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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO JURNAL MEDIA INFORMATIKA BUDIDARMA SINTECH (Science and Information Technology) Journal Abdimasku : Jurnal Pengabdian Masyarakat Journal of Intelligent Software Systems
Bagas Triaji
Universitas Teknologi Digital Indonesia, Yogyakarta
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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PROGRAMMER'S PERSPECTIVE IN YOGYAKARTA ABOUT OBJECT ORIENTED PROGRAMMING (OOP) IN SOFTWARE DEVELOPMENT USING CORRELATION ANALYSIS Bagas Triaji; Cucut Hariz Pratomo; Bambang Purnomosidi DP
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.632

Abstract

Pesatnya perkembangan teknologi menghasilkan era digitalisasi. Permintaan pengembangan perangkat lunak dan insinyur perangkat lunak di berbagai sektor industri, bisnis, dan pendidikan sangat tinggi. Yogyakarta adalah kota pendidikan, dimana banyak perguruan tinggi dan universitas berdiri. Namun, calon programmer sering memiliki pemahaman yang kurang memadai tentang paradigma OOP dari perspektif praktisi industri IT. Oleh karena itu, survei berikut melibatkan praktisi programmer profesional dilakukan untuk menganalisis bagaimana mereka melihat Object-Oriented Programming (OOP) ketika mengembangkan perangkat lunak dan bagaimana pengalaman mereka, dengan menggunakan analisis korelasi. Penelitian ini dilakukan untuk mengkaji aspek yang mempengaruhi preferensi programmer terhadap OOP. Hasil analisis korelasi menunjukkan bahwa programmer yang lebih berpengalaman akan lebih memilih paradigma OOP untuk menyelesaikan proyek meskipun mengalami beberapa hambatan dalam implementasi OOP, tetapi mereka tidak yakin bahwa OOP akan tetap digunakan sebagai paradigma yang mumpuni di masa depan.
Query Execution Performance Analysis of Column-Oriented Database in Dashboard Bagas Triaji; Widyastuti Andriyani; Totok Suprawoto; Muhammad Agung Nugroho; Rikie Kartadie
Journal of Intelligent Software Systems Vol 1, No 2 (2022): Desember
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.54 KB) | DOI: 10.26798/jiss.v1i2.768

Abstract

In making reports or dashboards from operational data, problems often occur in the query process with low speed in responding to an output, causing the server to experience overload. This condition often occurs in companies or higher education organizations in managing academic data. This condition can be improved by optimizing the database server by integrating relational databases with column-oriented databases to speed up query responses and save development costs. Based on the experiments that had been carried out, column-oriented has succeeded in optimizing with a significant difference in query execution time and the server does not crash.
Building a Knowledge Graph on Video Transcript Text Data Bagas Triaji; Widyastuti Andriyani; Bambang Purnomosidi DP; Faizal Makhrus
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (802.045 KB) | DOI: 10.26798/jiss.v1i1.585

Abstract

Youtube is a video platform which not only provides entertainment but also education in which knowledge can be dug based on video transcripts. The results of this knowledge can be formed as a knowledge graph to build a knowledge base that saves storage space. Moreover, it can be used for other purposes such as recommendation systems and search engines. Prosen built a knowledge graph using NLP to extract the text by identifying the subject-verb-object (SVO) and stored in the graph database. The construction of a knowledge graph on a Youtube video transcript was successfully carried out. However, there are still obstacles in the process of extracting text using NLP which is less optimal so it is possible that there is still a lot of knowledge that has failed to be obtained.
Analisis Perbandingan Teorema Bayes dan Case Based Reasoning Dalam Diagnosis Penyakit Myasthenia Gravis Bagas Triaji; Azanuddin Azanuddin; Ibnu Rusydi; Ita Mariami; Asyahri Hadi Nasyuha
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6436

Abstract

The medical industry faces several obstacles due to illness. Treatment of any condition, including myasthenia gravis, relies heavily on an accurate and precise diagnosis. Myasthenia gravis is an autoimmune disease that affects the neuromuscular junction and is characterized by sudden muscle weakness and fatigue due to the loss of acetylcholine receptors (AChRs) at the neuromuscular junction. Successful treatment planning and providing a good prognosis to the patient is highly dependent on accurate and rapid diagnosis. To diagnose Myasthenia Gravis, this study compares and contrasts Case Anthology with Bayes' Theorem. The neuromuscular condition called myasthenia gravis is characterized by a variable decrease in muscle strength. Correct and timely diagnosis is essential to start a successful course of therapy. Data from patients with Myasthenia Gravis symptoms and clinical indicators were collected for this study. To obtain an accurate diagnosis, the dataset was analyzed using Bayes' Theorem and Case Anthology techniques. Based on the current symptoms, Bayes' Theorem is used to estimate the probability of the condition, while Anthology of Cases is used to diagnose the patient. Based on symptoms, Bayes' Theorem predicts disease outcome probabilistically, but requires reliable initial assumptions and is susceptible to prior probabilities. On the other hand, Case Anthologies use information obtained from previous situations, but may be limited by the availability of relevant data and may experience difficulties in dealing with unique or unusual situations. This study helps us understand the benefits and limitations of each technique in diagnosing Myasthenia Gravis. A more accurate and effective diagnosis can be made by combining the two methods. These studies can serve as a foundation for creating more sophisticated diagnostic techniques integrated into clinical practice. The following is a summary of the percentages obtained using the Bayes Theorem and Case Anthology methods: For the diagnosis of Myasthenia Gravis, the Bayes Theorem technique produces a percentage value of 55% while the Case Anthology method only produces a percentage value of 26%. Therefore, the Bayes Theorem technique is better and more reliable in diagnosing Myasthenia Gravis.
Clustering Analysis of Poverty Levels in North Sumatra Province Using the Application of Data Mining with the K-Means Algorithm Widyastuti Andriyani; Asyahri Hadi Nasyuha; Yohanni Syahra; Bagas Triaji
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6867

Abstract

North Sumatra, as one of the largest provinces in Indonesia, has serious challenges related to poverty that require serious attention North Sumatra, as one of the largest provinces in Indonesia, has serious challenges related to poverty that require serious attention and in-depth analysis. Thus, research on poverty levels in this province becomes very relevant and urgent. Therefore, a more in-depth analysis is needed regarding poverty levels in various regions within this province using data mining methods. The data mining approach is a way to gain understanding from large amounts of data. In the context of the problem of poverty levels, data mining has the potential to help reveal patterns that may be hidden in economic and social data. One algorithm that is often applied in clustering analysis is the K-Means algorithm. The K-Means algorithm is a clustering method that is widely used in data analysis and allows grouping data based on similar characteristics, so that it can be used to classify areas with similar levels of poverty. The results of this research show that data mining with the application of the K-Means algorithm can help produce more effective decisions in analyzing clustering of poverty levels in North Sumatra Province involving the use of data over a ten-year period, namely from 2013 to 2022, which records the number of poor people based on District and city. 3 groups were produced, namely 3 levels of poverty, including relatively stable, very vulnerable and vulnerable. Data from 33 districts or cities in North Sumatra resulted in a poverty level clustering of 1 city that was very vulnerable, 4 cities that were vulnerable and 27 cities that were relatively stable.
Peningkatan Kompetensi Manajemen Basis Data Pada SMK Muhammadiyah 1 Yogyakarta Triaji, Bagas; Subagyo, Aloysius Agus; Laksana, Herdian Aji
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 3 (2024): SEPTEMBER 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i3.2345

Abstract

Pendidikan kejuruan di Indonesia khususnya sekolah menengah kejuruan (SMK) mempunyai peranan penting dalam mempersiapkan generasi muda memasuki dunia kerja. Salah satu jurusan yang sedang berkembang adalah Rekayasa Perangkat Lunak (RPL). Meskipun menekankan pada pemrograman web, SMK Muhammadiyah 1 Yogyakarta masih memerlukan peningkatan keterampilan manajemen basis data. Tim pengabdian melakukan observasi dan mengidentifikasi kebutuhan peningkatan pengetahuan tersebut. Metode yang digunakan antara lain pembuatan modul ajar sesuai  SKKNI nomor 268 tahun 2020 dan pelatihan bagi siswa didampingi oleh guru. Modul ini mencakup topik-topik penting seperti monitoring, kualitas data, dan keamanan database. Pelatihan dilakukan dengan pre-test dan post-test untuk mengukur keefektifan dan ditemukan bahwa pemahaman siswa meningkat secara signifikan. Hasil evaluasi dengan menggunakan paired t-test menunjukkan adanya perbedaan yang signifikan antara hasil pre-test dan post-test, menunjukkan keberhasilan pelatihan. Kegiatan ini berhasil meningkatkan keterampilan manajemen basis data bagi siswa, meskipun masih membutuhkan pendampingan pada beberapa bagian. Kegiatan ini dapat dikembangkan lebih lanjut seperti simulasi uji kompetensi atau sertifikasi profesi oleh Lembaga Sertifikasi Profesi (LSP). Hasil ini penting untuk memastikan lulusan sekolah kejuruan siap bersaing di industri teknologi.
Development of a Higher Education Data Warehouse Using the Data Vault 2.0 Method Triaji, Bagas; Subagyo, Aloysius Agus; Rifai, Muhammad Arif
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14215

Abstract

In this research, we investigate the potential of Data Vault 2.0 modeling as a solution to address the complexity of data management in higher education, which is often spread across multiple information systems. The main objective of this research is to confirm the effectiveness of Data Vault 2.0 in building a data warehouse, as well as facilitating the integration of data from different sources, such as the Academic Information System, Personnel Information System, and New Student Admission System. The research method used includes data collection and processing through the staging stage before being stored in the Data Vault structure consisting of hubs, links, and satellites. The research findings show that Data Vault 2.0 not only provides flexibility in development but also allows two developers to work in parallel without interfering with each other, speeding up the data integration process. In addition, the design evaluation results show that Data Vault 2.0 is able to accommodate dynamic changes in requirements, while facilitating the creation of dashboards for data visualization and analysis. The conclusion of this research emphasizes that although Data Vault 2.0 is more complicated than models such as star schema, it provides advantages in flexibility and better data integration. Further research is needed to address the challenges of data integration and deepen the understanding of the implementation of this model in various contexts.
Sistem Pakar Mendiagnosa Penyakit Cutaneous Larva Migrans Menggunakan Metode Dempster Shafer Nasyuha, Asyahri Hadi; Triaji, Bagas; Leswanto, Tomi
Jurnal Ilmiah FIFO Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2024.v16i1.008

Abstract

Cutaneous Larva Migrans merupakan suatu penyakit yang di sebabkan oleh parasit yang masuk ke dalam kulit dan berkembang biak sehingga menimbulkan infeksi pada kulit. Ada beberapa jenis parasit yang menyebabkan penyakit cutaneous larva migrans yaitu, Uncinaria Stenocephala Bunostum Phelebotonum Ancylostoma Braziliense dan Ancylostoma Caninum. Penyakit cutaneous larva migrans tidak terlalu familiar dikalangan masyarakat umum, oleh sebab itu kurangnya perhatian terhadap gejala awal penyakit ini. Akibatnya masyarakat baru menyadari terkena cutaneous larva migrans saat berada pada tahap lanjut. Maka dari itu dibuatlah sistem kecerdasan berbasis desktop yang menganut bidang ilmu sistem pakar yang menggunakan metode dempster shafer.Dempster shafer adalah suatu teori matematika untuk pembuktian berdasarkan fungsi kepercayaan dan pemikiran yang masuk akal, yang digunakan untuk mengkombinasikan potongan informasi yang terpisah untuk mengkalkulasikan kemungkinan dari suatu peristiwa. Sistem pakar ini dapat dipergunakan sebagai pedoman bagi dokter atau para ahli untuk mendiagnosa penyakit cutaneous larva migrans. Sistem pakar ini bisa dimanfaaatkan dalam melakukan pencarian dan penelusuran pengetahuan bagi yang ingin mendapatkan informasi terkait solusi penyakit cutaneous larva migrans.
Co-Authors Andriyani, Widyastuti Asyahri Hadi Nasyuha Azanuddin Azanuddin Bambang Purnomosidi Dwi Putranto Cucut Hariz Pratomo Faizal Makhrus Ibnu Rusydi Ita Mariami Laksana, Herdian Aji Leswanto, Tomi Nugroho, Muhammad Agung Rifai, Muhammad Arif Rikie Kartadie Subagyo, Aloysius Agus Totok Suprawoto Widyastuti Andriyani Yohanni Syahra