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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Majalah Ilmiah Matematika Komputer Syntax Idea Eduvest - Journal of Universal Studies
Maukar Maukar
Jurusan Sistem Informasi Fakultas Ilmu Komputer
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Engineering Health Professions Mathematics Neuroscience Social Sciences

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PEMBENTUKAN AUTOMATA HINGGA DETERMINISTIK MENGGUNAKAN POHON SINTAKS Maukar, Maukar
Majalah Ilmiah Matematika Komputer 2006: MAJALAH MATEMATIKA KOMPUTER EDISI APRIL
Publisher : Majalah Ilmiah Matematika Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (145.433 KB)

Abstract

Dalam proses kompilasi untuk bahasa sumber, tahap analisis leksikal di antaranya berperan sebagai pengenal suatu token yang ada dalam bahasa sumber tersebut. Automata Hingga Deterministik merupakan salah satu alat yang cukup efektif dijadikan sebagai pengenal. Banyak teknik yang dapat digunakan untuk membentuk Automata Hingga Deterministik, antara lain menggunakan fungsi nullabel, firstpos, lastpos, dan, followpos. Tulisan ini mencoba untuk mendeskripsikan proses pembentukan Automata Hingga Deterministik tersebut secara lugas dengan metodologi yang cukup efektif, artinya proses ini akan menghasilkan keluaran Automata Hingga Deterministik dengan jumlah state minimal.
SISTEM INFORMASI MANAJEMEN EKSPLORASI DAN PRODUKSI PERMINYAKAN JOINT OPERATING BODY PERTAMINA-PETROCHINA (JOB-PPEJ) Noridhah, Noridhah; Maukar, Maukar
Majalah Ilmiah Matematika Komputer 2006: MAJALAH MATEMATIKA KOMPUTER EDISI APRIL
Publisher : Majalah Ilmiah Matematika Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1900.796 KB)

Abstract

Di Indonesia khususnya diwilayah Tuban, Jawa Timur mempunyai salah satu daerah potensi penghasilminyak. Karena di Tuban terdapat blok-blok yang telah disurvei sebelumnya mempunyai kapasitassumber daya alam yang baik khususnya minyak dan gas bumi. JOB Pertamina - Petrochina East Java(JOB-PPEJ) merupakan salah satu perusahaan jointventure yang bergerak dalam bidang industriperminyakan di Indonesia yang telah melakukan pengeksplorasian diwilayah Tuban ini. Kecepatan,ketepatan dan efektifitas sangat mutlak diperlukan untuk dapat meningkatkan kinerja perusahaantersebut. Mengingat informasi yang digunakan cenderung bersifat hardcopy (paper). Denganmenggunakan teknologi informasi yang berbasis web-base dalam pengoJahan informasi JOB-PPEJ,dalam penulisan skripsi ini penulis mencoba untuk membuat suatu sistem manajemen dalam kemudahanakses informasi di JOB Pertamina - Petrochina East Java (JOB-PPEJ).
Persiapan Deteksi Plat dengan Modifikasi Metode Viola Jones KNN Purnomo, Jati; Maukar, Maukar
Syntax Idea Vol 3 No 4 (2021): Syntax Idea
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-idea.v3i4.1112

Abstract

Currently the system of automatic number plate recognition (ALPR, automatic license plate recognition) has started from anywhere in the country. Letter Plate there is a picture of the license plate number of the vehicle and then an image of the result of the algorithm for shopping alpha numerical images into text format. Although it may seem easy for humans, it turns out that plate detection is very complicated with computers while there are some location-related problems with, point of view, light, and occlusion. The purpose of this study is to know the results of the Can Plate Method Viola Jones KNN. This research methods the Viola Jones method (HaarCasscade) to build a plate detection system using the Python 3.0 programming language as well as the Open CV library. The information that lies in plate detection (from the way of insertion to completion and its supporting language programs) is minimal research in this field. At this stage, research can be done directly on the vehicle license plate object.
Recommendation system for football player recruitment using k-nearest neighbor Maukar, Maukar; Rodiah, Rodiah
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3847-3857

Abstract

In modern professional football, achieving a competitive edge depends not only on on-field performance but also on effective off-field strategies, particularly in player recruitment. This study proposes a machine learning-based recommendation system to support talent identification and optimal player placement using statistical performance data. The model analyzes a wide range of features, including shots, expected goals, expected assists, pass types, offensive contributions, and defensive actions across field zones. The dataset undergoes preprocessing steps such as normalization (per 90 minutes) and dimensionality reduction. A key innovation of this research is the use of principal component analysis (PCA) to reduce feature dimensionality, minimizing redundancy while retaining essential information, which improves model efficiency and scalability. The refined data is then processed using the k-nearest neighbors (KNN) algorithm with cosine similarity, allowing the system to identify players with similar performance profiles based on directional similarity in a high-dimensional space. This combination enhances recommendation accuracy by focusing on performance structure rather than raw values. The resulting system provides actionable insights into player suitability and potential, offering clubs a data-driven tool for informed scouting and recruitment decisions. The approach demonstrates the effectiveness of combining PCA and KNN in optimizing football player recommendation systems.
Phylogenetic Tree Formation Analysis of SARS-CoV-2 ORF3a Protein using Neighbor-Joining Mahfudhah, Nariswari; Rodiah, Rodiah; Maukar, Maukar
Eduvest - Journal of Universal Studies Vol. 3 No. 11 (2023): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v3i11.927

Abstract

SARS-CoV-2 or coronavirus disease is the cause of the world pandemic in 2019 (Adnan et al., 2020). In its development, SARS-CoV-2 has occurred mutations, resulting in the emergence of several new variants (Hartono and Yusuf, 2021). One of the efforts made to determine the occurrence of mutations is to build and analyze phylogenetic tree (van Dorp et al., 2020). ORF3a protein is one of the constituent genes of the SARS-CoV-2 virus (Ahmad et al., 2022). The dataset was obtained through a database that has been publicly published on the NCBI website (https://www.ncbi.nlm.nih.gov/). The data used are homo sapiens from China (Wu et al., 2020), USA (Daniel et al., 2020), France (Shannon et al., 2020), Indonesia (Rantam et al., 2021), Australia (Caly et al., 2020), and Mexico (Mendoza-Salazar et al., 2022). The phylogenetic tree was constructed using the Neighbor-Joining method. The result is ORF3a from Mexico and France are closely related. ORF3a from Mexico and France have the same level of distance and similarity with ORF3a from China and ORF3a from Indonesia have proximity to ORF3a USA.
Co-Authors Mahfudhah, Nariswari Noridhah Noridhah Purnomo, Jati Rodiah Rodiah