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All Journal Jurnas Nasional Teknologi dan Sistem Informasi JIKO (Jurnal Informatika dan Komputer) Jurnal Komputer Terapan Jurnal Informatika Universitas Pamulang Petir J-SAKTI (Jurnal Sains Komputer dan Informatika) Kumawula: Jurnal Pengabdian Kepada Masyarakat JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pengabdian UNDIKMA Jurnal Pengabdian Polinema Kepada Masyarakat International Journal of Multidisciplinary: Applied Business and Education Research J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Journal of Applied Business and Technology Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat
Candra Bella Vista
Politeknik Negeri Malang
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Analysis of System Requirements and Architecture for Facilitating Table-Based Data Clustering for Non-Technical Users Yoppy Yunhasnawa; Toga Aldila Cinderatama; Candra Bella Vista
Journal of Applied Business and Technology Vol. 4 No. 3 (2023): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v4i3.140

Abstract

Clustering is one of the key techniques in unsupervised learning analysis, aimed at grouping similar data objects into clusters based on shared characteristics. The broad benefits of clustering are evident across various sectors, such as business, marketing, finance, and many others. However, the complexity of implementing clustering, especially for those without a background in statistics or programming, poses a barrier. The appropriate selection of clustering methods and accurate interpretation of results require a solid understanding of statistics. This research aims to address this issue by crafting a detailed Software Requirements Specification for a user-friendly clustering application, equipped with an intuitive interface and effective tools, based on comprehensive literature study, which finally allowing non-experts to engage in the clustering process without in-depth knowledge of statistics or programming. As such, this study endeavors to provide a practical solution for utilizing clustering without excessive technical impediments.
Implementasi Machine Learning dalam Sistem Prediksi dan Rekomendasi Program Diet Terintegrasi LLM Endah Septa Sintiya; Sely Ruli Amanda; Candra Bella Vista; Agung Nugroho Pramudhita
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 2 (2025): Agustus 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i2.2025.144-151

Abstract

Malnutrition, both in the form of overweight and underweight, remains a global health challenge. Unhealthy urban lifestyles and limited access to appropriate nutritional interventions exacerbate this problem. Technology-based approaches such as machine learning and Large Language Models (LLM) offer opportunities to improve the effectiveness of dietary management. This study proposes the development of a machine learning-based and LLM-integrated diet program prediction and recommendation system applied to Cafe NUT Castle. The system was developed to digitize body composition data recording, predict diet programs (weight loss, weight gain, and body fat loss) using the Random Forest algorithm, and generate personalized initial diet recommendations through the integration of the Gemini Flash-Lite API. Based on the test results, the prediction model achieved an accuracy of 93% on the test data and 84% on 50 new datasets. Evaluation of the diet recommendations generated by LLM showed a feasibility level of 86.6% which was categorized as very feasible. These results indicate that the developed system is not only accurate in predicting diet programs but also effective in providing initial recommendations that can support decision-making in digital nutrition consultation services.
Pengembangan Chatbot Berbasis Framework RASA pada Website Bank Sampah Sriwilis Vista, Candra Bella; Tundjung, Mellyana; Fatmawati, Triana; Sintiya, Endah Septa
Jurnal Informatika Polinema Vol. 12 No. 2 (2026): Vol. 12 No. 2 (2026)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i2.9569

Abstract

Perkembangan teknologi informasi dalam bidang Natural Language Processing (NLP) membuka peluang pemanfaatan chatbot sebagai solusi layanan informasi berbasis website yang interaktif dan responsive di tengah keterbatasan tenaga pelayanan dan waktu operasional. Chatbot memungkinkan pengguna memperoleh informasi secara real-time tanpa keterlibatan operator manusia secara langsung, sehingga dapat meningkatkan efisiensi dan ketersediaan layanan. Penelitian ini bertujuan mengembangkan chatbot berbasis Framework Really Awesome Software Automation (RASA) pada Website Bank Sampah Sriwilis serta menganalisis pengaruh konfigurasi pipeline Natural Language Understanding (NLU) terhadap performa klasifikasi intent. Metode pengembangan sistem menggunakan model Waterfall yang meliputi tahap analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Dataset disusun dalam bahasa Indonesia, terdiri dari 9 intent dengan total 250 kalimat. Eksperimen dilakukan terhadap tiga konfigurasi pipeline, yaitu DIETClassifier sebagai model baseline, DIETClassifier dengan penambahan fitur leksikal melalui RegexFeaturizer dan LexicalSyntacticFeaturizer, serta LogisticRegressionClassifier sebagai model pembanding. Evaluasi kinerja model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model berbasis DIETClassifier memberikan peningkatan performa akurasi sebesar 5% dibandingkan Logistic Regression. Konfigurasi model dengan penambahan pipeline RegexFeaturizer dan LexicalSyntacticFeaturizer menghasilkan nilai accuracy terbaik sebesar 93%, precision 93%, recall 91%, dan F1-score 91%. Dengan demikian, pemilihan konfigurasi pipeline yang tepat serta penerapan fitur tambahan berpengaruh signifikan terhadap peningkatan performa chatbot berbasis RASA pada layanan informasi Bank Sampah Sriwilis.
Development of a Web-Based SQL Query Online Examination System with Automated Grading Using the MVC Design Pattern Yoppy Yunhasnawa; Atif Windawati; Toga Aldila Cinderatama; Candra Bella Vista; Moch. Zawaruddin Abdullah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3285

Abstract

In this study, the Researchers provide the design, development, and evaluation of a web-based SQL exam system that utilizes the Model-View-Controller (MVC) architectural pattern to enhance automated grading functionality and ease of maintenance. The main objectives of the system are to simplify the process of administering SQL exams, to make it user-friendly for students to enter their SQL statements, and as a means for teachers to automate the grading process. This allows a clear separation between three separate modules: Model to manage data, View to present the application to users, and Controller to manage the application logic. This separation allows for modular development, easier maintenance, and code reuse. The fundamental aspect of the system lies in its automated grading mechanism, which intelligently compares the SQL queries submitted by students with the corresponding validated answer keys stored in the database. Extensive black-box testing was conducted to ensure the reliability and accuracy of the system with various test cases to assess its ability to assess responses and provide real-time feedback to students, in addition to smooth and intuitive navigation within the system. All testing criteria yielded successful results with 100% agreement proving the robustness of the system with all possible locations that could potentially be used in higher education structures. The system provides a scalable and flexible approach to address the challenges associated with SQL assessment in academic institutions, thereby facilitating uniform, efficient, and objective evaluation standards. The system uses data up to October 2023 to prevent the model from becoming obsolete
Co-Authors Adhitya Bhawiyuga, Adhitya AdiNugroho, Rifkie Nurdian Agung Nugroho Pramudhita Amrozi, Aris Nur Annisa Puspa Kirana Annisa Taufika Firdausi Ariadi Retno Tri Hayati Ririd Astiningrum, Mungki Atif Windawati Cahaya Puspitaningrum, Ari Dhebys Suryani Hormansyah, Dhebys Suryani Dimas Wahyu Wibowo Dwi Puspitasari Elok Nur Hamdana Embriani Dewi Lestari Endah Septa Sintiya Febriyanto, Nugroho Gunawan Budiprasetyo Habibie Ed Dien Habibie Ed Dien Hendrawan, Muhammad Afif Ika Kusumaning Putri Kusumawardana, Arya Mamluatul Hani’ah Maskur Maskur Mita Kartina Sari Moch Zawaruddin Abdullah Nugraha, Girindra Fajar Nugroho Febriyanto Osa Mahanani Sihono Puspa Kirana, Annisa Rahayuningtias, Indah Rahmad, Cahya Rakhmat Arianto Rinanza Zulmy Alhamri, Rinanza Zulmy Rokhimatul Wakhidah Rosa Andrie Asmara Sely Ruli Amanda Toga Aldila Cinderatama Triana Fatmawati Tundjung, Mellyana Usman Nurhasan Veronica Elyzabeth Islami, Ratu Vit Zuraida Wilda Imama Sabilla Windawati, Atif Yoppy Yunhasnawa