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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal SITECH : Sistem Informasi dan Teknologi Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Sistem Komputer dan Informatika (JSON) Aiti: Jurnal Teknologi Informasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Teknika Journal of Business and Audit Information System (JBASE) IJECS: Indonesian Journal of Empowerment and Community Services Jurnal Pendidikan dan Teknologi Indonesia Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Jurnal Indonesia Sosial Teknologi Jurnal Informatika: Jurnal Pengembangan IT
Dwi Hosanna Bangkalang
Universitas Kristen Satya Wacana
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

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Implementasi dan Pelatihan Aplikasi Kasir Online Berbasis Android Pada UMKM Marikh Salatiga Nina Setiyawati; Dwi Hosanna Bangkalang
IJECS: Indonesian Journal of Empowerment and Community Services Vol. 1 No. 2 (2020): IJECS: Indonesian Journal of Empowerment and Community Services
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijecs.v1i2.967

Abstract

Marikh Salatiga adalah salah satu usaha mikro, kecil, dan menengah (UMKM) di Salatiga yang bergerak di bidang kuliner di mana pencatatan transaksinya masih dilakukan secara manual. Hal ini mengakibatkan beberapa permasalahan seperti data transaksi tidak terkelola dan tidak tersimpan dengan baik. Melihat permasalahan tersebut maka Marikh Salatiga membutuhkan sebuah sistem informasi khususnya transaction processing system di mana salah satu contohnya adalah aplikasi kasir untuk mengakomodasi proses pencatatan transaksi rutin harian yang diperlukan guna menjalankan bisnis. Pada kegiatan pengabdian masyarakat ini dilakukan pembangunan dan implementasi aplikasi kasir online berbasis Android yang diharapkan dapat mengakomodasi pencatatan transaksi di Marikh Salatiga. Adapun aplikasi yang dibangun memberikan dampak positif bagi Marikh Salatiga yaitu membantu efisiensi operasional serta mendukung pengambilan keputusan strategi yang berbasis data. Kata kunci: Aplikasi kasir, transaction processing system, Android, UMKM
Implementation and Training of Congregation Data Management Application at GPID Eben Haezer Palu Dwi Hosanna Bangkalang; Evangs; Nina Setiyawati; Kristoko Dwi Hartomo; Magdalena Ariance Ineke Pakereng
IJECS: Indonesian Journal of Empowerment and Community Services Vol. 6 No. 1 (2025): IJECS: Indonesian Journal of Empowerment and Community Services
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijecs.v6i1.5953

Abstract

Congregation data collection at GPID Eben Haezer is still done manually. This causes a lot of congregation data to be unsynchronized between the written data and the actual data. In addition, it also results in inefficient administrative services to the congregation. The vision of church digitalization also raises its own problems for the church, namely the unpreparedness of the church's human resources (HR) in digital capabilities. This Community Service (PkM) activity is to help and facilitate GPID Eben Haezer in implementing congregation data management applications and mentoring training in the process of adopting technology in church governance. The training activity was attended by 7 church admins and was carried out after the stages of formulating partner needs, adjusting and implementing the application. After the training, the application usability was measured using the System Usability Scale (SUS) and a score of 83 was obtained, indicating that the implemented application was EXCELLENT and ACCEPTABLE.  Keywords: Congregation Data Collection Application; Digital Skills; Training; System Usability Scale
UI/UX Design for Web-Based Syshoe Information System Using Design Thinking Approach Felda Alvian Firifki; Dwi Hosanna Bangkalang
SISTEMASI Vol 15, No 5 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i5.6412

Abstract

This study aims to design the UI/UX of the Syshoe web-based information system to improve service efficiency, expand market reach through digital media, and facilitate online ordering by providing users with more comprehensive information. The UI/UX design of the Syshoe information system was developed using the Design Thinking method to ensure that the system aligns with user needs and delivers a more effective user experience. The design process resulted in both low-fidelity and high-fidelity prototypes tailored to user requirements, which were subsequently evaluated using the System Usability Scale (SUS). The findings indicate that the UI/UX design of the Syshoe information system achieved an acceptable usability category, with a final SUS score of 79.7 from user evaluations and 80.8 from administrator evaluations. These results demonstrate that the system is feasible, comfortable, and effective for both users and administrators. Therefore, this study is expected to serve as a reference for the development of similar systems, particularly for MSMEs seeking to adopt digital transformation initiatives.
Pembangunan Model Speech Emotion Recognition Menggunakan SVM dan KNN pada Emosi Korban Kekerasan Berbasis Gender Setiyawati, Nina; Bangkalang, Dwi Hosanna
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 3: Juni 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026131

Abstract

Data terkini menunjukkan bahwa angka tindak kekerasan berbasis gender (KBG) di Indonesia masih tinggi. Oleh karena itu, optimalisasi layanan dukungan penanganan bagi korban KBG perlu dilakukan, bahkan hal ini menjadi salah satu tindakan prioritas. Salah satu yang dapat dilakukan adalah pemanfaatan machine learning untuk mengklasifikasi dan memonitor kondisi kesehatan mental berdasarkan deteksi dan pengenalan emosi. Pada penelitian ini diusulkan model Speech Emotion Recognition (SER) dengan menggunakan algoritma Support Vector Machine (SVM) dan K-Nearest Neighbor (KNN). Alur pemodelan dimulai dari akuisisi dataset yang kemudian dilanjutkan dengan pre-processing data. Adapun class emosi dalam penelitian ini lebih spesifik pada spektrum emosi masalah kesehatan mental, yaitu: emosi terkejut, getir, tertekan, takut; dengan jumlah dataset sebanyak 1000.  Setelah itu dilakukan feature extraction yang pada penelitian ini menggunakan gabungan dari Short-Time Fourier Transform (STFT), Mel Frequency Cepstral Coefficient (MFCC), Chroma, Mel Spectogram, dan Tonnetz. Dari feature yang dihasilkan, dilanjutkan melakukan pemodelan dan simulasi menggunakan SVM dan KNN. Model yang dihasilkan kemudian dievaluasi dimana hasilnya menunjukkan bahwa model SER dengan akurasi tertinggi dihasilkan oleh SVM, yaitu 0,97. Hasil F1-score baik pada model SVM maupun KNN menunjukkan nilai yang cukup baik yaitu lebih dari 0.84. Hal ini dikarenakan persebaran dataset pada setiap class bersifat imbang. Dari kelima label yang digunakan, label depressed emotion memiliki presisi tertinggi baik pada model SVM maupun KNN.   Abstract Recent data shows that the number of gender-based violence (GBV) in Indonesia is still high. Therefore, optimization of support services for handling GBV victims needs to be done, in fact this is one of the priority actions. One that can be done is the use of machine learning to classify and monitor mental health conditions based on emotion detection and recognition. In this study, a speech emotion recognition (SER) model is proposed using the SVM and KNN algorithms. The modeling flow starts from dataset acquisition which is then continued with data pre-processing. The emotion class in this study is more specific to the spectrum of emotions of mental health problems, namely: emotions of surprise, bitterness, depression, fear; with a dataset of 1000. After that, feature extraction was carried out which in this study used a combination of Short-Time Fourier Transform (STFT), Mel Frequency Cepstral Coefficient (MFCC), Chroma, Mel Spectrogram, and Tonnetz. From the resulting features, modeling and simulation were continued using SVM and KNN. The resulting model was then evaluated where the results showed that the SER model with the highest accuracy was produced by SVM, which was 0.97. The F1-score results for both the SVM and KNN models showed quite good values, namely more than 0.84. This is because the distribution of the dataset in each class is balanced. Of the five labels used, the depressed emotion label has the highest precision in both the SVM and KNN models.
Comparison and Implementation of CNN Facial Emotion Recognition Model with Hyperparameter Analysis on Multiple Datasets Xaviera Valentina Tandianto; Dwi Hosanna Bangkalang; Nina Setiyawati
Teknika Vol. 15 No. 1 (2026): March 2026
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v15i1.1445

Abstract

This study presents a systematic comparison and implementation of a Convolutional Neural Network (CNN) for Facial Emotion Recognition (FER) across multiple public datasets, namely FER-2013, FER+, RAF-DB, and AffectNet. Unlike previous studies that focused on a single dataset or different model architectures, The main contributions of this research consist of three aspects. First, a five-layer integrated CNN architecture is used to enable fair cross-dataset evaluation within a consistent training and testing framework. Second, structured hyperparameter tuning is performed, including variations in learning rate, batch size, filter configuration, and dropout rate, resulting in a stable and reproducible model configuration. Third, an in-depth analysis was conducted to explore the impact of annotation quality and dataset complexity on model performance. The experimental results show that FER+ achieved the highest accuracy and weighted F1 score thanks to better label consistency, followed by RAF-DB, while FER-2013 and AffectNet experienced a decline in performance due to label noise and higher pose and lighting variations. Further confusion matrix analysis shows that happy and neutral expressions are classified more reliably, while negative emotions such as anger, fear, and disgust remain challenging. To validate practical application, the best-performing model was implemented in a webcam-based facial expression recognition prototype using Python and OpenCV, demonstrating reliable frame-level emotion inference under controlled real-time conditions.
Multiplatform Topic Modeling Analysis of Gender-Based Violence in Indonesia Using LDA Annisa Putri Patricia; Nina Setiyawati; Dwi Hosanna Bangkalang
Teknika Vol. 15 No. 2 (2026): July 2026
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v15i2.1478

Abstract

Gender-based violence remains a critical social issue in Indonesia, generating substantial public discourse across digital platforms. This study applies Latent Dirichlet Allocation (LDA)-based topic modeling to identify and compare the dominant themes emerging in online discussions of gender-based violence across three platforms: X (formerly Twitter), YouTube, and the news portal Detik.com. A total of 21,000 data points were collected through keyword-based web scraping covering the period January 2020 to October 2025. The two-phase modeling process yielded coherence scores of 0.38 and 0.53 for X, 0.77 and 0.73 for YouTube, and 0.8 and 0.52 for Detik.com across the first and second phases, respectively, reflecting differences in language register and content structure across platforms. A two-phase modeling approach was employed for each platform to progressively refine topic quality and eliminate irrelevant outputs. The results show that LDA successfully identified platform-specific thematic patterns: X captured emotional and psychological dimensions of gender-based violence, YouTube surfaced legislative and advocacy-oriented discourse centered on the PKS Law, and Detik.com produced case-specific topics grounded in legal proceedings and journalistic reporting. Across all three platforms, domestic violence emerged as the most consistently prominent theme. These findings demonstrate that a multi-platform approach yields a more comprehensive and nuanced picture of public discourse on gender-based violence than any single-source analysis, and that LDA is an effective tool for large-scale thematic extraction from heterogeneous online text data.
LEARNING MANAGEMENT SYSTEM UMKM PADA SUPER APP USAHA KECIL DAN MENENGAH TERPADU BERBASIS MOBILE FIRST VIEW MENGGUNAKAN OAUTH-SSO Nina Setiyawati; Dwi Hosanna Bangkalang; Evangs Mailoa
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7282

Abstract

UMKM yang maju menjadi salah satu cara bagi suatu negara untuk bisa mewujudkan kondisi perekonomian yang merata. Oleh karen itu UMKM perlu diberdayakan sebagai bagian integral ekonomi rakyat yang mempunyai kedudukan, peran, dan potensi strategis untuk mewujudkan struktur perekonomian nasional. Salah satu strategi pemberdayaan UMKM adalah dengan pemanfaatan teknologi untuk membuat wadah yang memfasilitasi kebutuhan pelaku UMKM untuk belajar. Pada penelitian ini dibangun Learning Management System untuk UMKM yang diberi nama UMKMEdu. Dibangun dengan model proses prototyping dimana selama proses pembangunan aplikasi, klien dan calon pengguna dilibatkan serta dibuat prototype sebelum aplikasi dibangun. Untuk antarmuka pengguna, diterapkan mobile first view untuk memberikan pengalaman pengguna yang optimal ketika diakses melalui piranti smartphone dan hirarki visual yang fokus pada prinsip content-first. Selain itu, juga menerapkan OAuth-SSO untuk proses komunikasi data dari sumber daya yang telah dibangun sebe-lumnya yaitu Aplikasi Pendataan UMKM. Aplikasi yang dihasilkan diuji menggunakan blackbox testing dan didapatkan bahwa semua fungsi sudah berjalan sesuai dengan yang diharapkan.
Co-Authors Adam Surya Wijaya Ade Iriani Andeka Rocky Tanaamah Angelini, Siski Annisa Putri Patricia Asmara, Gilang Windu Bailaen, Elsa Anjamilen Budhi Kristianto Danny Manongga Deasy Carolina Dian Novita Kristiyani Elvina Giovanni Amelinda Evangs Evangs Mailoa Felda Alvian Firifki Fictor Imanuel Tanesab Ghozali, Tamjiz Adnan Hanna Prillysca Chernovita Hanusia Manuel Oktrivania Zamili Hendry, - Henny Hartono Herdin Yohnes Madawara Hetharion, Sthania Hindriyanto Dwi Purnomo Irwan Sembiring Jonathan Shinray Fang Kristoko Dwi Hartomo Lydia Liliana Magdalena Ariance Ineke Pakereng Mangundap, Astrella Christenia Clara Meiselia Ekawati Asoney Fina Nico Fernando Nina Setiyawati Pamula, Bonifasis Penidas Fodinggo Tanaem Pratyaksa Ocsa Nugraha Saian Purwoko, Agus Raras, Galuh Hanggana Royani, Ivana Lara Salu, Celvin Netaniel Septembri Rio Bagaskara Soebroto, Dorkas Tri Oktavena Sri Yulianto Prasetyo Sugiarto, Adrian Herma Titiana, Titiana Willson Mangoki Xaviera Valentina Tandianto Yayi Suryo Prabandari Yerymia Alfa Susetyo Yuliana T. B. Tacoh ‪Hanna P. Chernovita