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FASE-1: IMPLEMENTASI STANDAR ATURAN PEMODELAN UML SEBAGAI DASAR SPESIFIKASI KEBUTUHAN DI EFARMING CORPORA BANDUNG Yudi Priyadi; Gede Agung Ary Wisudiawan; Mahendra Dwifebri Purbolaksono; Pramoedya Syachrizalhaq Lyanda
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol 2 No 1 (2021)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (515.861 KB) | DOI: 10.31949/jb.v2i1.734

Abstract

In Phase 1 of this Abdimas, activities focused on the general analysis presented through system modeling rules and data modeling. This activity will have an impact on the next Abdimas phases. There is a problem focus on how to describe the system and the process of sending data. There was a problem in analyzing the requirements specifications in the process of sending agricultural activist data to its members. In general, the objectives regarding the potential/opportunities for empowerment of farmer members in the EFarming Corpora community can be increased by identifying requirements specifications, which will be defined through the creation of system modeling and data modeling. There is an adoption of the method through modification is carried out for Phase 1 of the Regular Scheme of community service activities, which will provide understanding to farmer activists in the Bandung Corpora Efarming Environment regarding information technology to support Farmer Community activities. The discussion of material implemented in this community service partner includes several supporting results in the next phase. This discussion is the basis for development that can be explored in the System Development Life Cycle stage, through the support of the Software Requirement Specification, Elicitation, Requirement Statement, Software Modeling, and Software Prototype. In its implementation, for Phase 1, Abdimas has a form of activity resulting from several activities: scientific training, a compilation of required information systems, and surveys and analysis of industrial needs.
Analisis Kesiapan Penerapan Process Mining pada Sistem Manajemen Pembelajaran Universitas Telkom Angelina Prima Kurniati; Gede Agung Ary Wisudiawan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8, No 6: Desember 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021863875

Abstract

Sistem manajemen pembelajaran (Learning Management System/ LMS) berbasis komputer telah banyak digunakan untuk mengelola pembelajaran dalam institusi pendidikan, termasuk universitas. LMS merekam dan mengelola akses pengguna secara otomatis dalam bentuk event log. Data dalam event log tersebut dapat dianalisis untuk mengenali pola penggunaan LMS sebagai pertimbangan pengembangan LMS. Salah satu metode yang dapat diadopsi adalah process mining, yaitu menganalisis data event log berbasis proses. Analisis data berbasis proses ini bertujuan untuk memodelkan proses yang terjadi dan terekam dalam LMS, mengecek kesesuaian pelaksanaan proses dengan prosedur, dan mengusulkan pengembangan proses di masa mendatang. Makalah ini mengeksplorasi kesiapan data penggunaan LMS di Universitas Telkom sebagai subjek penelitian untuk dianalisis dengan pendekatan process mining. Sepanjang pengetahuan kami, belum ada penelitian sebelumnya yang melakukan analisis data berbasis proses pada LMS ini. Kontribusi penelitian ini adalah eksplorasi peluang untuk menganalisis proses pembelajaran dan pengembangan metode pembelajaran berbasis LMS. Analisis kesiapan LMS dilakukan berdasarkan daftar pengecekan komponen yang dibutuhkan dalam process mining. Makalah ini mengikuti tahap-tahap utama dalam Process Mining Process Methodology (PM2). Studi kasus yang dieksplorasi adalah proses pembelajaran pada satu mata kuliah dalam satu semester berdasarkan event log yang diekstrak dari LMS. Hasil penelitian ini menunjukkan bahwa analisis data dalam LMS ini dapat digunakan untuk menganalisis performansi pembelajaran di Universitas Telkom dari kelompok pengguna yang berbeda-beda dan dapat dikembangkan untuk menganalisis data pada studi kasus yang lebih besar. Studi kelayakan ini diakhiri dengan diskusi tentang kelayakan LMS untuk dianalisis dengan process mining, evaluasi oleh tim ahli LMS, dan usulan pengembangan LMS di masa mendatang.  AbstractComputer-based Learning Management Systems (LMS) are commonly used in educational institutions, including universities. An LMS records and manages user access logs in an event log. Data in an event log can be analysed to understand patterns in the LMS usage to support recommendations for improvements. One promising method is process mining, which is a process-based data analytics working on event logs. Process mining aims to discover process models as recorded in the LMS, conformance checking of process execution to the defined procedure, and suggest improvements. This paper explores the feasibility of Telkom University LMS usage data to be analysed using process mining. To the best of our knowledge, there was no previous research doing process-based data analytics on this LMS. This paper contributes to explore opportunities to analyse learning processes and enhance LMS-based learning methods. The feasibility study is based on a data component checklist for process mining. This paper is written following the main stages on the Process Mining Project Methodology (PM2). We explore a case study of the learning process of a course in a semester, based on an event log extracted from the LMS. The results show that data analytics on this LMS can be used to analyse learning process performance in Telkom University, based on different user roles. This feasibility study is concluded with a discussion on the feasibility of the LMS to be analysed using process mining, an evaluation by the representative of the LMS expert team, and a recommendation for improvements.
ANALISIS FAKTOR KESUKSESAN SISTEM INFORMASI MENGGUNAKAN MODEL DELONE AND MCLEAN Gede Agung Ary Wisudiawan
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 2 No. 1 (2015)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.26 KB) | DOI: 10.33197/jitter.vol2.iss1.2015.71

Abstract

[id]Abstrak :Model kesuksesan sistem informasi merupakan model kausal yang berisikan dimensi-dimensi pembentuk kesuksesan sistem informasi. Dimensi user satisfaction berhubungan dengan service quality, information quality,system quality, perceived usefulness dan benefit. Penelitian ini mencoba menganalisis hubungan antara semua dimensi yang menyusun kesuksesan system informasi tersebut. System informasi yang digunakan sebagai kasus dalam penelitian ini adalah system informasi e-learning yang sudah digunakan oleh mahasiswa, dosen dan staff pada salah satu perguruan tinggi swasta di Bandung.Kata kunci :Model kesuksesan sistem informasi, Model DeLone & McLean, Model Seddon, Pearson Product Moment[en]AbstractInformation systems success model success is a causal model that contains the dimensions forming the success of information systems. Dimensions of user satisfaction related to service quality, information quality, system quality, perceived usefulness and benefits. This study tries to analyze the relationship between all the dimensions that make up the success of the information system. System information is used as a case in this study is the e-learning information system that has been used by students, faculty and staff at one of the private universities in Bandung.Keywords :Information success model, the DeLone & McLean model, the Seddon model, Pearson Product Moment
Process Mining for Disease Trajectory Analysis on the Indonesia Health Insurance Data Angelina Prima Kurniati; Guntur Prabawa Kusuma; Gede Agung Ary Wisudiawan
JURIKOM (Jurnal Riset Komputer) Vol 9, No 5 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i5.4924

Abstract

Process mining has been implemented in many domains, including healthcare. In healthcare, process mining projects aimed to inform sequential patterns of processes based on the actual process executions as they are recorded in the event log. Event log as the main input of process mining tasks can be extracted from the automatically recorded data of patient treatments or diagnoses. By understanding common patterns of patient diagnoses, we can analyse disease trajectories of a cohort of patients. Disease trajectory analysis has been used to describe the course or progression of diseases, especially chronic diseases, as experienced over time. We applied process mining as the main methodology for disease trajectory analysis, following the process mining project methodology, to analyse patient records on the Indonesia Health Insurance  (BPJS Kesehatan) Data Samples. We extracted the data samples, transform them into an event log, discover the disease trajectories based on process discovery algorithm, analyse it to inform their conformance to the event log. Contributions of our research are to promote process mining for disease trajectory analysis and to open wider opportunities to analyse Indonesia Health Insurance data representing Indonesia health conditions. As a case study, we explored disease trajectory of cancer patients
Process Mining using Inductive Miner Algorithm to Determine the actual Business Process Model Muhammad Wanda Wibisono; Angelina Prima Kurniati; Gede Agung Ary Wisudiawan
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4769

Abstract

At the beginning of 2019, the COVID-19 pandemic entered the country of Indonesia resulting in all learning activities being carried out online in all cities of Indonesia. Likewise, Telkom University concentrates all teaching and learning activities online using the CeLOE Learning Management System. Learning Management System is a system that helps lecturers in managing teaching and learning activities independently in educational institutions. CeLOE is a learning management system of Telkom University developed based on Moodle. In this study, we analyse the CeLOE event log using the process mining method. The goal is to find out the learning patterns of students using CeLOE during the COVID-19 pandemic. This research case study focuses on the activities of students of the Telkom University S1 Informatics study program for the first semester of 2020/2021 in using CeLOE LMS. The analysis of this study conducted a comparison of the performance of three variants of the inductive miner (IM) algorithm through conformance checking values. The results of the analysis obtained are value of conformance checking from the three variants of the inductive miner (IM) algorithm have an average fitness value of up to 1 prove that the inductive miner (IM) algorithm can make a model based on the event log well. Besides that, it has a fairly high precision value with a value range of 0.750-0.850 shows that the inductive miner (IM) makes a process model with relatively many variations of activities outside the event log and the IM process model is "overfit-ting" for all variants of the IM algorithm. Inductive miner (IM) is the best inductive miner (IM) algorithm variant with a fitness value of 1.0, precision value of 0.750, and the generalization value of this algorithm is relatively high (0.984). It is hoped that this research can contribute to the addition of new perspectives related to the implementation of process mining using inductive miner (IM) algorithm in the field of education
PELATIHAN PENGGUNAAN TOOLS CANVA PEMBUATAN MEDIA AJAR KREATIF UNTUK GURU SDN CIRANGRANG 2023 Mira Sabariah; Gede Agung Ary Wisudiawan; Nungki Selviandro; Zhafran Hafizh Izdihar Riyadi; Ahmad Muflih Nawir; Tasyrika Nurul Hajar; Raihan Sulthon Yaafi; Muthia Khairunissa
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 3 (2023)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v4i3.5995

Abstract

Penelitian ini bertujuan untuk menganalisis kepuasan para tenaga pengajar terhadap pelatihan media pembelajaran menggunakan tools Canva terhadap pembelajaran di SDN 059 Cirangrang Bandung. Fokus utama dari penelitian ini adalah untuk mengevaluasi tingkat kepuasan para tenaga pengajar yang ikut serta dalam pelatihan ini. Penelitian ini menggunakan metode survei yang dimana kami menyebarkan kuesioner kepada para tenaga pengajar. Kuesioner tersebut dirancang untuk mengukur tingkat kepuasan mereka terhadap pelatihan, sejauh mana mereka dapat mengimplementasikan penggunaan Tools Canva dalam pembelajaran, serta dampak yang dirasakan dalam proses pembelajaran di kelas. Hasil dari penelitian ini menunjukkan bahwasanya para tenaga pengajar yang ikut serta dalam pelatihan ini merasa puas dan sangat terbantu karena dengan memanfaatkan Canva ini, kegiatan belajar dan mengajar akan menjadi lebih bervariatif dan menyenangkan. Temuan ini memiliki implikasi penting dalam konteks pembelajaran di SDN 059 Cirangrang Bandung. Kepuasan para tenaga pengajar terhadap pelatihan ini menunjukkan bahwa penggunaan Tools Canva dalam media pembelajaran dapat meningkatkan efektivitas proses pembelajaran dan menciptakan pengalaman belajar yang lebih baik bagi siswa. Selain itu, temuan ini juga mendukung pentingnya pelatihan dan pengembangan profesional bagi tenaga pengajar dalam mengadopsi teknologi pembelajaran yang inovatif.