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All Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control jurnal teknik informatika dan sistem informasi Altruis: Journal of Community Services Patria : Jurnal Pengabdian Kepada Masyarakat Journal of Innovation and Community Engagement
Mewati Ayub
Program Studi Magister Ilmu Komputer Fakultas Teknologi Informasi Universitas Kristen Maranatha
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Public Health Social Sciences Other

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Pengembangan Pola Berpikir Sistematis Melalui Pengenalan Pemrograman Visual Pada Peserta didik Tingkat Menengah Atas Robby Tan; Maresha Caroline Wijanto; Oscar Karnalim; Setia Budi; Mewati Ayub; Diana Trivena Yulianti; Hendra Bunyamin; Sendy Ferdian Sujadi; Rossevine Artha Natasya
Altruis: Journal of Community Services Vol. 2 No. 4 (2021): Altruis
Publisher : University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/altruis.v2i4.18427

Abstract

Systematic thinking is a process of thinking that should be introduced from early age. While developing such thinking, students will learn how to solve a task by breaking it down to smaller tasks and complete them one by one. There are many activities that can support such thinking. One of them is to program visually. Visual programming is usually featured with drop-down blocks where students are only required to choose which process or logic needed than then put them in the play board. A training of such activity was done in a high school at Bandung, Indonesia with Scratch. Students were first introduced with Scratch, a software that is expected to help them think systematically. For conducting the training itself, several stages were followed. It started with introduction, and then followed by lecture and case-based practice. To engage students with the practice, the case study is COVID-19 where students are expected to deliver relevant information creatively, such as developing a game of social distancing, spray vs virus, etc. Evaluation shows that via this training, students were able to further develop their own systematic thinking via the creation of Scratch projects. Further, they believed that this training is interesting and can help them to study in the high school.
The Use of Python Tutor on Programming Laboratory Session: Student Perspectives Oscar Karnalim; Mewati Ayub
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 2, No 4, November-2017
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3314.027 KB) | DOI: 10.22219/kinetik.v2i4.442

Abstract

Based on the fact that the impact of educational tools can only be accurately measured through student-centered evaluation, this paper proposes a long-term in-class evaluation for Python Tutor, a program visualization tool developed by Guo. The evaluation involves 53 students from 4 Basic Data Structure classes, which were held in the even semester of 2016/2017 academic year. It is conducted based on questionnaire survey asked to the students after they have used Python Tutor in their half of programming laboratory sessions. In general, there are three findings from this work. Firstly, Python Tutor helps students to complete programming laboratory tasks, specifically for Basic Data Structure material. Secondly, Python Tutor helps students to understand general programming aspects which are execution flow, variable content change, method invocation sequence, object reference, syntax error, and logic error. Finally, based on student perspectives, Python Tutor is a helpful tool positively affecting the students.
Service Learning in Teachers and Students Mentoring for 2020 Bebras Challenge in Pandemic Era at Maranatha Bebras Bureau Christian University Mewati Ayub; Maresha Caroline Wijanto; Adelia Adelia; Billy Susanto Panca; Doro Edi; Julianti Kasih; Hapnes Toba; Risal Risal; Meliana Christianti; Robby Tan; Daniel Jahja Surjawan
Journal of Innovation and Community Engagement Vol. 2 No. 2 (2021)
Publisher : Universitas Kristen Maranatha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jice.v2i2.3802

Abstract

Bebras Challenge is a competition for elementary to high school students to educate informatics and computational thinking, followed by sixty countries all over the world. Bebras Indonesia Community in coordination with the International Bebras Committee holds the challenge yearly. Indonesia has participated in the Bebras Challenge since 2016. Faculty of Information Technology Maranatha Christian University as a Bebras Bureau has also been involved in the challenge since 2016. To prepare students for Bebras Challenge, Maranatha Bebras Bureau holds a teacher workshop yearly. The Teacher Workshop supports teachers to strengthen students in practicing Bebras tasks. Data on students who participated in the Bebras Challenge at Maranatha Bebras Bureau indicates increasing numbers from 2016 until 2020. This paper describes a service learning for mentoring teachers and students in the Bebras Challenge, which was held in the pandemic year 2020. Teacher mentoring was using a service learning approach, where the lecturers provided training to the teachers and then the teachers would share their knowledge back to their students. There were advantages and disadvantages of the execution during the pandemic. Although in a distance learning condition, teachers and students were still enthusiastic to participate in Bebras Challenge. The number of students who followed the 2020 Bebras Challenge nearly five times compared to 2019 in the Maranatha Bebras Bureau. The scores of elementary school students who followed the challenge showed very good results. On the other side, the results of junior and senior high school students were not as good as the scores of elementary school students.
Pelatihan dan Pendampingan Siswa SMA Santa Maria 1 Bandung dalam Persiapan Tantangan Bebras 2021 Mewati Ayub; Risal Risal; Andreas Widjaja; Nikita Rebeca Yemima Kolinug; Vanika Ipsandy
Patria : Jurnal Pengabdian Kepada Masyarakat Vol 4, No 2: September 2022
Publisher : Universitas Katolik Soegijapranata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24167/patria.v4i2.4167

Abstract

Kegiatan pengabdian masyarakat yang dilakukan Biro Bebras UK Maranatha merupakan pelatihan dan pendampingan siswa SMA Santa Maria 1 Bandung dalam menghadapi Tantangan Bebras 2021 untuk pertama kali. Pelatihan dilakukan secara daring melalui Google Meet selama bulan Oktober 2021, dengan pertemuan sekali dalam seminggu. Materi pelatihan bersumber dari soal Bebras yang dipakai pada Tantangan Bebras 2019 dan 2020, yang dapat diakses dari web latihan Bebras IPB. Peserta pelatihan terdiri dari 12 siswa SMA kelas 10, 11, dan 12. Berdasarkan kuesioner evaluasi yang diisi oleh peserta, peserta menyatakan pelatihan ini membantu mereka dalam mempersiapkan diri menghadapi Tantangan Bebras. Dari pra Tantangan yang dilakukan di akhir pelatihan, terdapat 64% siswa yang memperoleh nilai di atas 50, dengan nilai rata-rata 52.27. Siswa juga berpendapat bahwa soal Bebras yang menarik adalah soal yang terkait langsung dengan persoalan dalam kehidupan nyata
Pengembangan Aplikasi Maranatha E-signature Bernard Renaldy Suteja; Mewati Ayub; Kafka Febianto Agiharta
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 1 (2023): JuTISI (in progress)
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i1.5657

Abstract

Using digital signature in a document, especially in work from home situation, becomes crucial to misuse. The digital signature is a schema to identify somebody uniquely and to prove the originality of a document. The development of information technology allows digital signatures as a tool to ensure the originality of information. The aim of the study is to develop an application that uses Quick Response (QR) Code as a digital signature. So QR Code can work as a tool to authenticate the leader’s signature or document verification. After the application was built and applied, users’ evaluation was performed through questionnaires. The result shows that 44% of users state that the application has been well used and beneficial. There are some suggestions for application revision from 34% of users, whereas 22% have no comment.  
Perbandingan Akurasi Model Pembelajaran Mesin untuk Prediksi Seleksi Masuk Perguruan Tinggi Negeri Oktavianus Yopi Wardana; Mewati Ayub; Andreas Widjaja
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 1 (2023): JuTISI (in progress)
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i1.6126

Abstract

Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN) is still one of the favorite admission routes for high school students to continue their education at Perguruan Tinggi Negeri (PTN). SNMPTN uses semester 1 to 5 report card scores for 6 subjects that are inputted in Pangkalan Data Sekolah dan Siswa (PDSS). Prediction of SNMPTN can be done using machine learning models with various methods. This study aims to create a predictive model using the Decision Tree CART, Gaussian Naïve Bayes and Logistic Regression methods, make predictions and compare the level of accuracy of the models made. The methodology used in this research is Knowledge Discovery in Database (KDD). This is to get useful knowledge from data. The dataset used is data on the scores of 6 subjects for 5 semesters from class 2015 to 2022. Model evaluation uses the Split Percentage Method and K-Fold Cross Validation. The results show that the accuracy scores for the 3 models are different. Logistic Regression has a score of 0.82, followed by Decision Tree CART with a score of 0.75 and finally Gaussian Naïve Bayes with a score of 0.70. The hypothesis put forward by the researcher is in accordance with the results obtained, that the Logistic Regression model has a higher accuracy score. Mathematically, Logistic Regression is not too complicated when compared to other models. To get a model that fits with needs must involve iterating through the machine learning process and trying various variations.
Pelatihan Guru untuk Tantangan Bebras 2022 di Biro Bebras Universitas Kristen Maranatha Mewati Ayub; Oscar Karnalim; Robby Tan; Maresha Caroline Wijanto; Doro Edi; Hendra Bunyamin; Julianti Kasih; Diana Trivena Yulianti; Andreas Widjaja; Risal Risal; Rossevine Artha Nathasya
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 14, No 3 (2023): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v14i3.14326

Abstract

Tantangan Bebras merupakan salah satu kegiatan yang memperkenalkan computational thinking dan informatika kepada siswa sekolah. Bebras Indonesia melalui setiap mitra biro Bebras di seluruh Indonesia menyelenggarakan Tantangan Bebras setiap tahunnya yaitu pada minggu kedua bulan November. Biro Bebras Maranatha juga mempersiapkan guru-guru yang berada di bawah naungan Biro Bebras Maranatha dalam kegiatan pelatihan pada 7 Oktober 2022 secara hybrid dan technical meeting pada 28 Oktober 2022. Pelatihan untuk tahun 2022 dimulai dengan kuis soal-soal Bebras yang diambil dari soal-soal dalam Tantangan Bebras tahun-tahun sebelumnya untuk mengukur tingkat pemahaman guru dalam computational thinking. Kegiatan pelatihan dilanjutkan dengan pembahasan soal kuis melalui diskusi, penyampaian konsep computational thinking, serta pendaftaran dan persiapan siswa untuk Tantangan Bebras 2022. Pada akhir sesi pelatihan, guru-guru peserta mengisi kuesioner untuk mengetahui sejauh mana persiapan yang sudah dilakukan untuk Tantangan Bebras 2022. Pelaksanaan kegiatan dilaksanakan secara hybrid diikuti oleh 52 guru perwakilan sekolah. Dari 52 guru yang mengikuti kuis, nilai kuis berkisar antara 0 sampai 80 di mana rata-rata nilai adalah 35. Sebanyak 79% dari guru-guru yang mengikuti pelatihan ini sudah pernah mengikuti workshop Bebras di tahun-tahun sebelumnya dan 69% dari total guru tersebut telah memanfaatkan soal Bebras untuk pembelajaran di kelas. Selama proses pembekalan Tantangan Bebras, terdapat tiga tantangan terbesar yang dihadapi yaitu kemampuan berpikir siswa, persiapan guru untuk pembekalan, dan melatih siswa dalam membaca soal.
Pembelajaran Computasional Thinking melalui Program Gerakan Pandai untuk Guru dan PKBM Mewati Ayub; Maresha Caroline Wijanto; Robby Tan; Daniel Jahja Surjawan; Hapnes Toba; Meliana Christianti; Doro Edi; Hendra Bunyamin; Adelia Adelia; Risal Risal
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 7 No 3 (2023): Agustus
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v7i3.13430

Abstract

Program Gerakan Pandai yang digagas oleh Bebras Indonesia dengan dukungan Google bertujuan untuk membuat guru mulai menjadi guru penggerak dalam menyemaikan dan menumbuh-kembangkan kemampuan Computational Thinking (CT). Melalui gerakan PANDAI ini, diharapkan guru mengenal CT dan memperkenalkan CT kepada para siswa, sehingga siswa dapat mengembangkan kemampuan  berpikir komputasional yang bersifat kritis dan kreatif. Biro Bebras Maranatha menjalankan program Gerakan Pandai dalam dua batch yang dimulai pada bulan September 2020 sampai dengan Desember 2021. Pelatihan guru  batch1 diikuti oleh 148 guru, sedangkan batch2 diikuti 394 guru. Indikator guru yang berhasil menerapkan kemampuan CT adalah guru yang melaksanakan  paling sedikit 4 sesi microteaching dalam dua semester. Guru yang tuntas melakukan microteaching untuk batch1 ada 110 orang (74%), dan batch2 ada 184 guru (47%), dengan persentase rata-rata 60.5% untuk seluruh batch. 
Co-Authors Adelia Adelia Adelia Adelia Andreas Widjaja Bernard Renaldy Suteja Billy Susanto Panca Daniel Jahja Surjawan Daniel Jahja Surjawan Diana Trivena Yulianti Doro Edi Doro Edi Hapnes Toba Hendra Bunyamin Hendra Bunyamin Julianti Kasih Julianti Kasih Kafka Febianto Agiharta Maresha Caroline Wijanto Maresha Caroline Wijanto Maresha Caroline Wijanto Meliana Christianti Meliana Christianti Nikita Rebeca Yemima Kolinug Oktavianus Yopi Wardana Oscar Karnalim Oscar Karnalim, Oscar Risal Risal Risal Risal Robby Tan Rossevine Artha Natasya Rossevine Artha Nathasya Sendy Ferdian Sujadi Setia Budi Vanika Ipsandy