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All Journal Jurnal Ilmiah Informatika Komputer JUITA : Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURIKOM (Jurnal Riset Komputer) JURTEKSI Indonesian Journal of Applied Informatics Informasi Interaktif METIK JURNAL Jurnal Teknologi Informasi dan Multimedia Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Innovation and Future Technology (IFTECH) Zonasi: Jurnal Sistem Informasi Respati JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Information System Journal (INFOS) Journal of Computer Science and Informatics Engineering Batara Wisnu : Indonesian Journal of Community Services Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Teknologi Informasi SWAGATI: Journal of Community Service Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat Inovasi Indonesia
Fajri, Ika Nur
Program Studi Sistem Informasi, Universitas AMIKOM Yogyakarta
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Public Health Social Sciences Other

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Implementasi Sistem Informasi Berbasis Website Pada Gereja Ichtus Puildon Menggunakan Metode Waterfall Gilberth Patrick Daniel; Ika Nur Fajri; Yoga Prisyanto
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6671

Abstract

This research focuses on the development of a web-based information system for Ichtus Puildon Church, which faces issues in the management of congregation data that is still done manually. This process causes data to be easily lost and hard to access, as well as requiring more time and effort for report generation. The aim of this research is to design and implement an information system that can improve the efficiency of congregation data management. The approach used in this research is the Waterfall method, which includes problem identification, data collection through questionnaires, system analysis, and implementation. Testing is carried out using Black Box, White Box, and System Usability Scale (SUS) methods to evaluate the system's performance and user satisfaction. The results show that the application achieved a score of 74.2%, which falls into the "Good" category. Functional testing of login, menu access, and content management by the admin indicates that the system works well, provides a satisfactory user experience, and has the potential to improve the church's digital services.
Cross-Dataset Evaluation of Boosting Models for Hypertension Prediction Bety Wulan Sari; Dewi Ayu Murtiningsih; Donni Prabowo; Yoga Pristyanto; Ika Nur Fajri; Ike Verawati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.7620

Abstract

Hypertension remains a significant global risk factor for cardiovascular disease and related mortality, necessitating reliable early risk prediction models. Although boosting algorithms have demonstrated strong performance in structured medical data, limited studies have examined their consistency across heterogeneous datasets. This study aims to evaluate the cross-dataset performance and stability of three boosting models, such as XGBoost, LightGBM, and CatBoost, for hypertension prediction under multiple train–test split ratios. Two independent structured datasets were analyzed using 60:40, 70:30, 80:20, and 90:10 splits. To identify the optimal hyperparameters, grid search was performed using repeated stratified 5-fold cross-validation with three repetitions. Model effectiveness was measured using the evaluation metrics of accuracy, precision, recall, F1-score, and AUC. Results show that Dataset 1 gained consistently high predictive performance (accuracy > 0.98; AUC ≈ 1.00), indicating strong and well-separated predictive signals, whereas Dataset 2 demonstrated substantially lower discriminative ability (accuracy ≈ 0.71–0.72; AUC ≈ 0.50), suggesting limited predictive structure. Across both datasets, CatBoost consistently obtained the highest accuracy, particularly at the 90:10 split ratio. These findings demonstrate that dataset characteristics critically determine model effectiveness and that among the evaluated boosting algorithms, CatBoost delivered the strongest overall predictive performance.
Perancangan Sistem Informasi Pemesanan Berbasis Web di Restoran Pawon Jinawi Aldyan Gilang Primanda; Ika Nur Fajri
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i1.93524

Abstract

Abstrak:Pawon Jinawi merupakan sebuah usaha restoran yang bergerak dalam bidang penjualan makanan dan minuman. Restoran ini menyajikan berbagai menu rumahan khas Jawa. Namun, sistem pemesanan dan pengelolaan data di restoran ini masih dilakukan secara manual, yang menimbulkan masalah seperti lambatnya pelayanan dan risiko kehilangan catatan pesanan. Penelitian ini bertujuan untuk mengembangkan sistem informasi berbasis web yang memudahkan pelanggan dalam melakukan pemesanan  secara online. Sistem ini juga dirancang untuk membantu karyawan dalam pengelolaan data pesanan dan pembayaran secara lebih terstruktur. Metode pengembangan yang digunakan adalah waterfall, sebuah metode pengembangan perangkat lunak yang berjalan secara berurutan dan sistematis. Setiap tahap diselesaikan secara menyeluruh sebelum melanjutkan ke tahap berikutnya, untuk tahapannya mencakup lima tahap Requirement, Design, Implementation, Verification, dan Maintenance. Pengujian sistem dilakukan menggunakan metode Black box. Hasil penelitian ini yaitu sebuah sistem informasi pemesanan berbasis web. Setelah implementasi sistem akan meningkatkan efisiensi operasional restoran, dengan waktu pemrosesan pesanan yang berkurang sebesar 45%, serta peningkatan kepuasan pelanggan dalam hal kecepatan dan kemudahan proses pemesanan. Penelitian ini didukung oleh beberapa penelitian terdahulu yang menunjukkan manfaat dari penerapan sistem informasi untuk pengelolaan pemesanan di restoran==================================================Abstract:Pawon Jinawi is a restaurant business engaged in the sale of food and beverages. This restaurant serves a variety of Javanese home-style menus. However, the ordering system and data management in this restaurant are still done manually, which causes problems such as slow service and the risk of losing order records. This study aims to develop a web-based information system that makes it easier for customers to place orders online. This system is also designed to help employees manage order and payment data in a more structured way. The development method used is waterfall, a software development method that runs sequentially and systematically. Each stage is completed thoroughly before proceeding to the next stage, for the stages include five stages of Requirement, Design, Implementation, Verification, and Maintenance. System testing is carried out using the Black box method. The results of this study are a web-based ordering information system. After the implementation of the system will increase the operational efficiency of the restaurant, with order processing time reduced by 45%, as well as increased customer satisfaction in terms of speed and ease of the ordering process. This research is supported by several previous studies that show the benefits of implementing an information system for managing orders in restaurants
Klasifikasi Penyakit Anemia Menggunakan Algoritma Navïe Bayes Elda Putri Darmayanti; Ika Nur Fajri
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i1.94743

Abstract

Abstrak:Anemia merupakan kondisi medis yang umum di mana darah seseorang kekurangan sel darah merah yang sehat atau hemoglobin. Hemoglobin adalah protein dalam sel darah merah yang berfungsi untuk mengangkut oksigen dari paru-paru ke seluruh tubuh ketika seseorang terkena anemia, mereka mungkin merasa lelah, lemah, dan sesak napas. Anemia dapat disebabkan oleh berbagai faktor, termasuk kekurangan zat besi, vitamin B12, atau folat; kehilangan darah; dan kerusakan sumsum tulang. Dalam upaya untuk meningkatkan diagnosis awal dan akurasi klasifikasi penyakit anemia, penelitian ini menerapkan algoritma Naïve Bayes. Dataset yang digunakan dalam penelitian ini adalah dataset penyakit anemia yang didapatkan dari website kaggle.com, yang mencakup atribut-atribut penting seperti Gender, Hemoglobin, MCH, MCHC, MCV, dan Result. Pemilihan Naïve Bayes sebagai salah satu algoritma yang diuji didasarkan pada keunggulannya dalam menangani data dengan atribut sederhana serta kemampuannya mengelola data yang mengandung ketidakpastian. Naïve Bayes dikenal sebagai algoritma yang efisien untuk pengolahan dataset berukuran besar dengan struktur data yang sederhana. Selain itu, algoritma ini sering menjadi pilihan pada tahap awal eksplorasi data karena kesederhanaan implementasi, kecepatan pemrosesan, dan kemampuannya menghasilkan hasil yang cukup akurat dalam berbagai kondisi. Meskipun Naïve Bayes mungkin tidak selalu lebih akurat daripada SVM atau Decision Tree dalam kasus kompleks, algoritma ini menawarkan solusi yang lebih cepat, ringan, dan mudah diimplementasikan, yang sangat relevan untuk aplikasi medis dengan sumber daya terbatas. Pemilihan Naïve Bayes dalam penelitian ini bertujuan untuk mengeksplorasi keseimbangan antara kecepatan, efisiensi, dan akurasi dalam klasifikasi penyakit anemia=======================================Abstract:Anaemia is a common medical condition where a person's blood lacks healthy red blood cells or haemoglobin. Haemoglobin is a protein in red blood cells that serves to transport oxygen from the lungs to the rest of the body. When a person is anaemic, they may feel tired, weak, and short of breath. Anaemia can be caused by various factors, including iron, vitamin B12, or folate deficiency; blood loss; and bone marrow damage. In an effort to improve the early diagnosis and classification accuracy of anaemia, this study applied the Naïve Bayes algorithm. The dataset used in this research is an anaemia disease dataset obtained from the website kaggle.com, which includes important attributes such as Gender, Haemoglobin, MCH, MCHC, MCV, and Result. The selection of Naïve Bayes as one of the tested algorithms is based on its superiority in handling data with simple attributes and its ability to manage data containing uncertainty. Naïve Bayes is known as an efficient algorithm for processing large datasets with simple data structures. Moreover, it is often the algorithm of choice in the early stages of data exploration due to its simplicity of implementation, processing speed, and ability to produce reasonably accurate results under various conditions. While Naïve Bayes may not always be more accurate than SVM or Decision Tree in complex cases, it does offer a bargain
Indonesian Coffee Recommendation System based on Aroma and Flavor Profiles using the K-Means Clustering Algorithm Muhammad Fachmi Syahrial; Arif Nur Rohman; Ika Nur Fajri
SISTEMASI Vol 15, No 7 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i7.6379

Abstract

Indonesia's remarkable diversity of coffee sensory profiles presents both an opportunity and a challenge: consumers often struggle to identify coffees that match their taste preferences due to the absence of a recommendation system that aligns choices with measurable sensory attributes. This study develops an Indonesian coffee recommendation system based on K-Means Clustering using a dataset of 50 Indonesian coffee sensory profiles automatically collected through web scraping from the professional coffee review platform Coffee Review. The dataset comprises five quantitative sensory attributes: Aroma, Acidity, Body, Flavor, and Aftertaste. After applying Min-Max normalization, the K-Means algorithm with k-means++ initialization identified three optimal clusters (K = 3), determined using a combination of the Elbow Method, Silhouette Score (0.4889), Davies–Bouldin Index (0.831), and Calinski–Harabasz Score (45.41). The system recommends the top three coffee products by calculating the Euclidean distance between user preferences and the centroid of the nearest cluster. Functional evaluation using Black Box Testing across five test scenarios achieved a 100% success rate (5/5). This study contributes an objective sensory profile–based recommendation approach that addresses the cold-start problem in coffee recommendation systems and demonstrates strong potential for integration into local coffee applications and Indonesian coffee e-commerce platforms.
Hybrid LexRank-LDA-MMR for Indonesian Text Summarization Nasrul Amin Muis; Yoga Pristyanto; Ika Nur Fajri
Jurnal Nasional Teknologi dan Sistem Informasi Vol 12 No 1 (2026): April 2026
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v12i1.2026.97-104

Abstract

The rapid growth of digital text information makes it crystal clear that there is a need for automated tools that summarize text for rapid retrieval. Extractive methods employed include LexRank, Latent Dirichlet Allocation (LDA), and Maximal Marginal Relevance (MMR), and the study aimed at enhancing the quality of Indonesian text summaries with more than just regular LexRank. In this study, the role of LexRank was to assist in selecting meaningful sentences with centricity to the center of the graphs, while the role of LDA was to ensure that the sentences were topically relevant. The strength of MMR is maintaining the document's relevance and diversity, which reduces redundancy in the summaries. Summaries from two publicly available datasets, IndoSum and Liputan6, containing texts in Bahasa Indonesia, were analyzed at 30% and 50% compression levels and graded using ROUGE (ROUGE-1, ROUGE-2, ROUGE-L F1 score) measurements. Analysis of 5000 articles per dataset showed that the implementation of LexRank and LDA together with MMR resulted in a greater average ROUGE score than when using standard LexRank, irrespective of the set compression levels and across both datasets, demonstrating the effectiveness of the approach to enhance summary quality. The improvements recorded are most significant in ROUGE-1 and ROUGE-2, which indicates that these combination approaches can produce more informative and relevant summaries while preserving sentence-level diversity, which deepens the understanding of the information presented in the summary.
Sistem Informasi dan Klasifikasi Limbah Makanan Berbasis Website dengan Menggunakan Metode CNN Kelvin Jaya Pratama; Ika Nur Fajri
Jurnal Teknologi Informasi Vol 3, No 2 (2025): Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/juti.v3i2.1854

Abstract

Peningkatan jumlah limbah makanan yang beredar saat ini diakibatkan oleh tingginya permintaan makanan yang berkaitan dengan populasi umat manusia yang terus meningkat. Berdasarkan laporan dari Food and Agriculture Organization (FAO), sepertiga makanan terbuang sia-sia setiap tahunnya dan menyebabkan dampak buruk terhadap lingkungan, ekonomi, dan kesehatan. Kurangnya kesadaran dan pengetahuan masyarakat mengenai cara pengelolaan limbah makanan turut memperburuk masalah ini. Oleh karena itu, penelitian ini dilakukan bertujuan untuk mengembangkan sebuah sistem informasi berbasis website yang dilengkapi dengan fitur klasifikasi gambar limbah makanan menggunakan metode Convolutional Neural Network (CNN) dan arsitektur model MobileNetV2. Diharapkan produk yang dikembangkan dalam peneltiian ini dapat meningkatkan kesadaran masyarakat dan mengurangi dampak buruk limbah makanan terhadap lingkungan.
Pengembangan Sistem Informasi Pendakian Gunung “AyoMuncak” Berbasis Website dengan Pemanfaatan Data Geospasial Az Zahra Hijriah; Ika Nur Fajri; Agung Nugroho
Jurnal Teknologi Informasi Vol 4, No 1 (2025): Agustus 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/juti.v4i1.2125

Abstract

The increasing public interest in mountain hiking tourism in Indonesia has not been fully supported by the availability of accurate and integrated hiking information. This study aims to develop a web-based mountain hiking information system utilizing geospatial data to provide centralized and interactive information on hiking routes, weather forecasts, and hiker experiences. The system, named AyoMuncak, integrates interactive maps using Leaflet.js and weather data from the OpenWeatherMap API, and supports user-generated reviews. The system was developed using the waterfall model, which includes communication, planning, modeling, construction, and testing phases. Black box testing was used to ensure functional requirements were met. The results show that the system successfully delivers comprehensive information about 26 mountains in East Java, featuring mountain lists, location maps, weather forecasts, and review management. The system has been tested and proven to meet both user and admin needs. It is expected to enhance safety, convenience, and trip planning for hikers, while promoting the digitalization of tourism services based on spatial data.
Labuan Bajo Culinary Tourism Recommendation System: A Comparison of Content-Based Filtering Similarity Methods Sergius Septiade Masmur; Ika Nur Fajri; Arif Nur Rohman
SISTEMASI Vol 15, No 8 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i8.6830

Abstract

Labuan Bajo, as a national super-priority tourism destination, has experienced a significant increase in tourist visits, dominated by foreign tourists, which has driven the expansion of the culinary sector with a continuously increasing number of restaurants. This makes it difficult for tourists to choose dining options that match their preferences among the many available choices. Previous culinary tourism recommendation system research has only used a single similarity measurement technique without evaluating its effectiveness compared to other techniques. This study aims to build a culinary tourism recommendation system in Labuan Bajo using the Content-Based Filtering method, as well as to compare three similarity measurement techniques Cosine Similarity, Euclidean Distance, and Jaccard Similarity to determine which technique produces the most relevant recommendations. Data was obtained through scraping techniques on 150 restaurants in Labuan Bajo, covering category and rating attributes, which were then processed into a feature matrix for inter-item similarity calculation. Evaluation was carried out using Precision@5 with relevance criteria based on category similarity and rating proximity, followed by a Wilcoxon Signed-Rank Test to examine statistical significance between methods. The test results show that Cosine Similarity and Euclidean Distance produce an equal precision of 0.6947, higher than Jaccard Similarity at 0.6320, with the difference proven statistically significant (p < 0.001). The system was then implemented as a web application using the CodeIgniter framework, allowing users to select a similarity method and view restaurant recommendations interactively. This study demonstrates that considering the rating attribute, not just category, produces more relevant recommendations than a category-only approach.
Co-Authors Aditya Salman Agung Nugroho Agung Nugroho Aldyan Gilang Primanda Andi Muh. Rahul Rajes Topares Anggit Dwi Hartanto Anggit Dwi Hartanto, Anggit Dwi Ardani, Lutfasari arif nur rohman Arif Nur Rohman Arif Nur Rohman Arif Nur Rohman Asti Astuti, Ika ATIK NURMASANI Ayurira, Caren Legisna Aqila Az Zahra Hijriah Barus, Herianta Bety Wulan Sari Bety Wulan Sari, Bety Wulan Dari, Aprillia Wulan Nanda Dendi Agung Muhaziz Dewi Ayu Murtiningsih Dismas Banar Purnandi Donni Prabowo Dwi Hartanto, Anggit Dyah Anggita, Sharazita Elda Putri Darmayanti Eli Pujastuti, Eli Etik Anjar Fitriarti, Etik Anjar Femi Dwi Astuti Gilberth Patrick Daniel hallan, rosalia roja Hanifan, Hafid Hayaty, Mardhiya Hendra Kurniawan Ike Verawati Irwanto, Bagas Joy Raphaela Kelvin Jaya Pratama Kono, Maria Fatima Kurniawan, Febri Dwi Mahfud, Arisman Mangli, Luh Ajeng Roro Muhammad Fachmi Syahrial Muhammad Farhan Muhammad Irvan Murtiningsih, Dewi Ayu Mu’alif Lihawa Nasrul Amin Muis Natasaskara, Nandana Ayudya Norhikmah Norhikmah Nur Indah Kusumawardhani Nurhalisa, Vitra Pangestu, Rafel Alansyah Panji Ihsanudin Fajri Pinasti, Rafa Hadiya Pratama, Akbar Pratama, Subhan Rizky Putri Anggara, Rindina Adisya Radhita Rayhan Rahman Saputra, Rahman Rana Aphrodita, Ishiqa Rayhan, Radhita Rohim, Dwi Nur Roy Wenang Robbani Sergius Septiade Masmur Setioadi, Rizkiansyah Eka Sifa’ul Husna, Siti Okta Siska Siska Syamsul A Syahdan, Syamsul A W, Bambang Soedijono Widodo, Tegar Robi Wiwi Widayani Yoga Pristyanto Yoga Pristyanto Yoga Prisyanto Zahrotus Sa'idah Zaidan Putra, Bazil