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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Sosioteknologi Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Ilmiah KOMPUTASI CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Teknik Informatika UNIKA Santo Thomas JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Jurnal Teknologi Sistem Informasi dan Aplikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) JUTEKIN (Jurnal Manajemen Informatika) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) IJEEIT : International Journal of Electrical Engineering and Information Technology Jurnal Tekno Kompak Applied Technology and Computing Science Journal Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi bit-Tech Jurnal Informasi dan Teknologi JTIK (Jurnal Teknik Informatika Kaputama) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics G-Tech : Jurnal Teknologi Terapan Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) IICS KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Pengabdian Kepada Masyarakat Abdi Putra Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam International Journal Engineering and Applied Technology (IJEAT) Jurnal Sains Informatika Terapan (JSIT) Jurnal Pengabdian Masyarakat Bhinneka Biner : Jurnal Ilmiah Informatika dan Komputer Jurnal Pengabdian Masyarakat Bangsa Indonesian Journal of Community Empowerment Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Prosiding SENTIMETER : Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer
adang badru jaman,anggun fergina, adang badru jaman,anggun fergina
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Web-Based Drug Inventory System with FIFO Method and SCM Approach at Risa Farma Pharmacy Mayang Selpiyana; Anggun Fergina; Indra Yustiana
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2951

Abstract

Drug inventory management plays a crucial role in pharmacy operations as it directly relates to drug availability, service accuracy, and the prevention of losses caused by expired medicines. However, many small-scale pharmacies still rely on manual recording, which is prone to stock discrepancies, delayed detection of near-expired drugs, and low administrative efficiency. To address these issues, this study developed a web-based drug inventory system implementing the First In First Out (FIFO) method combined with a Supply Chain Management (SCM) approach. The system was developed using the System Development Life Cycle (SDLC), which includes planning, requirements analysis, system design, implementation, and functional as well as user testing. The results demonstrate that the system successfully reduces potential stock recording errors by up to 75% compared to manual methods and improves transaction recording efficiency by an average of 40%. The SCM approach enables the system to automatically issue alerts when stock reaches a minimum threshold and to provide restock recommendations based on demand data. A User Acceptance Test (UAT) involving 10 respondents produced a satisfaction score of 86%, indicating that the system is effective, user-friendly, and beneficial for pharmacy operations. This study concludes that the integration of FIFO and SCM in a web-based drug inventory system improves data accuracy, enhances operational efficiency, and minimizes the risk of expired medicines. Nevertheless, the system still faces limitations related to data security, internet dependency, and its suitability primarily for small-scale pharmacies.
Cluster Analysis of Electricity Customers in Sukabumi Regency Using K-Means Clustering Andhika Oktasandira; Nugraha Nugraha; Anggun Fergina
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2970

Abstract

The uneven distribution of electrical energy poses a formidable challenge to strategic infrastructure planning and equitable regional development, often hindering sustainable economic growth and exacerbating socio-economic disparities. This issue is particularly acute in a vast and geographically diverse region such as Sukabumi Regency. This study addresses this critical issue by applying the K-Means clustering algorithm to segment 47 sub-districts based on comprehensive electricity customer data from 2019 to 2023, aiming to uncover distinct patterns of energy consumption. The primary novelty of this research lies in (1) its granular application of cluster analysis to sub-district-level electricity customer data for regional energy planning in Indonesia, a previously underexplored area, and (2) the implementation of the results into an intuitive, Streamlit-based interactive web application. This tool serves as a powerful decision-making dashboard for stakeholders, enabling dynamic data exploration and geographical visualization. The methodology encompasses meticulous data collection from official sources, rigorous pre-processing involving data normalization, determining the optimal number of clusters using the well-established Elbow Method, and validating cluster quality with the robust Silhouette Coefficient. The results definitively indicate that three clusters representing Low, Medium, and High energy consumption tiers are the most optimal segmentation. This is substantiated by a strong Silhouette score of 0.6911, which confirms a cohesive and well separated cluster structure. The practical implications are significant, providing a data-driven framework for prioritizing infrastructure investments, enhancing resource allocation efficiency, and supporting the formulation of more targeted energy policies. Ultimately, this study offers a replicable model for other regions facing similar challenges, fostering more sustainable development pathways
Analisis Performa Model Embedding BGE Small Dan Minilm-L6 Terhadap Kualitas Retrieval Menggunakan Metrik Ragas Ahmad Ibrahim Maqbul; Anggun Fergina
Jurnal Sains Informatika Terapan Vol. 5 No. 2 (2026): Jurnal Sains Informatika Terapan (Juni, 2026)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v5i2.1184

Abstract

The application of Large Language Models in the medical domain is often hampered by issues of hallucination and limited up-to-date knowledge. Retrieval-Augmented Generation offers a solution for connecting LLM with factual data, but the quality of RAG output is highly dependent on the accuracy of the information retrieval process. This study aims to analyze the effect of chunk size and embedding model variations on retrieval quality in a medical chatbot system at the Nusa Putra Farmedika General Clinic. The method used is a comparative experiment by testing three chunk size variations (256, 512, and 1024 tokens) and comparing the performance of two embedding models, BGE Small and MiniLM-L6. The evaluation was conducted automatically using the RAGAS framework, focusing on the Context Recall and Context Precision metrics. These findings were implemented into a medical chatbot prototype as a form of functional validation. The results showed an inverse relationship between chunk size and retrieval quality, with a chunk size of 512 tokens producing the best level of information granularity. The BGE Small model proved to be slightly superior to MiniLM-L6 in capturing the semantics of clinical text. The most optimal configuration was achieved by combining the BGE Small model with a chunk size of 512, which produced the highest average score of 0.59, Context Recall of 0.45, and Context Precision of 0.74. This study recommends this configuration as a technical standard for the development of medical chatbot as a foundational step to improve context relevance and mitigate the potential for hallucinations.
Analisis Perbandingan Kinerja Tools Manajemen Proyek (Trello Vs Jira) Menggunakan Metode Pieces Anggun Fergina; Siti Zahra Sifa; Taufik Hidayat; Imam Sanjaya; Aulia Kusuma Wardani
Jurnal Sains Informatika Terapan Vol. 5 No. 2 (2026): Jurnal Sains Informatika Terapan (Juni, 2026)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v5i2.1186

Abstract

Effective project management highly depends on selecting the appropriate tools to support team productivity. This study focuses on comparing the performance of two popular project management platforms, Trello and Jira, which are widely used by software development teams. The issue addressed in this research concerns the differences in features and levels of flexibility that often make it difficult for organizations to determine the most efficient tool according to their needs. Therefore, this study aims to objectively evaluate the effectiveness of both platforms and provide recommendations for selecting project management tools that best suit organizational requirements. The benefit of this research is to provide information and references for project managers and software development teams in determining the most suitable project management platform. The method used is a comparative analysis based on the PIECES framework (Performance, Information, Economics, Control, Efficiency, and Service) with a quantitative approach through observation and questionnaire distribution to 30 respondents. The collected data were analyzed based on the six PIECES dimensions to measure the performance level of each platform. The results indicate that Trello achieved higher scores in the Performance (4.8), Economics (4.7), and Efficiency (4.6) dimensions, while Jira outperformed Trello in Information (4.9), Control (4.8), and Service (4.6). Overall, Jira obtained a higher average score of 4.35 compared to Trello's 4.16. In conclusion, Jira is more suitable for managing complex projects that require better control and information management, whereas Trello is more appropriate for small- to medium-scale projects that prioritize ease of use and operational efficiency.
Optimalisasi Publikasi Digital melalui Pendampingan Pembuatan Infografis sebagai Media Penyampaian Informasi Keamanan dan Pelayanan pada Media Sosial Polres Sukabumi Kota Taufik Hidayat; Anggun Fergina
Jurnal Pengabdian Masyarakat Bhinneka Vol. 4 No. 4 (2026): Juli
Publisher : Bhinneka Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58266/jpmb.v4i4.1511

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan di Polres Sukabumi Kota pada periode 17 Oktober hingga 17 Februari dengan tujuan membantu optimalisasi publikasi digital melalui pendampingan pembuatan infografis sebagai media penyampaian informasi keamanan dan pelayanan kepada masyarakat. Metode yang digunakan meliputi observasi, pendampingan pembuatan konten, dan koordinasi dengan bagian Humas Polres Sukabumi Kota. Kegiatan ini menghasilkan berbagai infografis mengenai bahaya narkotika, pencegahan pencurian kendaraan bermotor (curanmor), dan kewaspadaan terhadap bencana banjir yang dipublikasikan melalui media sosial resmi Polres Sukabumi Kota. Hasil kegiatan menunjukkan bahwa pemanfaatan infografis mampu meningkatkan kualitas publikasi digital serta mempermudah penyampaian informasi keamanan dan pelayanan kepada masyarakat. Selain memberikan manfaat bagi Polres Sukabumi Kota, kegiatan ini juga meningkatkan keterampilan desain grafis dan komunikasi visual. Dengan demikian, infografis melalui media sosial dapat menjadi media yang efektif dalam mendukung penyebaran informasi keamanan dan pelayanan publik.
Application of Transfer Learning Method on Convolutional Neural Network (CNN) to Identify Genuine and Fake Diplomas Rifa Awaludin; Anggun Fergina; Gina Purnama Insany
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3295

Abstract

The authenticity of diplomas plays a crucial role in maintaining the integrity of the education system and ensuring that recognized academic competencies align with an individual's actual achievements. Diplomas are not merely administrative documents, but strategic instruments in job recruitment and professional qualification assessment. However, with increasing educational mobility, document misuse through diploma forgery is becoming increasingly prevalent, potentially undermining public trust in educational institutions. Currently, the verification process is still largely carried out manually through visual inspection of document elements such as layout and stamps. The reliance on the examiner's experience makes this method vulnerable to inconsistencies and human error, especially when dealing with fake diplomas with visual qualities that increasingly resemble genuine documents. Diploma forgery is a problem that impacts the credibility of educational institutions and the validity of academic data. Manual inspection is often inconsistent and time-consuming. This study develops a model for classifying genuine and fake diplomas using a Convolutional Neural Network (CNN) with a transfer learning scheme. The performance of the ResNet50, VGG16, and MobileNetV2 architectures is comparatively analyzed. Data preprocessing included resizing, normalization, and augmentation. Test results showed the ResNet50 architecture achieved optimal performance with 92.63% accuracy, 92.16% precision, 94.00% recall, and 93.07% F1-score. The system was implemented in a Streamlit-based web application to facilitate the verification process.
Pendampingan Pengembangan Media Promosi Katalog dalam Meningkatkan Daya Saing UMKM Kopi Cap Oplet Maximillian Huang; Anggun Fergina; Lusiana Sani Parwati; Dede Sukmawan
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 12 (2026): Februari
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i12.4070

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan daya saing UMKM Kopi Cap Oplet melalui pengembangan media promosi katalog produk. Permasalahan yang dihadapi mitra adalah belum tersedianya media promosi yang terstruktur sehingga informasi produk belum tersampaikan secara optimal kepada konsumen. Metode yang digunakan dalam kegiatan ini adalah pendampingan partisipatif melalui tahapan observasi, identifikasi kebutuhan, perancangan katalog, penyusunan konten produk, serta sosialisasi penggunaan katalog kepada mitra. Hasil kegiatan menunjukkan bahwa UMKM Kopi Cap Oplet telah memiliki katalog produk yang lebih sistematis dan informatif sehingga memudahkan dalam proses promosi dan komunikasi kepada pelanggan. Berdasarkan hasil wawancara, mitra menyatakan bahwa katalog membantu meningkatkan profesionalitas usaha dan memperkuat citra produk di pasar. Dengan demikian, pendampingan pengembangan katalog memberikan kontribusi positif dalam mendukung peningkatan daya saing UMKM.
Platform Digital Berbasis AI untuk Memprediksi Keasaman Kopi dari Variabel Lingkungan: Bukti dari Kabupaten Bandung Amanna Dzikrillah Lazuardini; Anggun Fergina
Jurnal Sosioteknologi Vol. 25 No. 1 (2026): MARCH 2026
Publisher : Fakultas Seni Rupa dan Desain ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/sostek.itbj.2026.25.1.5

Abstract

Despite the importance of environmental control in specialty coffee production, predictive and data-driven systems that connect environmental conditions with coffee acidity remain limited, particularly in smallholder farming contexts. This study aims to design and implement a digital platform based on the Gradient Boosting algorithm to analyze the relationship between environmental factors (soil, topography, and climate) and coffee acidity (pH) levels in Bandung Regency. Through a machine learning approach, the developed model successfully captures complex non-linear relationships between environmental variables and coffee acidity, achieving a high level of accuracy (R² = 0.95) and reducing the RMSE from 0.077 to 0.040 within five learning iterations. The most influential environmental factor affecting coffee acidity was altitude (0.42), followed by soil pH (0.25) and rainfall (0.18). The predictive model was integrated into a web-based system (KopiAsa), allowing farmers to input environmental data and obtain real-time acidity predictions. This platform functions as a data-driven decision-support tool that enhances analysis efficiency, optimizes farm management, and strengthens the competitiveness of local coffee. The results accelerate the digital transformation of the agricultural sector by supporting precision agriculture and promoting more sustainable coffee production practices in Bandung Regency.
Integration of Blockchain and Digital Forensics for Data Transparency and Verification : A Systematic Literature Review Sri Nurhayati; Diana Effendi; Anggun Fergina; Irawan Afrianto; Estiko Rijanto; Irfan Dwiguna Sumitra
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 6 No. 2 (2025): INJIISCOM: VOLUME 6, ISSUE 2, DECEMBER 2025
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v6i2.18416

Abstract

Data integrity and transparency are increasingly critical concerns in the digital era. Various challenges in digital forensics arise from the growing prevalence of evidence manipulation and digital tampering, which can compromise the validity of legal investigations. This study conducts a systematic review of the potential application of blockchain technology as a solution for ensuring the authenticity and verification of digital data, employing the Systematic Literature Review (SLR) method guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. A total of 156 relevant articles sourced from the Scopus database and published between 2018 and 2025 were selected and analyzed. The results reveal a significant increase in publications since 2020, with five main research clusters identified, including the integration of Artificial Intelligence (AI) and cybersecurity. Key findings confirm that blockchain effectively functions as a trust layer, creating an immutable and transparent chain of custody. This study concludes that blockchain integration provides a strong foundation for developing more accountable, secure, and reliable digital forensic systems
Optimization of a Web-Based Sweeping Order System Using Supply Chain Management Approach Putri Aulia; Nugraha Nugraha; Anggun Fergina
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3657

Abstract

The order consolidation process, specifically "sweeping orders," is a critical yet often overlooked upstream activity in Supply Chain Management (SCM). At PT Flexo Solusi Indonesia, reliance on manual spreadsheet-based tools resulted in significant data fragmentation, entry errors, and processing delays, which severely hindered downstream logistics coordination and decision-making. This study aims to address this gap by designing and implementing a web-based sweeping order system integrated with SCM principles. Unlike typical inventory-focused systems, this research conceptually shifts the focus to "pre-processing" data synchronization to ensure early-stage supply chain integrity. The system development followed the Waterfall model, supported by a qualitative case study involving in-depth observation and interviews. To ensure research rigor, the system underwent comprehensive black-box testing and workflow validation, specifically evaluating indicators such as data accuracy, process traceability, and the elimination of redundant entry tasks. The results demonstrate that the centralized system successfully enforces sequential workflow validation, thereby mitigating data inconsistency risks and enhancing information flow between the warehouse, production, and shipping divisions. This study concludes that digitalizing upstream order consolidation is a prerequisite for achieving broader supply chain agility. It contributes to existing SCM literature by providing empirical evidence that operational efficiency is contingent upon the accuracy of initial data processing, serving as a scalable digital transformation blueprint for manufacturing SMEs.
Co-Authors Aan Setiawati Adang Badru Jaman adang badrujaman Adhitia Erfina Adil Berliana Aprilia Haryadi Ahmad Dinar Ahmad Ibrahim Maqbul Alex Alfariji, Salman Alpariji, Salman Alun Sujjada Alun Sujjada Alun Sujjada Alya Nurhalisah Alyanissa Putri Iskandar Amalia, Eneng Elsa Amalia, Phina Putri Amanna Dzikrillah Lazuardini Andhika Oktasandira Ani Nuraeni Any Elvia Jakfar Ardelia Ramadhani Ariyanti, Gisni Armelia Isabela Taek Arnold Herman Sama Aulia Kusuma Wardani Aulia Kusuma Wardani Awalansyah, Campaka Sepul Ayulianti, Radita Bahadir Ozsut Berniman Gofindo Malau Bunga Mutiara Sagita Nabila Dafa Afdal D Dava Febrian Dede Serlina Dede Sukmawan Dede Sukmawan Deni Mahdiana DENI SETIAWAN Deshinta Arovva Dewi Deudeu Sri Rahayu Dhea Adela Dhea Ayu Septiani Dhita Diana Dewi Dian Permata Sari Diana Effendi Dimas Arya Pamungkas Dini Aryani Dini Oktarina Dwi Handayani Dwi Sartika Simatupang Edwinanto Estiko Rijanto Fadilah, Fadhlan Subhan Fadillah Alviqih Fakhriyal Riyandi Yasin falentino sembiring Faris Danendra Fatur Rahman Gandi Fauzan, M. Azmi Feby Alfaraby Fikry Ardiansyah Efendi Firdaos, Helfi Apriliyandi Fitri Febrianti Fitria Nurulaeni Fitria Nurulaeni Gina Purnama Insany Gina Purnama Insany Gisni Ariyanti Gisni Ariyanti Handraputri, Chelika Patricia Hanifah, Endah Hendrawan, Yoga Herisma, Dera Destri Hermanto Hermanto Hermanto, H Ian Mulyana Ikhsan, Sultan Alif Nur Ilham Nurabduljabbar Komara Imam Sanjaya Imam Sanjaya Indra Yustiana Indra Yustiana Indra Yustiana Insany, Gina Purnama Irawan Afrianto Irfan Dwiguna Sumitra Irfan Dwiguna Sumitra Irpanudin Iskandar, Alyanissa Putri IVANA LUCIA KHARISMA Iwan Setaiawan Jaelani, Muhammad Fakhraj Jaman, Adang Badru Jelita Asian Junmulyana, Satria Kamdan Kharisma, Ivana Lucia Larasati, Indah Lisa Al Jamil Lucia Kharisma, Ivana Lusiana Sani Parwati Lusiana Sani Parwati M Azri Riyandi M Rifki Nurul R A M. Raiga Agusti Rustandi M. Sarhan Akasah M.kom, Alun Sujada Malik, Julhan Abdul Maulana Yusuf Maulana, Yosep Maulina, Siti Farda Maximillian Huang Mayang Selpiyana Mega Putri Utami Meutia Riany Miya Kurnia Moh. Abd. Aziz Hidayat Moh. Iqbal Maulana Muhamad Iqbal Ramadhan Muhammad Andi Solihin Muhammad Azmi Habibi Muhammad Ezra Haikal Muhammad Ikhsan Thohir Muhammad Ilham Juardi Muhammad Rofiiq Multiaha, M. Reza Mupaat Muslih, Muhamad Mutiara Permata Sari Nieka Julyana Nirmala Neva, Talitha Nisa Nurushalihah Nugraha Nugraha Nugraha Nugraha Nugraha Nugroho, Muhammad Daffadillah Nur Hidayah K Fadhilah Nuralam, Fraza Nurcahya Sumirat, Hana Obi Ramdhani Pamungkas, Muhammad Teguh Panji Pratama Panji Pratama Pebrian, Riko Prihatini Prihatini, Prihatini Putri Anugrah S Putri Aulia Putri Ayu Negara Putri Iskandar, Alyanissa Putri Syarifudin, Rayhanna Adisthi R, Rini Melani Rahmat Hidayat Raka Adriel Maheza Ramdhani, Mohammad Fajril Reka Reni Nur Anggraeni Renjani, Amelinda Reza Rama Putra Ridwan, Rafli Adnan rifa awaludin Rifa Awaludin Rizaldi, Fazrin Muhammad Rizki Maulana Rizki Maulana, Rizki Ruri Mutiara Ayuni S, Somantri Sagita Widya Sahira, Sarah Sally Agustin Elisya Salma Addiyanati Tsaqila Salman Alhidamkara Santi Rahmawati Satyawati Yuliani Sehan Zaki Nurmilad Seno Prasetyo Septiani, Dhea Ayu Setia, Moch Ichwan Silmy Ni’matul Kamila Siti Sarah Sobariah Lestari Siti Zahra Sifa Somantri Somantri Somantri, S Somantri, Somantri Sri Nurhayati Tampubolon, Nico Jaya Taufik Hidayat Taufik Hidayat Taufik Hidayat Tofik Hidayat Tubagus Dzikril Umar Aditiawarman Wibowo, Muhammad Hendryo Yasa, Aditama Yulva Cintakandida Yusup Solehudin Yusup, Angga Maulana Zaenal Alamsyah zahra, Nurazizah Zaman, Syamsul Zulfikar, Mohamad