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All Journal Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi JTERA (Jurnal Teknologi Rekayasa) INOVTEK Polbeng - Seri Informatika Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science bit-Tech Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Bakti Masyarakat Indonesia MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Computer Science and Information Technology (CoSciTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Masyarakat Bhinneka SmartComp The Eastasouth Journal of Information System and Computer Science Indonesian Journal of Community Empowerment Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Kharisma, Ivana Lucia
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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Implementasi Retrieval Augmented Generation dalam Sistem Chatbot Dermatologi Berbasis Website Kharisma, Ivana Lucia; Hidayat, Muhammad Syarif; Somantri, Somantri; Kamdan, Kamdan
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 3 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i3.12258

Abstract

Indonesia’s tropical climate, poor sanitation, and limited access to medical services especially in remote areas are key factors contributing to the high prevalence of skin diseases. Direct access to dermatologists remains difficult for many people. This study aims to develop a dermatological consultation Chatbot using a Retrieval Augmented Generation (RAG) approach, leveraging the LangChain framework, the LLaMA model, and the Qdrant vector database. The dataset includes 30 types of skin diseases sourced from the National Library of Medicine. The preprocessing stage involved whitespace normalization, removal of special characters, and handling of missing values to ensure data consistency before vectorization. Evaluation results showed high scores for Faithfulness (0.9429) and LLMContextRecall (0.9600), indicating that the responses were relevant and aligned with the source documents. However, a relatively low Precision score (0.4720) suggests a need for improved information accuracy. The Chatbot is integrated with the Chainlit platform, offering an interactive user interface that supports login, conversation history, and user feedback features to facilitate system development based on user input. The system demonstrated fast retrieval times (0.08–0.29 seconds), though answer generation remains slow due to CPU infrastructure limitations (255–283 seconds). Future improvements should focus on enhancing answer accuracy, optimizing the model's performance, enriching the medical reference dataset, and adding automated medical validation features to ensure the reliability of consultations. Therefore, this Chatbot system is expected to serve as a cost-effective and efficient alternative for providing initial information on skin conditions to individuals with limited access to healthcare services.
Application of Artificial Neural Network in Estimating Harvest Time of Lettuce and Spinach Plants in Nutrient Film Technique Hydroponic System Munawar, Zilfa Agustina; Insany, Gina Purnama; Kharisma, Ivana Lucia
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.v12i1.3261

Abstract

Hydroponic farming using the Nutrient Film Technique (NFT) system is widely implemented due to its efficiency in nutrient management and water use. Spinach and lettuce are leafy commodities widely cultivated using this system because they have a relatively short growth cycle and high economic value. However, determining harvest time is still often done manually based on experience, potentially leading to inaccurate decisions that impact the quality and quantity of production. This study aims to develop a prediction model for harvest time for hydroponic spinach and lettuce plants based on Artificial Neural Network (ANN) by utilizing environmental and physiological parameters of the plant. The parameters used include water temperature, air humidity, light intensity, pH, Electrical Conductivity (EC), and plant age. The dataset used consists of 1,200 observation data of NFT hydroponic cultivation results from January to July 2025. The data went through a preprocessing stage in the form of cleaning, normalization, and dividing training data and test data with a ratio of 80:20. The ANN model was built using the backpropagation method with training parameter optimization. Data was obtained from plant growth monitoring, then normalized and divided into training and test data. Test results showed a prediction accuracy of 92.8% based on MAPE, MAE, and R-squared. This model was implemented in a Streamlit-based web application to facilitate farmer use, making harvest timing more objective, measurable, and data-driven.
The IMPLEMENTASI YOLOV8 NANO PADA SISTEM MONITORING BUDIDAYA JAMUR TIRAM BERBASIS IOT Nopiandi, Andi; Yasin, Fakhriyal Riyandi; Prayoga, Rizki Haddi; Somantri, Somantri; Kharisma, Ivana Lucia
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10673

Abstract

Oyster mushrooms are one of the agricultural commodities with high economic value and are widely cultivated in Indonesia. However, the conventional process of monitoring their growth is still carried out manually, which requires considerable time and labor while also being prone to errors in decision-making. To address this issue, this study developed an automatic oyster mushroom growth monitoring system using Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The system uses a DHT22 sensor to measure temperature and humidity, a BH1750 sensor to measure light intensity, and an ESP32-CAM module to capture mushroom images. The data is transmitted through the ESP32 and analyzed using Python, while the images are processed by a YOLOv8 Nano model to classify mushroom growth stages into baglog, young mushrooms, and ready-to-harvest mushrooms. The monitoring results are displayed in real time on a dashboard and stored in a MySQL database. The model training results show fairly good performance, with an average precision of 0.69, recall of 0.78, and a mean Average Precision (mAP@0.5) of 0.71. Further testing was conducted on 15 test images for each mushroom stage, and all images were successfully detected according to their actual classes. Additionally, tests conducted on 10 negative images (without mushroom objects) also supported the system’s reliability. The success of the system is further supported by stable network connectivity for data transmission, adequate lighting in the cultivation room during image capture, and automatic adjustment of temperature and humidity according to the mushroom growth phase. This system demonstrates its capability to monitor mushroom growth conditions automatically and accurately, offering a practical solution for supporting more modern and efficient mushroom cultivation practices.
Implementation of Enterprise Resource Planning (ERP) Based Information System Using Odoo Software Utami, Mega Putri; Kharisma, Ivana Lucia
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 02 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i02.161

Abstract

Management and good data management is something that is very important for the continuity of a company. With management in a company, it is expected that all actions or activities carried out will run well and be controlled. The research focused on the use of an Enterprise Resource Planning (ERP) Based Information System using the odoo software used in the Purchasing & Materials department or more specifically known as PPIC. The purpose of this research is to find out how the use of ERP technology can facilitate coordination and communication between users so as to produce fast decision making. The implementation of this information system is expected to be one of the solutions in overcoming the problems that exist at PT Longvin Indonesia, especially the PPIC department.
Integrasi Informasi Pelanggan Berbasis Web Host Manager Complete Solution untuk Meningkatkan Responsivitas Customer Support PT Cloud Hosting Indonesia Ramadan, Rizky; Kharisma, Ivana Lucia
Jurnal Pengabdian Masyarakat Bhinneka Vol. 4 No. 3 (2026): Bulan Februari
Publisher : Bhinneka Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58266/jpmb.v4i3.944

Abstract

Kegiatan internship di PT Cloud Hosting Indonesia bertujuan untuk mengevaluasi efektivitas sistem Web Host Manager Complete Solution (WHMCS) dalam mengintegrasikan informasi pelanggan untuk meningkatkan responsivitas layanan. Metode yang digunakan meliputi observasi arsitektur sistem, praktik operasional penanganan tiket, serta analisis alur automasi billing dan aktivasi layanan. Hasil kegiatan menunjukkan bahwa integrasi WHMCS berhasil memusatkan data layanan, penagihan, dan riwayat tiket dalam satu platform terpadu, yang secara signifikan mempercepat Service Level Agreement (SLA) tim Customer Support. Namun, ditemukan kendala berupa latensi sinkronisasi data pada jam sibuk akibat beban kerja cron job yang tinggi. Kesimpulannya, WHMCS sangat krusial bagi efisiensi operasional perusahaan, namun diperlukan optimasi pada manajemen cache dan segmentasi prioritas tiket untuk menjaga stabilitas kualitas layanan.
Implementasi Teknologi YOLOv8n dan IoT pada Alat Pengusir Hama Burung dengan Raspberry Pi Bertenaga Solar Panel Kharisma, Ivana Lucia; Kamdan, Kamdan; Insany, Gina Purnama; Firdaus, Asep Rizki; Nasrulloh, Dendi
JTERA (Jurnal Teknologi Rekayasa) Vol 10, No 2: Desember 2025
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v10.i2.2025.35-44

Abstract

Hama burung adalah salah satu tantangan serius yang dihadapi pada sektor pertanian. Metode tradisional yang dilakukan untuk mengatasi hama burung hanya memberikan solusi sementara dan juga mengakibatkan petani tidak dapat melakukan aktifitas lainnya, karena harus menjaga sawah secara terus menerus. Untuk optimalisasi serta untuk mengatasi permasalahan yang muncul pada perancangan alat sebelumnya yaitu kendala pada koneksi internet yang tidak stabil, sumber listrik yang terbatas serta permasalahan penyimpanan lokal pada alat , dibutuhkan integrasi antara konsep kecerdasan buatan (AI) dan Internet of Thing (IoT). Pengembangan alat menggunakan model deteksi objek versi YOLOv8nano, Raspberry Pi sebagai Single Board Computer dan penambahan solar panel . Pengujian yang dilakukan secara langsung menunjukkan bahwa fungsionalitas dan kinerja alat telah sesuai dengan yang diharapkan. Alat mampu mendeteksi objek burung dengan kinerja nilai rata-rata confidence score 74,64%, sedangkan pada pengujian solar panel menunjukkan hasil daya listrik yang mampu disimpan dalam durasi waktu 12 rata-rata sebesar 13,31 volt. Penambahan sebuah dashboard monitoring, bermanfaat untuk memberikan informasi kinerja alat.  Terpenuhinya semua proses pengujian menunjukkan bahwa alat pengusir burung ini memiliki potensi besar untuk memudahkan petani dalam mengatasi masalah hama burung secara lebih efektif, sehingga mengurangi ketergantungan pada metode tradisional.
Co-Authors adang badru jaman,anggun fergina, adang badru jaman,anggun fergina Agung Gumelar AGUNG, DEDE Al-Basori, Muhamad Cepnur Alhidamkara, Salman Alun Sujjada Angelina, Nadila Apriliyanti, Silvi Ayu Lestari, Melani Bila, Nida Aulia Salsa Dede Sukmawan Delia Nur Annisa, Delia Nur Dewi, Dhita Diana Dwi Sartika Simatupang Fatalifi, Amerjid Ghulamson Firdaus, Asep Rizki Gunawan, Muhamad Sahrul Hafidzh Al Muhiddin, Muhammad Ibnu Sina, Rivaldi Insany, Gina Purnama Kamdan Khairiyah Ivanka, Najwa Kustandi, Agus Mamun, Yuliana Maulana Yusuf Muhammad Dzulqarnain, Fajar Muhammad Syarif Hidayat Munandar, Rifki Arief Munawar, Zilfa Agustina Mustopa, Ato Nasrulloh, Dendi Natanael, Brillian Aji Natasya, Sandra Neva, Talitha Nirmala Nopiandi, Andi Pamungkas, Dimas Arya Pauzi, Yoviar Perkasa, M. Juang Pajri Prayoga , Rizki Haddi Prayoga, Rizki Haddi Purba, Raihan Lutfhi Purnama Insany, Gina Rahman, Wigi Januar RAMADAN, RIZKY Ramdan, Hari Muhammad Rohmat, Satria Rizki Rosmawati Rosmawati Sebayang, Alvin Christoper Septiani, Dhea Ayu Serliani, Siska Meyisa Amelia Somantri, S Somantri, Somantri Sulaeman, Asep Surahman Tresna Ati, Mutiara Annisa Utami, Mega Putri Yansah, Ardi Yasin, Fakhriyal Riyandi Yustiana, Indra Zahra, Falya Amrina Zakaria, Muhammad Maulana Zaki Hibatullah, Muhammad