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All Journal 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 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 Jurnal Nasional Teknik Elektro dan Teknologi Informasi Online Learning in Educational Research Paradigma Teknovokasi : Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat Seminar Nasional Hasil Penelitian LP2M UNM Jurnal Pengabdian Masyarakat 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 Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Journal of Progressive Information, Security, Computer and Embedded System Paramacitra : Jurnal Pengabdian Masyarakat Jurnal MediaTIK SISFOTENIKA
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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Enhancing Computational Thinking Skills through Digital Literacy and Blended Learning: The Mediating Role of Learning Motivation Nirmala, Putri; Suhardi, Iwan; Kaswar, Andi Baso; Surianto, Dewi Fatmarani; B, Muhammad Fajar; Soeharto, Soeharto; Lavicza, Zsolt
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.
Sentiment Analysis of Local Sunscreen Skintific, Somethinc, and Avoskin with Naive Bayes and SVM Clarisha, Windi; Fani, A. Astri Merilsa; Surianto, Dewi Fatmarani; Fadilah, Nur
Jambura Journal of Electrical and Electronics Engineering Vol 7, No 2 (2025): Juli - Desember 2025
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v7i2.30257

Abstract

Indonesia’s beauty industry, particularly local sunscreen products, has experienced rapid growth alongside increasing public awareness of the importance of skin protection against ultraviolet rays. Consumer reviews on digital platforms have become a vital source of information to understand user perceptions and preferences. This study aims to analyze sentiment toward three local sunscreen brands—Skintific, Somethinc, and Avoskin—by comparing two text classification methods: Naïve Bayes and Support Vector Machine (SVM). To address the imbalance in the number of positive and negative sentiment data, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. The results show that applying SMOTE to Naïve Bayes significantly improved the accuracy from 81% to 93%, along with notable enhancements in precision, recall, and F1-score. Conversely, applying SMOTE to SVM slightly reduced accuracy from 92% to 91%, although the performance for positive sentiment remained stable. These findings indicate that the combination of Naïve Bayes and SMOTE is more effective in handling imbalanced data for sentiment analysis of beauty products. The implications of this study can serve as a basis for decision-making in product development and marketing strategies within the beauty industry, particularly in aligning with consumer sentiment.Industri kecantikan Indonesia, khususnya produk sunscreen lokal, menunjukkan pertumbuhan pesat seiring meningkatnya kesadaran masyarakat akan pentingnya perlindungan kulit dari sinar ultraviolet. Ulasan konsumen di platform digital menjadi sumber informasi penting untuk memahami persepsi dan preferensi pengguna. Penelitian ini bertujuan untuk menganalisis sentimen terhadap tiga merek sunscreen lokal—Skintific, Somethinc, dan Avoskin—dengan membandingkan dua metode klasifikasi teks, yaitu Naïve Bayes dan Support Vector Machine (SVM). Untuk mengatasi ketidakseimbangan jumlah data antara sentimen positif dan negatif, digunakan teknik Synthetic Minority Over-sampling Technique (SMOTE). Hasil menunjukkan bahwa penerapan SMOTE pada Naïve Bayes meningkatkan akurasi dari 81% menjadi 93%, serta memperbaiki precision, recall, dan F1-score secara signifikan. Sebaliknya, penerapan SMOTE pada SVM justru sedikit menurunkan akurasi dari 92% menjadi 91%, meskipun performa untuk kategori sentimen positif tetap stabil. Temuan ini menunjukkan bahwa kombinasi Naïve Bayes dengan SMOTE lebih efektif dalam menangani data tidak seimbang untuk analisis sentimen produk kecantikan. Implikasi dari penelitian ini dapat digunakan oleh pelaku industri kecantikan sebagai dasar pengambilan keputusan dalam pengembangan dan pemasaran produk berbasis persepsi konsumen.    
Analisis Metode Fuzzy C-Means (FCM) dalam Menentukan Performansi Kinerja Karyawan Lapendy, Jessica Crisfin; Resky, Andi Aulia Cahyana; Surianto, Dewi Fatmarani
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 11, No 1 (2025): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v11n1.29-41

Abstract

Tercapainya sasaran perusahaan di setiap tahunnya dipengaruhi oleh kualitas sumber daya manusia atau karyawan yang dimiliki oleh perusahaan terkait. Kualitas ini berkaitan dengan kompetensi yang dimilikinya, baik itu dalam aspek skill maupun knowledge. Untuk melihat kualitas dari karyawan yang ada di perusahaan terkait, perlu dilakukan penilaian performansi kinerja karyawan. Oleh karena itu, penelitian ini bertujuan untuk menilai performansi kinerja karyawan yang ada di salah satu perusahaan swasta Makassar yang sebelumnya melakukan penilaian dengan melihat dari segi keuangan dan program kerja yang berhasil dipenuhi oleh setiap divisi. Perlunya penilaian kinerja adalah agar dapat membantu Human Resource Development (HRD) ataupun manajer dalam mengambil keputusan yang berkaitan dengan prestasi yang telah dicapai oleh setiap karyawan. Dalam penilaian kinerja karyawan ini digunakan metode Fuzzy C-Means yang merupakan teknik pengklasteran data yang ditentukan oleh derajat keanggotaan. Setelah tahapan-tahapan metode penelitian dilakukan dengan menggunakan Matlab, dihasilkan 3 klaster yang mengelompokkan kualitas karyawan menjadi karyawan dengan performansi kinerja baik sebanyak 11 karyawan, kinerja sedang sebanyak 11 karyawan, dan kinerja buruk sebanyak 6 karyawan. Hasil pengklasteran tersebut didasarkan pada hasil pengolahan data dari 5 kriteria penilaian, yaitu kejujuran, kedisiplinan, kepemimpinan, kehadiran, dan kualitas kerja. Di antara kelima kriteria tersebut, terdapat 2 kriteria yang cukup mempengaruhi hasil penilaian performansi kinerja karyawan di perusahaan terkait, yaitu kepemimpinan dan kualitas kerja. Adapun hasil evaluasi jumlah klaster dilakukan menggunakan metode silhouette coefficient dengan nilai tertinggi didapatkan yakni 0,5653 pada jumlah klaster adalah 3. The achievement of company goals each year is influenced by the quality of human resources or employees owned by the company. This quality is related to the competence they have, both in terms of skills and knowledge. To see the quality of employees in related companies, it is necessary to assess employee performance. Therefore, this study aims to assess the performance of existing employees in one of Makassar's private companies that previously conducted an assessment by looking at the financial aspects and work programs that were successfully fulfilled by each division. The need for performance appraisal is to be able to help Human Resource Development (HRD) or managers in making decisions related to the achievements that have been achieved by each employee. In this employee performance assessment, the Fuzzy C-Means method is used, which is a data clustering technique determined by the degree of membership. After the stages of the research method were carried out using Matlab, 3 clusters were produced which grouped the quality of employees into employees with good performance as many as 11 employees, moderate performance as many as 11 employees, and poor performance as many as 6 employees. The clustering results are based on the results of data processing from 5 assessment criteria, namely honesty, discipline, leadership, attendance, and work quality. Among the five criteria, there are 2 criteria that are quite influential in the results of employee performance assessment in related companies, namely leadership and work quality. The results of evaluating the number of clusters are carried out using the silhouette coefficient method with the highest value obtained, namely 0.5653 at the number of clusters is 3.
Pemberdayaan Masyarakat Sekolah melalui Penguatan Literasi Digital Berbasis AI dan AR dalam Eksplorasi Sains di SMAN 4 Barru : Penelitian Surianto, Dewi Fatmarani; Zulfikar, Muh Ihsan; Hasnining, Ayu; Agusyana, Nurrahmah; Nirmala, Putri; Awalia, Andi Dio Nurul
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.2795

Abstract

The development of digital technology requires teachers to have adequate digital literacy in order to be able to design innovative, relevant, and adaptive learning that meets the needs of students. This activity aims to improve the competence of teachers at SMAN 4 Barru in utilizing AI Chatbot (LioraTa'), ChatGPT, and Augmented Reality (AR) for biology learning. The implementation method was carried out through Participatory Action Research (PAR) involving 26 teachers and students from SMAN 4 Barru. Evaluation was conducted through pre-tests and post-tests as well as direct observation of practice. The first result showed an increase in the average score from 8.896 (74%) on the pre-test to 10.733 (89%) on the post-test, indicating a significant improvement in teachers' understanding of digital literacy. The second result was that teachers acquired practical skills in designing chatbot conversation flows, compiling ChatGPT-based teaching materials, and utilizing AR for biology experiments, making learning more interactive and contextual. The third result was that teachers reported an increase in confidence in using digital technology and awareness of the importance of AI and AR-based learning innovations to support the quality of education. In conclusion, this training successfully had a positive impact on teachers' mastery of concepts, practical skills, and readiness to integrate digital technology into biology learning, while also strengthening their position.
Perbandingan Cosine Similarity dan Weighted Jaccard Similarity dalam Pengembangan Mesin Pencari Perpustakaan Digital Pamput, Jessicha Putrianingsih; Muthmainnah, Aindri Rizky; Surianto, Dewi Fatmarani; Fadilah, Nur
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8773

Abstract

This study addressed the problem of low relevance in search results within the digital library system of the Department of Informatics and Computer Engineering (JTIK), Universitas Negeri Makassar. The purpose of this research was to improve the accuracy and relevance of search outcomes, enabling users, particularly students, to access academic materials and research references more efficiently. A search engine system was developed using a term-weighting method based on term frequency and document distribution. The system incorporated similarity measurement techniques to evaluate the degree of match between user queries and document content. An experimental approach was applied, which involved observation, data collection, text preprocessing, implementation of term weighting, and the comparison of cosine similarity and Weighted Jaccard similarity for ranking search results. The The evaluation was conducted using the Precision@K metric and a paired t-test to measure the significance of performance differences between methods. The test results showed that Weighted Jaccard obtained an average Precision@K value of 0.933, slightly higher than Cosine Similarity with an average of 0.9. However, Cosine Similarity produced a higher average similarity value. In addition, system testing was conducted in two stages, namely assessing user satisfaction with search results and assessing system performance. These findings confirmed that the combination of term-weighting and cosine similarity effectively enhanced the relevance and performance of digital library search systems.
K-Means++ and TF-IDF for Grouping Library Books by Topic Pamput, Jessicha Putrianingsih; Muthmainnah, Aindri Rizky; Risal, Andi Akram Nur; Surianto, Dewi Fatmarani
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8272

Abstract

The grouping of library materials in the Department of Informatics and Computer Engineering (JTIK) at Universitas Negeri Makassar (UNM) is still conducted using a conventional system that relies on predefined categories and librarian intuition. This approach often leads to inconsistencies in book categorization, making it difficult for users to find relevant references efficiently. To address this issue, this research applies the K-Means++ clustering method, which optimizes centroid initialization for more accurate cluster formation. Books are grouped based on the TF-IDF weighting matrix, resulting in six distinct clusters characterized by unique centroid values. Analysis of the top 10 words per cluster highlights dominant topics within each group. The clustering quality was evaluated using the Silhouette Coefficient, with the highest value of 0.04299, indicating a well-separated cluster structure. These findings demonstrate that K-Means++ effectively organizes books based on word similarity, enhancing library material management and improving information retrieval in the JTIK library.
Co-Authors A. Arianugerah Ilham A. Arianugerah Ilham AA Sudharmawan, AA Abdal, Nurul Mukhlisah Abdul Muis Mappalotteng Abdul Wahid Adiba, Fathiah Adiba, Fhatiah Agusyana, Nurrahmah Ahmar, Ansari Saleh Ainun Zahra Adistia Akbar, Mohammad Arsan Akmal Hidayat Akmal Hidayat Amiruddin Amri, Muh. Aidil Amukune, Stephen Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Andi, Tenriola Andika Isma Anwar Wahid Arifiyanti, Fitria Arsyad, Meisaraswaty Asis Nojeng Asri Ismail Awalia, Andi Dio Nurul Awaliah, Widiarti Azis, Putri Alysia B., Muhammad Fajar Bakri, Muh. Fajrin Baso, Fadhlirrahman Budiarti, Nur Azizah Eka Cahyana Resky, Andi Aulia Clarisha, Windi Dary Mochamad Rifqie Della Fadhilatunisa Dhaffa Mulya Rahman Dhia Rhania Dillah, Salsa Diny Anggriani Adnas Dwi Rezky Anadari Sulaiman Edy, Marwan Ramdhany Erva Irianti Fadhlirrahman Baso FADIAH, NUR Fajar B, Muhammad Fani, A. Astri Merilsa Fathahillah Fathahillah Fathahillah Fhatiah Adiba Fhatiah Adiba Fitriani Dzulfadhilah Fitriyanty Dwi Lestary Fizar Syafaat Furqan Ali Yusuf Haerunnisya Makmur Hardy M, Galang Hartini Ramli Hasnining, Ayu Helmy, Ahnaf Riyandirga Ariyansyah Putra Hidayat M., Wahyu Ilyas, Sitti Nurhidayah Indanasufya, Indanasufya Inez Sri Wahyuningsi Manguling Irwandi Ishaq, Muhammad Fahrul Rosi Ivan Fadillah Akram Iwan Suhardi Jariah S.Intam, Rezki Nurul Jariah, Rezki Nurul Jasruddin Jumadi Mabe Parenreng Jumadil Ahmad Safi’i Jusniar Khaerunnisa Nur Fatimah Syahnur KHAERUNNISA NUR FATIMAH SYAHNUR Kurnia Prima Putra Lapendy, Jessica Crisfin Lavicza, Zsolt Lestary, Fitriyanty Dwi Lutfiah Tri Syahyaningsih M. Miftach Fakhri Makmur, Haerunnisya MARDIAH, AINA Marhawati, Marhawati Muh. Juharman Muhammad Agung Muhammad Akil Musi Muhammad Ansarullah S. Tabbu Muhammad Fajar B Muhammad Fajar B MUHAMMAD ILHAM Muhammad Nur Yusri Muhammad Rafli Aditya H. Muhammad Rakib Muhammad Syafruddin Akmal Muhammad Try Dharsana Muharni Muharni Mulia, Musda Rida Muthmainnah, Aindri Muthmainnah, Aindri Rizky Nafil Rizqullah Rajab Nafil Rizqullah Rajab Nashiruddin Sahal Muhtadi Nasrullah, Asmaul Husnah Natsir, Nasrah Ninik Rahayu Ashadi NIRMALA, PUTRI Nur Fadiah NUR FADILAH Nur Rahmi Nur Risal, Andi Akram Nurjannah Nurul Fadhilah Nurul Fadhillah S Nurul Fadhillah S Nurul Mukhlisah Abdal Pamput, Jessicha Pamput, Jessicha Putrianingsih Parenreng, Jumadi M. Putri Zhachilia Susanto R, Mutmainnah Rauf, Annajmi Resky, Andi Aulia Cahyana Rezki Angriani Pratiwi Kadir Rezki Nurul Jariah Rezki Nurul Jariah S.Intam Ridwan Daud Mahande Rivai, Andi Tenri Ola Rosidah Rusli, Risvan S, Muh. Rizal S, Nurul Fadhillah Sari Wulandari Sari, Putri Nanda Sasmita Sasmita Satria Gunawan Zain Setialaksana, Wirawan - Shabrina Syntha Dewi Shasa Inayah Vega Shasa Inayah Vega Siti Syarifah Wafiqah Wardah Siti Syarifah Wafiqah Wardah Soeharto Soeharto Sudarmanto Jayanegara Surianto, Dewi Fatmawati Syahrul Syam, Abd. Azis Syamsurijal Syamsurijal, Syamsurijal Tenriola, Andi Udin Sidik Sidin Wahid, M Syahid Nur Wahid, Yokogeri Abdullah Wahyu Hidayat M Wahyu Hidayat M WAHYUDI Warda Wahyuni Wardah, Siti Syarifah Wafiqah Wardani, Ayu Tri WULANDARI Wulandari Wulandari Wulandari Wulandari Wulandari Zulfikar, Muh Ihsan Zulhajji, Zulhajji