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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)
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Information System Development Based-on ERP and RAD Methods: Application For Activities Information Broadcasting Sunardi Sunardi; Abdul Fadlil; Faqihuddin Al-anshori; Shoffan Saifullah
JUITA : Jurnal Informatika JUITA Vol. 8 Nomor 2, November 2020
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (976.866 KB) | DOI: 10.30595/juita.v8i2.7684

Abstract

As technology develops, information systems become very important in institutions. Information systems support the delivery of information quickly and accurately. The system is a reference at the Persada Islamic Boarding School Ahmad Dahlan University to develop an information delivery system using applications integrated. Manual systems cause the information to be less relevant, requiring an integrated and comprehensive system that can effectively and efficiently deliver information to students. The application developed using Enterprise Resource Planning (ERP) and Rapid Application Development (RAD) methods. The application of these methods requires two main steps, including determining ERP and RAD for implementation. The process for obtaining an ERP method requires steps such as Material Requirement Planning, Close-Loop, and Manufacturing Resource Planning, and Enterprise Resource Planning. The RAD method requires steps such as Requirement Planning, RAD Design Workshop, and Implementation. Application testing used black-box and alpha testing. Each of these tests obtained an accuracy of 95% and 97.7%. Thus, this application can be implemented in Persada very well on mobile and desktop platforms. Besides, the app used information broadcasting to users in real-time for any information in Persada.
Green turtle and fish identification based on acoustic target strength Sunardi Sunardi; Azrul Mahfurdz; Shoffan Saifullah
International Journal of Advances in Intelligent Informatics Vol 4, No 1 (2018): March 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i1.147

Abstract

Fisherman accidentally caught sea turtles in their fishnet. It could be dangerous for its population. This study measures the turtle target strength (TS) using modified echosounder. The result could be used to improve the efficiency of turtle repellent device. The experiment conducted in a hatchery fiber tank contained saline water. The Green were 1, 3, 12 and 18 years old. This study used three species of fish, which serves to distinguish the value between fish and sea turtles. TS of the animals were calculated incorporating reference targets (sphere). The echo power of the turtle was compared with the solid steel sphere which is confirmed good agreements with the theoretical values. The echo power reference by applying Fast Fourier Transform (FFT) analysis has been used in calculating TS of the animal. The time domain of the echo evaluation in different angles shows the difference in the structure of the echo signal between the tortoise's body parts. This study reveals that high echo strength is acquired from the carapace and the plastron parts. The finding also showed that there are significant differences between 3, 12, 18 years old turtles and fish in every angle measurement.
Poultry Disease Detection Simulation using Case-Based Reasoning based on Nearest Neighbor Retrieval Ivana Puspita Sari; Isna Nur Aini; Satya Ghifari Adipratama; Shoffan Saifullah
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2021): Inovasi Teknologi dan Pengolahan Informasi untuk Mendukung Transformasi Digital
Publisher : Jurusan Teknik Informatika

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

Abstract

Tujuan: Mendeteksi penyakit unggas (ayam) dan memberikan solusi alternatif dengan simulasi sistem. Sehingga dapat memberikan kontribusi dalam pengembangan teknologi bidang peternakan.Perancangan/metode/pendekatan: Penelitian ini menggunakan metode Case-Based Reasoning (CBR). Metode CBR menggunakan rule-based dalam penyelesaian masalah (khususnya deteksi penyakit ayam). Selain itu,  retrieve pada CBR menggunakan metode Nearest Neighbor Retrieval dalam mencari kemiripan berdasarkan bobot yang diberikan. Hasil: Simulasi sistem mampu mendeteksi penyakit unggas dengan nilai similarity kasus percobaan yang diujikan sebesar 69,3% dan percobaan gejala lain memiliki similarity sebesar 99.9%. Hal ini ditunjukkan dalam proses deteksi sistem dan perhitungan perhitungan manualnya. Keaslian/ state of the art: Penelitian ini menggunakan CBR-Nearest Neighbor Retrieval berdasarkan rule dan kemiripan kasus yang ada.
Fuzzy-AHP approach using Normalized Decision Matrix on Tourism Trend Ranking based-on Social Media Shoffan Saifullah
Jurnal Informatika Vol 13, No 2 (2019): July 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.845 KB) | DOI: 10.26555/jifo.v13i2.a15268

Abstract

This research discusses multi-criteria decision making (MCDM) using Fuzzy-AHP methods of tourism. The fuzzy-AHP process will rank tourism trends based on data from social media. Social media is one of the channels with the largest source of data input in determining tourism development. The development uses social media interactions based on the facilities visited, including reviews, stories, likes, forums, blogs, and feedback. This experiment aims to prioritize facilities that are the trend of tourism. The priority ranking uses weight criteria and the ranking process.  The highest rank is in the attractions of the Park/Picnic Area, with the final weight calculation value of 0.6361. Fuzzy-AHP can rank optimally with an MSE value of ≈0.0002.
Comparison of machine learning for sentiment analysis in detecting anxiety based on social media data Shoffan Saifullah; Yuli Fauziyah; Agus Sasmito Aribowo
Jurnal Informatika Vol 15, No 1 (2021): January 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v15i1.a20111

Abstract

All groups of people felt the impact of the COVID-19 pandemic. This situation triggers anxiety, which is bad for everyone. The government's role is very influential in solving these problems with its work program. It also has many pros and cons that cause public anxiety. For that, it is necessary to detect anxiety to improve government programs that can increase public expectations. This study applies machine learning to detecting anxiety based on social media comments regarding government programs to deal with this pandemic. This concept will adopt a sentiment analysis in detecting anxiety based on positive and negative comments from netizens. The machine learning methods implemented include K-NN, Bernoulli, Decision Tree Classifier, Support Vector Classifier, Random Forest, and XG-boost. The data sample used is the result of crawling YouTube comments. The data used amounted to 4862 comments consisting of negative and positive data with 3211 and 1651. Negative data identify anxiety, while positive data identifies hope (not anxious). Machine learning is processed based on feature extraction of count-vectorization and TF-IDF. The results showed that the sentiment data amounted to 3889 and 973 in testing, and training with the greatest accuracy was the random forest with feature extraction of vectorization count and TF-IDF of 84.99% and 82.63%, respectively. The best precision test is K-NN, while the best recall is XG-Boost. Thus, Random Forest is the best accurate to detect someone's anxiety based-on data from social media.
Analisis Ekstraks Ciri Fertilitas Telur Ayam Kampung dengan Grey Level Cooccurrence Matrix Shoffan Saifullah; Sunardi Sunardi; Anton Yudhana
JURNAL NASIONAL TEKNIK ELEKTRO Vol 6, No 2: Juli 2017
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.215 KB) | DOI: 10.25077/jnte.v6n2.376.2017

Abstract

This research used chicken eggs to perform the analysis in the identification process fertility chicken eggs. The method in the identification process using Gray Level Co-occurrence Matrix (GLCM). The identification process by using GLCM using the 6 main parameters to determine the characteristics (feature extraction). The parameters used are: ASM (Angular Second Moment), Contrast, Correlation, Variance, IDM (Inverse Difference Moment), and Entropy. Each parameter will give different values and is able to distinguish and classify images based fertility chicken eggs chicken eggs. The identification process gives results that the image of a chicken egg fertile and infertile able to distinguish from GLCM parameters and show that using 10 samples of chicken eggs able to be grouped based on their fertility.Keywords:Chicken Eggs, Feature Extraction, GLCM ParametersAbstrak— Penelitian ini menggunakan telur ayam kampung untuk melakukan analisis dalam proses identifikasi fertilitas telur ayam. Metode dalam proses identifikasi menggunakan Gray Level Coocurence Materik (GLCM). Proses identifikasi dengan menggunakan GLCM menggunakan 6 parameter utama untuk mengetahui ciri-ciri (ekstraksi ciri). Parameter yang digunakan yaitu: ASM, Kontras, Korelasi, Varians, IDM, dan Entropy. Masing-masing parameter akan memberikan nilai yang berbeda dan mampu membedakan dan mengelompokkan citra telur ayam kampung berdasarkan fertilitas telur ayam. Proses identifikasi memberikan hasil bahwa citra teluer ayam kampung fertile dan infertile mampu dibedakan dengan parameter-parameter GLCM dan menunjukkan bahwa dengan menggunakan 10 sampel telur ayam kampung mampu dikelompokkan berdasaarkan fertilitasnya.Kata Kunci : Telur ayam kampung, Ekstraksi Ciri, Parameter GLCM
Segmentation Comparing Eggs Watermarking Image and Original Image Anton Yudhana; Sunardi Sunardi; Shoffan Saifullah
Bulletin of Electrical Engineering and Informatics Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.281 KB) | DOI: 10.11591/eei.v6i1.595

Abstract

The research used watermarking techniques to obtain the image originality. The aims of the research were to identify small area in eggs properly and compared preprocessing, the methods, and the results of image processing. The study has been improved from the previous papers by combined all methods and analysis was obtained.This study was conducted by using centroid and the bounding box for determining the object and the small area of chicken eggs. The segmentation method was used to compare the original image and the watermarked image. Image processing using image data that are subject watermark to maintain the authenticity of the images used in the study will the impact in delivering the desired results. In the identification of chicken eggs using watermark image using several methods are expected to provide results as desired. Segmentation also deployed to process the Image and counted the objects. The results showed that the process of segmentation and objects counting determined that the original image and watermarked image had the same value and recognized eggs. Identification had determined percentage of 100% for all the samples.
K-MEANS CLUSTERING FOR EGG EMBRYO'S DETECTION BASED-ON STATISTICAL FEATURE EXTRACTION APPROACH OF CANDLING EGGS IMAGE Shoffan Saifullah
SINERGI Vol 25, No 1 (2021)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2021.1.006

Abstract

This research discusses the detection of embryonic eggs using the k-means clustering method based on statistical feature extraction. The processes that occur in detection are image acquisition, image enhancement, feature extraction, and identification/detection. The data used consisted of 200 egg image data, consisting of 100 test data and 100 new test data. The acquisition process uses a smartphone camera by capturing candled egg objects. The results of image acquisition become a reference in the process of image enhancement and feature extraction using Statistical Feature Extraction. The statistical feature extraction applied is the Gray Level Co-occurrence Matrix (GLCM) method, which consists of 6 features, namely Energy, Contrast, Entropy, Variance, Correlation, and Homogeneity. The results of feature extraction (6 features) are grouped by the K-means Clustering method. The clustering process uses Euclidean distance calculations to determine the proximity of features. The results of grouping and testing give the best average results with an accuracy of ≈ 74% from several test samples.
A proposed method for handling an imbalance data in classification of blood type based on Myers-Briggs type indicator Ahmad Taufiq Akbar; Rochmat Husaini; Bagus Muhammad Akbar; Shoffan Saifullah
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 4, Year 2020 (October 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13625

Abstract

Blood type still leads to an assumption about its relation to some personality aspects. This study observes preprocessing methods for improving the classification accuracy of MBTI data to determine blood type. The training and testing data use 250 data from the MBTI questionnaire answers given by 250 respondents. The classification uses the k-Nearest Neighbor (k-NN) algorithm. Without preprocessing, k-NN results in about 32 % accuracy, so it needs some preprocessing to handle data imbalance before the classification. The proposed preprocessing consists of two-stage, the first stage is the unsupervised resample, and the second is the supervised resample. For the validation, it uses ten cross-validations. The result of k-Nearest Neighbor classification after using these proposed preprocessing stages has finally increased the accuracy, F-score, and recall significantly.
Website-Based E-Pharmacy Application Development to Improve Sales Services Using Waterfall Method Suhirman Suhirman; Ahmad Tri Hidayat; Wahyu Adjie Saputra; Shoffan Saifullah
International Journal of Advances in Data and Information Systems Vol. 2 No. 2 (2021): October 2021 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i2.1226

Abstract

An online shop is a way of trading and shopping online via the internet. Online sales in the business sector will significantly help reduce operational costs, especially for customer activities; in its contribution to commerce, online sales can also increase selling power and widely facilitate the marketing of a product. “Seger Waras” Pharmacy is an agency engaged in the business of selling medicines and medical equipment. “Seger Waras” Pharmacy requires an online sales website or online store, which is intended to maximize service to existing or new customers. Therefore, the authors conducted research on the design of the e-pharmacy application, which is a web-based medicine sales system at the Seger Waras Pharmacy. This study aims to increase the revenue of the relevant agencies and provide complete information about drug use to customers. Data collection methods use observation and interview methods for system models using Data Flow Diagrams, Entity Relationship Diagrams, and Context Diagrams. The software used by MySQL as a database server, Apache as a web server, Sublime Text 3 for writing PHP and HTML programming languages, and Bootstrap as a framework. The result of the system that has been completed is an online store application that makes it possible to sell and purchase drugs online; the online shop at the “Seger Waras” Pharmacy can increase sales turnover and promote business.
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 Dreżewski, 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