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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Jurnal Informatika dan Teknik Elektro Terapan Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Faktor Exacta Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JURNAL INSTEK (Informatika Sains dan Teknologi) Jiko (Jurnal Informatika dan komputer) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) KOMPUTIKA - Jurnal Sistem Komputer JURNAL MANAJEMEN BISNIS JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Informatika Global Jambura Journal of Electrical and Electronics Engineering Jurnal Informatika dan Rekayasa Perangkat Lunak Klasikal: Journal of Education, Language Teaching and Science Jurnal Teknik Informatika (JUTIF) Mattawang: Jurnal Pengabdian Masyarakat PENGABDI: Jurnal Hasil Pengabdian Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence International Journal of Electronics and Communications Systems Jurnal Nasional Teknik Elektro dan Teknologi Informasi Online Learning in Educational Research Seminar Nasional Pengabdian Kepada Masyarakat Paradigma Edukasia: Jurnal Pendidikan dan Pembelajaran Teknovokasi : Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat Seminar Nasional Hasil Penelitian LP2M UNM Information Technology Education Journal Jurnal Pengabdian Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Journal of Embedded Systems, Security and Intelligent Systems Ininnawa: Jurnal Pengabdian Masyarakat Journal of Security, Computer, Information, Embedded, Network and Intelligence System Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Progressive Information, Security, Computer and Embedded System Paramacitra : Jurnal Pengabdian Masyarakat Jurnal MediaTIK SISFOTENIKA Artificial Intelligence in Educational Decision Sciences
Dewi Fatmarani Surianto
Universitas Negeri Makassar
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Unraveling the Effects of AI Usage on Burnout among Programmers: An Apriori Algorithm Data Mining Approach Muhammad Fardan; Ana Sulistiana Alwi; Khalil Mubaraq Darwing; Dewi Fatmarani Surianto; Putri Nirmala; Nurrahmah Agusnaya
Information Technology Education Journal Vol. 4, No. 3, August (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i3.9858

Abstract

Burnout is a growing problem across various industries, particularly among programmers who face high workloads and prolonged stress. In this digital era, the use of technologies such as AI can be a solution to reduce workloads and improve employee well-being. This study aims to identify how the use of AI can reduce burnout levels in programmers. The method used is a cross-sectional research design with data collection through a survey using the Google Form platform, and data analysis using descriptive techniques and the Apriori algorithm to find patterns in the relationship between the duration of AI use, workload, and burnout levels. The results show that the use of AI can help reduce burnout levels by lowering workloads, providing a basis for more effective interventions in the workplace.
Comparative Analysis of the Performance of Hadith Text Classification Methods: A Case Study with ANN and SVM Dewi Fatmarani Surianto; Muhammad Fajar B; Musda Rida Mulia; Indanasufya Indanasufya
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 1 (2024): March 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i1.2942

Abstract

Hadith is the second holy book for Muslims after the Quran, containing instructions from the Prophet Muhammad SAW, and narrated by Ulama / Mufti. As one of the main sources of Islamic teachings, hadith is used to explain and illustrate the teachings of the Quran. This study aims to compare the performance of hadith text classification using Artificial Neural Network (ANN) and Support Vector Machine (SVM) with Hadith Bukhari dataset. The stages include preprocessing, feature extraction with TF-IDF, classification, and evaluation. The evaluation results show different performance between ANN and SVM in two scenarios: with and without stemming. The use of stemming has a significant impact on model performance, reducing word variation and can result in a decrease in accuracy. The SVM model consistently showed higher accuracy than ANN in both scenarios, with the highest accuracy reaching 85% for classification without stemming. This study provides insight into the application of ANN and SVM in hadith text classification, emphasizing the importance of selecting a method that suits the characteristics of the data.
A Hybrid Framework for Plagiarism Detection: Integrating Token-Based Similarity with Density-Based Clustering Muhammad Fajar B; Fitriyanty Dwi Lestary; Dewi Fatmarani Surianto
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 1 (2025): March 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i1.7664

Abstract

Plagiarism detection in academic assignments remains a critical challenge in maintaining academic integrity in higher education. This study proposes an automated method to detect content similarity between student assignment documents by combining Jaccard Similarity and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms. The process begins with the collection of student assignment files in digital format, followed by text extraction to form a set-based representation of each document. Jaccard Similarity is then used to compute the degree of similarity between every document pair, and the resulting similarity matrix is transformed into a distance matrix as input for DBSCAN. Experiments conducted on 23 documents yielded 253 unique document pairs. The results demonstrate that the method successfully identified pairs with high similarity scores—such as 0.9114 and 0.7226—which were visually confirmed through a heatmap and effectively grouped into clusters by DBSCAN. Parameter settings of eps = 0.3 and min_samples = 1 proved optimal for distinguishing original documents from those exhibiting substantial content overlap. This approach is not only accurate and efficient, but also eliminates the need for predefined cluster numbers, making it suitable for deployment in automated plagiarism detection systems for academic texts.
Segmentation of Student Lifestyle Patterns for Insomnia Risk Identification Using the K-Means Algorithm Athiyyah Anandira; Azzah Ulima Rahma; Amanda Putri Lestari; Dewi Fatmarani Surianto
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i3.8683

Abstract

Insomnia is a common sleep disorder that occurs in college students due to unbalanced lifestyle patterns. This study aims to categorize students based on their lifestyle patterns and identify the risk of insomnia by applying the K-Means algorithm. Data were obtained from 198 active students of JTIK UNM batch 2021-2024 through a questionnaire. Five main variables were analyzed, such as sleep duration, caffeine consumption, gadget use, number of assignments per week, and hours of sleep. After the researchers transformed and normalized data, the clustering process had resulted in two clusters. The first cluster showed a higher risk of insomnia due to late bedtime and excessive gadget usage, while the second cluster tended to undergo a healthier lifestyle. The Davies-Bouldin Index value of 0.22 indicates superlative clustering qualities. This study provides an overview of student characteristics based on lifestyle and potential risk of insomnia.
Analysis of Naive Bayes and Support Vector Machine Algorithms in Classification of Diabetes Cases Based on Lifestyle Factors Andi Dio Nurul Awalia; Muhammad Fadhil Hani; Dewi Fatmarani Surianto
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 3 (2025): September 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i3.9783

Abstract

The increase in diabetes mellitus cases globally, including in Indonesia, demands a more adaptive lifestyle-based risk prediction strategy. This study aims to evaluate and compare the efficiency of Support Vector Machine (SVM) and Naive Bayes in the diabetes risk classification process using a Hybrid clustering-classification approach . The data analyzed in this study were obtained from the Kaggle platform , with 8,500 data of diabetes patients analyzed based on the attributes of age, gender, and smoking history. The Clustering process was carried out using K-Means (k=3), resulting in three main groups with different lifestyle characteristics. The classification results showed that Naive Bayes provided stable performance with an F1-score of 0.975. Meanwhile, SVM excelled in terms of F1-score 98.3% and perfect AUC (1,000), and was able to classify all data in cluster C3 without error. However, SVM recorded a higher classification error in the majority cluster . This study concluded that SVM was superior by 0.8% over Naive Bayes . Naive Bayes is more suitable for balanced data, while SVM is effective for detecting patterns in minority groups. These findings support the use of a hybrid approach in lifestyle data-based diabetes early detection systems. Future research directions include integrating additional variables and ensemble techniques to improve model generalization.
ANALYSIS OF FUZZY C-MEANS IN PERSONALITY CLUSTERING BASED ON THE OCEAN MODEL Jessicha Pamput; Salsa Dillah; Aindri Muthmainnah; Dewi Fatmarani Surianto
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 3 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8369

Abstract

Personality is the pattern of an individual's behavior in daily life, reflected in their thoughts, feelings, and actions. The Big Five Personality Traits Model, known as OCEAN, helps to understand the complexity of human personality through five main traits. The identification and classification of personality, particularly among students, impacts academic performance, personal development, anxiety levels, and risky behaviors. Collaboration between educators, mental health professionals, and career advisors is crucial to creating an educational environment that supports students' holistic development. The Fuzzy C-Means (FCM) method is used to identify students' personalities with adequate accuracy. This study adopts the OCEAN model with FCM to efficiently identify and classify students' personalities. Data were obtained from 142 respondents, resulting in 27% of respondents being classified in cluster 1, 21% in cluster 2, 18% in cluster 3, 16% in cluster 4, and 18% in cluster 5. This study has important implications for students, educators, and educational institutions to understand that learning patterns, social interactions, and decision-making processes can be influenced by an individual's personality.
Enhancing Computational Thinking Skills through Digital Literacy and Blended Learning: The Mediating Role of Learning Motivation Putri Nirmala; Iwan Suhardi; Andi Baso Kaswar; Dewi Fatmarani Surianto; Muhammad Fajar B; Soeharto Soeharto; Zsolt Lavicza
Online Learning In Educational Research (OLER) Vol. 5 No. 1 (2025): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v5i1.504

Abstract

In the digital era, computational thinking becomes an essential skill to overcome technological challenges in 21st centuryeducation. This study investigates the impact of digital literacy and blended learning on computational thinking skills, focusing on the mediating role of learning motivation. A total of 413 university students from blended learning environments participated, using a structured questionnaire with validated scales for digital literacy, computational thinking, and learning motivation. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test direct and mediation relationships. The results showed that digital literacy and blended learning significantly influenced computational thinking, with learning motivation acting as a mediator that strengthened this relationship. Digital literacy showed a greater influence than blended learning. These findings highlight the importance of integrating digital literacy and motivational strategies into blended learning to optimize the development of computational thinking skills, as well as providing insights for learning design that is relevant to the needs of the 21st century.
Data-Driven Clustering of Stunting Prevention Services for Pregnant Women and Infants Using Fuzzy C-Means Hanum Zalsabilah Idham; Ayu Safitri; Andi Akram Nur Risal; Dewi Fatmarani Surianto; Firdaus
Artificial Intelligence in Educational Decision Sciences Vol 1 No 2 (2026): Artificial Intelligence in Educational Decision Sciences
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aieds.v1i2.22

Abstract

Purpose – This study addresses persistently high stunting rates in South Sulawesi, Indonesia, which remain above national targets despite declining trends. We developed a clustering model to overcome limitations of traditional methods in handling complex health data with overlapping characteristics, aiming to identify priority regions requiring targeted interventions.Methods – Using 2,267 structured records from Satu Data Indonesia covering maternal and child health indicators, we implemented Fuzzy C-Means (FCM) algorithm with systematic preprocessing, optimal cluster determination via Elbow Method, and quality validation using Silhouette Coefficient.Findings – Analysis revealed three distinct clusters for pregnant women (representing good, moderate, and low service coverage areas) and three corresponding clusters for infants. Validation showed Silhouette values ranging from 0.204 to 0.645, indicating variable cluster separation quality with Cluster 0 pregnant women achieving highest cohesion (0.638) and Cluster 2 infants showing strongest separation (0.645).Research limitations – Data quality limitations affected cluster cohesion in some areas, particularly Cluster 1 infants (0.204 Silhouette value), constraining generalizability. The FCM approach accommodates real-world data complexity better than rigid clustering methods but requires high-quality input data.Originality – This research contributes an adaptive framework for evidence-based stunting prevention through sophisticated data-driven segmentation. Findings offer immediate practical value for health policymakers in resource allocation and intervention planning, with potential adaptation to other regional contexts facing similar public health challenges.
Peningkatan Pemahaman Warga Desa Sokkolia Tentang Pengolahan Ubi Jalar Menjadi Produk Kripik Berbagai Rasa Andika Isma; Amiruddin; Dewi Fatmarani Surianto; M Miftach Fakhri; Asri Ismail; Asis Nojeng; Rosidah
Vokatek : Jurnal Pengabdian Masyarakat Volume 1: Issue 1 (Februari 2023)
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/vokatekjpm.v1i1.26

Abstract

Ubi jalar merupakan salah satu produk pangan yang memiliki kandungan gizi yang cukup lengkap dan memberikan banyak manfaat bagi tubuh. Mitra kegiatan pengabdian masyarakat ini adalah Desa Sokkolia, Kecamatan Bontomarannu, Kabupaten Gowa, Sulawesi Selatan. Desa Sokkolia memiliki potensi yang sangat besar untuk dimanfaatkan dan diolah menjadi berbagai produk lain, seperti roti, biskuit, kiripik, dan sebagainya. Kegiatan Pengabdian dilaksanakan pada Bulan Agustus – November 2022 di Desa Sokkolia, Kabupaten Gowa. Metode Pengabdian terdiri dari ceramah, diskusi, praktek, dan evaluasi. Dari hasil evaluasi, diperoleh simpulan bahwa pengetahuan serta keterampilan warga Desa Sokkolia meningkat utamanya dalam pemanfaatan ubi jalar menjadi kripik berbagai rasa.
Pelatihan Tindakan Kelas (PTK) Bagi Guru-Guru SDN 1 Centre Patalassang Di Kabupaten Takalar M. Miftach Fakhri; Muhammad Fajar B; Akmal Hidayat; Dewi Fatmarani Surianto; Andika Isma; Rosidah; Wirawan Setialaksana
Vokatek : Jurnal Pengabdian Masyarakat Volume 1: Issue 1 (Februari 2023)
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/vokatekjpm.v1i1.27

Abstract

Salah satu usaha agar mutu pendidikan di Indonesia dapat ditingkatkan adalah dengan memperbaiki proses belajar di dalam maupun di luar kelas. Proses belajar mengajar ini dapat diperbaiki salah satunya adalah dengan cara mengadakan Penelitian Tindakan Kelas (PTK). PTK merupakan hal yang sangat penting sehingga wajib ada pada semua sekolah-sekolah di Indonesia, salah satunya di SD 1 Centre Patalassang, Kabupaten Takalar. Metode Pelaksanaan Pengabdian yang dilakukan adalah ceramah, diskusi, serta evaluasi. Adapun hasil evaluasi dari pre-test dan post-test yang diperoleh adalah rata-rata skor jawaban peserta pelatihan sebesar 31,75 persen atau kategori rendah, sedangkan rata-rata skor jawaban post-test peserta pelatihan sebesar 87,41 persen kategori sangat tinggi. Ini berarti program ini dianggap berhasil karena skor jawaban post-test peserta pelatihan lebih tinggi dibandingkan dengan skor jawaban pre-test.
Co-Authors A. Arianugerah Ilham A. Arianugerah Ilham AA Sudharmawan, AA Abdal, Nurul Mukhlisah Abdul Muis Mappalotteng Abdul Wahid Abdul Wahid Adiba, Fathiah Adiba, Fhatiah Adnas, Diny Anggriani Agusyana, Nurrahmah Ahmar, Ansari Saleh Ahnaf Riyandirga Ariyansyah Putra Helmy Aindri Muthmainnah Aindri Rizky Muthmainnah Ainun Zahra Adistia Akbar, Mohammad Arsan Akmal Hidayat Akmal Hidayat Akmal, Muhammad syafruddin Amanda Putri Lestari Amiruddin Amri, Muh. Aidil Amukune, Stephen Ana Sulistiana Alwi Andi Akram Nur Risal Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Andi Dio Nurul Awalia Andi Tenri Ola Rivai Andi, Tenriola Andika Isma Anwar Wahid Arifin, Afrisal Arifiyanti, Fitria Asis Nojeng Asri Ismail Athiyyah Anandira Awalia, Andi Dio Nurul Awaliah, Widiarti Ayu Hasnining Ayu Safitri Ayu Safitri Azis, Putri Alysia Azzah Ulima Rahma B., Muhammad Fajar Bahar, Muhammad Mahdinul Bakri, Muh. Fajrin Baso, Fadhlirrahman Cahyana Resky, Andi Aulia Clarisha, Windi Dary Mochamad Rifqie Della Fadhilatunisa Dhaffa Mulya Rahman Dilla, Salsa Dillah, Salsa Dwi Rezky Anadari Sulaiman Edi Suhardi Rahman Edy, Marwan Ramdhany Erva Irianti Fadhlirrahman Baso FADIAH, NUR Fani, A. Astri Merilsa Fathahillah Fhatiah Adiba Fhatiah Adiba Firdaus Firdaus Firdaus Fitriani Dzulfadhilah Fitriyanty Dwi Lestary Fizar Syafaat Furqan Ali Yusuf Haekal Febriansyah Ramadhan Hanum Zalsabilah Idham Hardy M, Galang Hartini Ramli Hidayat M., Wahyu Ilyas, Sitti Nurhidayah Indanasufya Indanasufya Inez Sri Wahyuningsi Manguling Irwandi isma, Nur Ivan Fadillah Akram Iwan Suhardi Jariah S.Intam, Rezki Nurul Jariah, Rezki Nurul Jasruddin Jessicha Pamput Jessicha Putrianingsih Pamput Jumadi Mabe Parenreng Jumadil Ahmad Safi’i Jusniar . Khaerunnisa Nur Fatimah Syahnur Khalil Mubaraq Darwing Kurnia Prima Putra Lapendy, Jessica Crisfin Lutfiah Tri Syahyaningsih M. Miftach Fakhri M. Syahid Nur Wahid Makmur, Haerunnisya Mappangara, Surianto MARDIAH, AINA Marwan Ramdhany Edy Meisaraswaty Arsyad Muh. Juharman Muhammad agung Muhammad Akil Musi Muhammad Fadhil Hani Muhammad Fadhullah Muhammad Fahrul Rosi Ishaq Muhammad Fajar B Muhammad Fardan MUHAMMAD ILHAM Muhammad Nur Yusri Muhammad Rafli Aditya H. Muhammad Rakib Muhammad Try Dharsana Muharni Muharni Muhtadi, Nashiruddin Sahal Muliadi Musda Rida Mulia Muthmainnah, Aindri Muthmainnah, Aindri Rizky Mutmainnah R Nafil Rizqullah Rajab Nafil Rizqullah Rajab Nashiruddin Sahal Muhtadi Nasrullah, Asmaul Husnah Natsir, Nasrah Ninik Rahayu Ashadi NIRMALA, PUTRI Nur Fadiah NUR FADILAH NUR FADILLAH Nur Risal, Andi Akram Nurhidayat Nurhidayat Nurjannah Nurjannah Nurjayanti Nurjayanti Nurrahmah Agusnaya Nurul Fadhilah Nurul Fadhillah S Nurul Fadhillah S Nurul Mukhlisah Abdal Pamput, Jessicha Pamput, Jessicha Putrianingsih Parenreng, Jumadi M. Putri Nanda Sari Putri Nirmala Putri Zhachilia Susanto Raden Mohamad Herdian Bhakti Rahman, Dhaffa Mulya Rahmaniar Rahmat Kurniawan Ramadhan, Haekal Febriansyah Resky, Andi Aulia Cahyana Rezki Angriani Pratiwi Kadir Rezki Nurul Jariah Rezky Anisar, Muh. Alief Ridwan Daud Mahande Ridwan Daud Mahande Risaldi, Muhammad Rosidah Rosidah Rusli, Risvan S, Aprilianti Nirmala S, Muh. Rizal S, Nurul Fadhillah S.Intam, Rezki Nurul Jariah Salsa Dillah Sari Wulandari Sasmita Sasmita Setialaksana, Wirawan - Shabrina Syntha Dewi Shasa Inayah Vega Shasa Inayah Vega Siti Syarifah Wafiqah Wardah Soeharto Soeharto Sri Riski Wulandari Sudarmanto Jayanegara Surianto, Dewi Fatmawati Syahrul Syahrul Syahrul Syahyaningsih, Lutfiah Tri Syam, Abd. Azis Syamsurijal Syamsurijal, Syamsurijal Tenriola, Andi Udin Sidik Sidin Wahid, M Syahid Nur Wahid, M. Syahid Nur Wahid, Yokogeri Abdullah Wahyu Hidayat M Wahyu Hidayat M Wahyudi Warda Wahyuni Wardani, Ayu Tri WULANDARI Wulandari Wulandari Zsolt Lavicza Zulfikar, Muh Ihsan Zulhajji, Zulhajji