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All Journal Jurnal Nasional Teknologi Komputer The Journal of Information Technology, Computer Science, and Electrical Engineering
M. Azhari Rizko
Universitas Pembangunan Panca Budi
Computer Science & IT

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Implementation of the Insertion Sort Algorithm to Sort Positive Integers in Ascending Order Using Flowgorithm Zulham Sitorus; Dhimas Prayogi; M. Azhari Rizko; Ade Guna Suteja; Muhammad Raihan Harahap
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 3 (2024): October 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i3.120

Abstract

The advancement of information technology has had a significant impact on various fields, including education. One area that has been greatly influenced is the teaching of programming algorithms, where technology helps simplify the understanding of fundamental concepts, such as data sorting algorithms. This study focuses on the implementation of the Insertion Sort algorithm using the Flowgorithm application to facilitate the understanding of the data sorting process. Flowgorithm is a software tool that enables the creation of flowcharts to visually represent the steps of an algorithm, which can then be translated into programming languages. The Insertion Sort algorithm was chosen due to its simplicity and its effectiveness in sorting small datasets. This study covers the design and implementation of the algorithm using Flowgorithm, testing with positive integer data, and verifying the correctness of the sorting results through manual calculations. The test results show that the algorithm works correctly, producing the proper sequence from unsorted data. Additionally, the pseudocode generated from the Flowgorithm design can be translated into a programming language like Python. This research contributes to enhancing the understanding of algorithmic concepts, particularly sorting algorithms, by using Flowgorithm as an effective learning tool.
ANALISIS PREDIKSI TINGKAT KEHADIRAN SISWA MENGGUNAKAN ALGORITMA NAIVE BAYES DAN LOGISTIC REGRESSION M. Azhari Rizko; Muhammad Iqbal; Muhammad Syahputra Novelan
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Student absenteeism, particularly unexcused absence, remains a critical challenge in basic education management that negatively impacts academic continuity and increases dropout risks. This study presents a predictive analysis model for student absenteeism levels using two machine learning algorithms: Naïve Bayes and Logistic Regression, applied to 1,533 active student records from SMP Negeri 5 Stabat across the 2021-2025 academic years. Predictor features comprise demographic factors, accessibility metrics, and parent socioeconomic indicators. Automated data processing was executed via a Python API backend connected directly to a MySQL database across five computational stages. Model evaluation was conducted under three train-test split scenarios (70:30, 80:20, and 90:10). Empirical results demonstrate that Logistic Regression consistently outperformed Naïve Bayes across all testing configurations. The highest classification performance was achieved by Logistic Regression under the 90:10 split ratio with an accuracy of 84.42%, while achieving 84.36% accuracy, 0.8421 precision, 0.8436 recall, and an F1-score of 0.8422 under the standard 80:20 split ratio. Conversely, Naïve Bayes yielded inferior generalization due to feature multicollinearity, recording its lowest performance at 62.34% under the 90:10 ratio and 64.17% under the 80:20 ratio. Sigmoid logit transformation in Logistic Regression proved highly robust in handling interdependent socioeconomic and demographic attributes. These findings confirm the efficacy of LR-based Decision Support Systems for early warning intervention in educational institutions.
Co-Authors Ade Guna Suteja Dhimas Prayogi Muhammad Iqbal Muhammad Raihan Harahap Muhammad Syahputra Novelan Sitorus, Zulham