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All Journal Teknomatika: Jurnal Informatika dan Komputer
Al Badawi, M. Abu Amar
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Computer Science & IT

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Analisis Kerentanan Menggunakan Vulnerability Assessment pada Situs Web Perguruan Tinggi Prihanto, Danang; Sholeh, Adkhan; Setiawan, Chanief Budi; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 16 No 2 (2023): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v16i2.1248

Abstract

Abstrak - Di Indonesia, terdapat beberapa fenomena yang menunjukkan rendahnya tingkat keamanan digital. Pada tahun 2021, terdapat 5.940 kasus web defacement dari beberapa sektor yang menjadi sasaran. Salah satunya dari sektor akademik, yaitu perguruan tinggi dengan total 2.217 kasus, menjadikannya sektor dengan kasus terbanyak. Oleh karena itu, peneliti melakukan pemindaian pada ketiga website FTTI. Penelitian dilakukan dengan tujuan dapat menganalisis dan mengetahui tingkat keamanan serta bentuk-bentuk kerentanan pada website FTTI di Universitas Jenderal Achmad Yani Yogyakarta, yaitu ftti.unjaya.ac.id, elearning.ftti.unjaya.ac.id, dan app.ftti.unjaya.ac.id. Dengan hasil yang diperoleh dari analisis, peneliti harus melaporkan kepada Kepala Pusat Sistem Informasi (PUSI) FTTI. Menggunakan metode vulnerability assessment dengan beberapa alat seperti Nmap, Nessus, dan WPScan. Pada metode ini terdapat beberapa tahapan, seperti persiapan (instalasi alat dan pengumpulan data yang diperlukan), mengidentifikasi kerentanan, dan analisis. Hasil penelitian ini menunjukkan bahwa dari ketiga website, terdapat berbagai tingkat kerentanan seperti Critcal, High, Medium, Low, dan Info. Pada website ftti.unjaya.ac.id yang menggunakan WordPress, tidak terdapat kerentanan yang parah setelah dilakukan pemindaian menggunakan ketiga alat yang digunakan. Sementara itu, pada elearning.ftti.unjaya.ac.id dan app.ftti.unjaya.ac.id, menunjukkan hasil penilaian VPR Top Threats bahwa keduanya berada pada tingkat Medium. Pada ketiga website yang telah dipindai, ditemukan bahwa ftti.unjaya.ac.id adalah website dengan tingkat kerentanan paling aman. Menurut hasil pemindaian, website elearning.ftti.unjaya.ac.id maupun app.ftti.unjaya.ac.id memiliki beberapa kerentanan dengan tingkat risiko High bahkan Critical.
Sistem Pendukung Keputusan Pemberian Beasiswa Kurang Mampu di SMA Negeri 2 Kupang Menggunakan Metode Profile Matching Da Costa, Jonia Nova; Priadana, Adri; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 13 No 1 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i1.1126

Abstract

At SMAN 2 Kupang, the scholarship program for underprivileged students greatly contributes to their educational attainment. Scholarships at SMAN 2 Kupang are awarded based on parents/guardians' income, number of dependents, possession of smart Indonesian cards, and disabilities. However, there is often an issue of inaccurate scholarship distribution. Some students who do not meet the eligibility criteria receive scholarships, while deserving students who are less fortunate do not receive them. To address this problem, we propose a scholarship decision support system utilizing the profile matching method as the calculation algorithm. The system is developed using the PHP programming language and MySQL database. The primary benefit of this system is to assist in the scholarship selection process based on predetermined criteria. The system includes student registration, profile matching calculation, and the ability to generate registration and calculation reports.
Portal Masjid “Mosque Wanted” Solusi Pencarian Lokasi Masjid, Info Kajian & Berita Seputar Masjid di Yogyakarta Puji Santoso, Imam; Saputra, Andika Bayu; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 13 No 2 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i2.1127

Abstract

The dissemination of information and news about mosques in the Yogyakarta area has predominantly relied on social media and the Internet. Most mosques, especially the larger ones, have established their own social media accounts to showcase their activities. However, the information shared is typically limited to text and graphics, such as WhatsApp broadcasts, Instagram posts, Facebook updates, Twitter tweets, or posters displayed within the mosque premises. This text and graphic-based approach restricts accessibility for individuals who are unable to attend mosque activities due to various reasons, including difficulties in navigating to the mosque. This research aims to develop a Web-based Geographical Information System (GIS) that provides a mosque search solution, study information, and news about mosques in Yogyakarta. The system utilizes a responsive web design to enhance the dissemination of information, facilitate navigation, and stimulate public interest in studying Islamic sciences in Yogyakarta. The outcomes of this study offer valuable support to mosque administrators in providing comprehensive information about the mosque, particularly for Islamic da'wah activities. By incorporating detailed information and location data into the system, the dissemination of da'wah information can be improved. Moreover, the system enables the community to easily locate nearby mosques that offer Islamic da'wah activities and access real-time information about these activities.
Penerapan Metode Rabin-Karp untuk Mengukur Kemiripan Kata Dua Dokumen Berbasis Web Saputra, Ramadhana; Cahyono, Ari; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 14 No 1 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i1.1128

Abstract

Scientific literature plays a significant role in the academic requirements of colleges, encompassing various types such as papers, reports, journals, and scripts. However, the issue of plagiarism, including the copying and plagiarizing of others' work, remains prevalent in the creation of scientific papers. In particular, digital content plagiarism often involves copy-pasting and quoting from original documents. To address this, measuring the similarity of words between documents becomes essential. In Dhamayanti's research, the recommendation is to enhance the Rabin-Karp algorithm by utilizing a distinct method [1]. This study builds upon previous research employing a string-matching method. Instead of the conventional cosine method, the substitution method employed string-Karp techniques within the Rabin-Karp algorithm, resulting in improved similarity percentages. The manufacturing of the application adopts the string-matching method using the Rabin-Karp algorithm. The algorithm matches 5-gram word sequences converted into hash values, and the similarity percentage is determined based on matching hash values. The presence of identical words indicates similarity. The application is tested using six scientific writing documents from diverse sources with related titles. Through 15 test runs, the accuracy level reached 90%.
Analisis Sentimen Opini Masyarakat Tentang Penggunaan Aplikasi Bimbingan Belajar Online di Masa Pandemi Covid-19 Menggunakan Metode Support Vector Machine (SVM) Gunawan, Albet; Saputra, Andika Bayu; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 15 No 2 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i2.1132

Abstract

Distance learning has emerged as a response to the Covid-19 pandemic, providing students with a new approach to learning. Online learning platforms, utilizing information technology, have become essential in connecting students and teachers. Online tutoring applications offer valuable supplementary educational materials, with various features to support the learning process. Analyzing sentiment on Twitter regarding these online tutoring applications is crucial in determining the best options for students. This study aims to develop an analytical model using the Support Vector Machine (SVM) for online tutoring applications during the Covid-19 pandemic. The research focuses on analyzing positive and negative sentiments within Twitter data, utilizing the Support Vector Machine (SVM) method. The training phase involved 800 manually labeled tweets, consisting of 400 positive and 400 negative sentiments. For testing, 23,511 labeled data points were used. The training data achieved an accuracy of 91.81%. The research successfully achieved an accuracy rate of 90.62% for training and 91% for testing.
Analisis Pola Konsumen Dalam Bertransaksi Bisnis di Bengkel Resmi AHASS Total Honda Motor Wardoyo, Budi; Cahyo, Puji Winar; Habibi, Muhammad; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 16 No 1 (2023): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v16i1.1133

Abstract

The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.
Analisis Kerentanan Menggunakan Vulnerability Assessment pada Situs Web Perguruan Tinggi Prihanto, Danang; Sholeh, Adkhan; Setiawan, Chanief Budi; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 16 No 2 (2023): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v16i2.1248

Abstract

Abstrak - Di Indonesia, terdapat beberapa fenomena yang menunjukkan rendahnya tingkat keamanan digital. Pada tahun 2021, terdapat 5.940 kasus web defacement dari beberapa sektor yang menjadi sasaran. Salah satunya dari sektor akademik, yaitu perguruan tinggi dengan total 2.217 kasus, menjadikannya sektor dengan kasus terbanyak. Oleh karena itu, peneliti melakukan pemindaian pada ketiga website FTTI. Penelitian dilakukan dengan tujuan dapat menganalisis dan mengetahui tingkat keamanan serta bentuk-bentuk kerentanan pada website FTTI di Universitas Jenderal Achmad Yani Yogyakarta, yaitu ftti.unjaya.ac.id, elearning.ftti.unjaya.ac.id, dan app.ftti.unjaya.ac.id. Dengan hasil yang diperoleh dari analisis, peneliti harus melaporkan kepada Kepala Pusat Sistem Informasi (PUSI) FTTI. Menggunakan metode vulnerability assessment dengan beberapa alat seperti Nmap, Nessus, dan WPScan. Pada metode ini terdapat beberapa tahapan, seperti persiapan (instalasi alat dan pengumpulan data yang diperlukan), mengidentifikasi kerentanan, dan analisis. Hasil penelitian ini menunjukkan bahwa dari ketiga website, terdapat berbagai tingkat kerentanan seperti Critcal, High, Medium, Low, dan Info. Pada website ftti.unjaya.ac.id yang menggunakan WordPress, tidak terdapat kerentanan yang parah setelah dilakukan pemindaian menggunakan ketiga alat yang digunakan. Sementara itu, pada elearning.ftti.unjaya.ac.id dan app.ftti.unjaya.ac.id, menunjukkan hasil penilaian VPR Top Threats bahwa keduanya berada pada tingkat Medium. Pada ketiga website yang telah dipindai, ditemukan bahwa ftti.unjaya.ac.id adalah website dengan tingkat kerentanan paling aman. Menurut hasil pemindaian, website elearning.ftti.unjaya.ac.id maupun app.ftti.unjaya.ac.id memiliki beberapa kerentanan dengan tingkat risiko High bahkan Critical.
Co-Authors Adri Priadana Ari Cahyono Chanief Budi Setiawan Da Costa, Jonia Nova Gunawan, Albet Muhammad Habibi Prihanto, Danang Puji Santoso, Imam Puji Winar Cahyo Saputra, Andika Bayu Saputra, Ramadhana Sholeh, Adkhan Wardoyo, Budi