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Abstrak :
Pendidikan merupakan salah satu aspek penting dalam upaya pencegahan tindak pidana korupsi. Namun kurikulum pendidikan tanpa disertai kultur masyarakat yang kooperatif tidak akan pernah berdampak serius. Pembentukan kultur ini perlu stimulan, dan dalam artikel ini kami menawarkan konsep Perilaku Sosial George Homans dan Interaksionis Simbolik George Herbert Mead sebagai alternatif pendekatan kepada permasalahan yang ada. Penelitian ini menggunakan metodologi kualitatif melalui pendekatan studi literatur. Hipotesis kami adalah kurangnya penghargaan (reward) terhadap individu yang berani bersikap antikorupsi merupakan salah satu penyebab dari minimnya kultur tersebut terbangun di tengah masyarakat. Mereka yang berani menjalankan nilai-nilai dasar antikorupsi justru sering mendapatkan tekanan dari peer group. Hal ini memberikan stimulan yang negatif bagi implementasi nilai-nilai antikorupsi.

Abstrak :
Data pokok pendidikan (Dapodik) merupakan sistem pendataan PAUD, Dikdas, dan Dikmen berbasis sistem TIK yang memuat data sekolah, data siswa, data pendidik dan tenaga kependidikan, dan entitas data sekolah lainnya. Dapodik berperan sebagai basis data kebijakan pendidikan seperti BOS, bansos, tunjangan, UN dan penerbitan data statistik pendidikan Indonesia. Berdasarkan konsep Open Government Data, Dapodik masih memiliki permasalahan pada desain dan implementasinya sehingga penelitian ini untuk mengevaluasi Kebijakan Dapodik sebagai Open Government Data. Pendekatan penelitian ini post-positivisme dengan metode qualitative case-study dengan desain penelitian deskriptif. Hasil penelitian menyarankan bahwa Kemendikbudristek perlu menyempurnakan regulasi (permendikbud) yang mengatur tantang Dapodik terutama terkait dengan pemenuhan standar Open Government Data yang berlaku, seperti Prinsip Sebastopol dan atau Sunlight Foundation. Selain itu, untuk menyukseskan implementasi Dapodik agar memenuhi kebutuhan basis data kebijakan, faktor adopsi teknologi, kesiapan organisasi, dan adaptasi dorongan eksternal perlu diperkuat melalui koordinasi dan kolaborasi berbagai pihak. ......Basic education data (Dapodik) is an ICT system-based data collection system for early childhood education, primary education, and secondary education which consist of school data entities. Dapodik roles as a database for education policies such as BOS, social assistance, allowances, National Examination, and the publication of Indonesian education statistics. Based on the concept of Open Government Data, Dapodik still has problems in its design and implementation, so this research is to evaluate Dapodik's policy as Open Government Data. This research approach is post-positivism with a qualitative case-study method with a descriptive research design. The results suggest that the Ministry of Education and Culture needs to improve the regulations (permendikbud) that regulate Dapodik's challenges, especially those related to compliance with applicable Open Government Data standards, such as the Sebastopol Principles and or the Sunlight Foundation. In addition, for the successful implementation of Dapodik to meet the requirement of policy databases, technology adoption, organizational readiness, and adaptation of external factors need to be strengthened through coordination and collaboration of various parties.

Abstrak :
Pengembangan Sistem Informasi Penjadwalan Sidang (SISIDANG) versi terbaru (disebut SISIDANG baru) pada tugas akhir ini bertujuan agar dapat digunakan untuk proses tugas akhir dan sidang di semester genap 2022/2023 Fakultas Ilmu Komputer Universitas Indonesia. Pengembangan tersebut meliputi rancangan dan implementasi fitur baru seperti dashboard dan laporan honor, dan perbaikan fitur-fitur yang belum sempurna seperti laporan-laporan yang terkait dengan persidangan, penilaian sidang, pemberian revisi dari dosen, pengelolaan jadwal sidang, pengelolaan dosen, pengelolaan mata kuliah spesial, jadwal pribadi dosen, serta unggah berkas mahasiswa. Proses pengembangan dilakukan dengan metodologi Feature Driven Development (FDD) dengan kelebihan menciptakan progres yang cepat. Setelah pengembangan, dilakukan pengujian dan evaluasi agar dapat memastikan kinerja website dan kepuasan pengguna. Pengujian dan evaluasi SISIDANG baru diukur dengan User Acceptance Testing (UAT), survei fitur dashboard terkait dashboard design principle, dan System Usability Scaling (SUS). Hasil dari evaluasi menunjukkan bahwa SISIDANG baru telah cukup memenuhi kriteria pembuatan dashboard dan memenuhi kriteria cukup untuk tingkat usability. ......The goal of the development of the latest version of the Sistem Informasi Penjadwalan Sidang (SISIDANG) in this final project is to be able to be use for the whole final assignment process in the second semester of 2022/2023 at the Faculty of Computer Science, University of Indonesia. This development process consisted of designing and implementation process of new features such as dashboards and honorarium reports and improvements to lacking features such as reports related to final assignment presentation, final assignment assessments, final assignment evaluation, the scheduling process of final assignment, lecturers management, final assignment management, lecturer’s personal schedule feature, and uploading student files. The development process is carried out by using Feature Driven Development (FDD) methodology, which has the advantage of faster development progress. After the development process, testing and evaluation were carried out in order to ensure the website’s performance and user satisfaction meet user expectations. Testing and evaluation of the new system are measured with User Acceptance Testing (UAT), survey related to dashboard design principles, and System Usability Scaling (SUS). The results of the evaluation show that the new system has sufficiently met the criteria for making dashboards and the criteria for usability level.

Abstrak :
Salah satu poin penilaian akreditasi universitas adalah jumlah mahasiswa yang lulus tepat waktu dan mahasiswa yang drop-out (DO). Sayangnya, potensi terjadinya mahasiswa terlambat lulus atau drop out masih menjadi tantangan bagi Universitas Kristern Krida Wacana (UKRIDA). Untuk dapat melakukan tindakan mitigasi dan menyusun strategi retensi, perlu dilakukan prediksi terhadap mahasiswa yang berpeluang DO dan terlambat lulus menggunakan data informasi akademik. Hal tersebut dilakukan untuk membantu proses pengecekan mahasiswa DO yang sebelumnya masih manual. Selain itu, faktor informasi akademik apa saja yang memengaruhi hasil prediksinya. Model yang dibangun menggunakan algoritma-algoritma yang diantaranya Logistic Regression, Nave Bayes, Support Vector Machine (SVM), Decision Tree, Random Forest, dan Gradient Boosting. Hasilnya data yang digunakan untuk mendeteksi mahasiswa DO berhasil mencapai 99,42% pada metric precision dan 98,58% pada average precision. Data yang digunakan untuk mendeteksi mahasiswa terlambat lulus berhasil mencapai 78,51% pada metric precision dan AUC 82,86%. Faktor-faktor yang memengaruhi mahasiswa DO adalah status bayar karena terdapat mahasiswa yang hutang terprediksi DO, IPK dengan rata-rata dibawah 2 diprediksi DO, jumlah ulang mata kuliah di atas 1, tidak KRS di atas 2. Namun pada deteksi mahasiswa terlambat lulus, faktor-faktor yang memengaruhi hal tersebut adalah terdapat data yang lebih dari 1 Tidak KRS dan 24 kali mengulang mata kuliah serta dengan status bayar Hutang. ......One of the points of university accreditation assessment is the number of students who graduate on time and drop-out students (DO). Unfortunately, the potential for students to graduate late or drop out is still a challenge for Kristern Krida Wacana University (UKRIDA). To be able to take mitigation actions and develop retention strategies, it is necessary to predict students who are likely to drop out and graduate late using academic information data. This was done to help the process of checking DO students which was previously still manual. In addition, what academic information factors affect the prediction results. The model is built using algorithms including Logistic Regression, Naïve Bayes, Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting. As a result, the data used to detect DO students managed to reach 99.42% on metric precision and 98.58% on average precision. The data used to detect late graduating students managed to reach 78.51% on metric precision and 82.86% AUC. The factors that affect dropout students are paid status because there are students whose debt is predicted to drop out, GPA with an average of below 2 is predicted to drop out, the number of repeat courses is above 1, not KRS is above 2. -Factors that influence this are data that is more than 1 No KRS and repeats courses 24 times as well as with Debt payment status.

Abstrak :
XYZ Collaborative Learning in Completing Knowledge (JM-Click) adalah aplikasi berbasis mobile yang dapat membantu karyawan XYZ untuk dapat melakukan pembelajaran elektronik. Tujuan dari adanya JM-Click adalah menjadi tempat pengembangan diri bagi setiap karyawan. Akan tetapi tingkat penggunaan JM-Click masih kurang maksimal karena masih banyak pengguna yang merasa aplikasi masih sulit dipahami dan digunakan. Untuk meningkatkan penggunaan aplikasi, maka dilakukan uji kebergunaan agar dapat mengetahui hal apa saja yang masih dapat diperbaiki pada aplikasi JM-Click. Dilakukan evaluasi terhadap aplikasi menggunakan metode cognitive walkthrough. Berdasarkan hasil evaluasi, terdapat permasalahan kebergunaan pada 22 aksi yang diuji. Hasil evaluasi berupa masalah kebergunaan yang ditemukan kemudian dipetakan dengan pedoman kebergunaan aplikasi pembelajaran yang dibentuk oleh Kumar, Goundar, & Chand pada tahun 2019 untuk menghasilkan rekomendasi perbaikan terhadap aplikasi. Rekomendasi perbaikan yang dibentuk juga divalidasi dengan membandingkan hasil iterasi evaluasi cognitive walkthrough sebelum dan sesudah perbaikan. Berdasarkan hasil penelitian, perbaikan berupa penyesuaian ukuran area tekan, validasi tombol simpan isian, penggunaan ikon yang tepat, serta penggunaan tampilan dan navigasi yang konsisten dapat meningkatkan tingkat keberhasilan pengguna dalam menyelesaikan aksi pada aplikasi. Hasil penelitian diharapkan dapat membantu pihak XYZ untuk menyesuaikan pengembangan perangkat lunak JM-Click dengan kebutuhan utama penggunanya sehingga dapat memberikan dampak positif pada tingkat penggunaan aplikasi. ......XYZ Collaborative Learning in Completing Knowledge (JM-Click) is a mobile-based application that can help XYZ employees to do electronic learning. The purpose of JM- Click is to be a place for self-development for every employee. However, the usage level of JM-Click is still not optimal because many users feel that the application is still difficult to understand and use. To increase the usage of the application, a usability test is carried out to find out what things can still be improved from the JM-Click application. Evaluation of the application was performed using the cognitive walkthrough method. Based on the evaluation results, usability problems were found in the 22 actions tested. The results of the evaluation found in the form of usability problems were then mapped with the usability guidelines for learning applications formed by Kumar, Goundar, & Chand in 2019 to produce recommendations for improvements to the application. The improvement recommendations that were formed were also validated by doing a comparison of cognitive walkthrough iteration using before and after improvement prototypes. Based on the research results, improvements in the form of adjusting the size of the press area, validation on the save entry button, correct usage of icon, and using consistent display and navigation can increase the user's success rate in completing actions on the application. The results of the research are expected to help XYZ to adjust the development of the JM-Click to the main needs of its users so that it can have a positive impact on the usage level of the application. 

Abstrak :
[CSE 2011 is an integrated conference concentration its focus on computer science and education. In the proceeding, you can learn much more knowledge about computer science and education of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful., CSE 2011 is an integrated conference concentration its focus on computer science and education. In the proceeding, you can learn much more knowledge about computer science and education of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful.]

Abstrak :
Learning Technology for Education in Cloud investigates how cloud computing can be used to design applications to support real time on demand learning using technologies. The workshop proceedings provide opportunities for delegates to discuss the latest research in TEL (Technology Enhanced Learning) and its impacts for learners and institutions, using cloud.