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All Journal TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) SITEKIN: Jurnal Sains, Teknologi dan Industri JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO Seminar Nasional Teknologi Informasi Komunikasi dan Industri MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Building of Informatics, Technology and Science ADI Journal on Recent Innovation (AJRI) Media Jurnal Informatika Jurnal Sistem Informasi Science, Technology, and Communication Journal
Luh Kesuma Wardhani
UIN Syarif Hidayatullah Jakarta
Religion 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 Materials Science & Nanotechnology Mathematics Other

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A Comparative Analysis of Random Forest, XGBoost, and LightGBM Algorithms for Emotion Classification in Reddit Comments Anggraini, Nenny; Putra, Syopiansyah Jaya; Wardhani, Luh Kesuma; Arif, Farid Dhiya Ul; Hakiem, Nashrul; Shofi, Imam Marzuki
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.38651

Abstract

This research aims to compare the performance of three classification algorithms, namely Random Forest, XGBoost, and LightGBM, in classifying emotions in Reddit comments. Emotion classification in Reddit comments is a complex classification problem due to its numerous variations and ambiguities. This research utilizes the GoEmotions Fine-Grained dataset, filtered down to 7,325 Reddit comments with 5 different basic emotion labels. In this study, data preprocessing steps, feature extraction using CountVectorizer and TF-IDF, and hyperparameter tuning using GridSearchCV for each algorithm are conducted. Subsequently, model evaluation is performed using Cross-Validation and confusion matrix. The results of the study indicate that Random Forest outperforms the XGBoost and LightGBM algorithm with an accuracy of 75.38% compared to XGBoost with 69.05% accuracy and LightGBM with 66.63% accuracy.
Nearest Neighbor Interpolation and AES Encryption for Enhanced Least Significant Bit (LSB) Steganography Anggraini, Nenny; Wardhani, Luh Kesuma; Assyahid, Muhammad Hudzaifah; Hakiem, Nashrul; Yusuf, Muhammad; Setyawan, Okky Bagus
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.7079

Abstract

The increasing use of digital communication raises concerns about data security, especially when transmitting sensitive information. Steganography conceals messages within digital media to prevent detection. However, conventional methods face storage limitations, leading to message truncation or distortion, making hidden messages more detectable. This study proposes a combination of Nearest Neighbor Interpolation (NNI) and Least Significant Bit (LSB) steganography to dynamically expand the cover image, allowing larger encrypted messages to be embedded while maintaining image integrity. NNI was chosen over other interpolation techniques such as Bilinear and Bicubic due to its lower computational complexity and preservation of sharp edges, which minimizes blurring artifacts that could make steganographic alterations more noticeable. AES-128 encryption ensures message confidentiality before embedding. The system was developed as a web-based application to improve usability. The research followed the Waterfall Software Development Life Cycle (SDLC), and Black Box Testing validated system functionality. Testing results showed that the method successfully embedded and extracted messages without data loss, maintaining PSNR values above 40 dB, ensuring minimal perceptual distortion. However, the maximum interpolation limit was 5310 × 5310 pixels, beyond which system constraints caused failures. The stego-images retained original aspect ratios, reducing suspicion. Despite its success, the system remains vulnerable to modifications such as color changes, cropping, rotation, and compression, which can disrupt the message.
Multi-Class Fault Detection under Class-Imbalance in Wireless Sensor Network Using Random Undersampling and Extra Trees Saputra, David Yusup; Wardhani, Luh Kesuma; Nanang, Herlino
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5959

Abstract

Wireless Sensor Networks (WSNs) are widely used in various monitoring applications, including environmental observation, smart infrastructure, and Internet of Things (IoT) systems. Despite their widespread adoption, WSNs are highly susceptible to data errors caused by sensor degradation, hardware malfunctions, environmental disturbances, and communication issues. These faults can significantly reduce data reliability and lead to incorrect system decisions if not properly handled. This study proposes a multi-class data-fault detection approach for WSNs under imbalanced data conditions by integrating Random Undersampling (RUS) with the Extra-Trees classification algorithm. The proposed framework aims to address the class imbalance problem commonly found in sensor fault datasets while improving fault detection performance across multiple fault types. Experiments were conducted using a WSN dataset containing temperature and humidity measurements, in which three fault types: Bias, Drift, and Spike were analyzed alongside normal sensor data. The experimental results demonstrate that Random Undersampling leads to a substantial improvement in classification performance. Without RUS, the Extra-Trees classifier achieved an accuracy of 48% and failed to detect spike faults. After applying RUS, classification accuracy increased to 91%, accompanied by balanced precision, recall, and F1-score values across all classes. These findings indicate that the combination of Random Undersampling and Extra-Trees provides an effective and reliable solution for multi-class data fault detection in WSN environments.
User Interface and Exprience Gamification-Based E-Learning with Design Science Research Methodology Viva Arifin; Velia Handayani; Luh Kesuma Wardhani; Hendra Bayu Suseno; Siti Ummi Masruroh
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2427

Abstract

In 2020, the Islamic Elementary Teacher Working Group (KKG MI) held an E-Learning Training for Islamic Elementary School Teachers in DKI Jakarta about one of the gamification applications, Quizizz. According to observation, many teachers are still perplexed when utilizing the Quizizz program. This is due to the application’s design and different functionalities, which still appear complicated to some teachers who aren’t used to using it. The existing gamification application is also considered not to meet the learning needs at Islamic elementary schools in Jakarta. This study intends to analyze and design User Interface (UI) and User Experience (UX) designs for gamification-based e-learning applications as solutions to the problems found. Data collection begins with an observation and also a literature study, questionnaires, and interviews. For the design, Design Science Research Methodology (DSRM) is used, which consists of six stages: Problem Identification & Motivation, Define the Objective for a Solution, Design & Development, Demonstration, Evaluation and Communication. The results of the evaluation of the gamification-based e-learning design designed with the User Experience Questionnaire (UEQ) and Task Success show that the e-learning design is considered attractive and users can interact with e-learning effectively and easily.
IoT-based Integrated System Portable Prayer Mat and DailyWorship Monitoring System Luh Kesuma Wardhani; Nenny Anggraini; Nashrul Hakiem; M. Tabah Rosyadi; Amin Rois
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 3 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.3058

Abstract

Muslims have various difficulties in praying, such as difficulty memorizing the number of rak’ah they have been doing and determining the direction of the Qibla. In this research, we proposed a technological device for monitoring daily worship in Islam. We presented the IoT-based integrated system as a portable prayer mat serving as a rak’ah counter, Qibla direction finder, and a mobile worship monitoring system. A prototyping approach was used to produce a portable smart prayer mat, and Rapid Application Development was used to develop a mobile daily worship system. The device comprises an Arduino AT Mega 2560 powered portable prayer mat through a force-sensitive resistor sensor and an HMC 5883L compass module. The device sends the prayer activity to the worship applications in detail. The daily worship monitoring application itself has numerous features that enable users to track their daily worship activities, including the Hijri calendar, the time of compulsory prayers, the fulfillment of sunnah prayers, and fasting. Evaluation results showed that the system detected the rak’ah correctly in each cycle with average pressure to the FSR sensor of 81.36. The average time required to connect with a smartphone was 0.862 seconds. It also functions well as a Qibla finder. The black box testing results showed that the device and application performed effectively. It can send the worship data recapitulation to the application using Bluetooth.
Co-Authors Addini Yusmar Amin Rois Angga Kurniawan Anggraini, Nenny Arif, Farid Dhiya Ul Arini Arini Arini Arini Arini Arini Ariq Cahya Wardhana Assyahid, Muhammad Hudzaifah Azhar Azhar Denny Saputra Deny Saputra Dzul Fadli Rahman Elin Haerani Fajar Nugraha Wahyu Febrian Wahyu Ramadhan Fikriansyah Martunus Fitri Insani Gustri Mulianti Hendra Bayu Suseno Herlino Nanang Husni Teja Sukmana Iik Muhamad Malik Matin Iik Muhammad Malik Matin Imam M Shofi Kahfi Del Vieri Lee Kyung Oh M. Tabah Rosyadi Matin, Iik Muhammad Malik misra hartati Muhammad Yusuf Nashrul Hakiem Nashrul Hakiem Nenny Anggraini Nenny Anggraini, Nenny Oh, Lee Kyung Okfalisa Okfalisa Okfalisa Okfalisa Rahmad Kurniawan Ramadhan, Febrian Wahyu Rizka Hafsari Saputra, David Yusup Setiawan, Rinaldi Setyawan, Okky Bagus Shofi, Imam Marzuki Shofi, Imam Marzuki Siti Atinah Siti Ummi Masruroh Syopiansyah Jaya Putra Teguh Budianto Velia Handayani Viva Arifin Yudi Setiadi Yusra, Yusra