dibandingkan dengan CLAHE.

Co-Authors Abdul Fadlil Adityo Nugroho, Adityo Afiqa, Nurul Agung Tri Utomo Agus Sasmito Aribowo Agus Sasmito Aribowo Ahmad Taufiq Akbar Ahmad Tri Hidayat Aji Prasetya Wibawa Akbar, Bagus Muhammad Alek Setiyo Nugroho Alfiani, Oktavia Dewi Alin Khaliduzzaman Alin Khaliduzzaman Alisya Amalia Putri Hasanah Andi Muhammad Dirham Dewantara Andiko Putro Suryotomo Andri Pranolo Anton Satria Prabuwono Anton Satria Prabuwono Anton Yudhana Arianti, Berliana Andra Arief Hermawan Awang Hendrianto Pratomo Azlan, Faris Farhan Azrul Mahfurdz Bambang Yuwono Bambang Yuwono Betty Yel, Mesra Budi Santosa Devia, Elmi Dharmawan, Tio DreÅ¼ewski, RafaÅ‚ Drezewski, Rafal Drezewski, Rafał Dwi Wahyuningrum Dwiyanto, Felix Andika Faqihuddin Al-anshori Felix Andika Dwiyanto Ghazali, Ahmad Badaruddin Haekal, Haekal Hari Prapcoyo Herlina Jayadianti Heru Cahya Rustamaji Hidayat, Ahmad Tri Humairoh, Nanda Lailatul Ismail, Amelia Ritahani Isna Nur Aini Ivana Puspita Sari Japkowicz, Nathalie Judanti Cahyaning Junaidi Junaidi Kaswijanti, Wilis Khaliduzzaman, Alin Kusuma, M. Apriandi Lean Karlo Tolentino Luh Putu Ratna Sundari Mubarak, Zulfikar Yusya Muhammad Nur Hendra Alvianto Nathalie Japkowicz Nisa, Syed Qamrun Noormaizan, Khairul Akmal Nur Heri Cahyana Nuril Anwar, Nuril Nuryana, Zalik Opi Irawansah, Opi Prapcoyo, Hari Putra, Agung Bella Utama Putra, Seno Aji Rabbimov Ilyos Rabbimov, Ilyos Rafal Drezewski Rafal Drezewski Rafal Drezewski Rafal Drezewski Rochmat Husaini Rochmat Husaini Rustamadji, Heru Saidah, Andi Santosa, Budi Satya Ghifari Adipratama Seno Aji Putra Siti Khomsah, Siti Suhirman SUHIRMAN SUHIRMAN Sularso Sularso, Sularso Sunardi - Sunardi - Sunardi Sunardi Sunardi, Sunardi Taufiq Akbar, Ahmad Tri Andi, Tri Tundo, Tundo Tuti Purwaningsih, Tuti Wahyu Adjie Saputra Wilis Kaswidjanti Wilis Kaswidjanti Wilis Kaswijanti Wisnalmawati Wisnalmawati Yuhefizar Yuhefizar Yuli Fauziah Yuli Fauziyah

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