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All Journal Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Proceeding of the Electrical Engineering Computer Science and Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer)
Arifiansyah, Fitra
Institut Teknologi Bandung
Computer Science & IT Electrical & Electronics Engineering Engineering

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Reality of the internet and social media addiction in Indonesian students Nasy`an Taufiq Al Ghifari; Akhmadi Surawijaya; Fitra Arifiansyah; Agus Komarudin; Denny Hidayat Tri Nugroho; Dimitri Mahayana
Jurnal Informatika Vol 15, No 1 (2021): January 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v15i1.a18951

Abstract

The use of the Internet and social media today is inseparable from the life of modern society. This can lead to an addiction to the Internet and social media. This research aims to answer whether the phenomenon of Internet and social media addiction is a scientific reality or not in Indonesia, especially in Indonesian Students who are undergoing adaptation of the learning process from offline to online due to the Covid-19 pandemic situation. Data collection was conducted with a survey of 2002 respondents. Before the questionnaire was distributed, a validity test and reliability test with Alpha Cronbach's were conducted, and the results showed that all questions on the questionnaire were valid and reliable. Based on the survey results, 20.18% of respondents experienced mild addiction, 4.85% of respondents experienced moderate addiction, and 0.45% of respondents experienced severe addiction to Internets. While the survey results for social media addiction were 14.99% of respondents experienced mild addiction, 4.7% of respondents experienced moderate addiction, and 0.45% of respondents experienced severe addiction. Judging by the philosophy of science, Internet and Social Media Addiction are said to be science and not pseudoscience because it has fulfilled the characteristics of science that is logical, empirical, and can be falsified. There needs to be special attention from the Indonesians about the addiction to the Internet and social media so that this addiction can be anticipated and the inflicted symptoms can be minimized.
Automatic Grading System for Spreadsheet Formula Kurniandha Sukma Yunastrian; Saiful Akbar; Fitra Arifiansyah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2086

Abstract

Spreadsheet is one of the tools that can be used to learn data analysis. Data analysis in spreadsheet can be done using formula. Spreadsheet tools can also be used for exams. For the assessment, there is a problem when the number of answers that need to be checked is large, that is it takes a long time to check all the answers. For this reason, an automatic grading system (autograder) that can evaluate formula in spreadsheet is needed. The method used in developing the autograder system is matching the answer key formula with the student's answer formula. The autograder system assesses the answer by calculating the similarity of the student's answer formula with the answer key formula. This paper explains how to build an autograder system that can evaluate the formula. At the end, an autograder system has been built successfully. It has been tested with 43 testcases and all of them are passed.
DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS Bayu Samodra; Vebby Amelya Nora; Fitra Arifiansyah; Gusti Ayu Putri Saptawati Soekidjo; Muhamad Koyimatu
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6177

Abstract

The increasing complexity of programs in software development requires understanding and analysis of code structure, especially in Python, which dominates machine learning and data science applications. Manual static analysis is often time-consuming and prone to errors. Meanwhile, static analysis tools for Python, like PyCG and Code2graph, are still limited to generating call graphs without including dependency and control flow analysis. This research addresses these shortcomings by proposing the development of a web-based tool that integrates the generation of function call graphs, function dependency graphs, and control flow graphs using Abstract Syntax Tree (AST), Graphviz, and Streamlit. With an iterative SDLC methodology, this tool was developed gradually to visualize Python function code as a heterogeneous graph. Evaluation of 11 Python function codes showed a success rate of 95.45% in analyzing and visualizing Python function codes with various levels of complexity. The limitations of Graphviz present an opportunity for future research to focus on improving scalability and Python code analysis.
Simplifikasi Graf Pemanggilan Fungsi: Pendekatan Community Detection Untuk Mempermudah Pemahaman Struktur Kode Tioria Marlini Purba, Risa; Purba, Risa Tioria Marlini; Tonang, Ari Sandy Putra Ari; Karim, Abdulah; Soekidjo, Gusti Ayu Putri Saptawati; Muhamad, Koyimatu; Arifiansyah, Fitra
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Dalam pengembangan perangkat lunak skala besar, pemahaman terhadap struktur kode sangat penting untuk menganalisis interaksi antar-fungsi dalam kode sumber. Graf pemanggilan fungsi (function call graph) merupakan kakas yang efektif untuk memetakan hubungan antar-fungsi, yang membantu pengembang dalam menelusuri jalur eksekusi dan memahami pola struktur kode modular yang kompleks. Namun, pada kode sumber yang rumit, graf pemanggilan fungsi sering kali menjadi sangat besar dan sulit diinterpretasi karena banyaknya node dan edge yang terlibat. Untuk mengatasi masalah ini, teknik simplifikasi graf melalui community detection diterapkan sebagai solusi untuk mengelompokkan fungsi-fungsi yang saling terkait dalam cluster, sehingga menghasilkan visualisasi yang lebih terstruktur dan mudah dipahami. Penelitian ini bertujuan untuk mengembangkan kakas berbasis Python yang mampu menyederhanakan graf pemanggilan fungsi menggunakan algoritma Girvan-Newman. Kakas ini memanfaatkan pustaka networkx untuk membentuk graf dan menerapkan deteksi komunitas, ast untuk parsing kode, serta matplotlib dan streamlit untuk visualisasi dan interaksi pengguna. Hasil eksperimen pada 10 program dengan ukuran 10-85 baris kode menunjukkan bahwa metode community detection mampu mereduksi jumlah node dan edge dalam graf pemanggilan fungsi hingga 60%, dengan skor modularitas tertinggi 0.6605. Evaluasi dengan 25 pengembang perangkat lunak menunjukkan tingkat kepuasan 80% dalam hal kemudahan penggunaan dan peningkatan produktivitas analisis kode.   Abstract In large-scale software development, understanding the code structure is crucial for analyzing the interactions between functions in the source code. A function call graph is an effective tool for mapping the relationships between functions, assisting developers in tracing execution paths and understanding object-oriented complex code structures. However, in complex source code, the function call graph often becomes very large and complicated to interpret due to the many nodes and edges involved. To address this issue, graph simplification techniques, such as community detection, are applied as a solution to group related functions into clusters, thereby producing a more structured and easier-to-understand visualization. This study aims to develop a Python-based tool that simplifies function call graphs using the Girvan-Newman algorithm. The tool utilizes the networkx library to construct graphs and apply community detection, ast for code parsing, and matplotlib and streamlit for visualization and user interaction. The results of experiments on 10 programs, ranging in size from 10 to 85 LOC, showed that the community detection method was able to reduce the number of nodes and edges in the function invocation graph by up to 60%, achieving the highest modularity score of 0.6605. An evaluation of 25 software developers revealed an 80% satisfaction rate in terms of ease of use and increased productivity in code analysis.
Analyzing Software Evolution Dynamics using Execution Path-aware Graph Divergence Fitra Arifiansyah; Muhammad Zuhri Catur Candra; Gusti Ayu Putri Saptawati
Journal of ICT Research and Applications Vol. 20 No. 1 (2026)
Publisher : DRPM - ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2026.20.1.6

Abstract

Software comprehension is a fundamental activity in software maintenance, and its complexity grows as systems evolve across releases. Call graphs (CG) are widely used to support this process because they capture the calling relationships among functions. However, obtaining meaningful comparisons between different versions of a CG remains challenging. Network Portrait Divergence (NPD) provides a graph invariant and computationally efficient metric for assessing structural differences by analyzing global distributions of node distances and neighborhood patterns. Although it is effective, NPD does not include execution semantics, even though execution paths often convey the behavioral changes that matter to developers. This study introduces a refinement of NPD that replaces neighborhood-oriented features with features derived from execution paths, represented through distributions of path lengths. The modified metric is evaluated in a controlled scenario using synthetic data, designed to distinguish the effects of structural changes including new call and changes to control flow. The results show that the proposed NPD is more responsive to modifications that influence execution behavior. Scenarios that create new execution paths and restructure control flow result in substantially higher divergence. These findings suggest that including execution path information offers a more behavior-oriented view of software evolution and complements topology-based approaches.
Co-Authors Akbar, Saiful Akhmadi Surawijaya Bayu Samodra Denny Hidayat Tri Nugroho Dimitri Mahayana Gusti Ayu Putri Saptawati Karim, Abdulah Komarudin, Agus Koyimatu, Muhamad Kurniandha Sukma Yunastrian Muhammad Zuhri Catur Candra Nasy`an Taufiq Al Ghifari Purba, Risa Tioria Marlini Tioria Marlini Purba, Risa Tonang, Ari Sandy Putra Ari Vebby Amelya Nora Yunastrian, Kurniandha Sukma