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Computational Thinking: The Essential Skill for being Successful in Knowledge Science Research Bachtiar, Adam Mukharil
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol 4 No 1 (2023): INJIISCOM: VOLUME 4, ISSUE 1, JUNE 2023
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v4i1.9558

Abstract

The VUCA world concept was established in 2016 as the new challenge universe in the 21st century. Humans live in Society 5.0 and the VUCA world simultaneously. The digital word has been a noisy word since then. There are a lot of requisite skills to be a survival kit for this kind of era. The VUCA world's affection is spreading in the way of thinking and creating innovation, especially in the research domain. As a newcomer, Knowledge Science should state the requisite skills for its researchers to conduct their research successfully. Many researchers offered computational thinking as a candidate for an essential skill to satisfy the effect of the VUCA world. This study was focused on conducting a descriptive analysis method based on several literature reviews for mapping how computational thinking can serve as a best practice for Knowledge Science research. This study successfully revealed the connection between Computational Thinking.
Pandawa App: Student Guide Application after the Covid-19 Pandemic Rafdhi, Agis Abhi; Bachtiar, Adam Mukharil; Hayati, Euis Neni; Mega, Raiswati Untsa
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol 4 No 2 (2023): INJIISCOM: VOLUME 4, ISSUE 2, DECEMBER 2023
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v4i2.13895

Abstract

The purpose of this research is to design a mobile-based application that functions as a pre-lecture socialization platform so that the post-Covid-19 transition period can be maintained and carried out well. The research method used in this research is descriptive analysis with a qualitative approach. We used an object-oriented approach with the System Development Life Cycle Prototyping in the application development process. The results show that the Pandawa application development can provide lecture guidance properly using a digital platform that can be accessed via smartphone. The main concept of this application is to contain procedures or guidelines for implementing face-to-face lectures during the transition period from the Covid-19 pandemic in the New Normal era. In addition, this application also has a feature integrated with the local government for reporting if there are residents who test positive for Covid-19. Therefore, it can be followed up directly and quickly. In the end, this application is present as an information medium to adapt new habits in the world of education, especially at the tertiary level.
Classification of brain tumor based on shape and texture features and machine learning Rizki, M. Alfi; Faisal, Mohammad Reza; Farmadi, Andi; Saragih, Triando Hamonangan; Nugrahadi, Dodon Turianto; Bachtiar, Adam Mukharil; Keswani, Ryan Rhiveldi
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 6 No. 4 (2024): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/27236g49

Abstract

Information from brain tumour visualisation using MRI can be used for brain tumour classification. The information can be extracted using different feature extraction techniques. This study compares shape-based feature extraction such as Zernike Moment (ZM), and Pyramid Histogram of Oriented Gradients (PHOG) with texture-based feature extraction such as Local Binary Patterns (LBP), Gray Level Co-occurrence Matrix (GLCM), Histogram of Oriented Gradients (HOG) in brain tumour classification. This research aims to find out which feature extraction is better for handling brain tumour images through the accuracy and f1-score produced. This research proposes to combine each feature based on its approach, i.e. ZM+PHOG for shape-based feature extraction and LBP+GLCM+HOG for texture-based feature extraction with default parameters from the library and modified parameters configured based on previous research. The dataset used comes from Kaggle and has three classes: meningioma, glioma, and pituitary. The machine learning classification models used are Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB) and K-Nearest Neighbours (KNN) with default parameters from the library. The models were evaluated using 10-fold stratified cross-validation. This research resulted in an accuracy and f1-score of 84% for texture-based feature extraction with modified parameters in RF classification. In comparison, shape-based feature extraction resulted in accuracy and f1-score of 70% and 68% with modified parameters in RF classification. From the results, it can be concluded that texture-based feature extraction is better in handling brain tumour images compared to shape-based feature extraction. This study suggests that focusing on texture details in feature extraction can significantly improve classification performance in medical imaging such as brain tumours
Pemodelan data warehouse pada jurusan teknik informatika unikom Dharmayanti, Dian; Bachtiar, Adam Mukharil; Heryandi, Andri
Majalah Ilmiah UNIKOM Vol. 12 No. 2 (2014): Majalah Ilmiah Unikom
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1160.85 KB)

Abstract

Informasi sangat dibutuhkan tidak hanya sebagai hasil rekapitulasi saja akan tetapi suatu informasi dapat digunakan untuk membantu dalam proses pengambilan keputusan bagi pihak manajerial maupun eksekutif. Program Studi Teknik Informatika ketika akan melaksanakan akreditasi menghadapi kesulitan dalam menghimpun informasi dikarena penyajian informasi didapat dari berbagai basis data dan file eksternal. Basis data dan file eksternal yang digunakan belum mempunyai struktur yang sama sehingga diperlukan lagi usaha untuk menyeragamkan data. Data warehouse adalah sebuah koleksi data yang berorientasi subjek, diintegrasikan, time-variant, dan non volatile untuk mendukung proses pembuatan manajemen pengambilan keputusan. Hasil dari data warehouse merupakan informasi hasil intisari dari berbagai macam basis data.Hasil penelitian menghasilkan fakta bahwa atribut data pada diagram relasi OLTP masih belum bisa memenuhi kebutuhan data yang ada pada diagram relasi data warehouse dengan membandingkan antara diagram relasi OLTP dengan diagram relasi data warehouse. Terdapat kekurangan data pada OLTP Program Studi Teknik Informatika UNIKOM yang mengakibatkan data pada data warehouse tidak bisa diisi. Dari hasil penelitian ini diharapkan nantinya akan ada integrasi data pada seluruh basis data yang berhubungan dengan data warehouse agar model data warehouse yang telah dibentuk dapat diimplementasi pada penelitian berikutnya
ANALISA PEMANFAATAN MULTIPROTOCOL LABEL SWITCHING PADA ROUTING PROTOCOL OPEN SHORTEST PATH FIRST Friyanto, Angga; Bachtiar, Adam Mukharil; Baihaqi, Abdu Sofyan
Majalah Ilmiah UNIKOM Vol. 18 No. 2 (2020): Majalah Ilmiah Unikom
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/miu.v18i2.3937

Abstract

Digital transformation in various sectors has increased the need for network infrastructure to sustain high traffic. The availability of network resources is an important component in business processes in the digital era. Apart from adding infrastructure, a solution that can be done to meet these needs is optimization. OSPF (Open Shortest Path First) as a mechanism for determining the dynamic data transmission path has good features and performance by calculating automatically using an algorithm that calculates the bandwidth width. In data transmission, MPLS (Multiprotocol Label Switching) is a method of data transmission using labels in the process of forwarding data packets. This study analyzes the optimization of MPLS utilization as a data packet delivery mechanism for OSPF routing protocol communication. The analysis was carried out by comparing the data from the observation of the OSPF network system using MPLS and the OSPF network system without MPLS. From the analysis conducted by comparing the delay and packet loss, it is concluded that the network system using MPLS is more efficient and faster in data communication. Key Words : MPLS, OSPF, Routing, Traffic Engineering, Transmisi Data