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All Journal Pro Bisnis Telematika Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal CoreIT JITK (Jurnal Ilmu Pengetahuan dan Komputer) Building of Informatics, Technology and Science Journal of Information Systems and Informatics Journal of Computer Science and Engineering (JCSE) Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia

Azhari Shouni Barkah

Universitas AMIKOM Purwokerto

Author-ID : 2855843

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering

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EVALUASI PENERAPAN SISTEM INFORMASI DAN TEKNOLOGI INFORMASI MENGGUNAKAN COBIT FRAMEWORK DI STMIK AMIKOM PURWOKERTO Azhari Shouni Barkah; Melia Dianingrum
Pro Bisnis Vol 8, No 1: Februari (2015)
Publisher : Universitas Amikom Purwokerto

Implementasi teknologi informasi untuk mendukung STMIK AMIKOM Purwokerto dalam mencapai tujuan sudah erupakan suatu kebutuhan yang sangat penting. Evaluasi terhadap implementasi teknologi informasi dengan menggunakan Model COBIT Framework sangat berguna baik bagi pengguna, pengembang teknologi informasi maupun para pengelola. Evaluasi terhadap proses teknologi informasi perlu dilakukan agar manajemen STMIK AMIKOM Purwokerto dapat melakukan perbaikan-perbaikan. Tujuan penelitian ini adalah sejauh mana STMIK AMIKOM Purwokerto telah menerapkan tata kelola sistem informasi dan teknologi informasi. Tujuan lain dari penelitian ini yaitu bagaimana tingkat kematangan penerapan tata kelola sistem informasi dan teknologi informasi serta rekomendasi yang cocok untuk meningkatkan tata kelola sistem informasi dan teknologi informasi di STMIK AMIKOM Purwokerto. Hasil penelitian ini menunjukkan skor tingkat kematangan penerapan tata kelola SI/TI di STMIK AMIKOM Purwokerto yang dipoleh yaitu 3 dan berada pada level Defined Proccess.

SISTEM INFORMASI PENJUALAN ONLINE PAKAIAN JADI DI CV. KLINIK REBEL AJIBARANG Azhari Shouni Barkah; Anggun Purnomo
Pro Bisnis Vol 7, No 1: Februari (2014)
Publisher : Universitas Amikom Purwokerto

CV.Klinik Rebel Ajibarang merupakan sebuah toko berlatar belakang penjualan dalam bentuk pakaian jadi dan accecories. Namun CV.Klinik Rebel Ajibarang masih menggunakan sistem manual dalam melakukan pencatatan data transaksi penjualan. Tujuan penelitian ini adalah Merancang dan membangun Sistem Informasi Online Penjualan Pakaian Jadi Di CV.Klinik Rebel Ajibarang yang dapat membantu dalam proses penjualannya. Metode pengumpulan data yang dilakukan adalah wawancara, observasi, studi kepustakaan, Sedangkan metode pengembangan sistem yang digunakan adalah SDLC (System Development Live Cylcle) Waterfall dengan tahapan (1) analisis sistem; (2) desain sistem; (3) implementasi sistem dan (4)operasi dan pemeliharaan. Hasil dari penelitian ini adalah berupa website sistem informasi online penjualan pakaian jadi di CV.Klinik Rebel Ajibarang.Kata Kunci: Website, Sistem Informasi, Penjualan, SDLC waterfall.

NIST SP 800-44v2: PEDOMAN PANDUAN SISTEM KEAMANAN PUBLIK WEB SERVER Azhari Shouni Barkah
Telematika Vol 2, No 2: Agustus (2009)
Publisher : Universitas Amikom Purwokerto

World Wide Web (WWW) adalah salah satu cara yang paling penting bagi suatu organisasi untuk mempublikasikan informasi, berinteraksi dengan pengguna internet, dan membangun kehadiran e-commerce atau e-government. Akan tetapi, jika sebuah organisasi tidak tepat dalam mengkonfigurasi dan mengoperasikan situs Web umum, mungkin akan rentan terhadap berbagai ancaman keamanan. Web server merupakan tempat atau wadah di mana informasi tersebut disimpan dan dipublikasikan untuk dapat diakses oleh pengguna internet. Oleh karena itu, diperlukan sebuah sistem keamanan publik web server, sesuai dengan tujuannya yaitu mengamankan dan melindungi kerahasiaan, integritas dan ketersediaan informasi tersebut.

Android Apps Vulnerability Detection with Static and Dynamic Analysis Approach using MOBSF Kusreynada, Sabrina Uhti; Barkah, Azhari Shouni
Journal of Computer Science and Engineering (JCSE) Vol 5, No 1: February (2024)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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

Ensuring the security of Android applications is paramount, especially for apps like Mobile JKN, launched by the Social Security Agency on Health “BPJS Kesehatan” under the Ministry of Health Republic Indonesia, which contain sensitive participant data. Such information is often targeted by cybercriminals seeking personal gain through data theft by exploiting security vulnerabilities within the application. To address these risks, a thorough analysis was conducted to detect security loopholes in the Mobile JKN application. The study used the Mobile Security Framework (MOBSF) tools and involved static and dynamic analyses. Despite the application’s implementation of secure SSL Pinning and detection of rooted devices, the static analysis revealed potential security loopholes, including dangerous permission access, weak cryptographic methods, and vulnerable hardcoded secrets. Moreover, the application was found vulnerable to Janus, SQL Injection, and padding oracle attacks. While the dynamic analysis showed satisfactory implementation of SSL Pinning and no performance degradation, it also revealed that root detection was lacking, and debugger connections were not detected while the application was running. These findings emphasize the critical need for immediate security enhancements in the Mobile JKN application.

Perbandingan Algoritma Support Vector Machine, Decision Tree, dan Logistic Regresion Pada Analisis Sentimen Ulasan Aplikasi Netflix Ramadani, Nevita Cahaya; Tahyudin, Imam; Shouni Barkah, Azhari
Jurnal Nasional Teknologi dan Sistem Informasi Vol 10, No 2 (2024): Agustus 2024
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v10i2.2024.110-117

Penelitian ini bertujuan untuk menganalisis sentimen terhadap ulasan pengguna Netflix menggunakan algoritma machine learning seperti Support Vector Machine (SVM), Decision Tree dan Logistic Regression. Dataset yang terdiri dari 3000 ulasan pengguna diambil dari Google Play Store dan melalui proses preprocessing teks yang mencakup penghapusan karakter, tokenisasi, penghapusan stopword, stemming, serta penyaringan token pendek. Metode TF-IDF digunakan untuk ekstraksi dan pembobotan fitur dalam analisis. Evaluasi hasil menunjukkan bahwa SVM secara konsisten memberikan akurasi yang lebih tinggi dibandingkan Decision Tree dan Logistic Regression dalam klasifikasi sentimen, dengan SVM mencapai akurasi rata-rata 88.18% dan puncak tertinggi 92.69% dalam K-Fold Cross Validation. Implikasi praktis dari penelitian ini adalah Netflix dapat memanfaatkan analisis sentimen untuk meningkatkan pengalaman pengguna dan pengelolaan layanan lebih baik.

AN EVALUATION OF THE SUCCESSFUL IMPLEMENTATION OF THE INFORMATION SYSTEM PLATFORM MERDEKA MENGAJAR USING HUMAN ORGANIZATION TECHNOLOGY FIT MODEL APPROACH Abidin, Uun; Hariguna, Taqwa; Barkah, Azhari Shouni
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4282

The implementation of technology in education has great potential to improve the quality of learning that supports the implementation of the Merdeka curriculum. The Merdeka Mengajar platform (MMP) is designed to help educators by providing various features including self-development, inspiration and teaching. Uneven ICT infrastructure and teachers' personal abilities are problems in the implementation of the MMP, so it is necessary to analyze the success of the implementation of the MMP. The purpose of this study is to analyze the success of the implementation of the information system for the Merdeka Mengajar Platform by adopting the Hot Fit Model by expanding the Technology component with the ICT Infrastructure variable, expanding the Human component with the personal competence variable, expanding the organizational component with the organizational culture variable and the training & learning variable which can affect the successful implementation of the MMP. The data obtained were 328 respondents who were analyzed using SmartPLS 3.2.9. The analysis results obtained the proposed conceptual model has an accuracy of 58.6%. Net benefits are influenced by system use, user satisfaction, personal competence, structure, environment, organizational culture, and training & learning. Service quality, system quality, information quality, and ICT infrastructure have a positive impact on system use and user satisfaction.

Optimizing Marketplace Registration Page Design with Predictive Heatmap Analysis Bagaskoro, Galih; Eko Saputro, Rujianto; Shouni Barkah, Azhari; Nanjar, Agi
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14547

Optimizing marketplace registration pages is crucial for improving user experience and conversion rates. This study evaluates the design of registration pages for four leading Indonesian marketplaces Tokopedia, Shopee, Blibli, and Lazada—using Predictive Heatmaps from UX Pilot alongside Heuristic Evaluation and Gestalt Principles. The analysis identifies key usability issues, such as distractions from branding elements, inconsistent visual hierarchy, and a lack of real-time validation and feedback mechanisms. Findings indicate that while branding elements effectively capture user attention, they often divert focus from essential features, a trend observed not only in these marketplaces but also in broader UI design contexts. such as Call-to-Action (CTA) buttons and registration forms. Shopee and Lazada successfully utilize high-contrast CTA buttons to direct user interaction, whereas Tokopedia and Blibli suffer from visual distractions caused by mascots and unnecessary decorative elements. Heatmap results also reveal inconsistent grouping of interface components, reducing page efficiency. To enhance user experience and conversion rates, recommendations include improving CTA button visibility through contrasting colors and strategic placement, minimizing decorative distractions, and implementing real-time validation and feedback. The application of Gestalt Principles further aids in optimizing interface organization by grouping related elements more effectively. This study underscores the importance of a structured design approach incorporating heuristic and predictive analytics to enhance the usability of online registration pages. Future research may explore the impact of interactive elements and A/B testing in refining registration interfaces.

Technology Acceptance Model TAM using Partial Least Squares Structural Equation Modeling PLS- SEM Latif, Imam Sofarudin; Saputro, Rujianto Eko; Barkah, Azhari Shouni
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1104

The rapid advancement of digital technologies necessitates a deeper focus on user acceptance and satisfaction, particularly within the framework of the Technology Acceptance Model (TAM), analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This systematic literature review examines 36 articles published between 2020 and 2025, revealing that factors such as trust, system quality, perceived enjoyment, service quality, and technological self-efficacy significantly influence user satisfaction. These external variables enhance the explanatory power of TAM, providing a richer understanding of user interactions with digital platforms such as e-commerce, e-learning, and mobile banking. PLS-SEM's ability to manage model complexity, non-normal data distributions, and interrelated constructs further validates its suitability for this research. The findings suggest that integrating these external factors improves both the theoretical and practical aspects of TAM in the context of technology adoption. Future research could explore additional industry-specific applications for emerging technologies.

The Success Evaluation of Platform Merdeka Mengajar (PMM) Implementation in Purbalingga Regency Using HOT-Fit Model Abidin, Uun; Hariguna, Taqwa; Barkah, Azhari Shouni
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.33441

The industrial 4.0 revolution increasingly develops. It also affects the education field. This issue can be used to improve the quality of education by improving teachers quality. The Merdeka Mengajar platform (PMM) is used to improve the quality of teachers in implementing the Merdeka curriculum (Independent Platform). When it is implemented, teachers have difficulty to adapt the independent teaching platform and not all teachers understand technology. The purpose of this research is to analyze the factors that influence the successful implementation of the Merdeka Mengajar Platform (PMM) using the Hot fit method which assesses system success from the aspects of human, organization and technology. The research sample was 220 vocational high school teachers in Purbalingga Regency. The results of this research can be concluded that all variables contained in the Hot Fit model. They are Service Quality, System Quality and Information Quality, System Use and User Satisfaction. Structure and Environment have a positive and significant effect on the successful implementation of the Merdeka Mengajar Platform (PMM) used by vocational teachers in Purbalingga Regency. The Research Model in this study has a level of feasibility and accuracy of 71.6%, while the rest is influenced by other variables which is not included in this study. By this research, we can find out the factors that influence the successful implementation of the Merdeka Mengajar Platform (PMM) in Purbalingga Regency.

Evaluasi Pengaruh Varian Daftar Stopword terhadap Kinerja Klasifikasi Teks Al-Qur'an dengan Support Vector Machine dan Backpropagation Neural Network Ajis Solihin, Afit; Utomo, Fandy Setyo; Barkah, Azhari Shouni
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 7 (2025): JPTI - Juli 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.875

Latar belakang penelitian ini adalah tantangan dalam mengklasifikasikan teks Al-Qur'an, yang disebabkan oleh kompleksitas struktur bahasa Arab dan perbedaan antara bahasa Arab klasik dan modern. Penggunaan teknik Natural Language Processing (NLP), khususnya stopword removal, menjadi penting dalam meningkatkan akurasi klasifikasi teks. Namun, pengaruh penggunaan varian stopword terhadap performa model klasifikasi teks Al-Qur'an belum banyak dieksplorasi. Tujuannya adalah untuk mengevaluasi pengaruh penerapan varian daftar stopword yang berbeda terhadap kinerja dua algoritma klasifikasi teks, yaitu Support Vector Machine (SVM) dan Backpropagation Neural Network (BPNN), dalam mengklasifikasikan ayat-ayat Al-Qur'an. Penelitian ini juga bertujuan untuk menganalisis bagaimana teknik seleksi fitur Chi-Square dan representasi TF-IDF dapat mempengaruhi efektivitas model. Metode yang digunakan meliputi pengumpulan dataset ayat-ayat Al-Qur'an dalam Bahasa Indonesia yang melalui preprocessing seperti tokenisasi, normalisasi, dan penghapusan stopword menggunakan tiga varian stopword list: Sastrawi, NLTK, dan kombinasi keduanya. Model klasifikasi diterapkan dengan algoritma SVM dan BPNN, serta dievaluasi menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa algoritma SVM memberikan performa yang lebih baik dan konsisten dibandingkan BPNN. Penggunaan stopword NLTK memberikan hasil terbaik dengan akurasi tertinggi sebesar 0,5849 dan F1-score 0,5438 pada SVM. BPNN menunjukkan hasil yang kurang optimal dengan akurasi tertinggi hanya 0,4292 dan F1-score yang lebih rendah dari 0,3 pada semua varian stopword. Kontribusi penelitian ini adalah menegaskan pentingnya pemilihan daftar stopword yang tepat untuk meningkatkan kinerja klasifikasi teks Al-Qur'an serta memberikan wawasan berharga dalam pengembangan sistem klasifikasi teks keagamaan yang lebih akurat menggunakan algoritma pembelajaran mesin.

Co-Authors Abidin, Uun Abidin, Zaheera Zainal Ajis Solihin, Afit Anggun Purnomo Bagaskoro, Galih Berlilana Berlilana Darmono Fandy Setyo Utomo Harimanto, Bambang Harimato, Bambang Heru Supriyanto Imam Tahyudin Kusreynada, Sabrina Uhti Latif, Imam Sofarudin Melia Dianingrum Muhtyas Yugi Nanjar, Agi Nugroho, Khabib Adi Ramadani, Nevita Cahaya Rizki Wahyudi Rujianto Eko Saputro Selamat, Siti Rahayu Setiyawan, Dillyana Tugas Sumiati, Ai Irma Taqwa Hariguna

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