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Darius Andana Haris
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jiksi@fti.untar.ac.id
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INDONESIA
JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi)
Published by Universitas Tarumanagara
ISSN : 23028769     EISSN : 23032529     DOI : -
Core Subject : Science, Education,
Computer Science & IT Mathematics Other
Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Tarumanagara (FTI Untar) Jakarta sebagai media publikasi karya ilmiah mahasiswa program studi Teknik Informatika dan Sistem Informasi FTI Untar. Karya-karya ilmiah yang dihasilkan berupa hasil penelitian kualitatif dan kuantitatif, perancangan sistem informasi, analisis dan perancangan progam aplikasi. Jurnal ini terbit dua kali dalam setahun yaitu pada bulan Januari dan Agustus.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 937 Documents
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IMPLEMENTASI METODE KLASIFIKASI UNTUK IDENTIFIKASI JENIS KACANG KERING BERDASARKAN FITUR MORFOLOGI Reyhan; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32860

Abstract

Identification of dry bean species is a critical challenge in the agricultural industry, especially to ensure the quality and optimal utilization of the product. This study focuses on the application of a morphological feature-based classification method to automatically recognize dry bean species. Features such as size, shape, surface texture, and color are used as the basis for classification. Several classification algorithms, including K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), Decision Tree, were tested to find the most effective algorithm in identifying the types of beans. The research dataset includes various types of dry beans with different morphological variations. The experimental results show that the morphological feature-based classification approach is able to achieve a high level of accuracy, with Artificial Neural Network (ANN) being the algorithm that shows the best performance. The implementation of this method is expected to provide practical solutions in managing the quality and processing of dry beans in the agricultural sector.
Abstractive Text Summarization Berita Bahasa Indonesia Menggunakan Retrieval-Augmented Generation Antonius Sakti Wiradinata; Viny Christanti Mawardi
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32861

Abstract

This research discusses the application of Abstractive Text Summarization (ATS) to Indonesian language news using the Retrieval-Augmented Generation (RAG) method. Increased access to news through various digital platforms often causes users to have difficulty identifying relevant information among the large amount of news available. RAG integrates retrieval and generation techniques to produce coherent and informative news summaries. In this research, news from the CNN and CNBC sites was collected via web scraping to form a dataset. The data is processed through several stages, including preprocessing, embedding, information retrieval, and summary generation. Summary quality evaluation was carried out using the ROUGE metric, where the test results show that this system has good performance in the precision aspect, with a ROUGE-1 Precision value of 0.7432 and ROUGE-2 Precision of 0.6174. However, a lower ROUGE Recall value indicates that there is important information that is not fully included in the summary. These results indicate that the RAG method in ATS is effective in helping users obtain core information concisely, but there needs to be improvement in capturing the entire news context
PERBANDINGAN KINERJA METODE PEMBELAJARAN MESIN UNTUK ANALISIS SENTIMEN ULASAN FILM Eugene Vincent Arends
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32862

Abstract

Analisis dari sentimen dapat membantu pembuat film dan studio membentuk strategi marketing, menilai kualitas film, analisis kompetisi, dan menganalisa tren yang lebih luas dalam industri film. Sentimen analisis ini dilakukan pada 50.000 ulasan film di IMDB dan menggunakan metode K-Nearest Neighbor, Naïve Bayes, dan Random Forest untuk mengklasifikasi positif atau negatifnya sentiment sebuah ulasan. Ulasan dalam format teks diubah menjadi representasi vector dengan menggunakan TF-IDF (term frequency–inverse document frequency) vectorizer. K-Nearest Neighbor (K-NN) menghasilkan akurasi terbaik 74%, Naïve Bayes (NB) menghasilkan akurasi 85%, dan Random Forest (RF) menghasilkan akurasi 85%. Naïve Bayes dan Random Forest mendapatkan hasil dengan akurasi terbaik. Naïve Bayes memprediksi ulasan negatif yang lebih akurat, sedangkan Random Forest memprediksi ulasan positif yang lebih akurat.
PERBANDINGAN KINERJA ALGORITMA EXTREME GRADIENT BOOSTING DAN RANDOM FOREST UNTUK PREDIKSI HARGA RUMAH DI JABODETABEK Dhiwa Aqsha
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32863

Abstract

The demand for housing continues to increase along with population growth. Predicting house prices is crucial to assist prospective buyers and investors in making more informed decisions. This study aims to predict house prices in the Jabodetabek area by comparing the performance of two machine learning algorithms, namely Extreme Gradient Boosting and Random Forest, to produce accurate price estimates. The prediction process includes data preprocessing, key variable exploration, and model evaluation using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R²). The results show that the Random Forest model performs best, with an MAE of 95,200,513.25, an MSE of 1.47e+19, and an R² of 0.77, outperforming the Extreme Gradient Boosting model with an MAE of 121,836,703.27, an MSE of 3.03e+19, and an R² of 0.52. Thus, this research is expected to serve as an effective tool for stakeholders in mitigating risks in property investment decisions in the Jabodetabek area.
IMPLEMENTASI KUALITAS MINUMAN WINE MENGGUNAKAN METODE KLASIFIKASI Johan Ryan Hutajulu
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32864

Abstract

This study aims to evaluate wine quality using three different classification algorithms: K-Nearest Neighbor (KNN), Artificial Neural Network (ANN), and Polynomial regression. The data used in this study comes from the Wine Quality repository, which includes various chemical attributes of wine, such as alcohol content, acidity, and sugar. Each algorithm is evaluated based on several performance metrics, including precision, recall, f1-score, and accuracy.
PERBANDINGAN AKURASI ALGORITMA XGBOOST DAN SVR DALAM PREDIKSI HARGA CRYPTOCURRENCY Nazwa Fadhil
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32865

Abstract

The purpose of this study is to compare the effectiveness of two machine learning algorithms, XGBoost and Support Vector Regression (SVR), in predicting cryptocurrency prices to address the challenges posed by market volatility. This study evaluates the performance of both algorithms through various metrics including mean absolute error (MAE), root mean squared error (RMSE), mean squared error (MSE), and mean absolute percentage error (MAPE) using transaction data of 10 cryptocurrencies. The results show that XGBoost significantly outperforms SVR, achieving consistently low MAPE values across all cryptocurrencies, demonstrating its ability to effectively capture market price movements. In contrast, SVR showed mixed performance, succeeding with certain cryptocurrencies but struggling with others, highlighting their inconsistency in predicting market trends. This study concludes that XGBoost is a more effective algorithm in predicting cryptocurrency prices and demonstrates its potential to improve financial forecasting in the cryptocurrency sector.
Virtual Assisten Dengan Metode Rule Base Untuk UMKM Latitaka Borneo Berbasis Telegram Devi Ayu Permatasari; Viny Christanti Mawardi; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32866

Abstract

Latitaka Borneo MSMEs play a role in preserving local culture through typical Kalimantan herbal products. However, limitations in providing responsive customer service are a challenge amidst market competition. To overcome this problem, this research develops a virtual assistant based on a rule-based method that is integrated with the Telegram platform. This system is able to answer general questions, provide product information, and assist customers in the ordering process automatically. System testing involves evaluation using confusion matrices and cosine similarity to assess response accuracy and semantic relevance. The evaluation results show that the virtual assistant is able to increase operational efficiency and consistency of Latitaka Borneo services, so that it can better meet customer needs. It is hoped that this research can be a solution to increase the competitiveness of MSMEs through customer service automation.
Sistem Reservasi Perawatan Gigi Berbasis Website Pada Klinik Marvel Dental Chavia Rossyerin Prabowo Sutjiadi; Agus Budi Dharmawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32867

Abstract

In the midst of rapid global business development, information technology plays an important role in the health sector, especially in improving the quality of services to the community. The computerized system supports business success by speeding up and making various types of work more efficient, however Marvel Dental Clinic still has not implemented information technology to improve the quality of its services so there are several problems that arise, namely the reservation process is currently still done manually. Where this is a manual process, when patients make a reservation, they need to contact them via WhatsApp. The manual reservation process results in uncertainty in knowing the waiting time and uncertainty in getting an admin response. Another problem is that if you make a reservation for dental care using Whatsapp, if many patients make reservations, reservation applications can be piled up, so that the clinic does not know that there are reservations from these patients. This research aims to design and build a website-based dental care reservation system using the PHP programming language by utilizing the Laravel framework and the SDLC Prototype development method. This system makes it easier for patients to order services online and manage schedules more efficiently.
PEMBANGUNAN WEBSITE PENJUALAN BAJU CUSTOM PADA TOKO PROJECT7 Willyam Jordan Kusuma
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32868

Abstract

Custom clothing is an apparel product that is currently trending, because many people want clothes with different motifs, or with pictures on them. However, because of the large number of customers who want orders, a website is needed to ensure that there is stock of clothes that are sold or are out of stock at that time. This study aims to build a sales website. The Waterfall Model method or waterfall model is used in designing the sales website, the Waterfall method provides a sequential software lifecycle approach, starting from analysis, design, coding, testing, and supporting stages. The development of the sales website uses HTML and CSS programming languages. Data collection uses a Google form questionnaire containing questions with answers on a scale of "strongly disagree" to "strongly agree", to complete the needs of the manager. This study produces a sales website with sales features that are generally found in ordinary online stores.
PERANCANGAN APLIKASI WEBSITE UNTUK LAYANAN ASPIRASI MAHASISWA DAN MANAJEMEN ORGANISASI DPM FTI UNTAR Salsabila Azhary Firdaus; Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32869

Abstract

The Student Representative Council of the Faculty of Information Technology, Tarumanagara University (DPM FTI Untar) is a student legislative body that plays an important role in facilitating student aspirations with the faculty. The main problem faced is the lack of integrated aspiration management system and digital organization management. This research aims to develop a web application that facilitates the management of student aspirations, member attendance system, and organizational archive management to increase transparency and student participation. The application development uses the Agile Software Development Life Cycle (SDLC) methodology which includes the stages of requirements analysis, interface design, system development, testing, and documentation. The design wants to be built using the PHP programming language and MySQL database. This research also includes an analysis of the DPM FTI organizational structure, database design, and infrastructure specifications needed to support application implementation. The results of this research are expected to optimize the process of managing student aspirations and organizational management of DPM FTI Untar in a more efficient, structured, and integrated manner.

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