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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business JUITA : Jurnal Informatika International conference on Information Technology and Business (ICITB) Annual Research Seminar JPSriwijaya JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) INTECOMS: Journal of Information Technology and Computer Science KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal ULTIMATICS Jurnal Pendidikan Matematika (JUDIKA EDUCATION) Informatik : Jurnal Ilmu Komputer IJID (International Journal on Informatics for Development) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) SEINASI-KESI Jurnal Riset Informatika CSRID (Computer Science Research and Its Development Journal) Jurnal Informatika Global CCIT (Creative Communication and Innovative Technology) Journal JSAI (Journal Scientific and Applied Informatics) Journal of Information Systems and Informatics Mulia International Journal in Science and Technical Zonasi: Jurnal Sistem Informasi Indonesian Journal of Electrical Engineering and Computer Science TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Generic Jurnal AbdiMas Nusa Mandiri Jurnal Pendidikan dan Teknologi Indonesia ABDI MOESTOPO: Jurnal Pengabdian pada Masyarakat Mejuajua Malcom: Indonesian Journal of Machine Learning and Computer Science Proceeding of International Conference Health, Science And Technology (ICOHETECH) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Abdimas Maduma Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics JUKEMAS : Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi dan Aplikasi
Ermatita -
Universitas Sriwijaya
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Implementasi Algoritma Naïve Bayes Untuk Analisis Klasifikasi Survei Kesehatan Mental (Studi Kasus: Open Sourcing Mental Illness) Alfarezy, Reza; Ermatita, Ermatita; Wadu, Ruth Mariana Bunga
Informatik : Jurnal Ilmu Komputer Vol 19 No 1 (2023): April 2023
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v19i1.4696

Abstract

Kesehatan mental telah menjadi sorotan penting dalam kehidupan masyarakat sekarang, dan tidak luput dari berbagai industri dalam dunia kerja, termasuk industri teknologi. Kesadaran akan kepentingan kesehatan mental pekerja masih sering dianggap rendah, dan hal ini juga tidak luput dalam industri teknologi, oleh karenanya Open Source Mental Illness (OSMI), sebagai lembaga yang bergerak di bidang kesehatan mental, mengadakan survei untuk mengetahui kesadaran mengenai kesehatan mental pada pekerja dalam industri teknologi. Hasil dari survei ini telah dirilis sebagai dataset, di mana dataset ini kemudian dapat dianalisis lebih lanjut menggunakan data mining dengan metode klasifikasi sebagai analisis kesadaran kesehatan mental berdasarkan data pada survei. Algoritma klasifikasi yang digunakan adalah Naïve Bayes, yang mana hasil klasifikasi ini dapat digunakan lebih dalam untuk analisis lanjut mengenai kesadaran pengaruh kesehatan mental pada pekerja industri teknologi, dalam bentuk model prediksi. Dataset yang digunakan awalnya terdiri dari 1259 record data, dimana setelah dilakukan praproses didapatkan 1254 record data. Penelitian ini dilakukan ujicoba dengan pembagian data uji sebesar 30% dan data latih sebesar 70%, dimana didapatkan hasil akurasi sebesar 72%. Analisis data mining ini kemudian dilaksanakan dalam bahasa pemrograman Python, untuk mendapatkan suatu model prediksi sederhana yang kemudian digunakan untuk sistem prediksi sederhana berbasis website.
Analisis Kebutuhan dan Minat dalam Pemanfaatan Teknologi Digital di SMK Depok Menggunakan SEM–PLS Pratama, M Octaviano; Alyani, Neni; Madya, M Miftahul; Ermatita, Ermatita; Kareen, Pamela
TIN: Terapan Informatika Nusantara Vol 6 No 6 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i6.8578

Abstract

Pandemi COVID-19 telah mempercepat penerapan teknologi digital dalam pendidikan termasuk di Sekolah Menengah Kejuruan (SMK), yang menuntut keseimbangan antara pembelajaran teoritis dan praktikal. Namun, setelah pandemi berakhir, muncul pertanyaan mengenai sejauh mana teknologi tersebut tetap relevan dan diterima oleh guru maupun siswa. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi penerimaan dan keberlanjutan penggunaan teknologi digital dalam kegiatan belajar mengajar di SMK Kota Depok pasca pandemi. Penelitian menggunakan pendekatan kuantitatif dengan metode structural equation modeling–partial least squares (SEM–PLS) terhadap 99 responden (63 siswa dan 36 guru). Instrumen berupa kuesioner Likert lima poin mencakup lima konstruk utama: komunikasi, kemudahan, efektivitas, biaya, dan minat keberlanjutan. Hasil pengujian reliabilitas menunjukkan nilai Cronbach’s Alpha > 0,70 pada konstruk komunikasi, kemudahan, dan minat, menandakan konsistensi internal yang baik, sementara konstruk efektivitas (0,595) dan biaya (0,491) berada di bawah ambang batas. Uji validitas konvergen menunjukkan Outer Loading > 0,70 pada 73% indikator guru dan 58% indikator siswa. Analisis struktural memperlihatkan bahwa hipotesis tentang keinginan melanjutkan penggunaan teknologi signifikan (p < 0.05), sedangkan hipotesis kesesuaian teknologi dengan kebutuhan hanya didukung sebagian. Temuan ini menegaskan bahwa model pembelajaran hibrida menjadi pilihan paling relevan untuk mendukung keberlanjutan pembelajaran digital di SMK.
Evaluating Medxa SIMRS Implementation Success Using HOT-Fit and Multiple Regression Muhammad Haykal Alfariz Saputra; Ermatita Ermatita
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1392

Abstract

The implementation of Hospital Management Information Systems (HMIS) is essential for improving service quality, strengthening operational efficiency, and supporting evidence-based decision-making in hospitals. Nevertheless, the success of HMIS implementation is shaped not only by technological performance, but also by human and organizational factors. This study aimed to evaluate the implementation success of Medxa SIMRS at Mohammad Hoesin Hospital, Palembang, using the Human–Organization–Technology Fit (HOT-Fit) model. A quantitative cross-sectional survey was conducted among 67 active users of Medxa SIMRS using a structured Likert-scale questionnaire. Data were analyzed using descriptive statistics and multiple linear regression in Python to examine the influence of the Human, Organization, and Technology dimensions on Net Benefit. The descriptive findings showed that all HOT-Fit dimensions were rated in the good to very good categories, indicating generally positive user perceptions of the system. Regression analysis demonstrated that, simultaneously, the Human, Organization, and Technology dimensions significantly explained variation in Net Benefit (p < 0.05). However, in the partial analysis, only the Technology dimension had a statistically significant positive effect on Net Benefit. These results indicate that system quality, information quality, and service quality are the main determinants of perceived system benefits in this setting. The findings suggest that hospitals should prioritize technological optimization while strengthening organizational support and user readiness to maximize the success of HMIS implementation.
Pelatihan Pemanfaatan Teknologi Informasi dan Digital Marketing untuk Meningkatkan Daya Saing UMKM di Desa Sungai Rebo Ali Ibrahim; Endang Lestari Ruskan; Ermatita Ermatita; Fathoni Fathoni; Rizka Dhini Kurnia; Al farissi; Ahmad fali Oklilas; Yadi Utama; Purwita Sari; Naretha Kawadha Pasemah Gumay
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 3 (2026): April 2026
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i3.339

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi lokal, termasuk di Desa Sungai Rebo, Kecamatan Banyuasin I, yang sebagian besar masyarakatnya menggantungkan penghasilan dari usaha kecil di sektor kuliner, kerajinan, dan perdagangan rumah tangga. Meskipun demikian, rendahnya pemanfaatan teknologi informasi serta keterbatasan kemampuan dalam pemasaran digital menyebabkan daya saing produk UMKM di desa tersebut belum berkembang secara optimal. Kondisi ini membuat jangkauan pemasaran produk masih terbatas pada pasar lokal dan belum mampu memanfaatkan peluang pasar yang lebih luas melalui media digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan daya saing UMKM di Desa Sungai Rebo melalui penerapan teknologi informasi dan digital marketing sebagai strategi promosi produk secara berkelanjutan. Program ini dilaksanakan melalui pendekatan pelatihan dan pendampingan yang melibatkan pelaku UMKM sebagai mitra utama dalam setiap tahapan kegiatan, mulai dari identifikasi kebutuhan, pelatihan, hingga evaluasi hasil. Metode kegiatan meliputi asesmen awal untuk memetakan kemampuan digital pelaku UMKM, pelatihan penggunaan teknologi informasi dasar seperti pengelolaan perangkat digital dan aplikasi pengolahan foto produk, serta pelatihan digital marketing yang mencakup pembuatan konten promosi dan pemanfaatan media sosial. Selain itu, dilakukan pendampingan intensif dalam implementasi strategi digital marketing sesuai dengan karakteristik usaha masing-masing peserta. Hasil kegiatan menunjukkan adanya peningkatan kemampuan pelaku UMKM dalam memanfaatkan teknologi informasi untuk mendukung kegiatan usaha dan memperluas jangkauan pemasaran produk mereka. Hasil pre-test dan post-test menunjukkan adanya peningkatan signifikan pada pemahaman dasar teknologi informasi. Sebelum kegiatan, hanya 28% peserta yang memahami penggunaan perangkat digital untuk kegiatan bisnis; setelah pelatihan, tingkat pemahaman meningkat menjadi 78%.
A Two-Stage Hybrid Oversampling and Ensemble Learning Framework for Improved Type 2 Diabetes Mellitus Classification Permatasari, Siti Fatimah Nurdiah; Ermatita, Ermatita
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 8 No. 2 (2026): May
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v8i2.308

Abstract

Type 2 Diabetes Mellitus (T2DM) screening using clinical tabular data commonly suffers from class imbalance, where non-diabetic records dominate diabetic cases, causing models to bias toward the majority class and yield poor detection of the positive (diabetic) class. This study aims to improve T2DM classification on an imbalanced dataset by increasing minority-class detection while maintaining acceptable overall performance. The main contribution is a leakage-safe framework that integrates two-stage hybrid oversampling (RandomOverSampler followed by Borderline-SMOTE) and soft-voting ensemble learning to obtain more balanced predictions. Experiments were conducted on the Diabetes Bangladesh (DiaBD) dataset, containing 5,288 clinical records with a binary target, diabetic (Yes/No, mapped to 1/0). The data were stratified into train_full/test splits (80/20) and further into train/validation splits (80/20 of train_full). Features were normalized using MinMaxScaler fitted only on the training set and applied to validation and test sets to prevent data leakage. Class imbalance handling was applied only on the training set using the proposed two-stage oversampling (ROS Borderline-SMOTE; borderline-1, k_neighbors=3). Classification models included SVM (RBF), Random Forest, and Gradient Boosting, as well as soft-voting ensembles of two and three models. Results show that the baseline setting (No OS) can achieve high accuracy but low minority detection; for instance, SVM (No OS) reached an accuracy of 0.9374 with a Recall_pos of 0.0909 and an F1_pos of 0.1587. After oversampling, SVM (OS) improved minority recall to 0.7273 with F1_pos 0.4188, although accuracy decreased to 0.8688 due to increased false positives. The best-balanced performance was achieved by the SVM + RandomForest soft-voting ensemble (OS) with accuracy 0.9125, Recall_pos 0.6545, and the highest F1_pos 0.4932. Overall, the proposed two-stage hybrid oversampling combined with soft-voting ensembles improves T2DM detection on imbalanced tabular data, and the findings highlight that model selection should prioritize Recall_pos and F1_pos rather than accuracy alone.
Optimasi Strategi Penjualan Produk Zaskia Melalui Integrasi Algoritma K-Nearest Neighbors (KNN) dan Regresi Linier Ermatita; Belly Nagustria Belly
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.8074

Abstract

This study aims to evaluate the model's performance in classifying and predicting the number of product sales based on several attributes. The K-Nearest Neighbors (KNN) algorithm was used for the classification task and showed good performance with an accuracy of 91.22%, recall of 92.96%, and precision of 90.18%. These results indicate that the model has a high generalization ability in recognizing sales patterns. For quantitative prediction of the number of sales, a linear regression model is used with independent variables such as regular price, selling price, rating, number of ratings, and number of favorites. The regression model yielded a coefficient of determination (R²) of 0.78, indicating that 78% of the variability of the sales amount can be explained by these variables. The coefficient analysis results show that the rating, number of ratings, and number of favorites have a positive influence on the sales amount, while the selling price and normal price have no significant effect. The Root Mean Squared Error (RMSE) value of 33.09 indicates a fairly low level of prediction error. These findings indicate that the model used is effective in helping analyze and forecast product sales.
Assessing an Innovative Virtual Museum Application using Technology Acceptance Model Shinta Puspasari; Ermatita; Zulkardi
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3758

Abstract

This study discusses the assessment of a virtual museum application development based on machine learning models for Palembang culture education through the Sultan Mahmud Badaruddin II museum cultural heritage by using the Technology Acceptance Model approach. The application was tested to measure the user acceptance of the application and pre-test and post-test to measure the effect size of the application as a learning media. A total of N=32 student participants were involved in testing the Sultan Mahmud Badaruddin II innovative virtual museum application for museum visitors was dominated by students who came to the museum to learn the culture and history of Palembang. Hypothesis testing results show that the perceived usefulness and perceived ease of use variables do not affect the attitude toward the use of the innovative virtual museum application. The attitude toward the use of the variable affects the behavioural intention to use, which directly also has a moderate effect on the actual use of the application where the dependent variables have the value of R2 > 0.5. The developed app is recommended as alternative learning media during a pandemic where the app testing participants express interest in using the app to enhance the Palembang culture learning experience.
Sentiment Analysis of E-Commerce Mobile Application Reviews for Digital Product Development Insights Balqis, Rugaiyah; Ermatita, Ermatita; Abdiansah, Abdiansah
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 3 (2026): MALCOM July 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i3.3045

Abstract

This paper presents a systematic sentiment analysis framework for Indonesian-language e-commerce reviews, designed for scalable extraction of insights for digital product development. The system applies a Support Vector Machine (SVM) classifier with a Radial Basis Function (RBF) kernel and TF-IDF bigram feature extraction to the PRDECT-ID dataset comprising 5,400 product reviews from Tokopedia across 29 categories. To ensure reliable classification under realistic class conditions, the proposed pipeline integrates multi-stage text preprocessing (case folding, slang normalization, stopword removal, and Sastrawi-based stemming) and stratified 80:20 train-test splitting without artificial resampling. The experimental evaluation confirmed a test-set accuracy of 92.04%, a weighted F1-score of 0.92, and an AUC-ROC of 0.9741. These results validate the efficacy of the proposed SVM-TF-IDF architecture for reliable, interpretable sentiment classification. Furthermore, category-level negative sentiment profiling identifies Computers and Laptops, Automotive, and Toys and Hobbies as priority intervention domains (negative rate ?60%), while keyword-level TF-IDF analysis reveals critical user concerns regarding delivery services, product specification mismatches, and quality disappointment, providing tangible guidance for product development teams. Future work should explore transformer-based architectures (BERT, IndoBERT) for contextual sentiment capture, investigate cross-marketplace generalizability, and address real-time deployment scalability.
DIGITAL INSTRUMENT FOR INFANT AND TODDLER MORTALITY REVIEW USING USER-CENTERED DESIGN METHOD Royan Dwi Saputra; Rahmat Izwan Heroza; Dwi Rosa Indah; Allsela Meiriza; Pacu Putra; Ermatita Ermatita
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (945.278 KB) | DOI: 10.34288/jri.v4i4.174

Abstract

Abstract The Infant Mortality and Toddler Mortality rates are still relatively high in Indonesia. Data from the South Sumatra Health Office shows a relatively high number of infant and toddler mortality cases in Banyuasin and Musi Banyuasin Regency, with about 68 and 51 cases in 2017. Through the Program Kerja Sama (PKS) of the family health directorate of the health ministry of the Republic of Indonesia and the Public Health Faculty of Sriwijaya University. Find problems related to the absence of instruments in digital form, which are useful for conducting studies on infant and under-five mortality problems in health facilities, which were expected to assist in recording and reporting the review process run more effectively and efficiently. This research uses the User-Centered Design (UCD) method because it optimizes the application prototype according to the needs and desires of the end-user, which in this case is the health worker in the Health Facilities in Banyuasin and Musi Banyuasin Regency. The UCD method phases include understanding the use context, specifying the user requirements, designing the solutions, and evaluating against requirements. The results of the study were that the average usability score was 94, meaning that this application's prototype has been made according to the needs and desires of end-users. Also, the prototype of this application is feasible to implement.
Co-Authors Abdiansah, Abdiansah Adi Sutrisman Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Sanmorino Aidil Putrasyah Al Farissi Albert Albert Aldin, Moehammad Alfarezy, Reza Ali Amran Ali Bardadi Ali Bardardi Ali Ibrahim Ali Ibrahim Allsela Meiriza, Allsela Andini Dwi Lestari Anita Desiani Apriansyah Putra Arnelawati Artika Arista Ayuputri, Niken Balqis, Rugaiyah Bambang Suprihatin Barlian Khasoggi Barlian Khasoggi Belly Nagustria Belly bin Awang, Mohd Khalid Budi Prayoga, Muhamad Hafiz Cindo, Mona Dafid Dedik Budianta Deris Stiawan Dian Palupi Rini Dian Palupi Rini Dien Novita Dominica, Alviona Terry Dwi Asa Verano Dwi Lestari, Rizky Dwi Meylitasari Br. Tarigan Dwi Rosa Indah Endang Lestari Ruskan Endy Suherman Erwin, Erwin Eva Darnila Eva Darnila Fajriana, Fajriana Fajriana, Fajriana Falih, Noor Fathoni - Fathoni - Fauza Adelma Syafrizal Fuadi, Wahyu Geovani, Dite Gumay, Naretha Kawadha Pasemah Hadipurnawan Satria Hafyz Sytar, M. Hartini Hartini Hijriani, Nurul Huda Ubaya Huda Ubaya Husnawati Husnawati Ika Oktavianti ina aisyah handayani Indra Maulana Irmanda, Helena Nurramdhani Ispramono Hadi, Sigit Iwan Pahendra Jaidan Jauhari Johannes Petrus Joko Purnomo Kareen, Pamela Ken Dhita Tania Khairun Nisak, Novrinda Kurniawan, Mochamad Aryo Aji Kurniawan, Rizky Fariz Andry Lovinta Happy Atrinawati M Fariz Januarsyah M. Fariz Januarsyah M. Miftakul Amin Madya, M Miftahul Marissa Utami Matondang, Nurhafifah Mauliza Mauliza, Mauliza Megah Mulya Meizalina, Mutiara Amalia Mgs Afriyan Firdaus Mira Afrina Mohammed Y. Alzahrani Mona Cindo Monterico Adrian Muhammad Adrezo Muhammad Fachrurrozi Muhammad Haykal Alfariz Saputra Muhammad Qurhanul Rizqie Muhammad Sadli Muhammad Sadli, Muhammad Muhammad, Duwen Imantata Mutammimul Ula Mutia Fadhila Putri Naretha Kawadha Pasemah Gumay Neni Alyani Noprisson, Handrie NUNI GOFAR Nurul Chamidah Nurul Mufliha Eka Putri Nurul Mufliha Eka Putri Octaria, Orissa Osvari Arsalan Pacu Putra Parwito Patimah, Endah Permatasari, Siti Fatimah Nurdiah Pratama, M Octaviano Primanita, Anggina Purwita Sari Purwita Sari, Purwita Putra, Erwin Dwika Rachma nia Rahman, Puti Ayu Andhini Rahmat Budiarto Rahmat Izwan Heroza Rahmat Izwan Heroza Rendra Gustriansyah Reza Firsandaya Malik Richardo, M Denny Richki Hardi Rifkie Primartha Rizka Dhini Kurnia Rizka Dhini Kurnia Rizki Kurniati Royan Dwi Saputra Ruth Mariana Bunga Wadu Safithri, Selviana Rizki Salamah, Fitri Samsuryadi Samsuryadi Shinta Puspasari Soraya, Atika Suci Destriatania Suci Destriatania Sukemi Sukemi Susan Dwi Saputri Susan Dwi Saputri Sytar, M. Hafizh Terttiaavini, Terttiaavini Tjahjanto, Tjahjanto Tryadriani, Rasqia Nurzulia Verano, Dwi Asa Verlly Puspita Wahyu Fuadi Wahyu Ningsih Yadi Utama Yadi Utama Yudha Pratomo Yudha Pratomo Yudha Pratomo Yundari, Yundari Zalika, Indah Zulkardi