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All Journal Information Technology and Telematics Dinamik Jurnal Ilmiah Dinamika Teknik Elkom: Jurnal Elektronika dan Komputer Scientific Journal of Informatics Jurnal Ilmiah Giga Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science Jurnal Teknologi Sistem Informasi dan Aplikasi IKRA-ITH ABDIMAS J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Informasi dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JURNAL MAHAJANA INFORMASI Jurnal Abdimas Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pengabdian kepada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Pengabdian Pada Masyarakat Jurnal Kabar Masyarakat SmartComp Fundamentum: Jurnal Pengabdian Multidisiplin Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Andan Jejama: Indonesian Journal Of Community Engagement Jurnal Teknik Informatika dan Teknologi Informasi
Veronica Lusiana
Universitas Stikubank (UNISBANK) Semarang
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PENGENALAN CHATBOT AI PADA GURU SEKOLAH MINGGU UNTUK MEMBUAT ILUSTRASI CERITA Budi Hartono; Veronica Lusiana; Antono Adhi; Mohammad Riza Radyanto
J-ABDI: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 3: Agustus 2025
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pengabdian kepada masyarakat (PKM) ini bertujuan untuk memperkenalkan penggunaan teknologi chatbot AI kepada para guru sekolah minggu Gereja Kristen Jawa, Banyumanik, Semarang. Guru sekolah minggu dihadapkan pada tantangan untuk menyampaikan cerita atau kisah di dalam Alkitab secara menarik bagi anak-anak sekolah minggu, sehingga mereka bisa lebih mudah memahami cerita dan pesan tersebut. Tim PKM melihat potensi pemanfaatan chatbot AI yang sedang berkembang pesat, antara lain ChatGPT, Gemini, dan Popai-Pro, untuk membuat gambar ilustrasi cerita melalui pendampingan dan praktik kepada guru sekolah minggu. Teknologi ini dapat membantu guru dalam menyampaikan materi cerita dengan gambar ilustrasi yang lebih menarik.
MENINGKATKAN DAYA TARIK PEMBELAJARAN INFORMATIKA MELALUI DESAIN VISUAL DENGAN CANVA DI SMA NEGERI 1 BRINGIN KABUPATEN SEMARANG Wismarini, Theresia Dwiati; Murti, Hari; Lestariningsih, Endang; Redjeki, Rara Sriartati; Hartono, Budi; Anwar, Sariyun Naja; Lusiana, Veronica; Ardhianto, Eka
Intimas Vol 5 No 2 (2025)
Publisher : Fakultas Teknologi Informasi dan Industri Unisbank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/intimas.v5i2.10149

Abstract

The rapid development of information technology requires teachers to present learning materials in a creative and visual manner. Informatics teachers at SMA Bringin face challenges in creating visually engaging teaching materials due to limited graphic design knowledge, which results in low student engagement and less effective delivery of content. To address this issue, a community service activity in the form of Canva training for informatics teachers at SMA Bringin was conducted. This activity followed a participatory and hands-on approach (learning by doing). The training took place over two days in the school's computer lab and was attended by 15 informatics teachers as well as several other subject teachers. Evaluation results showed 35% improvement in participants' understanding of Canva, based on a comparison of pre-test and post-test scores. Participants also displayed high creativity and enhanced visual skills in their final tasks, which involved creating educational materials using Canva. The satisfaction survey revealed that 93% of participants found the training highly beneficial and expressed their intention to adopt Canva in regular teaching. Overall, this training successfully improved the digital literacy of teachers, particularly in designing visual teaching media using Canva. Participants provided feedback suggest the organization of follow-up training focusing on animation or interactive video-based learning.
PEMANFAATAN TEKNOLOGI DIGITAL MARKETING DALAM UPAYA PUBLIKASI DAN PROMOSI DESA WISATA Imam Husni Al Amin; Dewi Handayani U.N; Budi Hartono; Veronica Lusiana
ANDAN JEJAMA: Indonesian Journal of Community Engagement (IJCE) Vol. 4 No. 2 (2025): Indonesian Journal of Community Engagement (IJCE) ANDAN JEJAMA
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/ijceaj.v4i2.17

Abstract

The development of the region's potential encourages awareness that the area has the potential to become a tourist destination, especially in the form of a tourist village. In this regard, visionary and proactive figures are needed to unite all components of the community to collectively build and actively participate in attraction activities during tourist visits. The management of this effort is directed and organized by the community itself, and the youth, as initiators and movers, are equipped with skills to publicize and promote their tourist village using information technology, especially digital marketing.The utilization of digital marketing is a primary strategy in marketing and promoting the tourism potential of Desa Wisata Wonolopo. Information technology is used to disseminate information through social media and other digital platforms, so that the potential of Desa Wisata Wonolopo can be widely recognized by the public. The optimization of information technology usage, particularly through digital marketing, becomes a crucial means to promote and publicize Kampung Jamoe in the village of Wonolopo. This is particularly strategic in introducing the potential of traditional baby-carrying herbal products to a broader audience, with the hope of reviving the local economy in that area.
Perancangan Desain Jaringan Menggunakan UISP Design Center bagi Tenaga Pendidik dan Kependidikan Bidang TIK Kabupaten Semarang Jefri Alfa Razak; Veronica Lusiana; Sariyun Naja Anwar; Mohammad Riza Radyanto; Endang Lestariningsih
FUNDAMENTUM : Jurnal Pengabdian Multidisiplin Vol. 3 No. 4 (2025): November : FUNDAMENTUM : Jurnal Pengabdian Multidisiplin
Publisher : Asosiasi Peneliti Dan Pengajar Ilmu Sosial Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/fundamentum.v3i4.1235

Abstract

This community service project was motivated by the limited technical competency among TIK (Information and Communication Technology) personnel in Semarang Regency schools in designing optimal computer network infrastructure. This situation resulted in slow, unstable, and poorly managed digital learning services within these schools. The main objective of this activity was to enhance the competency of 24 TIK personnel to enable them to design efficient, secure, and professional networks tailored to their schools' needs. The solution provided was hands-on training using the UISP Design Center, a web-based network design platform. The training was conducted face-to-face over two days and covered hierarchical topology, VLAN and QoS management, and practical design simulation. Measurement results demonstrated a significant increase in the participants' cognitive competency, evidenced by the average score rising from 45.2% on the pre-test to 82.5% on the post-test. Participants successfully applied these concepts to produce accurate designs for network topology, logical segmentation, and Bills of Materials (BOM). The high level of participant satisfaction confirms the effectiveness of this training in closing the skill gap. This activity successfully enhanced the network planning capability of the partner schools.
Klasifikasi Tingkat Kematangan Buah Pisang Raja Menggunakan Metode CNN Berbasis Android Febriana, Trissa Noor Aulia; Lusiana, Veronica
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.37790

Abstract

Raja banana (Musa paradisiaca L.) is a banana cultivar commonly enjoyed in Indonesia. In addition to being consumed as a fresh fruit, Pisang Raja is often processed into various banana-based foods, such as banana chips, fried bananas, banana fritters, and other banana products. For farmers, post-harvest sorting of Pisang Raja requires a significant amount of time and effort. Therefore, a system is needed to assist farmers and the community in general to determine the ripeness level of Pisang Raja fruit more efficiently and clearly. The classification process of Pisang Raja fruit ripeness levels is carried out through precision calculations in a system, using a dataset consisting of 300 images covering 3 types of Pisang Raja ripeness levels. The classification process for the ripeness levels of Pisang Raja fruit utilizes the Convolutional Neural Network (CNN) method with the TensorFlow module for training and testing data. Based on experimental results, the accuracy in classifying the ripeness levels of Pisang Raja fruit reaches a value of 95%."
Perbandingan Proses Klasterisasi Data Menggunakan K-Means Clustering dan Agglomerative Hierarchical Clustering Hartono, Budi; Lusiana, Veronica; Al Amin, Imam Husni
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8766

Abstract

Large amounts of data require good processing and analysis. One of the data analysis techniques is data clustering, which is grouping data into several groups or data clusters based on the similarity of data characteristics. This study observed the clustering process and cluster results using the K-Means and Agglomerative Hierarchical Clustering (AHC) algorithms or methods. Clustering was carried out using three different amounts of data, namely 10 (A10 data), 30 (B30 data), and 60 (C60 data), with choices of two, three, and four clusters. The experimental results obtained were that the A10 data cluster was the same, but the C60 data was different. Both methods provide the same cluster results, namely in the number of cluster members and their data numbers; conversely, different cluster results are obtained if there are differences in the number of cluster members. The B30 data cluster results for three clusters are the same, while for two and four clusters they are different. The results of this study are expected to provide a better understanding of the data clustering process and can be a basis for selecting a more appropriate clustering method.
Klasifikasi Dokumen Publik Berbasis NLP: Otomatisasi Proses Informasi Menuju Keterbukaan Data yang Adaptif dan Transparan Retnowati Retnowati; Veronica Lusiana; Eko Nur Wahyudi
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.v5i2.5693

Abstract

In the era of public information disclosure, digital documents have become strategic assets in supporting transparent, accountable, and participatory governance. Effective management of these documents is essential to ensure that public information services are responsive and accessible. However, document classification tasks carried out by Public Information and Documentation Officers (PPID) still rely heavily on manual processes, which are time-consuming, inefficient, and prone to human error. To address this challenge, this study aims to develop an intelligent classification model for public documents using Artificial Intelligence (AI) and Natural Language Processing (NLP), integrated within the Data Lifecycle Management (DLM) framework. The proposed solution was designed using the Design Science Research (DSR) methodology and implemented through Agile development practices. Evaluation was conducted in a simulated laboratory environment that mirrors real-world PPID operations.The developed model leverages transformer-based architectures, particularly BERT (Bidirectional Encoder Representations from Transformers), and is compared against traditional algorithms such as Naive Bayes and K-Nearest Neighbors (KNN). Experimental results show that the BERT model achieves superior performance, with an accuracy of 89%, precision of 0.88, recall of 0.89, and F1-score of 0.88. These metrics confirm that Transformer-based models are highly effective for classifying public documents into categories of information accessibility: available at all times, periodic, immediate, and exempted from disclosure.This research highlights the potential of AI-powered classification to streamline public information services, reduce workload, and enhance compliance with information disclosure laws. The findings support national development priorities such as RPJMN 2025 by contributing to digital transformation in the public sector. The study also provides a replicable framework for other government agencies aiming to implement adaptive and transparent document classification systems.
Klasifikasi Tingkat Kematangan Buah Kersen Menggunakan Citra HSI Dengan Metode K-Nearest Neighbor (KNN) Pratama, Krisna Aditya; Atmaja, Wahyu Priyo; Lusiana, Veronica
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 11, No 1 (2022): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v11i1.3171

Abstract

Buah kersen sering dianggap buah yang tidak bermanfaat, ternyata buah kecil ini memiliki banyak manfaat tersembunyi. Dalam artikel ini penulis ingin mengidentifikasi dan mengklasifikasi kematangan buah kersen menggunakan citra HSI dengan metode KNN. Tujuan penelitian ini adalah memberikan hasil berupa tingkat kematangan buah kersen menggunakan aplikasi matlab. Dengan menggunakan metode K-Nearest Neighbor (KNN) untuk menentukan tingkat kematangan buah kersen. Data training yang digunakan berjumlah 18 data, terdiri dari 6 data matang, 6 data setengah matang dan 6 data mentah. Kata kunci : Matlab, KNN, HSI
Analisis Metode Elbow SSE, Silhouette Score, dan Jaccard Stability dalam Pemilihan Jumlah Klaster Data yang Optimal Hartono, Budi; Lusiana, Veronica
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9271

Abstract

This study discusses the selection of the optimal number of clusters (K) in the K-Means algorithm by utilizing a combination of the Elbow method with the SSE (Sum of Squared Errors) and Silhouette Score metrics. The main problem is that the optimal K value is unknown. Choosing K that is too small can combine different patterns (under-clustering), and choosing K that is too large can break the same pattern into several clusters (over-clustering). The experiment used two-dimensional test data with variations in the number of data 20, 30, 40, 50, and 60. K-Means was run in the range of K = 2 to K = 8, then the SSE value was calculated to form the Elbow curve and the average Silhouette value to evaluate the quality of the cluster. This study added a cluster stability test using the Jaccard Stability value. The highest Silhouette value of 0.4619 was obtained from the data 20 for K = 2. The highest Jaccard stability value of 0.9507 was obtained from 60 data sets for K = 2. The experimental results show that the Elbow method, Silhouette value, and Jaccard stability can be used complementarily in determining the optimal K. In some test data, both metrics produce consistent K recommendations, while in certain test data, Elbow can provide several candidates, so that validation using the Silhouette value is needed to select the optimal K.
SISTEM MONITORING DAN ESTIMASI LAMA WAKTU KUNJUNGAN PELANGGAN MENGGUNAKAN ALGORITMA YOLO BERBASIS DEEP LEARNING (STUDI KASUS: JARAK COFFEE & EATERY) Anggraini, Melly; Lusiana, Veronica
INTECOMS: Journal of Information Technology and Computer Science Vol. 9 No. 2 (2026): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/1jt60018

Abstract

Perkembangan teknologi Artificial Intelligence (AI) dan Computer Vision telah memberikan dampak signifikan terhadap sistem monitoring. Penelitian ini mengembangkan sistem monitoring dan estimasi lama waktu kunjungan pelanggan menggunakan algoritma YOLO berbasis deep learning di Jarak Coffee & Eatery. Permasalahan utama adalah kurangnya efektivitas metode monitoring manual dalam mengelola data kunjungan pelanggan yang menyebabkan kesulitan mendapatkan informasi akurat mengenai durasi kunjungan. Tujuan penelitian ini adalah mengimplementasikan algoritma YOLO untuk mendeteksi dan melacak pelanggan secara real-time serta mengembangkan sistem yang mampu menghitung durasi kunjungan secara otomatis. Menggunakan metode Waterfall dengan tahapan analisis kebutuhan, perancangan sistem, implementasi menggunakan YOLOv11 dan BoT-SORT, serta pengujian. Hasil model YOLOv11 mencapai performa sangat baik dengan mAP@0.5 sebesar 96,5%, precision 93,4%, dan recall 93,4%, serta mampu menghitung durasi kunjungan dengan threshold minimal 30 detik untuk memfilter false positive. Sistem menghasilkan output visualisasi real-time dan log CSV yang dapat digunakan untuk analisis durasi kunjungan dan optimalisasi operasional. Kata Kunci: Algoritma YOLO, Deep Learning, Computer Vision, Object Detection, Durasi Kunjungan Pelanggan
Co-Authors Adi Nugroho, Hermawan Aisyah Nur Ramadhayani Alfian, Riyan Anggraini, Melly Antono Adhi ARIFUDIN, WAHYU Aryasatya, Rakryan Atmaja, Wahyu Priyo budi hartono Budi Hartono Budi Hartono Deva Ega Marinda Dewi Handayani Untari Ningsih Dian Kristiawan Nugroho Dimas Wahyu Edy Supriyanto Edy Winarno Eka Ardhianto Eko Nur Wahyudi Endang Lestariningsih Febriana, Trissa Noor Aulia Felix Andreas Sutanto Hari Murti Hartono, Budi Hartono, Budi Hidayat, Agung Rizqi Ibnu Yuwono, Afian Ilham Ramadhan, Hafidh Imam Husni Al Amin Iskandar Zulkarnein Jefri Alfa Razak Krisna Aditya Pratama Kristianto, Teguh Ma’sum, Muhammad Ali Miftah Khul Janah Muhammad Muslimin Ningsih, Dewi Handayani .U Oka Rosalin, Agnes Pratama, Krisna Aditya Pusdita, Tistantia R. Soelistijadi Radyanto, Mohammad Riza Ramadhani, Insan Rara Sri Artati Redjeki Ratnaduhita, Aurellia Razak, Jeffri Alfa Retnowati Retnowati Rina Candra Noor Santi Sariyun Naja Anwar Setiaji, Isnan Sri Eniyati Sri Wahyuni Sumarno, Davis Danendra Tahta Febri P, Gilar Taufan Maynard Prananda Sancaka1 Teguh Khristianto Umi Kholifah WAHYU PRIYO ATMAJA Wahyu Priyo Atmaja Widiyanto Tri Handoko Widyawati, Lanjar Wismarini, Th Dwiati Wiwien Hadikurniawati Wulan Nur Afifah, Wulan Nur Zulkarnein, Iskandar