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All Journal Jurnal Teknologi dan Manajemen Informatika JSI: Jurnal Sistem Informasi (E-Journal) JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal ULTIMA InfoSys Mejuajua Journal of Mathematics, Computation and Statistics (JMATHCOS)
Naretha Kawadha Pasemah Gumay
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Implementasi Agile dalam Perancangan Aplikasi Akademik Learning Management System (LMS) Institut Teknologi Kalimantan Berbasis Website Apps Naretha Kawadha Pasemah Gumay; Widya Sartika; Darul Ma'ruf Karim; Dessca Eka Satya Putri; Khalia Rahma Puteri; Bima Agy Bagaskara Saputra; Ricy Firnando; Anna Dwi Marjusalinah; Ardina Ariani
Jurnal Sistem Informasi Vol 15, No 2 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v15i2.22719

Abstract

Kemajuan teknologi yang pesat telah memiliki dampak signifikan pada sistem pendidikan di seluruh dunia, yang mengarah pada adopsi teknologi informasi dalam pendidikan. Penggunaan LMS, seperti Moodle, telah menjadi populer dalam mendukung berbagai jenis pembelajaran. Artikel ini mengeksplorasi penggunaan metode Agile dalam desain dan pengembangan LMS di ITK dan mengidentifikasi tantangan dan hambatan yang mungkin muncul dalam implementasi Agile. Penelitian ini bertujuan untuk mempelajari efektivitas Agile dalam menghasilkan LMS yang responsif dan adaptif, mengidentifikasi hambatan dan kendala selama implementasi Agile, dan memberikan pedoman praktis untuk menggunakan Agile dalam desain LMS. Metodologi Agile memungkinkan LMS ITK untuk mengembangkan perangkat lunak yang berdasarkan pada prinsip-prinsip serupa atau yang fokus pada pengembangan sistem dalam periode pendek yang memerlukan penyesuaian yang cepat oleh para pengembang terhadap perubahan dalam berbagai bentuk. Model scrum yang digunakan pada metode agile memudahkan pengembang dalam melakukan kolaborasi design dengan membagi tugas dalam beberapa sprint sehingga dapat menghasilkan design dalam waktu singkat untuk memudahkan user dalam menjalankan Website App LMS ITK berupa Courses kuliah, dapat belajar bahasa Inggris (Learn English), ikut pelatihan soft skill atau hard skill melalui (Improve My Skills) dan dapat berpartisipasi dalam lomba (Join Competitions). Metode black box digunakan untuk mengevaluasi desain UI dari LMS ITK dan hasilnya adalah seluruh desain dapat dijalankan dengan valid dan siap untuk di publish kepada user.  Kata Kunci:Agile, Scrum, LMS
Peningkatan literasi digital petani melalui sosialisasi pemanfaatan teknologi digital di Desa Cempaka Ogan Komering Ulu (OKU) Timur Nabila Rizky Oktadini; Naretha Kawadha Pasemah Gumay; Anna Dwi Marjusalinah; Allsela Meiriza; Dinda Lestarini; Dinna Yunika Hardiyanti; Sarifah Putri Raflesia
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 6 (2025): November
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i6.34460

Abstract

AbstrakPemanfaatan teknologi digital di sektor pertanian dapat meningkatkan efisiensi dan produktivitas petani. Kegiatan ini bertujuan untuk mensosialisasikan literasi digital dan pengelolaan pengetahuan kepada Kelompok Tani (Poktan) Harapan Kita II di Kecamatan Cempaka Kabupaten Ogan Komering Ulu (OKU) Timur yang berjumlah 29 orang. Adapun petani yang tergabung dalam kelompok tani Harapan Kita II memiliki komoditas pertanian yang beragam seperti padi, tanaman buah seperti pepaya, jambu, dan berbagai jenis sayuran. Pelaksanaan kegiatan pengabdian kepada masyarakat dilaksanakan dengan beberapa tahapan yaitu persiapan, pembuatan materi penyuluhan dan pelatihan, penyuluhan dan pelatihan, pendampingan, serta monitoring dan evaluasi. Hasil kegiatan adalah adanya peningkatan literasi digital petani terkait masalah hama dan penyakit tanaman, yang berimplikasi pada kemampuan mereka dalam mengakses informasi dan berbagi pengetahuan. Diharapkan kegiatan ini dapat terus berlanjut untuk mendukung keberlanjutan pertanian modern. Kata kunci: sosialisasi; literasi digital; pertanian; berbagi pengetahuan. AbstractThe utilization of digital technology in the agricultural sector can enhance farmers’ efficiency and productivity. This activity aims to promote digital literacy and knowledge management among the Harapan Kita II Farmers Group (Poktan) in Cempaka District, Ogan Komering Ulu (OKU) Timur, consisting of 29 members. The farmers in this group cultivate various agricultural commodities such as rice, fruit crops like papaya and guava, as well as a variety of vegetables. The implementation of this community service program was carried out through several stages, including preparation, development of extension and training materials, delivery of extension and training sessions, assistance, and monitoring and evaluation. The results of this activity indicate an improvement in farmers’ digital literacy concerning pest and disease management, which has implications for their ability to access information and share knowledge. It is expected that this program will continue to support the sustainability of modern agriculture. Keywords: socialization; digital literacy; agriculture; knowledge sharing.
Pelatihan Pemanfaatan Teknologi Informasi dan Digital Marketing untuk Meningkatkan Daya Saing UMKM di Desa Sungai Rebo Ali Ibrahim; Endang Lestari Ruskan; Ermatita Ermatita; Fathoni Fathoni; Rizka Dhini Kurnia; Al farissi; Ahmad fali Oklilas; Yadi Utama; Purwita Sari; Naretha Kawadha Pasemah Gumay
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 3 (2026): April 2026
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i3.339

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi lokal, termasuk di Desa Sungai Rebo, Kecamatan Banyuasin I, yang sebagian besar masyarakatnya menggantungkan penghasilan dari usaha kecil di sektor kuliner, kerajinan, dan perdagangan rumah tangga. Meskipun demikian, rendahnya pemanfaatan teknologi informasi serta keterbatasan kemampuan dalam pemasaran digital menyebabkan daya saing produk UMKM di desa tersebut belum berkembang secara optimal. Kondisi ini membuat jangkauan pemasaran produk masih terbatas pada pasar lokal dan belum mampu memanfaatkan peluang pasar yang lebih luas melalui media digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan daya saing UMKM di Desa Sungai Rebo melalui penerapan teknologi informasi dan digital marketing sebagai strategi promosi produk secara berkelanjutan. Program ini dilaksanakan melalui pendekatan pelatihan dan pendampingan yang melibatkan pelaku UMKM sebagai mitra utama dalam setiap tahapan kegiatan, mulai dari identifikasi kebutuhan, pelatihan, hingga evaluasi hasil. Metode kegiatan meliputi asesmen awal untuk memetakan kemampuan digital pelaku UMKM, pelatihan penggunaan teknologi informasi dasar seperti pengelolaan perangkat digital dan aplikasi pengolahan foto produk, serta pelatihan digital marketing yang mencakup pembuatan konten promosi dan pemanfaatan media sosial. Selain itu, dilakukan pendampingan intensif dalam implementasi strategi digital marketing sesuai dengan karakteristik usaha masing-masing peserta. Hasil kegiatan menunjukkan adanya peningkatan kemampuan pelaku UMKM dalam memanfaatkan teknologi informasi untuk mendukung kegiatan usaha dan memperluas jangkauan pemasaran produk mereka. Hasil pre-test dan post-test menunjukkan adanya peningkatan signifikan pada pemahaman dasar teknologi informasi. Sebelum kegiatan, hanya 28% peserta yang memahami penggunaan perangkat digital untuk kegiatan bisnis; setelah pelatihan, tingkat pemahaman meningkat menjadi 78%.
E-Service Quality Analysis of the MyTelkomsel Application Using CSI, IPA, and PGCV Ananda Khoirunnisa; Dwi Rosa Indah; Ardina Ariani; Ari Wedhasmara; Naretha Kawadha Pasemah Gumay; M. Rudi Sanjaya; Mukhlis Febriady
ULTIMA InfoSys Vol 17 No 1 (2026): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v17i1.4497

Abstract

This study evaluates the e-service quality of the MyTelkomsel application in response to ongoing user concerns, particularly slow service response and the limited effectiveness of the automated support system. A structured questionnaire based on the five SERVQUAL dimensions was used and demonstrated strong validity and reliability. Data were collected from one hundred users in Java and Sumatera. The analysis combined three methods: the Customer Satisfaction Index, Importance Performance Analysis, and Potential Gain in Customer Value. The findings show that the application achieved a Customer Satisfaction Index score of 67.75 percent, indicating that users are generally satisfied but expect further improvement. The Importance Performance Analysis recorded a suitability level of 74.54 percent, with several attributes placed in the high-importance low-performance quadrant, including login security, chatbot speed, complaint handling, and personal data protection. The Potential Gain in Customer Value results indicate that chatbot-related attributes and transaction reliability provide the highest potential for increasing customer value. Overall, the study highlights specific service attributes that require priority enhancement to strengthen user satisfaction and service quality.
Comparative Analysis of SMOTE, WMOTE, and ADASYN Oversampling Methods on Multinomial Naive Bayes Performance in Classifying Toddlers Nutritional Status Dewi Sartika; Naretha Kawadha Pasemah Gumay; Rendra Gustriansyah; Yesinta Florensia; Miftahul Falah
Jurnal Teknologi dan Manajemen Informatika Vol. 12 No. 1 (2026): Juni 2026
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v12i1.16438

Abstract

Class imbalance in toddler nutritional status data often reduces the ability of classification models, especially in predicting minority classes. This study aims to analyze the impact of three oversampling techniques, namely SMOTE, WMOTE, and ADASYN, on improving the performance of the Multinomial Naive Bayes (MNB) algorithm. A dataset of 243 data was processed through a preprocessing stage by converting categorical variables using numeric labels. To meet the MNB algorithm's requirement for non-negative data, continuous numeric features (such as birth weight, birth height, weight, height, and age) were normalized using the Min-Max Scaler to the range [0, 1]. This process discretizes continuous values onto a probability scale to ensure feature compatibility with the Multinomial distribution. Data balancing was performed only on the training dataset, where the SMOTE method produced 374 data, ADASYN produced 375 data, and WMOTE produced 373 data. The evaluation results show that although all three oversampling methods experienced a slight decrease in global accuracy, the model's ability to detect minority classes improved, as evidenced by increases in G-Means and Balanced Accuracy. The test results concluded that MNB-ADASYN was the best model for prioritizing high sensitivity to all class labels, while MNB-WMOTE provided the most consistent global accuracy stability while maintaining performance on minority classes.
KNOWLEDGE DISCOVERY OF PUBLIC SATISFACTION ON E-HEALTH PLATFORM THROUGH ENSEMBLE LEARNING AND THEMATIC ANALYSIS Syakillah Nachwa; Ken Ditha Tania; Naretha Kawadha Pasemah Gumay
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.7035

Abstract

As Indonesia’s national digital health platform, the SATUSEHAT application is central to the country's healthcare integration. However, maintaining user satisfaction remains a challenge. This study evaluates public sentiment by analyzing over 30,000 Google Play Store reviews using an ensemble approach of machine learning and thematic analysis. To address substantial data imbalance, five base classifiers were compared with three ensemble models using Random Under-Sampling and SMOTE. Results indicate that the Stacking Ensemble with SMOTE outperformed all other models, achieving an Accuracy of 91.1% and an AUC-ROC of 0.919. Sentiment analysis reveals a critical dissatisfaction rate, with 83.3% of reviews being negative. By mapping user complaints to the ISO/IEC 25010 software quality framework, it was identified that functional suitability and reliability account for 80.7% of the reported issues. This research contributes a robust methodology for Indonesian-language sentiment analysis and demonstrates the utility of ISO/IEC 25010 in translating raw user feedback into actionable software engineering requirements. Practically, the findings provide the Ministry of Health with an evidence-based roadmap to resolve critical barriers in authentication, OTP delivery, and certificate retrieval.
Knowledge Discovery Through Sentiment Analysis and Topic Modeling of BCA Mobile and MyBCA Salsa Anindya Putri; Ken Ditha Tania; Naretha Kawadha Pasemah Gumay
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9782

Abstract

The swift adoption of mobile banking in Indonesia highlights the growing demand for secure and innovative digital financial services. PT Bank Central Asia Tbk (BCA) offers two primary applications, BCA Mobile and myBCA, catering to millions of users. Gaining insight into user perceptions is crucial for enhancing service quality and building trust. This research uses sentiment analysis and topic modeling on Google Play Store reviews for both applications to facilitate knowledge discovery. Reviews were labeled using IndoBERT, and seven classification models were assessed, including five machine learning methods and two deep learning techniques. The Gated Recurrent Unit (GRU) model demonstrated the highest performance, achieving an accuracy of 89.70%. In the realm of topic modeling, a comparison between Latent Dirichlet Allocation (LDA) and BERTopic revealed that BERTopic delivered the highest coherence score of 0.6244, identifying eight significant negative topics. The findings indicate that BCA Mobile users frequently reported issues such as login failures, unexplained balance deductions, and missing features, while myBCA users encountered problems like post-update errors, login difficulties, and challenges with face verification. This research aligns with Sustainable Development Goal (SDG) 9 by showing how knowledge discovery from user reviews can promote innovation and enhance resilient, user-centered digital banking infrastructures.
Comparative Sentiment Analysis and Topic Modeling of Dola AI User Reviews for Knowledge Discovery Nadia Ramadhani; Ken Ditha Tania; Naretha Kawadha Pasemah Gumay
Journal of Applied Informatics and Computing Vol. 10 No. 5 (2026): October 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i5.13834

Abstract

As artificial intelligence (AI) technologies become more widely adopted, users increasingly express their experiences through online reviews, providing valuable insights into user satisfaction and opportunities for application improvement. This study compares the performance of Support Vector Machine (SVM), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) for sentiment classification of Dola AI user reviews and applies Latent Dirichlet Allocation (LDA) to identify the dominant topics within each sentiment category. The research followed the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework using 28,226 Google Play Store reviews collected through web scraping. The reviews were represented using Term Frequency–Inverse Document Frequency (TF-IDF), class imbalance was addressed using the Synthetic Minority Oversampling Technique (SMOTE), and model performance was evaluated through 5-fold stratified cross-validation using accuracy, weighted precision, weighted recall, and weighted F1-score. The results showed that SVM achieved the highest average performance, with an accuracy of 77.68% and a weighted F1-score of 80.02%, followed by Naïve Bayes with a weighted F1-score of 78.60% and K-Nearest Neighbor with 70.42%. Furthermore, LDA identified six topics in positive reviews, three topics in neutral reviews, and two topics in negative reviews. Positive reviews mainly highlighted the application's ease of use, AI capabilities, and conversational features, whereas negative reviews primarily focused on application performance, the quality of AI-based image editing, and advertisements. These findings provide deeper insights into user perceptions and offer data-driven recommendations for improving the quality and user experience of the Dola AI application.
Co-Authors Ahmad Fali Oklilas Al Farissi Ali Ibrahim Allsela Meiriza, Allsela Ananda Khoirunnisa Anna Dwi Marjusalinah Ardina Ariani Ari Wedhasmara Bima Agy Bagaskara Saputra Darul Ma'ruf Karim Dessca Eka Satya Putri Dewi Sartika Dinda Lestarini Dinna Yunika Hardiyanti Dwi Rosa Indah Endang Lestari Ruskan Ermatita - Fathoni - Ken Ditha Tania Khalia Rahma Puteri M. Rudi Sanjaya Miftahul Falah Mukhlis Febriady Nadia Ramadhani Oktadini, Nabila Rizky Purwita Sari Rendra Gustriansyah Ricy Firnando Rizka Dhini Kurnia Salsa Anindya Putri Sarifah Putri Raflesia Syakillah Nachwa Widya Sartika Yadi Utama Yesinta Florensia