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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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Sistem Monitoring dan Penyiraman Otomatis Pada Bibit Sawit Berbasis Android Fajar, Muhammad Holid; Waluyo, Anita Fira
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.v7i1.24026

Abstract

The quality of oil palm fruits is very important, and effective seedling care is one of the techniques to produce quality oil palm seedlings. However, seedling care is often constrained by watering, because seedling owners cannot control oil palm seedlings at all times. The purpose of this project is to create a tool and mobile application used to control soil moisture and automatic watering based on android In this study, sensor testing and interviews were used as data collection methods. To determine soil moisture, this system uses a soil moisture sensor. Then the NodeMCU ESP8266 microcontroller will process the data obtained from the sensor, after which the data will be stored in real time in the Firebase realtime database. Android applications made with the Java programming language can be used for monitoring. This system can facilitate the owners of oil palm seedlings in controlling and watering the seedlings, even though they are traveling, the owner of the seedlings can control the oil palm seedlings using the Android application, so that with regular seedling care it will produce quality oil palm
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
Workshop Pengolahan Data Nilai Siswa Menggunakan Microsoft Excel di SD Negeri Jumeneng Anita Fira Waluyo; Irma Handayani; Ikrima Alfi; Wahyu Sri Utami; Farida Ardiani; Selfi Artika
Jurnal ABDI RAKYAT Vol. 1 No. 1 (2024): JURNAL ABDI RAKYAT
Publisher : Universitas Teknologi Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/jar.v1i1.293

Abstract

Workshop on processing student grades data using Microsoft Excel is a training activity that aims to introduce the use of Microsoft Excel in managing and analyzing student grades data effectively. This workshop is aimed at teachers at SD Negeri Jumeneng with the aim of increasing their understanding of using Excel as a tool for processing data. In this workshop, the participants will be given an explanation regarding the use of Excel in processing student grade data. The material includes an introduction to relevant basic Excel formulas such as SUM, AVERAGE, MAX, MIN, IF, and others. In addition, participants will also be given guidance on graphing student grade data using Excel. This workshop was carried out through a practical approach by providing training to participants to apply Excel formulas and functions in processing student value data. It is hoped that this workshop will provide significant benefits for teachers at SD Negeri Jumeneng in managing and analyzing student grade data more efficiently using Microsoft Excel.
Implementasi Canva Dalam Peningkatan Pembelajaran di SDN Gabahan Waluyo, Anita Fira; Handayani, Irma; Alfi, Ikrima; Utami, Wahyu Sri; Kalifia, Anna Dina; Artika, Selfi
Jurnal ABDI RAKYAT Vol. 2 No. 1 (2025): JURNAL ABDI RAKYAT
Publisher : Universitas Teknologi Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/jar.v2i1.484

Abstract

The main challenge faced by educators in the current digital era is creating interesting and informative learning materials. Graphic design plays an important role in creating effective learning materials. As an easy-to-use graphic design platform, Canva can be an effective solution to meet these needs. Using Canva in graphic design to create learning materials is a community service that aims to improve the quality of learning materials by utilizing the Canva graphic design platform. This research aims to provide tools and knowledge for educators in creating interesting and informative learning materials. This training was carried out using interactive lecture methods, direct practice and question and answer. The measurement of the results achieved is an increase in educators' skills and understanding in using Canva for graphic design. This is proven by the quality of the learning materials produced after the training. Evaluation of the learning materials that have been created also shows improvements in visual appeal, message clarity and overall learning effectiveness. Thus, the use of Canva in graphic design for creating learning materials has had a positive impact in improving the quality of learning and students' learning experiences.
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.
Co-Authors Aji Nugraha, Gilang Wisnu Alfatah, Ahmat Alfi, Ikrima Ali, Hilmi Amilianto, Alif Sufi Apriliyanto, Echa Arganta, Nanda Fahri Artika, Selfi 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 Kalifia, Anna Dina Karoh, Sabilatul Isti Khadijah, Ayu Suci Kusuma, Alfian Nur M. Wira Tama Febriwahono Muhamad Difa Khairuddin Muhammad Fachrie Muhammad Rizqi Retrianto Murti Retnowo Pratama, Ryan Ali Prayogo, Muhammad Tegar Putra, Taufik Rizki Putri, Dhea Desliana Putri, Revi Ananda Kirana Rahayu, Vani Ramadhan, Muhamad Ali Nugroho Ramadhan, Rayka Mulya Refwahajan, Fiqih Retrianto, Muhammad Rizqi Rofik Hakiki Sabrina, Klabut Ratih Valiza Dwi Saputri, Afina Dwi Satria, Fajar Selfi Artika Septiandy Kusmawan, Egy Sirajudin Sirajudin Utami, Wahyu Sri Wahyu Sri Utami Widia Widia