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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. 
PELATIHAN COMPUTATIONAL THINKING UNTUK GURU SDK 6 BPK PENABUR BANDUNG MELALUI BEBRAS TASK DAN AKTIVITAS UNPLUGGED Mewati Ayub; Hendra Bunyamin; Oscar Karnalim; Robby Tan; Maresha Caroline Wijanto; Doro Edi; Julianti Kasih; Andreas Widjaja; Adelia; Meliana Christianti; Wenny Franciska Senjaya; Swat Lie Liliawati; Rossevine Artha Nathasya
Jurnal Abdimas Ilmiah Citra Bakti Vol. 5 No. 3 (2024)
Publisher : STKIP Citra Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38048/jailcb.v5i3.3799

Abstract

Konsep computational thinking (CT) diperlukan dalam dunia digital saat ini agar setiap orang dapat belajar dan bekerja secara cerdas. Untuk membangun kembali interaksi antar guru dan siswa yang terkendala pada saat pandemi Covid 19, maka interaksi yang efektif antar guru dan siswa dalam pembelajaran pasca pandemi dapat dilakukan dengan menerapkan CT dalam pembelajaran.  Pelatihan CT untuk guru-guru SDK 6 BPK Penabur dilakukan dengan tujuan agar setiap guru dapat menerapkan konsep CT dan aktivitas unplugged dalam pembelajaran yang bersifat interaktif. Pelatihan guru yang dilaksanakan secara luring pada 15 Maret 2024 dan 22 Maret 2024, diikuti oleh 30 orang peserta. Setelah materi konsep CT, Bebras task, dan aktivitas unplugged disampaikan, guru diberi tugas kelompok untuk membuat rencana penerapan CT dalam mata pelajaran serta membuat rencana aktivitas unplugged untuk membantu siswa dalam menerapkan CT dalam persoalan sehari-hari. Hasil dari tugas kelompok yang dibuat peserta menunjukkan nilai rata-rata sangat baik dalam penerapan CT dan aktivitas unplugged. Sebagian besar peserta berpendapat penerapan CT sangat bermanfaat untuk diterapkan dalam pembelajaran di tingkat sekolah dasar untuk melatih anak berpikir kritis dan kreatif dalam memecahkan masalah di kehidupan sehari-hari.
Sistem Pendeteksi Pengirim Tweet dengan Metode Klasifikasi Naive Bayes Maresha Caroline Wijanto
Jurnal Teknik Informatika dan Sistem Informasi Vol 1 No 2 (2015): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v1i2.584

Abstract

Until Januari 2015, social media users reached 29% of the world population. In Indonesia itself had 28% active users from total populasi of Indonesia. The usage of social media gives positives and negatives effect. The negatives effect are the increasing number of fraud by using SMS or social media, such as Twitter. Many people are deceived by the tweet messages sent from known user account when in fact the sender is other person. Because of that, there is a need to have a system to detect wheteher the tweet sender is the same person or not. Naive Bayes classifiers method is used to classify that. The data source is taken from tokens selected based on two models, the minimum n-time number of occurrences and the n-th highest number of occurrences. Each tweets also processed into six different types of tweets, such as formal tweet or lowercase tweet. The test uses tenfold cross-validation and measured by the value of accuracy, precision, recall, and F-score. The common result shows 82,145% level of accuracy. Second model to select the tokens shows consistency level of accuracy for each types of tweets. The fifth types of tweets also get the highest level of accuracy for both models to select the tokens.
Pengembangan Admisi Universitas Berbasis Sistem Pengelola Pengetahuan Nathanael Liman; Maresha Caroline Wijanto; Mewati Ayub; Bernard Renaldy Suteja; Try Atmaja Linggan Jaya
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 2 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i2.4651

Abstract

 The study will develop a prototype to implement a knowledge management system using the information retrieval method. As a study case, the knowledge about university admission will be used. The users of the system consist of guests, admin, and admission staff. The guest can search for information in the dashboard and give suggestions. The admission staff can add new knowledge or modify the existing knowledge. The new knowledge should be verified and approved by the admin. The testing was performed to verify that the system works as it should be, especially for information searching. The results show that searchingusing lowercase and without stopword, or punctuation gives better similarity index. Searching using unigram also has better similarity index.
Implementasi Realtime Cloud Service dalam Pengelolaan Nilai Tugas Akhir Mahasiswa Lydia Noviani Kusumo; Maresha Caroline Wijanto; Robby Tan; Yudita Royandi
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 2 (2023): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i2.6566

Abstract

Final Project is one of the requirements that must be fulfilled by students to complete their studies at the university. In this case study in a non-technical study program at a private university, each student will be accompanied by two supervisors and will be tested by two examiners. Students will face three trials and each lecturer needs to give an assessment, both the process and the product. The grade of the product is also prioritized because this study program expects that each student can produce a product that has added value for society. With so many things involved and manual recording, it is necessary to create a final assignment grade management system. To simplify implementation, the system is created by utilizing a realtime cloud service, namely Firebase. Firebase is a service from Google to make it easier for developers to develop applications on various platforms. Data is stored in JSON and synchronized in real time to each user. This system can be accessed by Admins and Lecturers, this system is also equipped with a Dashboard as a recapitulation of existing data, trial reminders via email, and data import-export. Based on the survey conducted, it easier for Admins and Lecturers to manage final assignments.