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All Journal Semantik Jurnal Simetris Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Jurnal Transformatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnal Informatika Upgris International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budimas : Jurnal Pengabdian Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Intech : Information Technology Journal of UMUS JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Vivabio : Jurnal Pengabdian Multidisiplin Buletin Poltanesa Abdi Masya Jurnal Pengabdian Multidisiplin Journal Of Human And Education (JAHE) Community: Jurnal Pengabdian Pada Masyarakat Journal of Computing Theories and Applications Jurnal Informatika: Jurnal Pengembangan IT LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Teknik Informatika dan Teknologi Informasi
Etika Kartikadarma
Universitas Dian Nuswantoro
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Penggunaan Metode Rapid Application Development (RAD) untuk Merancang Aplikasi Absensi QR Code Berbasis Website Endri Mujiono; Yani Parti Astuti; Etika Kartikadarma; Edy Mulyanto; Erlin Dolphina; Sindhu Rakasiwi
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 2 (2025): Agustus: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i2.5604

Abstract

This study aims to design and develop a QR Code-based attendance application using the Rapid Application Development (RAD) method, which is implemented at Bina Utama Kendal Vocational High School. The application was created to overcome the limitations of the manual attendance system currently in use, such as vulnerability to data loss, difficulties in maintaining accurate records, and inefficiency in attendance recapitulation. The RAD method was chosen because it emphasizes user involvement throughout the development process, ensuring that the resulting system meets user needs. The development stages included requirement planning, design, system development, and implementation. This web-based attendance application uses QR Code technology to record student attendance quickly, accurately, and in real time. Each student’s QR Code is scanned to mark their presence, which minimizes errors and prevents attendance fraud. In addition, the system includes features for managing student data, generating automatic attendance reports, and providing real-time monitoring for teachers and administrators.The system was tested using the Black Box method, which confirmed that all features function correctly and meet the requirements specified in the design phase. Furthermore, a user satisfaction survey conducted with 150 respondents (teachers, students, and staff) indicated a very high level of acceptance, with an average of 94.25% respondents strongly agreeing on the ease of use, accuracy, and benefits of this application. Overall, the study demonstrates that the QR Code-based attendance application significantly improves the efficiency, reliability, and accuracy of attendance management at Bina Utama Kendal Vocational High School.
Integrating Hybrid Statistical and Unsupervised LSTM-Guided Feature Extraction for Breast Cancer Detection De Rosal Ignatius Moses Setiadi; Arnold Adimabua Ojugo; Octara Pribadi; Etika Kartikadarma; Bimo Haryo Setyoko; Suyud Widiono; Robet Robet; Tabitha Chukwudi Aghaunor; Eferhire Valentine Ugbotu
Journal of Computing Theories and Applications Vol. 2 No. 4 (2025): JCTA 2(4) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.12698

Abstract

Breast cancer is the most prevalent cancer among women worldwide, requiring early and accurate diagnosis to reduce mortality. This study proposes a hybrid classification pipeline that integrates Hybrid Statistical Feature Selection (HSFS) with unsupervised LSTM-guided feature extraction for breast cancer detection using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Initially, 20 features were selected using HSFS based on Mutual Information, Chi-square, and Pearson Correlation. To address class imbalance, the training set was balanced using the Synthetic Minority Over-sampling Technique (SMOTE). Subsequently, an LSTM encoder extracted non-linear latent features from the selected features. A fusion strategy was applied by concatenating the statistical and latent features, followed by re-selection of the top 30 features. The final classification was performed using a Support Vector Machine (SVM) with RBF kernel and evaluated using 5-fold cross-validation and a held-out test set. Experimental results showed that the proposed method achieved an average training accuracy of 98.13%, F1-score of 98.13%, and AUC-ROC of 99.55%. On the held-out test set, the model reached an accuracy of 99.30%, precision of 100%, and F1-score of 99.05%, with an AUC-ROC of 0.9973. The proposed pipeline demonstrates improved generalization and interpretability compared to existing methods such as LightGBM-PSO, DHH-GRU, and ensemble deep networks. These results highlight the effectiveness of combining statistical selection and LSTM-based latent feature encoding in a balanced classification framework.
Pemberdayaan Mahasiswa Melalui Bisnis Kopi Berobak Berbasis Keterampilan Interpersonal dan Kewirausahaan Yani Parti Astuti; Erwin Yudi Hidayat; Abu Salam; Cinantya Paramita; Etika Kartikadarma; Adhitya Nugraha; Junta Zeniarja
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 2 (2026): MEI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i2.3340

Abstract

Pendidikan tinggi modern menuntut mahasiswa untuk tidak hanya unggul secara akademis, tetapi juga memiliki keterampilan praktis seperti kewirausahaan dan interpersonal. Pengembangan jiwa kewirausahaan mahasiswa juga menjadi salah satu upaya penting dalam menciptakan generasi muda yang mandiri, kreatif, dan produktif. Kegiatan ini merupakan implementasi pembelajaran berbasis pengalaman (experiential learning) dalam mata kuliah Keterampilan Interpersonal melalui realisasi bisnis nyata, yaitu “DiSanka Kopi,” sebuah usaha kopi gerobak keliling. Kegiatan ini bertujuan untuk menerapkan teori kewirausahaan, mulai dari perencanaan, analisis keuangan, operasional, hingga pemasaran, serta mengasah kemampuan kerja sama tim, komunikasi, dan pemecahan masalah. Usaha ini telah beroperasi selama dua bulan di lingkungan strategis di Jalan Baru dekat kampus Universitas Diopnegoro Fakultas Psikologi, menyasar segmen mahasiswa dan masyarakat umum. Metode pelaksanaan meliputi riset, pengembangan produk, analisis HPP, branding, dan eksekusi operasional harian. Hasil kegiatan menunjukkan respons pasar yang positif dengan penjualan rata-rata 40 cup per hari dan berhasil mencapai titik impas (BEP) dalam waktu singkat. Analisis keuangan menunjukkan Return on Investment (ROI) yang diproyeksikan tercapai dalam 2,14 bulan, membuktikan kelayakan model bisnis. Lebih penting, proyek ini berhasil menjadi sarana efektif bagi mahasiswa untuk mengembangkan kompetensi interpersonal dan manajerial secara langsung di lapangan.
Pendampingan bagi Siswa – Siswi MI Miftahul Hidayah dalam Perilaku Hidup Bersih dan Sehat untuk Deteksi Kesehatan Usus Menggunakan Software Aplikasi Erwin Yudi Hidayat; Yani Parti Astuti; Abu Salam; Cinantya Paramita; Dhita Aulia Octaviani; Etika Kartikadarma; Erlin Dolphina; Catur Supriyanto
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 1 (2026): JANUARI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i1.3194

Abstract

Setiap manusia pasti menginginkan sehat tak terkecuali anak – anak dan juga orang dewasa. Di usia anak – anak, mereka belum memikirkan bagaimana agar hidup ini menjadi sehat. Untuk itu perlu adanya pendampingan dan juga arahan kepada anak – anak tentang perilaku hidup bersih dan sehat. Hal ini akan diterapkan tim pengabdi dari Udinus kepada siswa MI Miftahul Hidayah. Bersama dengan pakar kesehatan dari Poltekkes Semarang merumuskan hal apa yang akan diberikan kepada siswa MI Miftahul Hidayah. Sehingga muncullah ide bahwa kesehatan bisa dimulai dengan diri sendiri dengan melakukan perilaku hidup bersih dan sehat. Oleh karena itu dilakukan pendampingan kepada siswa tentang konsumsi jajanan yang tidak menyimpang dari nilai gizi untuk mempertahankan kesehatan usus. Untuk itu siswa dikenalkan sebuah software aplikasi yang mengetahui atau mendeteksi kesehatan usus setiap orang dengan menginput data diri siswa masing – masing. Selain pendampingan dan arahan tentang konsumsi jajanan, siswa juga diberikan penyuluhan tentang kebersihan lingkungan yang harus dijaga agar tidak dihinggapi penyakit seperti demam berdarah yang saat ini meresahkan masyarakat. Karena demam berdarah disebabkan oleh nyamuk yang sangat menyukai tempat yang tidak bersih dan air yang tergenang. Dengan adanya pendampingan penyuluhan ini, diharapkan siswa selalu mengkonsumsi jajanan yang tidak meninggalkan nilai gizi dan juga selalu memperhatikan kebersihan lingkungan di manapun berada. Selain itu, siswa juga akan menyadari bahwa ilmu teknik informatika bisa mendeteksi kesehatan kita dengan software aplikasi. Melalui aplikasi yang diterapkan, maka siswa siswi akan mengetahui kesehatan ususnya masing – masing..
Implementation of Virtual Banking in E-Commerce Sales of Jamu Products Tri Listyorini; Etika Kartikadarma; Devva Ricovani Susanto
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.433

Abstract

Herbal medicine is familiar in the world of health, because there are no side effects if processed correctly. In Kudus, there are SMEs that process Klanceng into various health drinks, namely CV Jamu Klanceng. Marketing of Jamu Klanceng is still manual, namely opening outlets for sales. In addition, relying on sales to promote products from Jamu Klanceng. This technique causes sales of Jamu Klanceng to gradually decline, eroded by sales that have utilized information technology. This research combines information technology to play a role in marketing this product from Jamu Klanceng. The system to be built is based on a website, where payments are made using virtual banking. With this kind of payment, you avoid fraudulent orders and scams that often occur in this online era. The method in this study uses the waterfall method. Data collection is by conducting interviews and observations to CV Jamu Klanceng. In this research the design is compiled using a flow chart, which serves to design the system to fit the existing flow. This design uses Entity Relationship Diagram, Data Flow Diagram and relations between tables. The next step is to implement the design into the Hypertext Pre-processors programming language and use the MySQL database. The system that was built made the marketing and sales of Jamu Klanceng efficient and effective. There is no limit on sales as long as stock lasts, orders can be made for 24 hours. Unlike offline selling, there are time and effort limits.
A Sentiment Analysis of Free Nutritious Meal Program on Platform X: Comparing Naive Bayes, SVM, Random Forest, and IndoBERT Alrijal Nur Ilham; Etika Kartikadarma
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12959

Abstract

The Free Nutritious Meal Program (MBG), launched by the Indonesian government in January 2025, generated various public responses on social media, particularly on platform X. This study aims to analyze public sentiment toward the MBG Program and compare the performance of four sentiment classification methods: Naive Bayes, Support Vector Machine (SVM), Random Forest, and IndoBERT. The dataset was collected through tweet crawling using the keywords “MBG” and “Makan Bergizi Gratis” during the period of July–December 2025, resulting in 1,906 Indonesian-language tweets. The preprocessing stage included cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Sentiment labeling was performed using the InSet Lexicon and produced 1,113 negative tweets and 793 positive tweets. Manual validation on part of the dataset was conducted by two independent annotators and achieved a Cohen’s Kappa score of 0.78, indicating substantial agreement. For classical machine learning models, feature extraction was carried out using TF-IDF, while IndoBERT used contextual text representations without stemming. Class imbalance in classical models was handled using SMOTE, whereas IndoBERT applied class weighting. The experimental results show that IndoBERT achieved the best performance with an accuracy of 92.93%. Among the classical models, SVM produced the highest performance with an accuracy of 92.15%, followed by Naive Bayes and Random Forest. Word frequency analysis also revealed that positive sentiment was mainly associated with support for the program and nutrition-related topics, while negative sentiment was dominated by concerns about food safety, budget management, and criticism of the program. Based on the findings, IndoBERT is more effective in understanding the context of Indonesian-language tweets. However, TF-IDF-based classical models, especially SVM, still provide competitive performance with lower computational requirements, making them suitable for sentiment analysis in public policy studies.
A Comparison of Classical Machine Learning and IndoBERT on Sentiment Analysis of Danantara Program in X Silvan Pradana; Etika Kartikadarma
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13280

Abstract

The rapid growth of social media has made it a primary channel for the public to express opinions on national strategic economic policies, including the establishment of the Danantara entity. This study aims to map public sentiment on Platform X and compare the performance of classical frequency-based architectures with transformer-based models. A common research gap in previous studies is the reliance on Bag-of-Words models, which fail to capture local context and sarcasm in informal text. A total of 9,525 tweets from the period January–May 2025 were collected via crawling and labeled using a hybrid approach combining InSet Lexicon and manual validation by experts (Cohen’s Kappa = 0.81). To address significant class imbalance (66.5% negative), SMOTE was applied to classical models. Experimental results reveal a significant performance gap: the classical TF-IDF + SVM model achieved a positive-class F1-score of only 59% due to feature distortion caused by SMOTE in the TF-IDF space, while the fine-tuned IndoBERT model substantially outperformed it with a global accuracy of 95.80% and a positive-class F1-score of 81%. These findings demonstrate that the deep transformer approach is far more robust in extracting semantics from informal Indonesian social media text, with practical implications for public policy decision-making.
A Sustainable Computational Framework for Breast Cancer Screening: Optimizing High-Dimensional Feature Spaces via MVP-PCA for Resource-Constrained Environments Etika kartikadarma; Ahmad Zainul Fanani; Pujiono; Affandy
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3858

Abstract

The rapid integration of Electronic Health Records (EHR) demands the efficient processing of high-resolution medical images. However, deep learning architectures applied to mammography classification often produce massive, high-dimensional feature spaces susceptible to the curse of dimensionality and anatomical noise. Furthermore, conventional dimensionality reduction approaches tend to cause over-reduction, which destroys crucial microcalcification textures. To address these challenges, this study proposes a CPU-efficient hybrid dimensionality reduction framework integrating Mean Vector Projection (MVP) and Principal Component Analysis (PCA) on features extracted by SqueezeNet. The MVP layer acts as a crucial pre-conditioner to stabilize intra-class variance before PCA decomposition. Experimental results demonstrate that the proposed MVP-PCA framework successfully linearizes the feature space and achieves an extreme compression rate of 99.11%, reducing 264,702 features to 2,355 essential components. The peak accuracy reaches 97.58% with a minimal False Negative rate (2 cases), providing a sustainable diagnostic solution for healthcare facilities with limited technological resources.
Web-Based Complaint Handling System:A Pre-Post Cohort Evaluation of E-Service Quality Melati Oktafiyani; Etika Kartikadarma; Handy Nur Cahya; Wikan Isthika; Dayangku Azriani binti Awang Ismail
International Journal of Artificial Intelligence Research Vol 10, No 2 (2026): December
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v10i2.1753

Abstract

Customer complaint management remains a critical challenge because fragmented communication channels act as an informational “black box” for consumers, increasing uncertainty and weakening organizational trust. While prior studies focus primarily on technical deployment or post-adoption satisfaction, empirical evidence isolating how system-driven transparency drives trust recovery remains scarce. This study designs and evaluates a web-based Customer Complaint Handling System (CCHS) built on a three-tier Model–View–Controller (MVC) architecture to address this gap. Methodologically, a single-cohort longitudinal pretest–posttest design was executed involving 84 identical participants tracked over two sequential 30-day operational periods. Data were collected using a 20-item instrument covering five dimensions adapted from Electronic Service Quality (E-S-QUAL) and Information Systems Success frameworks. Reliability was confirmed via Cronbach’s alpha (?pre = 0.842; ?post = 0.891). Quantitative tracking revealed highly significant positive shifts across all dimensions (p < 0.001) following system implementation. Notably, Transparency & Information achieved the most substantial growth (? = +3.09; 213.1%), heavily driven by real-time status visibility (? = +3.40), while Satisfaction & Trust increased by +2.44 points (120.8%). Conversely, Fairness & Resolution Quality exhibited bounded improvement (? = +1.10), proving that automated architectures act as operational facilitators rather than replacements for human judgment. These findings demonstrate that digital process visibility operates as an independent driver of trust recovery, offering actionable guidance for digital service governance. 
Co-Authors Abu Salam Adhitya Nugraha Aditya Wahyu Ramadhan Affandy Affandy Affandy Affandy Afida, Dita Ahmad Zainul Fanani Ajib Susanto Akbar Dwi Syahputra Alrijal Nur Ilham Alvin Jaya Hulu, Alvin Angga Apriano Hermawan Arnold Adimabua Ojugo Ashari Juang, Ashari Astuti, Yani Parti Azhara Devi Sandi Bimo Haryo Setyoko Catur Supriyanto Christy Atika Sari Cinantya Paramita Dayangku Azriani binti Awang Ismail De Rosal Ignatius Moses Setiadi Desi Purwanti Devva Ricovani Susanto Dhani, Iqbal Dhita Aulia Octaviani Dianna Yanuaresta Dico Tri Rosandi Doheir, Mohamed Dwi Puji Prabowo Edy Mulyanto Eferhire Valentine Ugbotu Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto, Egia Rosi Ekaprana Wijaya Endri Mujiono Erika Devi Udayanti Erlin Dolphina Erwin Yudi Hidayat Fahmi Amiq Fahri Firdausillah Farikh Al Zami Fauzi Adi Rafrastara Filmada Ocky Saputra Habib Mustofa Hafidhoh, Nisa'ul Hafidhoh, Nisa’ul Hafidhoh, Nisa’ul Handy Nur Cahya Heribertus Himawan Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ihwati Ummi Iskandar, Marcelino Johary, Lakui Junta Zeniarja Kumoro, Imanuel Dimas Cahyo Kurniawan, Defri Kusni Ingsih L. Budi Handoko Lakui Johary Marcelino Iskandar Meilani Dwi Permatasari Melati Oktafiyani Muhamad Ni&#039;am Syukri Roni Asmi Muhammad Hafidz Muljono, - Najma Fatimah, Nandhita Nathaniel Alexander Nila Tristiarini, Nila Nisa&#039;ul Hafidhoh Nova Rijati Octara Pribadi Pujiono Pujiono Pujiono Purwanto Purwanto Rahma, Khalida Nur Raihan Yusuf Ricardus Anggi Pramunendar Rino Agung Robet Robet Rohman, Muhammad Syaifur Safa Firdaus, Muhammad Argya Sakti, Maulana Bima Saputra, Filmada Ocky Saraswati, Galuh Wilujeng Sari Ayu Wulandari Sari Wijayanti Sari Wijayanti Sari Wijayanti Setyawati, Vilda A. V. Silvan Pradana Sindhu Rakasiwi Sudibyo, Usman Sugiyanto - Suyud Widiono T. Sutojo Tabitha Chukwudi Aghaunor Tri Listyorini Trisnapradika, Gustina Alfa Usman Sudibyo Utomo, Danang Wahyu Wardatunizza, Indah Wibowo, Alrico Rizki Widayat Yutriatmansyah, Widi Widi Widayat Yutriatmansyah Wikan Isthika Wikan Isthika, Wikan Winarsih, Nurul Anisa Sri Yani Parti Astuti Yani Parti Astuti Yunita Kemala Sari Yutriatmansyah, Widi Widayat Yutriatmansyah, Widi Widayat Zaenal Arofi, Muhammad Labib