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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jupiter Semantik Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI IJID (International Journal on Informatics for Development) Aplikasia: Jurnal Aplikasi Ilmu-Ilmu Agama KOMPUTA : Jurnal Ilmiah Komputer dan Informatika JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) GUYUB: Journal of Community Engagement Jurnal Nasional Teknik Elektro dan Teknologi Informasi Solo International Collaboration and Publication of Social Sciences and Humanities Engagement: Jurnal Pengabdian Kepada Masyarakat
Shofwatul ‘Uyun
Department Of Informatics, Faculty Of Science And Technology, Universitas Islam Negeri Sunan Kalijaga Yogyakarta, Indonesia
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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Data Search Process Optimization using Brute Force and Genetic Algorithm Hybrid Method Riwanto, Yudha; Nuruzzaman, Muhammad Taufiq; Uyun, Shofwatul; Sugiantoro, Bambang
IJID (International Journal on Informatics for Development) Vol. 11 No. 2 (2022): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3743

Abstract

High accuracy and speed in data search, which are aims at finding the best solution to a problem, are essential. This study examines the brute force method, genetic algorithm, and two proposed algorithms which are the development of the brute force algorithm and genetic algorithm, namely Multiple Crossover Genetic, and Genetics with increments values. Brute force is a method with a direct approach to solving a problem based on the formulation of the problem and the definition of the concepts involved. A genetic algorithm is a search algorithm that uses genetic evolution that occurs in living things as its basis. This research selected the case of determining the pin series by looking for a match between the target and the search result. To test the suitability of the method, 100-time tests were conducted for each algorithm. The results of this study indicated that brute force has the highest average generation rate of 737146.3469 and an average time of 1960.4296, and the latter algorithm gets the best score with an average generation rate of 36.78 and an average time of 0.0642.
Evaluation of the Maturity Level of Information Technology Security Systems Using KAMI Index Version 4.2 (Case Study: Islamic Boarding Schools in Yogyakarta Special Region Province) Arromdoni, Bad’ul Hilmi; Nuruzzaman, Muhammad Taufiq; 'Uyun, Shofwatul; Sugiantoro, Bambang
IJID (International Journal on Informatics for Development) Vol. 12 No. 1 (2023): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.3987

Abstract

The development of information technology worldwide has changed very rapidly. There has been a data theft on the information system belonging to one of the most prominent Islamic Boarding Schools in the Yogyakarta area. Thus, special attention is needed to evaluate information technology security using the Information Security Index version 4.2. The research methods include extracting information, literature study, data collection, data validation, data analysis, and recommendations. The evaluation results are at the basic framework fulfilment level with a value of 343; the electronic system category has a low status with a value of 15 and 5 improvements; the governance category,  the risk management category,  the framework category,  the asset management category, and the information security technology category, have a maturity level II status with 12, five, eight, four, and eight recommendations respectively, while the supplement category for third party security areas with a value of 60%, securing cloud infrastructure services 56% and protecting personal data 61% with 14 recommendations.
Evaluation of IT Governance at Islamic Boarding Schools in the Special Region of Yogyakarta based on the COBIT 5 Framework Mardlian, M. Sa’id Abdurrohman Kunta; Nuruzzaman, Muhammad Taufiq; 'Uyun, Shofwatul; Sugiantoro, Bambang
IJID (International Journal on Informatics for Development) Vol. 11 No. 2 (2022): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3988

Abstract

Nowdays,  almost all aspects of company operations are supported by information technology systems.  Many pesantren have utilized information technology in supporting operational activities such as: using computers, accessing the internet, having a website, and managing information technology systems. The purpose of this study is to implement the COBIT 5 framework in the DSS (Deliver, Service, Support) domain in evaluating information technology governance and calculate the capability level value and gap analysis at Islamic Boarding Schools. The results of the Capability Level Analysis in the COBIT 5 DSS Domain obtained from 42 Islamic Boarding Schools showed that DSS01, DSS02, and DSS03 on average were at level 2, DSS04, DSS05, DSS06 on average at level 1. The results of the Gap Analysis in the COBIT 5 DSS Domain show that in DSS01, DSS02, and DSS03 the average GAP is 3, in DSS04, DSS05, and DSS06 the average GAP is 4. The result shows that Information Technology Governance in Islamic Boarding Schools in the Special Region of Yogyakarta based on an assessment with the COBIT 5 Framework is still low status and needs to be improved, as evidenced by the low Capability Level Value and the high GAP Value.
Analysis of Factors Affecting the Students’ Acceptance Level of E-Commerce Applications in Yogyakarta Using Modified UTAUT 2 Candra, Dori Gusti Alex; Nuruzzaman, Muhammad Taufiq; 'Uyun, Shofwatul; Sugiantoro, Bambang; Pratiwi, Millati
IJID (International Journal on Informatics for Development) Vol. 12 No. 1 (2023): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.3990

Abstract

Yogyakarta is listed as the region with the highest number of residents engaging in e-commerce transactions. A total of 10.2% of the population are active e-commerce sellers, while 16.7% belong to the buyer category. Research by IDN Times showed that e-commerce application users have been dominated by students, with a percentage of 44.2%.  The purpose of this study is to analyze the factors that influence students’ level of acceptance of e-commerce applications in Yogyakarta using the modified UTAUT 2. This is quantitative research with multiple linear regression models using SPSS software version 25 with a sample size of 303 people. Data analysis in this study was conducted in a few steps, including descriptive analysis, validity test, reliability test, classical assumption test and hypothesis testing. The results of this study indicate that the student’s level of acceptance of e-commerce applications is within good criteria. The variables that have a positive effect on the behaviour intention (BI) are performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), habit (HB), price value (PV), perceived risk (PR), perceived security (PS), and trust (TR) are variables that negatively affect the variable behaviour intention (BI). All independent variables affect the dependent variable or behaviour intention (BI) with a total of 63.3% and the difference with a total of 36.7% is caused by other factors not examined by the researcher.
Optimisation of Residual Network Using Data Augmentation and Ensemble Deep Learning for Butterfly Image Classification Diniati Ruaika; Shofwatul Uyun
IJID (International Journal on Informatics for Development) Vol. 12 No. 2 (2023): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.4038

Abstract

Image classification is a fundamental task in vision recognition that aims to understand and categorize an image under a specific label. Image classification needs to produce a quick, economical, and reliable result. Convolutional Neural Networks (CNN) have proven effective for image analysis. However, problems arise due to factors such as the model’s quality, unbalanced training data, overfitting, and layers’ complexity. ResNet50 is a transfer learning-based convolutional neural network model frequently used in many areas, including Lepidopterology. Studies have shown that ResNet50 performs with lower accuracy than other models for classifying butterflies. Therefore, this study aims to optimise the accuracy of ResNet50 using an augmentation approach and ensemble deep learning for butterfly image classification. This study used a public dataset of butterflies from Kaggle. The dataset contains 75 different butterfly species, 9.285 training images, 375 testing images, and 375 validation images. A sequence of transformation functions was applied. The ensemble deep learning was constructed by incorporating ResNet50 with CNN. To measure ResNet50 optimisation, the experimental results of the original dataset and the proposed methods were compared and analysed using evaluation metrics. The research revealed that the proposed method provided better performance with an accuracy of 95%.
MONITORING KUALITAS AIR SECARA KOLABORATIF DI SUNGAI BOYONG, YOGYAKARTA Awaliyah, Dien Fitri; Uyun, Shofwatul; Sulistiyowati, Eka
Aplikasia: Jurnal Aplikasi Ilmu-ilmu Agama Vol. 24 No. 1 (2024):
Publisher : UIN Sunan Kalijaga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/aplikasia.v24i1.3573

Abstract

Biotilik is an uncomplicated method to monitor the stream quality and can be handled communally with the help of information technology. However, involving community in a monitoring, especially those based on applications, is a challenge that requires a comprehensive approach. Therefore, this research was conducted to measure how deep the community can be involved and the significancy of the community services. A collaborative approach has been done, starts with activity planning, mobile app developing, introducing the app to the community, until doing some collaborative regular monitoring activities through biomonitoring workshops. The communities involved in this study include KPLS, Waterforum Kalijogo, and the Entomology Study Group. The results show that mobile applications are successfully created and adopted by the community, although there are some community members who have difficulty accessing them, especially senior citizens. Biomonitoring workshops were conducted several times along with measurements of community knowledge and skills before and after the workshop. The result shows that the change in knowledge was not statistically significant because the public was already familiar with biomonitoring.  Changes in skills occurred in this study because the community conducted biomonitoring workshops for some time and was assisted by mobile applications. ======================================= Metode biotilik adalah metode pemantauan kualitas air yang sederhana dan dapat dilakukan secara komunal dengan bantuan teknologi informasi. Walaupun begitu, pelibatan masyarakat dalam pemantauan air secara komunal apalagi yang berbasis pemanfaatan aplikasi merupakan tantangan yang membutuhkan pendekatan yang komprehensif. Untuk itu penelitian ini dilakukan untuk mengukur seberapa besar masyarakat dapat terlibat dalam pengembangan pengetahuan dan keterampilan pemantauan kualitas sungai dan bagaimana dampak yang dihasilkan oleh kegiatan tersebut. Pendekatan kolaboratif yang dimulai dengan perencanaan kegiatan, perancangan aplikasi mobile untuk membantu pemantauan kualias air, pengenalan aplikasi, sampai kepada kegiatan pemantauan secara berkala. Komunitas yang terlibat berasal dari Komunitas Pecinta Lingkungan dan Sungai (KPLS), Waterforum Kalijogo, dan Kelompok Studi Entomologi. Hasil menunjukkan bahwa aplikasi mobile yang dibangun dapat diadopsi oleh masyarakat, meskipun ada beberapa yang kesulitan mengaksesnya terutama warga senior. Selanjutnya, workshop biomonitoring dilakukan beberapa kali bersamaan dengan pengukuran terhadap pengetahuan dan keterampilan masyarakat sebelum dan sesudah workshop. Hasilnya, perubahan pengetahuan tidak signifikan secara statistik karena masyarakat sudah cukup mengenal biomonitoring.  Perubahan keterampilan terjadi di dalam penelitian ini karena masyarakat melakukan workshop biomonitoring dalam beberapa waktu dan dibantu dengan aplikasi mobile.
Participatory Water Quality Monitoring System for the Gajahwong River, Yogyakarta City, Indonesia Sulistiyowati, Eka; Uyun, Shofwatul
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 8 No 1 (2024): May 2024
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v8i1.1525

Abstract

This paper presents the development of Suka Peta (an integrated web-based system of participatory water quality monitoring), which has been developed by the researcher team of the State Islamic University Sunan Kalijaga, Yogyakarta, Indonesia. The system is designed to collect various types of data to generate a report on the water quality status of a river. The study followed a method for research and development that includes the design, development, implementation, and evaluation stages. The final product of this research is a web-based application that could be accessed publicly through www.status-sungai.com. During the evaluation stage, we conducted an FGD with stakeholders in the Gajahwong River community. The result confirmed that the application has a high potential for engaging the community in water quality monitoring. In addition, the participants have been able to use the application and participate in water quality monitoring efforts.
Klasifikasi Persediaan Stok Darah Menggunakan Algoritma K-NN, Decision Tree, dan JST Backpropagation Rijal Fauzan, Yulis; Fajarendra, Yusril Iza; Ridha , M Noor Tasiur; 'Uyun, Shofwatul
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13755935

Abstract

The demand for blood is critical for various purposes, such as surgeries, transplants, cancer treatments, dialysis, and disaster victims. The availability of blood at the Blood Transfusion Unit (UTD) of the Indonesian Red Cross (PMI) is crucial, as a shortage of stock can endanger patients' lives. Therefore, this study aims to evaluate the condition of blood stock to determine whether it is safe or insufficient. This research focuses on comparing blood stock classification at PMI Kota Yogyakarta using three algorithms: K-Nearest Neighbor, Decision Tree, and Artificial Neural Network (Backpropagation). The study objects consist of 216 blood stock data point. Testing is conducted using the K-Fold Cross Validation method with a k value of 8 on 216 data points. The research results show that the K-Nearest Neighbors (KNN) algorithm achieves an Accuracy of 85.18%, Recall of 85.03%, Precision of 89.25%, F1-Score of 87.09%, and Specificity of 84.39%. The Decision Tree algorithm achieves an Accuracy of 84.72%, Recall of 88.18%, Precision of 86.15%, F1-Score of 87.15%, and Specificity of 78.08%. The Artificial Neural Network (Backpropagation) algorithm shows the best performance with an Accuracy of 93.05%, Recall of 96.06%, Precision of 92.42%, F1-Score of 94.20%, and Specificity of 89.35%. Thus, it can be concluded that the Artificial Neural Network (Backpropagation) algorithm outperforms the other algorithms in classifying blood stock availability.  Keywords—PMI, Blood, Classification, K-Nearest Neighbor, Decision Tree, Backpropagation
KLASIFIKASI CITRA EUROSAT MENGGUNAKAN ALGORITMA KNN, DECISION TREE DAN RANDOM FOREST Iza Fajarendra, Yusril; Rizal Fauzan, Yulis; 'Uyun, Shofwatul
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 4 (2024): JATI Vol. 8 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i4.10458

Abstract

Penggunaan teknologi citra satelit telah berkembang pesat dan banyak dimanfaatkan untuk penelitian, mencakup pegunungan, sungai, danau, dan lainnya. Dalam penelitian ini, digunakan dataset EuroSat yang memiliki 10 label yang mendeskripsikan perubahan bentuk lahan dan pemukiman di wilayah Eropa. Perubahan tersebut disebabkan oleh kerusakan akibat aktivitas manusia dan alam seperti pertanian, irigasi, dan bencana alam. Selain itu, kompleksitas dan variabilitas dataset EuroSat yang beragam memerlukan pendekatan yang mampu mengenali pola-pola halus dan berbeda pada setiap kategori. Oleh karena itu, penelitian ini bertujuan untuk mengkomparasikan kinerja beberapa algoritma dalam klasifikasi citra satelit. Dalam hal ini, digunakan tiga algoritma yaitu KNN, Decision Tree, dan Random Forest untuk dibandingkan kinerjanya dalam klasifikasi citra data EuroSat. Metode penelitian yang digunakan meliputi import data, normalisasi data, konversi label ke one-hot encoding, ekstraksi fitur, dan normalisasi fitur menggunakan model VGG16 yang ditraining terlebih dahulu untuk mendapatkan representasi fitur yang informatif. Fitur yang diekstraksi kemudian digunakan sebagai input untuk ketiga algoritma tersebut. Pengujian performa model dilakukan menggunakan K-Fold Cross Validation. Hasil yang diperoleh memperlihatkan bahwa Random Forest memiliki kinerja terbaik dengan accuracy 81,32%, recall 81,33%, precision 81,18%, dan f1 score 80,82%. Penelitian ini menunjukkan bahwa penggunaan algoritma Random Forest dapat meningkatkan akurasi dan performa dalam klasifikasi citra satelit.
A Hybrid Classification Model Based on BERT for Multi-Class Sentiment Analysis on Twitter Uyun, Shofwatul; Rosalin, Rizqi Praimadi; Sari, Luky Vianika; Sucinta, Hanny Handayani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i2.30665

Abstract

Social media is one of the media to convey opinions and sentiments. Sentiment analysis is an important tool for researchers and business people to understand user emotions efficiently and accurately. Choosing the right classification model has a significant impact on sentiment classification performance. However, the diversity of model architectures and training techniques poses its own challenges. In addition, relying on a single classification model often causes noise, bias, data imbalance, and limitations in handling data variations effectively. This study proposes a hybrid classification model where BERT is the baseline. Furthermore, BERT will be hybridized using LSTM, and BERT is hybridized with CNN to improve sentiment analysis on Twitter social media data. The hybrid approach aims to reduce the limitations of a single model classifier by increasing model effectiveness, reducing bias, and optimizing the model on imbalanced data. The following are the steps in this study, data preprocessing, data balancing, tokenization, model training, and performance evaluation. Three models were trained: the baseline BERT model, the BERT-CNN hybrid, and the BERT-LSTM hybrid. Model performance was assessed using accuracy, precision, recall, and F1 score. Experimental results show that the baseline BERT model achieves an accuracy of 91.45%, while BERT-LSTM achieves 91.60%, and BERT-CNN achieves the highest accuracy of 91.80%. However, further analysis is needed to determine whether these improvements are statistically significant and whether the hybrid model offers additional benefits beyond accuracy, such as remembering underrepresented sentiment categories.
Co-Authors Abdullah, Mohd. Fikri Azli bin Afiyah, Ishmah Agung Nur Hidayat Ahmad Mustafid Ahmad Subhan Yazid Akbar, Riolandi Akhmad Imam Fahrizal Alfarizi, Naufal Faiz Amarudin, Hanif Arif Riyandi Arromdoni, Bad’ul Hilmi Awaliyah, Dien F. Awaliyah, Dien Fitri Bambang Sugiantoro Danang Aji Bimantoro Daru Prasetyawan Diniati Ruaika Dony Fahrudy Dori Gusti Alex Candra Eka Sulistiyowati Eka Sulistyowati Eka Sulistyowati, Eka Elvanisa Ayu Muhsina Elvanisa Ayu Muhsina, Elvanisa Ayu Endra Yuliawan Fahrudy, Dony Fajarendra, Yusril Iza Fauzi, Muhammad Dzulfikar Hardandrito, Awan Gumilang Heni Hapsari Iin Intan Uljanah Imam Riadi Istianto, Yudi Iza Fajarendra, Yusril Lina Choridah Madikhatun, Yuni Mardlian, M. Sa’id Abdurrohman Kunta Maria Ulfah Siregar MUHAMMAD ABDUL GHOFUR Muhammad Akid Musyafa Muhammad Anshari, Muhammad Muhammad Edi Iswanto Muhammad Fadzlur Rahman Muhammad Rifqi Ma'arif Muhammad Taufiq Nuruzzaman Murdifin, Murdifin Mustafid, Ahmad Nuri Guntur Perdana Nurochman Nurochman Nuruzzaman, Muhammad Taufiq Pratiwi, Millati Qonitat, Ihda Imroatun Qorry Aina Fitroh Rahardyan, Seto Rebeccah Ndungi Ridha , M Noor Tasiur Rijal Fauzan, Yulis Riwanto, Yudha Rizal Fauzan, Yulis Rosalia Susilowati Rosalin, Rizqi Praimadi Saiful Machbub Mutaqin Sari, Luky Vianika Sherly Andini Siti Helmiyah Sri Hartati subanar subanar Sucinta, Hanny Handayani Toni Efendi Tundo, Tundo Ulfah, Aniq Noviciate Yulis Rijal Fauzan Yuni Madikhatun Yuni Madikhatun