p-Index From 2021 - 2026
5.626
P-Index
This Author published in this journals
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 Paradigma Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Claim Missing Document
Check
Articles

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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (593.587 KB) | DOI: 10.29207/resti.v5i5.3431

Abstract

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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (723.494 KB) | DOI: 10.29207/resti.v5i6.3540

Abstract

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

Abstract

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

Abstract

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

Abstract

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.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (546.322 KB) | DOI: 10.29080/systemic.v5i2.798

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1221.396 KB) | DOI: 10.28989/compiler.v10i1.946

Abstract

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

Abstract

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.
K-Means Segmentation Based-on Lab Color Space for Embryo Detection in Incubated Egg Shoffan Saifullah; Rafal Drezewski; Alin Khaliduzzaman; Lean Karlo Tolentino; Rabbimov Ilyos
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23724

Abstract

The quality of the hatching process influences the success of the hatch rate besides the inherent egg factors. Eliminating infertile or dead eggs and monitoring embryonic growth are very important factors in efficient hatchery practices. This process aims to sort eggs that only have embryos to remain in the incubator until the end of the hatching process. This process aims to sort eggs with embryos to remain hatched until the end. Maximum checking is done the first week in the hatching period. This study aims to detect the presence of embryos in eggs. Detection of the existence of embryos is processed using segmentation. Egg images are segmented using the K-means algorithm based on Lab color images. The results of the image acquisition are converted into Lab color space images. The results of Lab color space images are processed using K-means for each color. The K-means process uses cluster k=3, where this cluster divides the image into three parts: background, eggs, and yolk. Egg yolks are part of eggs that have embryonic characteristics. This study applies the concept of color in the initial segmentation and grayscale in the final stages. The initial phase results show that the image segmentation results using k-means clustering based on Lab color space provide a grouping of three parts. At the grayscale image processing stage, the results of color image segmentation are processed with grayscaling, image enhancement, and morphology. Thus, it seems clear that the yolk segmented shows the presence of egg embryos. Based on this process and results, the initial stages of the embryo detection process used K-means segmentation based on Lab color space. The evaluation uses MSE and MSSIM, with values of 0.0486 and 0.9979; this can be used as a reference that the results obtained can detect embryos in egg yolk. This protocol could be used in a non-destructive quantitative study on embryos and their morphology in a precision poultry production system in the future.
Sistem Pendukung Keputusan Pemilihan Cafe di Yogyakarta dengan Menggunakan Metode Simple Additive Weighting (SAW) Muhammad Nur Hendra Alvianto; Shoffan Saifullah
Journal of Innovation Information Technology and Application (JINITA) Vol 2 No 1 (2020): JINITA, June 2020
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.99 KB) | DOI: 10.35970/jinita.v2i1.187

Abstract

The development of the culinary business in Indonesia is developing very fast, one of which is the business of blending coffee drinks or commonly called café. This business is growing very fast, and there are many variants of concoctions in Indonesia, one of which is located in Yogyakarta. The many cafes that open in Yogyakarta have an impact on students' confusion to choose which recommendations are most comfortable for students to use as a place of discussion or place of study. Besides, usually, newcomers, especially students who have just arrived in Yogyakarta, tour the city in search of places that are comfortable to use to unwind. In this study, conducting interviews with 10 respondents, the results were processed and processed using the Simple Additive Weighting (SAW) method. SAW is one of the methods used in making decisions. This method is used to determine the best café recommendations in Yogyakarta. These café recommendations are expected to be in accordance with what students are looking for by taking into account café facilities, café locations, and the price range offered. The calculation result of the SAW method in the recommended cafe in Yogyakarta is Cafe B, with a yield of 9.4, which is the highest value. Based on the results of these calculations and analysis, the facilities provided by the café are the main attraction for visitors. Besides, the use of the SAW method can also provide the best café recommendations as initial recommendations for new students in Yogyakarta
Co-Authors Abdul Fadlil Adityo Nugroho, Adityo Afiqa, Nurul Agus Sasmito Aribowo Ahmad Taufiq Akbar Ahmad Tri Hidayat Aji Prasetya Wibawa Akbar, Ahmad Taufiq Akbar, Bagus Muhammad Alek Setiyo Nugroho Alfiani, Oktavia Dewi Alin Khaliduzzaman Alin Khaliduzzaman Alisya Amalia Putri Hasanah Andi Muhammad Dirham Dewantara Andi Nurkholis 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 Betty Yel, Mesra Budi Santosa Devia, Elmi Dharmawan, Tio Dreżewski, RafaÅ‚ Drezewski, Rafal Drezewski, Rafał Dwi Wahyuningrum Dwiyanto, Felix Andika Faqihuddin Al-anshori Ghazali, Ahmad Badaruddin Haekal, Haekal 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 Katamsyi, Kaifa Ahlal 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 Rochmat Husaini Rochmat Husaini Rustamadji, Heru Saidah, Andi Santosa, Budi Satya Ghifari Adipratama Seno Aji Putra 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 Yuhefizar Yuhefizar Yuli Fauziah Yuli Fauziyah