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Irfan Syamsuddin
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INDONESIA
Journal of Informatics and Computer Engineering Research
Published by Politeknik Negeri Ujung Pandang
ISSN : -     EISSN : 30896320     DOI : https://doi.org/10.31963
Core Subject : Science,
Computer Science & IT
Journal of Informatics and Computer Engineering Research PNUP is research journal as a forum for scientific communication between academics, researchers and practitioners in disseminating research results in the fields of Information System, Networking, Mobile Applications, Software Engineering, Web Programming Mobile Computing, Science Application, Virtual Reality, Multimedia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 2 (2025)" : 5 Documents clear
ANALISIS PENCARIAN TEKS EMOSI DALAM TWEET BERBAHASA INDONESIA MENGGUNAKAN TF-IDF DAN COSINE SIMILARITY Saputra, Adi; Ferdilian, M Lazuardi; Irsyad, Hafiz; Rahman, Abdul
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6012

Abstract

Social media platforms such as Twitter present a wide range of emotional expressions from users in short and informal texts, which pose significant challenges for automated analysis. This study develops a search system for Indonesian-language tweets that identifies user emotions based on semantic similarity to a given text query. The method employs Term Frequency-Inverse Document Frequency (TF-IDF) for feature weighting and Cosine Similarity to measure textual similarity. Preprocessing stages including normalization, tokenization, stopword removal, and stemming are applied to enhance text representation accuracy. The system is tested using emotion-based queries and returns relevant tweets with high semantic match scores. Experimental results show that 50% of the top retrieved tweets match the expected emotional context. This approach proves effective in detecting emotions in short texts and offers potential for further development in sentiment-driven opinion analysis and emotion-aware recommendation systems
PERANCANGAN INCUBATOR TELUR PUYUH OTOMATIS BERBASIS IOT Ardiniansyah, Alvin; Nofitasari, Nofitasari; Riyanto, Bagus; Hariansyah, Muhammad
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6013

Abstract

The success rate of quail egg hatching is highly dependent on the stability of temperature, humidity, and frequency of egg turning during the incubation period. Conventional incubators that are still widely used by small farmers tend to be less efficient because they rely on manual supervision, which can cause fluctuations in the incubation environment. Therefore, this study aims to design and compare the performance of an automatic quail egg incubator based on the Internet of Things (IoT) with a conventional manual system. The prototype of the automatic incubator uses an ESP32 microcontroller, DHT22 sensor, servo motor for egg rotation, and the Blynk application for remote monitoring. Testing was carried out for 18 days by comparing temperature, humidity, hatching power, and hatching weight between the two systems. The results showed that the IoT incubator was able to maintain a stable temperature in the range of 37.5–38°C with a fluctuation of ±0.3°C and produced a hatching power of 88%, higher than the conventional incubator which only reached 68%. The average hatching weight in the automatic incubator was also greater, namely 7.4 grams compared to 7.0 grams in the manual system. Based on these results, the application of IoT technology has been proven to increase the efficiency of the hatching process and reduce the need for manual monitoring. This innovation can be an appropriate solution in modernizing small to medium-scale poultry farms.
WEB-BASED PUBLIC RELATIONS CHATBOT USING LARGE LANGUAGE MODELS AND THE RETRIEVAL-AUGMENTED GENERATION Nuzul1, Andi Muhammad; Utomo, Muhammad Nur Yasir; Indrabulan, Tantri
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6014

Abstract

The Public Relations and Protocol Working Group (Pokja Humas) of Politeknik Negeri Ujung Pandang (PNUP) faces challenges in providing interactive and responsive information services. The official website functions only as a one-way medium, and the high volume of repeated questions causes delays in response time. This study developed a public relations chatbot based on Large Language Model (LLM) using the Retrieval-Augmented Generation (RAG) method to improve information services. The chatbot data were obtained through web scraping of the PNUP official website and internal PDF documents, which were processed through preprocessing, text splitting, and embedding using Hugging Face and stored in a FAISS vectorstore. The system was built using FastAPI as the backend and web-based interfaces for admin and user interactions. The results show that User Acceptance Test (UAT) involving 35 respondents achieved 91.93% acceptance (very good). The Retrieval-Augmented Generation Assessment (RAGAS) evaluation achieved average scores of 0.89 for Faithfulness, 0.91 for Answer Relevancy, 0.89 for Context Precision, and 0.89 for Context Recall, indicating that the chatbot produced relevant and contextually accurate answers.
RANCANG BANGUN APLIKASI WEBSITE YAYASAN BINA INSAN CENDIKIA LUKMANUL HAKIM KABUPATEN GOWA W. Hasyim , Muhammad Miftahurrahman; astian, Alvian B; Muh. Ahyar
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6016

Abstract

This study aims to design and develop an official website for the Bina Insan Cendikia Lukmanul Hakim Foundation by utilizing Visual Studio Code technology and the PhpMyAdmin database. The formulation of the problem raised in this study includes how to design an effective website in presenting foundation information and providing convenience for the public to participate through online donations. The benefits of developing this website include increasing the transparency of the foundation, facilitating public access to information, and encouraging active participation in foundation programs. As a solution, this study presents essential features such as foundation profiles, donation pages, and registration, all of which are designed to meet the information and interaction needs of users. The evaluation results show that this website has succeeded in achieving its stated goals, supporting the dissemination of foundation information, and facilitating participation effectively, with an average eligibility score of 92.6%, indicating that this website has succeeded in achieving its stated goals. Users highly rate the aspects of ease of use, attractive appearance, and completeness of the information presented.
ANALISIS DIAGNOSA PENYAKIT PADA TANAMAN KAKAO DENGAN MENGGUNAKAN METODE YOLOV8 Syahrir, Syahrir; Hamzidah, Nurul Khaerani; Rahmayani
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6017

Abstract

One of Indonesia's most important commodities, cocoa plants play a crucial role in both the agricultural and financial sectors. In any event, this plant is particularly susceptible to a variety of diseases that can completely reduce its effectiveness, including stem cancer, VSD, natural product spoilage, and others. This article discusses how to use the YOLOv8 technique to develop a framework for sickness conclusion research in cocoa plants. The YOLOv8 computation was selected for this analysis due to its emphasis on handling speed and object recognition with high accuracy. The results showed that the YOLOv8 demonstration could accurately identify damage, reaching a 90% mAP. As a result of these developments, the produced show may be a useful tool to help farmers better monitor and control pest attacks. It is expected that using YOLOv8 to identify damage to cocoa natural products will result in a more effective plan for reducing the likelihood of lower yields from insect attacks.

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