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All Journal Journal of Information Systems and Informatics Algoritme Jurnal Mahasiswa Teknik Informatika Klik - Jurnal Ilmu Komputer Jurnal Pengabdian Masyarakat Ilmu Komputer Indonesian Journal of Innovation and Educational Technology
Serly Oktarina
Universitas Sumatera Selatan
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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PELATIHAN MAIL MERGE UNTUK MENINGKATKAN ADMINISTRASI SURAT-MENYURAT PENGURUS RT 56 KELURAHAN BUKIT LAMA Ubaidillah Ubaidillah; Ruswa Dwipa; Serly Oktarina; Vanesha Rahmania; Rikkie Dekas; Jailani Jailani
Jurnal Pengabdian Masyarakat Ilmu Komputer Vol. 3 No. 2 (2026): Mei
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jpmik.v3i2.4166

Abstract

Administrasi surat-menyurat merupakan salah satu tugas penting pengurus RT dalam memberikan pelayanan kepada masyarakat. Namun, proses pembuatan surat masih banyak dilakukan secara manual sehingga membutuhkan waktu yang relatif lama dan berpotensi menimbulkan kesalahan dalam penulisan data warga. Salah satu solusi untuk meningkatkan efisiensi administrasi adalah memanfaatkan fitur Mail Merge pada Microsoft Word yang mampu menghasilkan dokumen secara otomatis berdasarkan data yang tersimpan pada Microsoft Excel. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan pengurus RT 56 Kelurahan Bukit Lama dalam menggunakan fitur Mail Merge untuk mendukung administrasi surat-menyurat. Metode pelaksanaan kegiatan meliputi observasi kebutuhan mitra, penyusunan materi, penyampaian materi, demonstrasi, praktik langsung, diskusi, dan evaluasi melalui pretest, posttest, serta penilaian praktik peserta. Kegiatan diikuti oleh enam peserta yang terdiri atas Ketua RT dan pengurus RT. Hasil evaluasi menunjukkan bahwa nilai rata-rata peserta meningkat dari 58,3 pada pretest menjadi 91,7 pada posttest atau mengalami peningkatan sebesar 57,3%. Selain itu, 100% peserta mampu membuat dokumen surat menggunakan fitur Mail Merge secara mandiri sesuai dengan studi kasus yang diberikan. Hasil tersebut menunjukkan bahwa pelatihan berhasil meningkatkan pemahaman dan keterampilan peserta dalam memanfaatkan Mail Merge sehingga proses administrasi surat-menyurat menjadi lebih cepat, akurat, dan efisien. Kegiatan ini diharapkan dapat mendukung digitalisasi administrasi di lingkungan RT serta meningkatkan kualitas pelayanan kepada masyarakat.
Analisis Pemanfaatan Artificial Intelligence dalam Transformasi Visual untuk Meningkatkan Efektivitas Manajemen Proyek Teknologi Informasi di PT Nexwave Indonesia Palembang Arda Prayoga; Serly Oktarina
Indonesian Journal of Innovation and Educational Technology Vol. 1 No. 2 (2026): Edisi Juli-Desember 2026
Publisher : Indonesian Publication Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67434/ijiet.v1i2.2670

Abstract

This study explores the utilization of Artificial Intelligence (AI) in visual transformation to enhance the effectiveness of project management, specifically examining the relationship between AI technology and project management practices. The rapid advancement of information technology requires organizations to manage projects more effectively and efficiently. In IT project management, presenting clear and informative data is a critical factor in supporting decision-making. However, transforming data into visual formats often requires considerable time and specialized skills, which can hinder the efficiency of information delivery. With these technological advancements, AI has emerged as a key solution for automating data processing and visual transformation. This study aims to analyze the utilization of AI in visual transformation to support IT project management. A qualitative method with a descriptive case study approach was employed, collecting data through observation, interviews, and documentation of AI implementation in project data visualization.
Rancang Bangun Desain UI/UX Pada Sistem Informasi Manajemen Sampah di Daerah X Irfan Candra Ramadhan; Adhis Shifa Aulia; Rizky Amalia; Muzzadi; Sri Rahayu; Serly Oktarina
Klik - Jurnal Ilmu Komputer Vol. 6 No. 1 (2025): Klik - Jurnal Ilmu Komputer
Publisher : Fakultas Ilmu Komputer Universitas Sumatera Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56869/klik.v6i1.617

Abstract

Abstrak— Sampah merupakan permasalahan lingkungan yang signifikan. Untuk mengatasi kendala pencatatan manual dalam pengelolaan bank sampah, penelitian ini merancang Sistem Informasi Manajemen Sampah berbasis web dengan pendekatan Systematic Literature Review (SLR) dan Prototyping. SLR digunakan untuk mengidentifikasi kebutuhan pengguna dan fitur utama sistem, sedangkan Prototyping memungkinkan pengembangan desain UI/UX secara iteratif. Sistem ini menyediakan fitur manajemen data admin, nasabah, sampah, dan transaksi, dengan antarmuka yang mudah digunakan dan responsif. Pengujian menggunakan metode Black Box Testing menunjukkan hasil yang sesuai dengan ekspektasi. Sistem ini diharap mampu mengoptimalkan efisiensi dalam pengelolaan sampah sekaligus mendukung inisiatif daur ulang yang melibatkan partisipasi aktif masyarakat sekitar.
Explainable XGBoost-Based Prediction of Student Reading Interest Using Digital Learning and Reading Behavior Indicators Delpiah Wahyuningsih; Heki Aprianto; Lili Indah Sari; Wishnu Aribowo Probonegoro; Sri Rahayu; Serly Oktarina
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1698

Abstract

Reading interest is an important indicator of academic engagement and lifelong learning, yet its relationship with digital learning behavior remains underexplored in higher education. This study proposes an explainable machine learning framework to predict student reading interest using digital learning behavior, reading habits, and demographic characteristics. Data were collected through self-reported questionnaires from 300 Indonesian university students. Reading interest was formulated as a binary target variable, and three feature scenarios were evaluated: digital behavior only (S1), reading behavior only (S2), and an integrated model combining all features (S3). The dataset was divided using an 80:20 stratified train–test split, with SMOTE applied only to the training data to address class imbalance while preventing information leakage. S3 achieved the highest ROC-AUC (91.92%) and cross-validation F1-score (86.62% ± 3.34%), while S1 obtained the same test accuracy (84.29%) and a slightly higher test F1-score (85.33%). SHAP analysis provided interpretability by identifying daily reading duration and monthly book count as key predictors. These findings indicate that multidimensional behavioral indicators can support early student-engagement screening systems. However, results from a single institutional context require cautious interpretation.
Stability-XAI: Analisis Stabilitas Fitur dan Interpretabilitas Model Machine Learning pada Prediksi Penyakit Jantung Ubaidillah Ubaidillah; Muhammad Taufik Roseno; Serly Oktarina
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 7 No 1 (2026): October 2026 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v7i1.17538

Abstract

Heart disease requires early detection with high accuracy. This study proposes a Stability-XAI approach integrating feature stability analysis and Explainable Artificial Intelligence (XAI) to enhance the transparency of heart disease prediction models. Utilizing four UCI Machine Learning Repository datasets (Cleveland, Hungarian, Switzerland, Statlog) totaling 990 samples, the workflow includes preprocessing, feature selection (ANOVA F-score, Mutual Information, RFE), Optuna hyperparameter optimization across Logistic Regression, Random Forest, and XGBoost models, and SHAP interpretation. Results demonstrate that Optimized Random Forest achieves peak performance with 92.63% accuracy and 96.80% ROC-AUC. Features cp, ca, and exang exhibited the highest consistency (stability score 1.000), while cp, ca, and thal contributed most significantly according to SHAP analysis. The Stability-XAI approach effectively produces a heart disease prediction model that is high-performing, transparent, and interpretable.
Comparing CNN Models for Rice Disease Detection: ResNet50, VGG16, and MobileNetV3-Small Muhammad Taufik Roseno; Serly Oktarina; Yuwinti Nearti; Hadi Syaputra; Nirmala Jayanti
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.865

Abstract

The Oryza sativa (rice) plant is an important staple food source, especially in the Asian region. Rice production is often disrupted by diseases such as Brown Spot, Leaf Scald, Rice Blast, Rice Tungro, and Sheath Blight, which can reduce yield and crop quality. This research aims to classify rice plant diseases using a deep learning approach with Convolutional Neural Networks (CNN) architecture, namely ResNet50, VGG16, and MobileNetV3-Small. The dataset used is Rice Leaf Disease Classification which consists of 1305 images with five disease labels. The data is divided into training, validation, and testing sets with proportions of 70%, 15%, and 15%. The results showed that the MobileNetV3-Small model provided the best accuracy on the test data of 79%, while VGG16 achieved the validation accuracy of 78.84%. Based on these results, MobileNetV3-Small is considered the most superior model for rice disease classification. This research shows the great potential of applying deep learning in automatic rice disease detection.
Development of a Digital Village Concept based on Information Technology Infrastructure and Strategy Management to Facilitate SPBE Ogan Ilir Regency Serly Oktarina; Muhammad Taufik Roseno; Ubaidillah Ubaidillah; Darius Antoni; Lailatuz Zahro; Hadi Syaputra
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.875

Abstract

Technology in the digital era is currently progressing very rapidly. This is marked by the increasingly massive number of social media users in everyday life. Survey results from the Indonesian Internet Service Providers Association (APJII) in 2022 recorded that the number of internet users in Indonesia reached 196.7 million people. This number increased by 23.5 million or 8.9% compared to 2018. With information technology and the internet, information is now becoming more easily spread and can be accessed by all levels of society thanks to the internet, not just people in urban areas, but people living there. in rural areas too. The Ogan Ilir Regency Government initiated information technology infrastructure including village internet or Digital Village to solve the problem of inequality in digitalization of society in rural and urban areas. Development and implementation of a digital village is a program that implements electronic-based government system (SPBE) services to the community and empowers the community based on the use of technology. This research aims to conduct a survey of information technology infrastructure to identify village potential, marketing and accelerating access and public services. Apart from that, this research also identifies digital-based life patterns of people in rural and urban areas, as well as to advance economic development in rural areas to improve SPBE services in Ogan Ilir Regency. The method used is a quantitative method for surveying and mapping the use of information technology in villages and ultimately producing the concept of an independent digital village. Research data was obtained from surveys and FGDs with the Ogan Ilir district government, village heads, village communities and micro, small and medium enterprises. Meanwhile, secondary data will be obtained through the results of MSME and village profiles from the Central Statistics Agency.
Co-Authors Adhis Shifa Aulia Arda Prayoga Darius Antoni Dekas, Rikkie Delpiah Wahyuningsih Hadi Syaputra Heki Aprianto Irfan Candra Ramadhan Jailani Jailani Lailatuz Zahro Lili Indah Sari Muhammad Taufik Roseno Muzzadi Nirmala Jayanti Rizky Amalia Ruswa Dwipa Sri Rahayu Sri Rahayu Ubaidillah Ubaidillah Ubaidillah Ubaidillah Vanesha Rahmania Wishnu Aribowo Probonegoro Yuwinti Nearti