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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ilmiah Matrik METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Sebatik IJISTECH (International Journal Of Information System & Technology) JUTEKIN (Jurnal Manajemen Informatika) METIK JURNAL Building of Informatics, Technology and Science Journal of Information Systems and Informatics Tematik : Jurnal Teknologi Informasi Komunikasi TEPIAN Buletin Poltanesa Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Media Jurnal Informatika Bulletin of Information Technology (BIT) J-Icon : Jurnal Komputer dan Informatika Sasambo: Jurnal Abdimas (Journal of Community Service)
Wahyuni - Wahyuni
STMIK Widya Cipta Dharma
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Social Sciences

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Android Based Heart Rate Detection Tools with Arduino Nano Hidayatul Muttaqin; Ita Arfyanti; Wahyuni
TEPIAN Vol. 2 No. 1 (2021): March 2021
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v2i1.337

Abstract

Android-based Heart Rate Detector Using an Android-Based Fingerprint Using Arduino Nano at Midwife Dwi Inggrini's Maternity Clinic with the hope of helping and simplifying the medical team in checking the heart rate of pregnant women without having to carry devices that are not portable, improving services and errors due to blackouts PLN electricity. The software development method used is the prototype method which includes data collection, design, prototyping, the testing phase by conducting Black Box and White Box testing. To access this tool the user must first connect the bluetooth android device with bluetooth HC-05 on the Arduino device, after the two Bluetooth devices are connected.
Course Schedule Optimization Using a Java-Based Ant Colony Optimization Theo Buana Pongsumarre; Wahyuni Wahyuni; Muhammad Fahmi
Media Jurnal Informatika Vol 17 No 2 (2025): Media Jurnal Informatika
Publisher : Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5961

Abstract

Course timetabling in higher education is a complex combinatorial problem due to constraints related to lecturer availability, limited classroom resources, and fixed weekly time-slot structures. As the number of courses and class sections increases, manual scheduling becomes increasingly inefficient and prone to conflicts, particularly room clashes and overlapping lecturer assignments. This study develops and evaluates an automatic course scheduling system based on the Ant Colony Optimization (ACO) algorithm and implements it as a Java-based desktop application to generate feasible timetables under real institutional conditions. An experimental computational approach is employed, in which artificial ants construct candidate schedules through probabilistic selection influenced by pheromone trails and heuristic information. Timetable quality is evaluated using a weighted cost function that prioritizes hard-constraint satisfaction, such as preventing lecturer and room clashes, while also incorporating soft-constraint penalties related to lecturer forbidden timeslots and schedule distribution balance. The system is tested using real academic data from an undergraduate study program, including courses, lecturers, classrooms, and predefined weekly timeslots. Experimental results show that the proposed system consistently generates conflict-free timetables, achieving a conflict value of zero across all repeated runs under the selected parameter configuration. Beyond feasibility, the optimization process continues to refine timetable quality by reducing soft-constraint penalties, as indicated by the convergence behavior observed across repeated executions. This repeated-run evaluation provides insight into the stochastic optimization characteristics of the ACO-based approach under fixed parameter settings. These findings indicate that the Java-based ACO approach effectively supports automated university course scheduling and provides a practical solution for producing feasible and well-structured timetables.
Implementation of a Virtual Tour for SMK Istiqomah Muhammadiyah 4 Samarinda City Using a 360° Camera Muhammad Akmal Amrullah Ali; Wahyuni Wahyuni; Jundro Daud Hasiolan
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2694

Abstract

The rapid development of digital technology has encouraged educational institutions to adapt and innovate in promoting their school profiles. This study discusses the implementation of Virtual Tour technology at SMK Istiqomah Muhammadiyah 4 Kota Samarinda by utilizing a 360° camera as a medium to introduce the school environment interactively. The purpose of this research is to provide an engaging and realistic virtual experience that allows users to explore school facilities without being physically present on site. This study employs the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The implementation process includes capturing 360° panoramic images using a 360° camera, processing and integrating the images through the Kuula platform, and publishing the Virtual Tour on the school’s official website. Testing was conducted using the black-box method and beta testing involving teachers, students, and prospective students to evaluate usability and user experience. The results show that the developed Virtual Tour application functions properly, runs smoothly on various devices, and provides a positive exploration experience for users. Most respondents stated that the application is easy to use, informative, and visually appealing. The implementation of this Virtual Tour is considered effective in increasing the school’s attractiveness, strengthening its modern institutional image, and supporting digital-based promotional strategies in today’s technological era.
Speech Emotion Classification Using MFCC Feature Extraction and Bagging-Based Ensemble Learning Ivan Haristyawan; Eka Arriyanti; Wahyuni Wahyuni
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8878

Abstract

Speech emotion classification, also known as Speech Emotion Recognition (SER), has become increasingly important with the growing prevalence of human–machine interaction, particularly in the domains of healthcare, online education, and customer service. This study aims to develop a robust speech emotion classification system by employing Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction and a Decision Tree–based Bagging algorithm for classification. The proposed approach is designed to address the challenges of low classification accuracy, especially under speaker-independent conditions and limited availability of labeled emotional speech data. The research workflow includes speech signal preprocessing, MFCC feature extraction, dataset partitioning through bootstrapping, ensemble model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. Experimental results on a balanced dataset comprising five emotion classes (anger, disgust, fear, happy, and sad) demonstrate that the proposed model achieves an overall accuracy of 61.04%. While the fear and happy emotions are classified effectively with recall values of 0.75, the anger class exhibits the lowest performance with an F1-score of 0.49. Confusion matrix analysis further reveals substantial acoustic overlap among several emotion categories, particularly the frequent misclassification of sad as disgust or anger. In conclusion, the integration of MFCC features with the Bagging algorithm improves model stability and robustness; however, further optimization of acoustic features and hyperparameters is required to enhance overall classification accuracy.
Co-Authors Adha Trisna Lidya Aexsa Alfyano Alyudani Andayani Andayani Anwar, Rafidan David Hendrawan Eka Arriyanti Ekawati, Hanifah Haristyawan, Ivan Helmelya Putri Jelita Heny Pratiwi Hidayatul Muttaqin Ita Arfyanti Ita Arfyanti Ivan Haristyawan Jajang Nurjaman Jhoanne Fredricka Jundro Daud Hasiolan Kelik Sussolaikah Mario Benediktus Weruin Muhammad Ahsanu Qaulan Muhammad Akmal Amrullah Ali Muhammad Fahmi Muhammad Ibnu Sa'ad Muhammad Ibnu Saad Saad Nila Ratna Sari Pitrasacha Adytia Pitrasacha Adytia Reza Andrea Riani Sela Rizky Zakariyya Rasyad Rizky Zakariyya Rasyad Siti Lailiyah Syamsuddin Mallala Theo Buana Pongsumarre Yudha Satria Yunita Yunita Yunita Yunita