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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Conference SENATIK STT Adisutjipto Yogyakarta INTECOMS: Journal of Information Technology and Computer Science JSAI (Journal Scientific and Applied Informatics) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Informasi dan Teknologi ILKOMNIKA: Journal of Computer Science and Applied Informatics JISA (Jurnal Informatika dan Sains) Journal of Computer System and Informatics (JoSYC) International Journal of Applied Business and Information Systems Infotek : Jurnal Informatika dan Teknologi Jurnal Indonesia : Manajemen Informatika dan Komunikasi International Journal Software Engineering and Computer Science (IJSECS) Journal Of Information System And Artificial Intelligence Journal of Scientific Research, Education, and Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Abdi Rakyat
Waluyo, Anita Fira
Universitas Teknologi Yogyakarta
Religion Aerospace Engineering Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Other

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Peringatan Dini Banjir Berbasis Internet Of Things (IOT) dan Telegram Waluyo, Anita Fira; Putra, Taufik Rizki
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.24109

Abstract

Flooding is a natural event that can have serious impacts on ecosystems, the economy and human life. In efforts to mitigate and control flood risks, early warning plays an important role in providing quick information to the public and the authorities. In this context, the application of the Internet of Things (IoT) provides an innovative solution by utilizing the latest technology to create an efficient and accurate flood early warning system. This research is intended to create a prototype river water level monitoring system using NodeMCU and the Telegram application programming interface as a first step in anticipating flooding. The main objective is to provide assistance to supervisory officers in monitoring river water levels in real time. This research method includes the development and integration of sensors connected to an IoT network to accurately detect changes in water level. The system also implements efficient data analysis algorithms to determine whether conditions require early warning. Telegram was chosen as communication platform to convey warning messages to the public. The IoT device is connected to a buzzer which will provide a sound warning when the water level reaches a threshold. The research results obtained show that water level conditions in the range of 2cm-50cm are categorized as Alert 1 status, so the buzzer (Alarm) is On. In the 51cm-99cm range, the status is Alert 2, and in the 100cm-400cm range the status is Alert 3 with the buzzer Off. Apart from that, via the Telegram bot the status of Alert 3, Alert 2, and Alert 1 will be informed
Implementasi Forward Chaining Dalam Sistem Pakar Untuk Menentukan Dosis Pemupukan Tahunan Kelapa Sawit Ramadhan, Rayka Mulya; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3357

Abstract

Proper fertilization of oil palm is crucial for increasing plant productivity, however farmers often face challenges in determining the correct fertilizer dosage based on plant conditions and soil types. This study aims to develop an expert system using the forward chaining method to determine the annual fertilizer dosage for oil palm. The forward chaining method was chosen due to its ability to draw conclusions progressively based on initial data (soil type and plant age). The system operates by applying pre-programmed rules to generate accurate fertilizer dosage recommendations. Testing results show that the system can provide precise dosages based on the age category and soil type of the oil palm. The implementation of this system is expected to assist oil palm farmers in improving agricultural efficiently.Keywords: Forward chaining; Expert system; Oil palm; Fertilizer dosageAbstrakPemupukan kelapa sawit yang tepat sangat penting untuk meningkatkan produktivitas tanaman, namun sering kali petani kesulitan dalam menentukan dosis pupuk yang sesuai dengan kondisi tanaman dan jenis tanah. Penelitian ini bertujuan untuk mengembangkan sistem pakar berbasis metode forward chaining dalam menentukan dosis pemupukan tahunan pada kelapa sawit. Metode forward chaining dipilih karena kemampuannya dalam menarik kesimpulan secara bertahap berdasarkan data awal (jenis tanah dan umur tanaman). Sistem ini bekerja dengan cara mengaplikasikan aturan (rule) yang sudah diprogramkan untuk menghasilkan rekomendasi dosis pupuk yang tepat. Hasil pengujian menunjukkan bahwa sistem dapat memberikan dosis yang akurat sesuai dengan kategori umur dan jenis tanah kelapa sawit. Dengan implementasi sistem ini, diharapkan dapat membantu petani kelapa sawit dalam meningkatkan hasil pertanian secaraefisien.
Klasifikasi Tujuan Penggunaan AI Oleh Mahasiswa Dengan Algoritma K-Nearst Neighbor Karoh, Sabilatul Isti; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3348

Abstract

Artificial intelligence (AI) technology is developing rapidly, particularly through platforms like ChatGPT and Gemini AI, which are widely used by students for various purposes. This fact highlights the importance of a more in-depth analysis of students' AI usage patterns. This study aims to classify the purposes of AI use by students using the K-Nearest Neighbor (K-NN) algorithm. The study was conducted using two classification approaches: multi-class classification and binary classification. Data were obtained from questionnaires with 305 respondents and processed using Python on the Google Colab platform using preprocessing, normalization, and data encoding stages. Test results show that the K-NN algorithm achieved a high accuracy of 77% in the binary classification scenario (Productive/Career and Entertainment/Personal), while in the multi-class classification scenario the highest accuracy only reached 34%. This finding indicates that K-NN performance is strongly influenced by the complexity of the number of classes and is more optimally applied to classifications with a limited number of classes.Keywords: K-Nearest Neighbor; AI usage classification; students; Binary Classification; Multi-class Classification.AbstrakTeknologi kecerdasan buatan ataupun Artificial Intelligence (AI) berkembang pesat, terutama melalui platform seperti ChatGPT dan Gemini AI yang banyak digunakan oleh mahasiswa untuk berbagai tujuan. Fakta ini menunjukkan pentingnya analisis yang lebih mendalam mengenai pola penggunaan AI oleh mahasiswa. Penelitian ini bertujuan untuk mengklasifikasikan tujuan penggunaan AI oleh mahasiswa memakai algoritma K-Nearest Neighbor (K-NN). Penelitian dilakukan melalui dua pendekatan klasifikasi, yaitu multi-class classification dan binary classification. Data didapatkan dari kuesioner terhadap 305 responden dan diolah memakai Python pada platform Google Colab menggunakan tahap pra-pemrosesan, normalisasi, dan pengkodean data. Hasil pengujian menunjukan algoritma K-NN mencapai akurasi tinggi yaitu 77% pada skenario klasifikasi biner (Produktif/Karir dan Hiburan/Personal), sementara pada skenario klasifikasi multi-kelas akurasi tertinggi hanya mencapai 34%. Temuan ini menandakan bahwa kinerja K-NN sangat dipengaruhi oleh kompleksitas jumlah kelas dan lebih optimal diterapkan pada klasifikasi dengan jumlah kelas yang terbatas. 
Pengembangan Sistem Informasi Manajemen Kepegawaian Berbasis Web dan Mobile pada PT Anugrah Salman Medika Saputri, Afina Dwi; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3365

Abstract

This study is motivated by the fragmented implementation of employee administrative processes, such as attendance, leave submission, and payroll management, which leads to low efficiency and potential data inconsistency. This study focuses on the development of an integrated web and mobile based employee information system to improve the effectiveness of personnel data management. The Waterfall model is applied in the system development process, consisting of requirements analysis, system design, implementation, and testing as the application development stages. The developed system integrates geolocation-based attendance, digital leave submission and approval, and digital payroll slips in PDF format. System testing was conducted using a black box approach to examine whether system functions align with user requirements. The testing results indicate that the main system features operate properly and have the potential to improve data management efficiency, information accuracy, and administrative transparency within the organization.Keywords: Management information system; Location-based attendance; Employee leave; Digital payroll slip; Web and mobile application AbstrakPenelitian ini dilatarbelakangi oleh masih terpisahnya proses administrasi kepegawaian, seperti absensi, pengajuan cuti, dan penggajian, yang menyebabkan rendahnya efisiensi dan potensi ketidaksesuaian data. Fokus penelitian ini adalah pengembangan sistem informasi kepegawaian terintegrasi berbasis web dan mobile sebagai upaya meningkatkan efektivitas pengelolaan data kepegawaian. Model Waterfall digunakan dalam pengembangan sistem dengan tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian sebagai alur pengembangan aplikasi. Sistem yang dikembangkan mengintegrasikan fitur absensi berbasis geolocation, pengajuan dan persetujuan cuti secara digital, serta penyajian slip gaji digital dalam format PDF. Pengujian terhadap sistem dilakukan dengan pendekatan black box guna memeriksa kesesuaian fungsi sistem terhadap kebutuhan pengguna. Berdasarkan hasil pengujian tersebut, fitur-fitur utama pada sistem dapat berjalan dengan baik dan berpotensi memberikan peningkatan pada efisiensi pengelolaan data, ketepatan informasi, serta keterbukaan proses administrasi kepegawaian di perusahaan. 
Sistem Pakar Diagnosa Penyakit Lambung Menggunakan Backward Chaining Sabrina, Klabut Ratih Valiza Dwi; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3395

Abstract

Gastric disorders are common health problems that require early detection to ensure appropriate treatment. This study examines the development of a web-based expert system to support the early diagnosis of gastric diseases by applying the Backward Chaining method as the inference mechanism and the Certainty Factor method to determine the level of diagnostic confidence. The knowledge base was constructed from symptom data and certainty weights obtained from medical experts, which were then integrated into the system to form a systematic inference process. System testing was conducted using 25 variations of symptom combinations to verify the performance of the backward chaining inference mechanism and certainty factor calculations. The evaluation results demonstrate that the system is capable of producing diagnostic outcomes that align with expert preferences, achieving an accuracy rate of 96%. This indicates that the reasoning process and confidence level calculations within the system operate as designed. The developed system has the potential to support early diagnosis of gastric diseases in a fast and accessible manner and can be utilized as a self-consultation tool for the general public.Keywords: Expert system; Backward chaining; Certainty factor; Gastric diseases AbstrakGangguan lambung termasuk permasalahan kesehatan yang banyak ditemukan sehingga memerlukan deteksi sejak dini agar penanganan dapat dilakukan secara tepat. Penelitian ini mengkaji pengembangan sistem pakar berbasis web untuk mendukung diagnosis awal penyakit lambung dengan menggunakan metode Backward Chaining sebagai mekanisme inferensi serta Certainty Factor untuk menentukan tingkat keyakinan. Basis pengetahuan disusun dari data gejala dan bobot yang diperoleh dari pakar, selanjutnya diintegrasikan ke dalam sistem guna membentuk proses inferensi yang sistematis. Pengujian sistem dilakukan menggunakan 25 variasi kombinasi gejala untuk memverifikasi kinerja mekanisme inferensi backward chaining dan perhitungan certainty factor. Hasil evaluasi menunjukkan kemampuan diagnostik yang dimiliki oleh sistem penyakit lambung dengan aturan serta bobot keyakinan dalam basis pengetahuan, dengan tingkat kesesuaian terhadap preferensi pakar sebesar 96%. Hal ini menandakan bahwa proses penalaran dan perhitungan tingkat keyakinan pada sistem telah berjalan sesuai dengan perancangan. Sistem yang dikembangkan berpotensi mendukung proses diagnosis awal penyakit lambung secara cepat dan mudah diakses, serta dapat digunakan sebagai alat bantu konsultasi mandiri bagi masyarakat. 
Conformer-Performer: An Efficient Architecture for Voice Activity Detection Apriliyanto, Echa; Waluyo, Anita Fira
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 4 No. 4 (2025): Vol. 4 No. 4 2025
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v4i4.979

Abstract

Voice Activity Detection (VAD) is a crucial pre-processing step for speech technologies, yet standard Conformer architectures suffer from quadratic computational complexity. This study introduces the Conformer-Performer, a novel architecture that replaces standard multi-head self-attention with the Fast Attention Via positive Orthogonal Random features (FAVOR+) mechanism to achieve linear complexity. The objective was to develop an efficient VAD model that maintains high accuracy suitable for resource-constrained applications. The model was trained on the multilingual FLEURS dataset using a teacher-student approach and extensive data augmentation. Experimental results demonstrate that the Conformer-Performer achieves an F1-score of 98.29%, which is highly competitive with the standard Conformer's 98.41%, while achieving a 7.8-fold reduction in peak GPU memory usage and a 3.46-fold speedup in CPU inference time. Furthermore, the proposed model significantly outperforms the SileroVAD baseline. These findings confirm that the Conformer-Performer offers a compelling balance of accuracy and efficiency, making it highly suitable for real-time, on-device speech processing.
Mobile Music Recommendation Using K-Nearest Neighbor and Artificial Intelligence Septiandy Kusmawan, Egy; Waluyo, Anita Fira
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 5 No. 1 (2026): Vol. 5 No. 1 2026
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v5i1.1000

Abstract

The development of online music services demands increasingly personalized and contextual recommendation systems. However, most existing systems are still limited to processing historical data without taking into account the emotional state or activities of users. This study aims to design a machine learning-based music recommendation system that generates recommendations based on the user's listening history and artificial intelligence (AI) to produce personalized song recommendations based on the user's mood and activity. The methods used include song data analysis from the Spotify API, the K-Nearest Neighbor (KNN) algorithm, and the application of a Large Language Model (LLM) as a prompt-based interactive interface. Test results show that the system is capable of providing song recommendations with a 95% similarity rate using machine learning based on the songs listened to by users, and the application of AI produces more specific recommendations according to user prompts.
Golden Goal Futsal Court Rental Mobile Application Using the First Come First Serve (FCFS) Algorithm and Payment Gateway Integration Sirajudin, Sirajudin; Sanjaya, Fadil Indra; Waluyo, Anita Fira
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2545

Abstract

The futsal pitch rental process at Golden Goal is still done manually through direct communication or text messages, which often results in various problems such as unstructured booking queues, schedule conflicts due to the lack of a clear queuing system, and late payments. These problems result in low operational efficiency and an increased potential for scheduling errors. This research aims to develop a mobile-based futsal pitch rental application equipped with the implementation of the First Come First Serve (FCFS) algorithm to ensure the booking process is carried out based on the user's arrival time in a fair and orderly manner. The system development method used is the Waterfall model, which includes requirements analysis, design, implementation, testing, and maintenance. The application was developed using the Flutter framework because it has the ability to produce Android and iOS applications with only a single codebase, faster development time, and stable and responsive interface performance. These advantages make Flutter suitable for building a real-time booking system that requires fast interaction and a consistent user experience. Furthermore, the application is integrated with Midtrans services as a payment gateway to facilitate automatic digital payment transactions. Testing results using the black-box method indicate that all key features, including schedule selection, FCFS-based queuing mechanism, payment processing, and rental data management, have run well as needed. The implementation of this system has proven to be able to reduce schedule conflicts, improve the accuracy of the booking process, and increase the efficiency of rental management at Golden Goal. Thus, this application can be an effective and modern solution to address the problem of futsal field rentals that have been handled manually.
Design and Development of IoT-Based Mobile Application for Heart Rate and Body Temperature Monitoring Den Bintang Restu Satria Shandra; Anita Fira Waluyo
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5945

Abstract

The rapid development of Internet of Things (IoT) technology has influenced many fields, especially healthcare delivery systems. This paper will analyze the effect of IoT-based mobile applications on the quality of healthcare services through real-time patient monitoring. The application developed in this study was used to monitor vital signs heart rate and body temperature using sensors attached to mobile devices. The research methodology includes system architecture design and implementation with MAX30102, DS18B20, and MLX90614 sensors where the ESP32 microcontroller acts as the main integration platform. The application development was done using Android Studio and Flutter frameworks. User testing showed significant improvements in the speed at which critical conditions are detected among patients and also in the time taken by healthcare providers to respond to such situations. User satisfaction ratings indicated high acceptance levels, thus proving a large potential market for digital healthcare. Results from this study also proved that IoT-mobile application integration can uplift standards in healthcare services while providing a practical solution for modern-day medical practice.
Web and Mobile-Based Online Watch Auction Application Using Waterfall Method Kusuma, Alfian Nur; Waluyo, Anita Fira
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 5 No. 1 (2026): Vol. 5 No. 1 2026
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v5i1.1061

Abstract

The advancement of mobile technology has driven the creation of digital solutions that simplify various activities, including the auction process. This study aims to design and develop a mobile-based online watch auction application using Flutter as the user interface development framework. In addition to the mobile application for users, a web-based admin dashboard was also developed to manage auction data, including creating auctions. The backend system was developed using Node.js with PostgreSQL as the database management system. The mobile application provides key features such as user registration, login, viewing auction lists, placing bids, and viewing bidding history. Meanwhile, the web admin system enables administrators to manage auction items and monitor the auction process efficiently. The test results show that the main features function according to user needs, and the system runs stably on both mobile devices and web platforms. This application is expected to serve as a practical and easy-to-use digital auction platform.
Co-Authors Aji Nugraha, Gilang Wisnu Alfatah, Ahmat Ali, Hilmi Amilianto, Alif Sufi Anna Dina Kalifia Apriliyanto, Echa Arganta, Nanda Fahri Den Bintang Restu Satria Shandra Fadil Indra Sanjaya Fajar Satria Fajar, Muhammad Holid Farida Ardiani Fiqih Refwahajan Harsojo Sabarman Ikrima Alfi Irma Handayani Irma Handayani, Irma Karoh, Sabilatul Isti Khadijah, Ayu Suci Kusuma, Alfian Nur M. Wira Tama Febriwahono Muhamad Difa Khairuddin Muhammad Fachrie Muhammad Rizqi Raka Siwi Muhammad Rizqi Retrianto Murti Retnowo Pratama, Ryan Ali Prayogo, Muhammad Tegar Putra, Taufik Rizki Putri, Dhea Desliana Rahayu, Vani Ramadhan, Muhamad Ali Nugroho Ramadhan, Rayka Mulya Refwahajan, Fiqih Retrianto, Muhammad Rizqi Revi Ananda Kirana Putri Rofik Hakiki Sabrina, Klabut Ratih Valiza Dwi Saputri, Afina Dwi Satria, Fajar Selfi Artika Septiandy Kusmawan, Egy Sirajudin Sirajudin Wahyu Sri Utami Widia Widia