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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pilar Nusa Mandiri SINTECH (Science and Information Technology) Journal Jurnal Teknik Informatika (JUTIF) Bulletin of Social Informatics Theory and Application
Junianto, Haris
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Computer Science & IT Education Social Sciences

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Evaluasi Aplikasi Raileo Melalui Analisis Sentimen Ulasan Playstore Dengan Metode Naive Bayes Junianto, Haris; Arsi, Primandani; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
SINTECH (Science and Information Technology) Journal Vol. 7 No. 1 (2024): SINTECH Journal Edition April 2024
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v7i1.1505

Abstract

Abstrak The Raileo application is a staffing platform owned by PT. KAI, functions as a personnel data management system. Effective application development requires data as a basis, and one source of data that can be utilized is user reviews. User reviews provide valuable information regarding application performance, user needs, and security aspects. However, challenges arise in managing review data which often contains sarcasm, creating ambiguous meaning and lowering accuracy levels. This research proposes a solution by applying sentiment analysis using Naive Bayes logarithms to 1047 Raileo review data. This method produces an accuracy rate of 94%, with positive and negative sentiment classification. The research results show the words that appear most frequently in Raileo reviews, such as "eror", "sulit", "titik presensi", "titik absen", "titik lokasi", "bug", "lemot," "gagal", "mantap", "bagus", "oke", "mudah", "mempermudah", "mantul", "lengkap","keren","ok", "inovatif", "inovasi", "semoga", "sukses", dan "membantu". These words can be used as a key to analyze all the sentiments contained in the review. In addition, this research identifies "presence point" as the highest negative sentiment word that needs attention in further development. From this sentiment analysis research, the Raileo application produces the highest sentiment value, namely positive sentiment
An efficient and interactive android-based neighborhood management Junianto, Haris; Saputra , Dhanar Intan Surya; Saputro, Rujianto Eko
Bulletin of Social Informatics Theory and Application Vol. 8 No. 2 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i2.681

Abstract

This research aims to design and develop a prototype Android-based Neighborhood Association management information system application using the Agile approach to assist Neighborhood Association administrators in real-time administrative processes and information dissemination. The Agile approach was selected to enhance flexibility and responsiveness in application development, enabling adjustments to potential user needs and changes that may occur during the development process. The application is expected to improve service quality and governance transparency at the Neighborhood Association level while facilitating residents' access to information and interaction with Neighborhood administrators. The application development process employs the Agile approach, involving the development team in iterative cycles to meet user requirements. Research results demonstrate the achievement of research objectives, with the application capable of managing resident data, Neighborhood Association finances, event scheduling, and Neighborhood Association news. The Agile approach used in the application's development provides the flexibility needed to adapt to changing user requirements, offering a solution to the challenges faced by Neighborhood Association administrators in performing their duties. This aligns with Agile principles, emphasizing user collaboration and responsiveness to changes.
Eksplorasi Sentimen Publik terhadap Film "˜Dirty Vote"™ melalui Metode Naïve Bayes dan Logistic Regression Junianto, Haris; Saputro, Rujianto Eko; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 3 (2024): Volume 10 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i3.78520

Abstract

Tahun 2024 merupakan tahun politik bagi masyarakat Indonesia, di mana mereka menggunakan hak pilih untuk menentukan pemimpin pemerintahan selama lima tahun ke depan. Dalam konteks ini, pendidikan politik menjadi sangat penting, terutama bagi warga yang kurang memahami seluk-beluk politik dan proses pemilihan umum. Menyadari pentingnya pemahaman tersebut, sekelompok akademisi menciptakan film berjudul "Dirty Vote" dengan tujuan meningkatkan kesadaran masyarakat mengenai proses pemilu serta meminimalisir potensi pelanggaran.Penelitian ini bertujuan untuk mengevaluasi opini publik terkait film "Dirty Vote" dengan menggunakan dua model klasifikasi, yaitu Naive Bayes dan Logistic Regression. Penelitian ini melibatkan beberapa tahap, mulai dari pengumpulan data melalui scraping komentar dari platform YouTube, preprocessing data, analisis eksploratif (Exploratory Data Analysis), hingga pengujian performa model menggunakan teknik K-fold Cross Validation, serta visualisasi data menggunakan Word Cloud. Dalam penelitian ini, sebanyak 8888 data komentar dianalisis menggunakan teknik pemrosesan bahasa alami untuk mengukur sentimen publik terhadap film tersebut. Hasil analisis menunjukkan bahwa algoritma Naive Bayes mengidentifikasi 91,30% sentimen positif dan 8,70% sentimen negatif, sedangkan algoritma Logistic Regression memberikan hasil yang lebih tinggi, dengan sentimen positif sebesar 95,65% dan negatif sebesar 4,35%. Dari segi performa, Logistic Regression terbukti lebih unggul dengan akurasi mencapai 95,5%, sedangkan Naive Bayes memiliki akurasi sebesar 91,1%. Pengujian performa dilakukan melalui satu kali pengujian penuh serta delapan kali pengujian dalam berbagai kondisi data, dengan evaluasi kinerja menggunakan ROC dan AUC. Hasil penelitian ini menunjukkan bahwa kedua algoritma memberikan evaluasi positif terhadap film "Dirty Vote", dengan Logistic Regression memberikan hasil yang lebih akurat.
COMPARISON OF LOGISTIC REGRESSION AND RANDOM FOREST IN SENTIMENT ANALYSIS OF DISDUKCAPIL APPLICATION REVIEWS Junianto, Haris; Saputro, Rujianto Eko; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.1802

Abstract

Civil registration administration institutions such as Disdukcapil have an important role in carrying out government functions, in supporting the smooth running of administrative services the Government presents the Disdukcapil Mobile Application platform which aims to provide efficient and fast services to the community regarding various population administration needs. Sentiment analysis of user reviews on the Play Store for the Disdukcapil application is needed to understand user perceptions and needs, as well as to improve service quality and application development. In this study, researchers conducted sentiment analysis using 2 algorithms, namely: Logistic Regression and Random Forest, which after comparing by testing the two algorithms with test data of 18810 user review data from PlayStore, obtained the performance results of each algorithm as follows: 90% accuracy, 91% precision, 89% recall, and f1 90% for the performance results of the Logistic Regression algorithm, while for the performance results of the Random Forest algorithm accuracy 89%, precision 92%, recall 86% and f1-score 89%. From these results the Logical Regression algorithm has better performance than the Random Forest algorithm.
PASSWORD STRENGTH STUDY USING THE ZXCVBN ALGORITHM AND BRUTE-FORCE TIME ESTIMATION TO STRENGTHEN CYBERSECURITY Saputra, Whisnu Yudha; Sugiarti, Sugiarti; Junianto, Haris; Suhartono, Didit
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6119

Abstract

This research analyzes password strength based on its length and complexity using brute force attack simulations. The study begins with collecting password data from various sources to ensure sufficient variation in complexity levels. Next, the passwords are evaluated using the Zxcvbn algorithm, which provides a strength score as well as information about the time required to crack them. The same passwords are also evaluated using Brute-force Time Estimation to calculate the estimated time required to crack the password. After both algorithms have been evaluated, the results are analyzed to find the correlation between the Zxcvbn score and the estimated brute force time. The results of the data analysis are then visualized in the form of graphs or diagrams to facilitate understanding and assessment of password security. This simulation estimates the time required to guess a password, depending on the level of password complexity. Although the simulation results show that long and complex passwords are more secure, the actual strength of the password is highly dependent on the tools used by the attacker. In addition, digital security is not only limited to passwords, but also depends on various loopholes that can be exploited, such as personal data leaks or software vulnerabilities. Therefore, a comprehensive security approach is essential to protect users from potential cyberattacks. This study aims to provide in-depth insights into the strength and vulnerability of passwords and the effectiveness of algorithms in assessing password security.
Co-Authors Arsi, Primandani Dhanar Intan Surya Saputra Didit Suhartono Kusuma, Bagus Adhi Rujianto Eko Saputro Saputra , Dhanar Intan Surya Saputra, Whisnu Yudha Sugiarti Sugiarti