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All Journal EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Communicatus: Jurnal Ilmu Komunikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Andragogi: Jurnal Diklat Teknis Pendidikan dan Keagamaan EDUKATIF : JURNAL ILMU PENDIDIKAN Indonesian Journal of Electrical Engineering and Computer Science G-Tech : Jurnal Teknologi Terapan Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Jurnal Pendidikan Annals of Mathematical Modeling Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Wawasan: Jurnal Kediklatan Balai Diklat Keagamaan Jakarta Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Kewarganegaraan Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Kepada Masyarakat Patikala As-Sidanah : Jurnal Pengabdian Masyarakat Indonesian Community Journal AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis Jurnal Natural
Selly Anastassia Amellia Kharis
Mathematics Department, Faculty Of Science And Technology, Universitas Terbuka, Indonesia
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CHATGPT SEBAGAI ALAT PENDUKUNG PEMBELAJARAN: TANTANGAN DAN PELUANG PEMBELAJARAN ABAD 21 Kharis, Selly Anastassia Amellia; Zili, Arman Haqqi Anna
Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Vol 15, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/paedagoria.v15i2.22039

Abstract

Abstrak: Chat Generative Pre-trained Transformer (ChatGPT) adalah model bahasa generatif yang dikembangkan oleh perusahaan riset kecerdasan buatan OpenAI pada tahun 2015. Penggunaan ChatGPT dalam dunia pendidikan telah menimbulkan tantangan dan peluang khususnya pada pembelajaran abad 21 yang perlu dipertimbangkan secara seksama. Penggunaan ChatGPT seharusnya dipandang sebagai alat pendukung pembelajaran. ChatGPT tidak dapat menggantikan peran guru. Penelitian ini bertujuan untuk untuk mengidentifikasi tantangan dan peluang penggunaan ChatGPT sebagai alat pendukung pembelajaran. Penelitian ini menggunakan studi literatur dengan pendekatan kualitatif. Berdasarkan hasil penelitian, penggunaan ChatGPT dalam pendidikan dapat memberikan peluang untuk pengalaman pembelajaran yang interaktif, fleksibel, dan memperkenalkan siswa pada teknologi khususnya kecerdasan buatan. Hal ini sejalan dengan kompetensi pembelajaran abad 21. Namun penggunaan ChatGPT juga menimbulkan sejumlah tantangan seperti masalah integritas akademis, interaksi sosial, dan ketergantungan pada teknologi yang dapat mengurangi keterampilan berpikir kritis siswa. Untuk memanfaatkan ChatGPT secara efektif dalam pembelajaran diperlukan pendekatan holistik dan terpadu. Pengembangan kebijakan yang jelas mengenai batasan penggunaan ChatGPT dalam pembelajaran, penyesuaian model pembelajaran, dan peningkatan literasi digital siswa dapat diterapkan untuk menghadapi tantangan penggunaan ChatGPT. Dengan pemahaman yang mendalam tentang tantangan dan peluang penggunaan ChatGPT, pemangku kebijakan pendidikan, guru dan siswa dapat mempersiapkan diri dengan lebih baik untuk mengintegrasikan ChatGPT secara efektif dalam lingkungan pembelajaran.Abstract:  The Chat Generative Pre-Trained Transformer (ChatGPT) is a generative language model developed by OpenAI in 2015. Its use in education presents challenges and opportunities, particularly in 21st-century learning, which require careful consideration. ChatGPT should be seen as a supportive learning tool and not a replacement for teachers. The research aims to identify the opportunities and challenges of ChatGPT as a learning aid, using a qualitative literature study approach. Based on research results, Its use in education offers opportunities for interactive, flexible learning experiences and introduces students to technology, especially artificial intelligence, aligning with 21st-century learning competencies. However, it also presents challenges such as academic integrity issues, social interaction concerns, and technology dependence potentially reducing students’ critical thinking skill. Effectively utilizing ChatGPT in 21st-century learning requires a holistic and integrated approach. Clear policy development regarding ChatGPT usage limits, adjustments to learning models, and enhancing students’ digital literacy can address these challenges. With a deep understanding of ChatGPT’s challenges and opportunities, education policymakers, teachers, and students can better prepare to integrate it effectively into the learning environment.
PENGGUNAAN GOOGLE TRENDS DALAM PERENCANAAN STRATEGI DIGITAL MARKETING PERGURUAN TINGGI JARAK JAUH DI INDONESIA Kharis, Selly Anastassia Amellia; Arisanty, Melisa; Putri, Agustiani; Zili, Arman Haqqi Anna
Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Vol 15, No 3 (2024): Juli
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/paedagoria.v15i3.22038

Abstract

Abstrak: Perkembangan teknologi informasi dan internet telah memberikan dampak yang signifikan pada dunia pendidikan, khususnya dalam pendidikan jarak jauh. Seiring dengan meningkatnya persaingan di antara perguruan tinggi jarak jauh di Indonesia, penting bagi mereka untuk mengadopsi strategi pemasaran digital yang efektif guna mencapai audiens target yang lebih luas dan meningkatkan daya saing mereka. Salah satu alat yang dapat digunakan dalam perencanaan strategi pemasaran digital adalah Google Trends. Penelitian ini bertujuan untuk mengeksplorasi penggunaan Google Trends dalam perencanaan strategi digital marketing perguruan tinggi jarak jauh di Indonesia. Metode penelitian yang digunakan adalah mixed method yang mengintegrasikan metode kuantitatif dan kualitatif. Data yang digunakan berasal dari data pada Google Trends. Hasil penelitian ini menunjukkan bahwa penggunaan Google Trends dapat memberikan wawasan yang berharga dalam memahami minat calon mahasiswa terkait dengan pendidikan jarak jauh di Indonesia. Melalui analisis data tren pencarian, perguruan tinggi jarak jauh dapat menyusun perencanaan strategi pemasaran mencakup beberapa hal, antara lain mengidentifikasi waktu melakukan promosi, menggunakan “Related Queries” untuk mencari kata kunci baru, mencari topik yang sedang trending, memetakan lokasi atau region yang perlu ditarget, dan analisa perbandingan kata kunci untuk mendapatkan keyword terbaik.Abstract:  The development of information technology and the internet has had a significant impact on the field of education, especially in distance learning. With the increasing competition among distance learning universities in Indonesia, it is crucial for them to adopt effective digital marketing strategies to reach a broader target audience and enhance their competitiveness. One tool that can be used in digital marketing strategy planning is Google Trends. This research aims to explore the use of Google Trends in the digital marketing strategy planning of distance learning universities in Indonesia. The research method used is a mixed method that integrates quantitative and qualitative methods. The data used comes from Google Trends data. The results of this research indicate that the use of Google Trends can provide valuable insights into understanding the interest of prospective students related to distance education in Indonesia. Through the analysis of search trend data, distance learning universities can develop marketing strategy plans that include several aspects, such as identifying the optimal timing for promotions, using “Related Queries” to discover new keywords, identifying trending topics, mapping locations or regions that need to be targeted, and conducting keyword comparison analysis to find the best keywords.
Pemberdayaan Gender, Pembangunan Gender, Belanja Pemerintah dan Pertumbuhan Ekonomi: Pendekatan Data Panel Robiansyah, Anton; Hartono, Darwin; Tampubolon, Endy Grade; Zubir, Edwar; Sukatmi, Sri; Kharis, Selly Anastassia Amellia
AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis Vol. 4 No. 2 (2024): AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis
Publisher : Perhimpunan Sarjana Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37481/jmeb.v4i2.748

Abstract

This research aims to determine the influence of gender empowerment and development as well as government expenditure on economic growth in districts/cities of East Java province in 2014-2020. The research method used is panel data regression analysis by selecting the best model between Common Effect, Fixed Effect and Random Effect with Chow test calculations. From the test results it was found that the best model was Fixed Effect. The results of data processing show that 97.70 percent of the GRDP variance is influenced by the gender empowerment index (IDG), gender development index (IPG) and government expenditure (G).
Identifying Digital Literacy Profiles in Distance Education: A K-Prototypes Clustering Approach Zili, Arman Haqqi Anna; Martinasari, Made Diyah Putri; Kharis, Selly Anastassia Amellia
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.34568

Abstract

Education quality is one of the main focuses of Indonesia’s Sustainable Development Goals (SDGs), particularly in the goal that emphasizes equitable access and lifelong learning. Universitas Terbuka (UT) is a higher education institution that implements an open and distance learning system. This setting creates a diverse student body in terms of age, occupation, and digital literacy levels. Segmenting students based on their digital literacy is both essential and challenging, as it involves combining demographic data with daily digital behavior. This study aims to identify the digital literacy profiles of UT students using cluster analysis with the K-Prototypes algorithm. Data were obtained from a survey of 10,396 students with 42 variables. The Elbow Method analysis revealed three distinct clusters, each reflecting unique engagement profiles. The first cluster, the Engaged Evening Digital User, is active during the evening and balances work with social activities. The second cluster, the Hyper Connected Communicator, relies heavily on messaging applications for social interaction. The third cluster, the Balanced Digital Citizen, shows a more even distribution of digital use across academic, entertainment, and communication activities. These clusters predominantly comprise Generation Z individuals, many of whom are actively engaged in the private sector. The profound implications of these findings lie in their capacity to forge highly targeted strategies for digital learning, communication, and student support, thereby enhancing educational outcomes. Furthermore, this research significantly advances methodological literature by demonstrating a powerful, integrated approach to clustering mixed-type attributes, offering a more nuanced understanding of learner profiles in distance education.
Implementation of ABC and ROP Methods for Inventory Control of Mandatory Pharmacy Drugs Nur Izani Maulani; Selly Anastassia Amellia Kharis
G-Tech: Jurnal Teknologi Terapan Vol 9 No 2 (2025): G-Tech, Vol. 9 No. 2 April 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v9i2.6613

Abstract

Grawira Farma Pharmacy in Kulon Progo manages Mandatory Pharmacy Drugs, which require strict regulation for self-medication. Managing the inventory of Mandatory Pharmacy Drugs is necessary to prevent shortages and stockouts. This study aims to analyze the planning and control of Mandatory Pharmacy Drugs inventory at Grawira Farma Pharmacy, using the Always Better Control (ABC) method for inventory planning, categorizing drugs into three groups. Group A consists of fast-moving drugs with 11 types (27.5%), accounting for 79.38% of total drug usage and an investment value of Rp 1,697,300.00, group B consists of moderately-selling drugs with 11 types (27.5%),  contributing 18.29% of total drug usage and an investment value of Rp 1,319,450.00, and group C consist of the slowest-selling drugs with 18 types (45%), representing 2.33% of total drug usage and an investment value of Rp 392,425.00. In addition to inventory planning, this study examines inventory control using the Reorder Point (ROP) method to determine when the reorder after grouping Mandatory Pharmacy Drugs. The research results obtained the reorder point of Mandatory Pharmacy Drugs, which include group A, ranging from 150-500 items, group B varies from 14-340 items, group C, ranging from 0-34 items.
A SIAR Model Approach to the Impact of Mudik Tradition on Covid-19 Transmission in Indonesia Darsih Idayani; Asmara Iriani Tarigan; Selly Anastassia Amellia Kharis; Heny Kurniawati
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7308

Abstract

In Indonesia, on March 2, 2020, the government announced the first case of Covid-19. Preventing the COVID-19 spread in Indonesia is challenging because the people are very diverse, and not everyone has the same understanding of the transmission of COVID-19. In addition, the Indonesians has mudik tradition, going home yearly on Eid al-Fitr. This study developed an epidemic model of Covid-19 spread SIAR by adding migration factors to represent the mudik tradition. The disease-free equilibrium point, the endemic equilibrium point, and its stability were determined. Numerical simulations were done using Covid-19 transmission data to analyze the trend of symptomatic and asymptomatic infected subpopulations. The results show that the dynamic characteristics of Covid-19 cases were semi-stable in compartments S, I, and A. This condition means that S, I, and A will rise at a certain time. In a disease-free situation, the susceptible subpopulation S is stable at a certain value. At the same time, other subpopulations are stable at almost zero and at zero. The susceptible subpopulation S in a disease-free situation is larger than during an epidemic. The number of people in disease-free conditions is smaller than those in epidemic conditions. In addition, migration at a certain level can increase the spread of Covid-19.
Predicting Digital Literacy Levels in Higher Education: A LightGBM Model Integrating Feature Selection for Improved Accuracy Arman Haqqi Anna Zili; Selly Anastassia Amellia Kharis
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8077

Abstract

Digital literacy has become an essential skill in higher education, particularly in online and distance learning settings. This study explores the use of Light Gradient Boosting Machine (LightGBM) to classify digital literacy levels among 10,393 students at Universitas Terbuka. To improve both efficiency and clarity of interpretation, feature selection was carried out using SelectKBest, which reduced the dataset to 33 predictors. The final model, evaluated through stratified 5-fold cross-validation, achieved an accuracy of 0.964 and a weighted F1-score of 0.964. The results show that limiting the number of features did not weaken predictive performance, while also making it easier to identify which aspects of digital literacy are most influential. Interestingly, the strongest predictors were not only technical skills but also ethical behavior, digital citizenship, and online communication. These findings highlight that digital literacy is multidimensional and that effective assessment tools must account for social and behavioral factors alongside technical competence. Taken together, applying feature selection with LightGBM offers an effective way to assess digital literacy in higher education. The method achieves strong predictive accuracy while keeping the model interpretable, giving universities clearer guidance for shaping interventions and curricula in online learning contexts.
TRAINING AND ASSISTANCE IN THE DEVELOPMENT OF LEARNING OUTCOME ASSESSMENT MATERIALS HIGH-ORDER THINKING SKILLS FOR HIGH SCHOOL MATHEMATICS TEACHERS IN SOUTH TANGERANG Elin Herlinawati; Selly Anastassia Amellia Kharis; Darsih Idayani; Hasoloan Siregar; Siti Umamah Naili Muna
As-Sidanah Vol 5 No 2 (2023): OKTOBER
Publisher : LP2M Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/assidanah.v5i2.382-398

Abstract

High Order Thinking Skill (HOTS) is students' ability to process knowledge and ideas in a certain way to give them new knowledge and implications. The general perception regarding HOTS questions is that they are high-level questions. Most teachers adopt olympic questions as HOTS questions due to a misperception that HOTS questions are difficult, even though HOTS questions can be made in various difficulty levels: low, medium, and high. In addition, the substantive aspect of Mathematics, especially the application of Mathematics in life, is also one of the problems in developing HOTS questions. The method of implementing community service (PkM) is by training and assisting in preparing SMA-level Mathematics HOTS questions. The results of this PkM activity are: (1) Increased knowledge and understanding of teachers in the technique of developing HOTS questions which can be seen in an increase in the average pre-test and post-test results by 9%, (2) Improved mathematical skills in the use of concepts and applied Mathematics on HOTS questions. This can be seen from the questions made by the teachers in this PkM activity, and (3) the participants' satisfaction with this PkM activity is shown by the questionnaire results with a satisfaction range of 85.71% - 96.43%.
TRAINING AND ASSISTANCE IN USING GEOGEBRA TO IMPROVE THE COMPETENCE OF HIGH SCHOOL MATHEMATICS TEACHERS Darsih Idayani; Wahyu Hidayat; Selly Anastassia Amellia Kharis; Asmara Iriani Tarigan; Sumartono Sumartono
As-Sidanah Vol 6 No 1 (2024): APRIL
Publisher : LP2M Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/assidanah.v6i1.182-192

Abstract

Mathematics teachers must adapt to technological developments in the digital era. Among other problems related to learning mathematics, students tend to feel bored and uninterested in mathematics. At the same time, most teachers need help keeping up with fast technology developments. The solution offered is training and mentoring activities for using the GeoGebra software in mathematics learning in South Tangerang City in collaboration with the Subject Teacher Deliberation of Mathematics or MGMP. The material presented was about introducing GeoGebra, graphs, and function operations. Moreover, it was about solving linear programming, geometry, and calculus in GeoGebra. The pretest and posttest results showed increased participants' knowledge about GeoGebra utilization. This condition is indicated by the significance value of the t-test, which is less than 0.05 and less than 0.001. In addition, activity evaluation was carried out by filling out evaluation forms and interviews. The evaluation results show that the training and mentoring activities have enabled participants to gain new knowledge about the GeoGebra as needed in teaching mathematics in high school.
Analisis Kinerja Model CNN-LSTM Berbasis Optical Character Recognition untuk Ekstraksi Informasi e-KTP Berdasarkan Kategori Teks Fauzan Ihza Fajar; Selly Anastassia Amellia Kharis; Asmara Iriani Tarigan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.37593

Abstract

Optical Character Recognition (OCR) technology plays an important role in automating information extraction from identity documents such as the Electronic Identity Card (e-KTP). However, recognizing long text sequences and handling complex character variations remain significant challenges. These issues can lead to high error rates. This study aims to address these limitations by exploring a deep learning–based OCR model that integrates Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Connectionist Temporal Classification (CTC) in an end-to-end framework without explicit character segmentation. CNN is employed to extract visual features, LSTM captures sequential dependencies, and CTC enables flexible alignment between input images and output text. The main contribution of this study lies in analysing the performance of a CNN-LSTM model with CTC in extracting e-KTP information across text categories with different complexity levels, namely Date and Place of Birth (TTL), name, and national identification number (NIK). Performance is evaluated using the Character Error Rate (CER). The results show that the model achieves the best performance on TTL with a CER of 0.84%, followed by NIK at 1.29%, and Name at 4.33% indicating higher difficulty in recognizing more complex text patterns. These findings demonstrate that model performance is influenced by text characteristics, particularly variability and sequence length. Overall, the proposed approach is effective for end-to-end e-KTP information extraction and provides insights for developing more adaptive OCR models.
Co-Authors AA Sudharmawan, AA Agustiani Putri Ajmal, Muhammad Anna Zili, Arman Haqqi Arman Haqqi Anna Zili Asmara Iriani Tarigan Asmara Iriani Tarigan Asmara Iriani Tarigan Bramastary, Aurelly Meidy Bustamam, Alhadi Danial, T Ahmad Darsih Idayani Darsih Idayani Darwin Hartono Derick Hendri Devvi Sarwinda Dian Lestari Dwi Antari Wijayanti Edward Zubir Edward Zubir Eka Wirajuang Daurrohmah Elin Herlinawati Elin Herlinawati Endang Wahyuningrum Endy Grade Tampubolon Fajar, Fauzan Ihza Fatia Fatimah Fauzan Ihza Fajar Fauzan Ihza Fajar Febri Maulana Hasoloan Siregar Hasoloan Siregar Heny Kurniawati Heny Kurniawati Hertono, Gatot Fatwanto Hirawati Lubis Indriyani, Annisa Irawan, Sam Rizky Kamrin Mir Kusriyah, Siti Martinasari, Made Diyah Putri Maulana Malik, Maulana Maulidia Permatasari, Sri Melisa Arisanty Melisa Arisanty Moh Muzammil Moh. Muzammil Muhammad Ajmal Muhammad Ajmal Muhammad Firman Karim Muhammad Firman Karim NadyaAsanul Husna Nur Izani Maulani Nur Mahin Nurmala Pangaribuan Nurmala Pangaribuan Nuryaningrum, Wahyu Nyoman A. Wibawa Pesi Suryani Putri, Agustiani Qonitah, Laity Riady, Yasir Robiansyah, Anton Robiansyah, Anton Sajida Humaira Sajida Humaira Saputra, Dimas Septian Siti Umamah Naili Muna Sri Maulidia Permatasari Sri Maulidia Permatasari Sukatmi, Sri Sumartono Sumartono Sumartono Tarigan, Asmara Iriani Tri Murdiyanto Tri Wijayanti Septiarini Wahyu Hidayat Wiradharma, Gunawan Yasir Riady Yasir Riady Yumiati Zubir, Edwar Zubir, Edward