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CLASSIFICATION OF STUDENT SATISFACTION WITH ONLINE LECTURE Nanang Ruhyana; Tati Mardiana; Fachri Amsury; Daning Nur Sulistyowati
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Abstra Covid-19 has had a significant impact on people's lives, resulting in the paralysis of almost the entire economy and education, especially in the education sector, resulting in many students being unable to carry out teaching and learning activities at schools or universities. Based on this, the Ministry of Education and Culture has issued an appeal to stop face-to-face teaching and learning activities at schools and universities and replace them with distance or online learning. Resulting in teaching and learning activities to be less than optimal for students or students, there is dissatisfaction with the distance or online learning system, the purpose of this study is to measure the level of student satisfaction with online lectures by applying data mining techniques, classifying the level of online learning satisfaction using an online learning approach. k-NN algorithm and Decision Tree with 100 questionnaire data that has been collected from active students who carry out online lectures with an accuracy rate of 96.00% from the k-NN algorithm and a satisfied precision value of 95.51%, a satisfied recall value of 98.84% on a precision value the dissatisfied class is 90.91%, the recall value of the dissatisfied class is 71.43%. While the accuracy results using the Decision Tree algorithm approach is lower with an accuracy of 95.00%. based on research results that the level of student satisfaction with distance learning or online is quite high. Keywords: covid 19, data mining, online, k-NN, decision tree

COMPARATIVE ANALYSIS OF THE K-NEAREST NEIGHBOR ALGORITHM ON VARIOUS INTRUSION DETECTION DATASETS Andri Agung Riyadi; Fachri Amsury; Irwansyah Saputra; Tiska Pattiasina; Jupriyanto Jupriyanto
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Security in computer networks can be vulnerable, this is because we have weaknesses in making security policies, weak computer system configurations, or software bugs. Intrusion detection is a mechanism for securing computer networks by detecting, preventing, and blocking illegal attempts to access confidential information. The IDS mechanism is designed to protect the system and reduce the impact of damage from any attack on a computer network for violating computer security policies including availability, confidentiality, and integrity. Data mining techniques have been used to obtain useful knowledge from the use of IDS datasets. Some IDS datasets that are commonly used are Full KDD, Corrected KDD99, NSL-KDD, 10% KDD, UNSW-NB15, Caida, ADFA Windows, and UNM have been used to get the accuracy rate using the k-Nearest Neighbors algorithm (k-NN). The latest IDS dataset provided by the Canadian Institute of Cybersecurity contains most of the latest attack scenarios named the CICIDS2017 dataset. A preliminary experiment shows that the approach using the k-NN method on the CICIDS2017 dataset successfully produces the highest average value of intrusion detection accuracy than other IDS datasets.

COMPARISON OF CLASSIFICATION ALGORITHMS FOR ANALYSIS SENTIMENT OF FORMULA E IMPLEMENTATION IN INDONESIA Fachri Amsury; Nanang Ruhyana; Tati Mardiana
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The Formula E racing series has become one of the world's most prestigious competitions. In 2022, Indonesia hosted the famous Formula E race. The event possesses the potential for economic benefits for Indonesia worth 78 million euros through the arrival of 35,000 spectators. Indonesians are enthusiastic about Formula E since it allows their nation to encourage tourists and gain international prominence. However, some people do not support this event. Since they regard that amid the COVID-19 pandemic, it is preferable for the government to focus on people affected by the pandemic rather than support a Formula E event. This study compares the Support Vector Machine and Naive Bayes algorithms in classifying public opinion in the Formula E race. This study gets its information from user comments on social media platforms, especially Twitter. The stages start with text preprocessing and include cleaning, case folding, tokenization, filtering, and stemming. Proceed with weighting using the TF-IDF approach. Data testing uses a confusion matrix to evaluate the classification results by testing accuracy, precision, and recall. Categorizing public opinion using the SVM algorithm has an accuracy of 82 percent, a precision of 97.86 percent, and a recall of 77.90 percent. On the other hand, the accuracy of the Naive Bayes technique is more limited, at 87.54 percent. Society's opinion on Twitter shows positive sentiment towards implementing Formula E.

Implementation of the Association Method in the Analysis of Sales Data from Manufacturing Companies Andri Agung Riyadi; Fachri Amsury; Nanang Ruhyana; Ihsan Aulia Rahman
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.491

The company produces sales data every day. Over time, the data increases, and the amount becomes very large. The data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. To overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database (KDD) concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.

Applied of Classification Technique in Data Mining For Credit Scoring Heriyanto Heriyanto; Ika Kurniawati; Fachri Amsury; Muhammad Rizki Fahdia; Irwansyah Saputra; Nanang Ruhyana; Asrul
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 12 No. 2 (2022): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

In the development of the banking business, credit issues remain interesting to study and uncover. Most of the problems occur not in the system implemented by the bank, but the problem occurs precisely in the human resources who manage credit, either in their relationship with consumers or in errors on the part of the bank which mispredicts in assessing consumers who apply for credit. Several studies in the computer field have been carried out to reduce credit risk which causes losses to the company. In this study, a comparison of the Naive Bayes, C4.5 and KNN algorithms was carried out which was applied to consumer data that received credit eligibility for good and bad customers. The best prediction results are nave Bayes with an accuracy of 95.95% and an AUC of 0.974. The results of this classification are implemented in the form of a website-based application that can be used to facilitate related parties in the credit scoring system.

Sosialisasi Internet Sehat Dan Aman Dalam Meningkatkan Literasi Digital Pada Yayasan Mathlaul Anwar Satu Ika Kurniawati; Muhammad Rizki Fahdia; Fachri Amsury; Heriyanto Heriyanto
TRIDHARMADIMAS: Jurnal Pengabdian Kepada Masyarakat Jayakarta Vol 3 No 1 (2023): PKM-TRIDHARMADIMAS (July 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/tridharmadimas.v3i1.1174

Pada era digitalisasi dan media social saat ini di dalam kehidupan sehari-hari banyak manfaat yang bisa diperoleh dengan penggunaan internet. Selain itu internet memiliki dua mata pisau yaitu negatif dan positif. Permasalahan yang terjadi saat ini kurangnya sosialisasi penggunaan internet sehat dan aman pada Yayasan Mathlaul Anwar Satu karena pengaruh dari konten bersifat negatif diberbagai media internet yang memuat gambar porno, perjudian, penipuan, pencemaran nama baik dan berita bohong, selain itu media sosial juga memiliki dampak negatif salah satunya adalah cyberbullying yang bisa menimpa remaja dan anak-anak. Kegiatan sosialisasi dalam bentuk pengabdian kepada masyarakat ini bertujuan untuk memberikan pengetahuan pemanfaatan internet secara bijak dan dapat menyaring informasi yang didapatkan, kemudian diharapkan dapat menghindari diri sendiri atau keluarga dari dampak-dampak negatif dari penggunaan internet. Hasil kegiatan ini diharapkan agar ada peran serta antara orangtua dan guru agar mampu membimbing serta memberikan pemahaman kepada remaja pentingnya berinternet sehat dalam kehidupan sehari-hari.

Sistem Informasi Perpustakaan Berbasis Web Pada SDIT Al-Insan Islamic School Bekasi Helmalia Putri Ismayani; Fachri Amsury
Jurnal Komputer Antartika Vol. 1 No. 3 (2023): September 2023
Publisher : Antartika Media Indonesia

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

Sistem informasi perpustakaan merupakan sarana pendidikan penting untuk mendukung kegiatan belajar siswa. Namun, pada SDIT Al-Insan Islamic School, perpustakaan masih mengandalkan sistem manual dalam pencarian, peminjaman, dan pengembalian buku, menyebabkan efektivitas dan efisiensi terganggu. Dokumentasi data juga tidak teratur, dan minimnya waktu berkunjung ke perpustakaan membatasi akses siswa. Untuki mengatasii masalahi tersebut, penelitiani inii bertujuani untuki merancangi dani membanguni sistem informasi perpustakaan berbasisi web menggunakan modeli waterfall. Metode pengembangan ini terdirii dari analisis kebutuhan sistem, idesain, implementasi, integrasi idan ipengujian, serta pengoperasian dan pemeliharaan. Teknik pengumpulan data melibatkan observasi, wawancara dengan Kepala Sekolah, dan studii pustaka. Data dianalisis untuk memahami kebutuhan pengguna dan menyusun desain sistem. Sistem iinformasi iperpustakaan berbasis iweb ini ibertujuan iuntuk mengkomputerisasi proses manual sehingga kesalahan dalam peminjaman buku dapat diminimalisasi. Sistem akan memberikan kemudahan bagi petugas perpustakaan dalam mengelola data dan informasi, serta memfasilitasi akses informasi bagi pengguna untuk penelusuran koleksi, peminjaman, dan pengembalian buku. Ruang lingkup penelitian ini mencakup pengolahan data pengguna, pengelolaan data buku, transaksi peminjaman idan ipengembalian buku, pengelolaan arus kas, serta pembuatan laporan. Penerapan aplikasi Visual Studio Code, PHP, MySQL, dan PhpMyAdmin digunakan dalam pengembangan sistem. Diharapkan sistem informasi perpustakaan berbasis web ini akan meningkatkan efisiensi dan efektivitas pengelolaan perpustakaan, memudahkan akses informasi, serta memberikan kontribusi positif bagi proses pembelajaran di SDIT Al-Insan Islamic School.

Penerapan Metode Waterfall Pada Sistem Informasi Pendaftaran dan Pembayaran Membership Komunitas United Indonesia Putria Pebriana Sitanggang; Intan Permatasari; Syahrur Rhamadan; Fachri Amsury
Jurnal Komputer Antartika Vol. 1 No. 4 (2023): Desember 2023
Publisher : Antartika Media Indonesia

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

Di era industri 4.0 ini, penggunaan sistem informasi sangat dibutuhkan untuk keperluan dalam organisasi, perusahaan, komunitas dan lainnya. Termasuk dalam Komunitas United Indonesia, yang terdapat sebuah transaksi pendaftaran dan pembayaran didalamnya. Namun, kegiatan ini masih berlangsung secara manual sehingga memerlukan waktu dan tenaga yang berlebih. Penerapan sistem informasi untuk pendaftaran dan pembayaran membership pada komunitas United Indonesia dapat dilakukan. Dengan menggunakan metode Waterfall yang merupakan pendekatan SDLC paling awal yang digunakan untuk pengembangan perangkat lunak. Urutan dalam Metode Waterfall bersifat serial yang dimulai dari proses perencanaan, analisa, desain, dan implementasi pada sistem. Maka dari itu dalam penelitian ini kami menggunakan metode tersebut. Dalam penelitian ini kami akan membuatkan sistem informasi yaitu sebuah website untuk dapat digunakan oleh pengurus serta member United Indonesia dalam proses transaksi yang telah ada. Dapat disimpulkan bahwa sistem informasi pendaftaran dan pembayaran dapat membantu United Indonesia dalam mempercepat proses pendaftaran dan pembayaran karena sebelumnya masih menggunakan sistem manual. Sistem informasi pendaftaran dan pembayaran ini dapat diterapkan pada tempat lain yang membutuhkan dengan beberapa penyesuaian. Masih banyak potensi fitur yang dapat dikembangkan seiring dengan berkembangnya kebutuhan pada United Indonesia. In this industrial era 4.0, the use of information systems is needed for purposes in organizations, companies, communities And others. Including in the United Indonesia Community, which has a registration And payment transaction in it. However, this Activity still takes place manually so that it requires excessive time And energy. The application of information systems for membership registration And payment in the United Indonesia community can be done. By using the Waterfall method which is the earliest SDLC approach used for software development. The sequence in the Waterfall Method is serial in nature starting from the planning, analysis, design, And implementation processes of the system. Therefore in this research we use this method. In this study we will create an information system, namely a website to be used by the Management And members of United Indonesia in the existing transaction process. It can be concluded that the registration And payment information system can help United Indonesia in speeding up the registration And payment process because previously it was still using a manual system. This registration And payment information system can be applied to other places that need it with some adjustments. There are still many potential features that can be developed along with the growing needs of United Indonesia.

CLASSIFICATION OF STUDENT SATISFACTION WITH ONLINE LECTURE Nanang Ruhyana; Tati Mardiana; Fachri Amsury; Daning Nur Sulistyowati
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Abstra Covid-19 has had a significant impact on people's lives, resulting in the paralysis of almost the entire economy and education, especially in the education sector, resulting in many students being unable to carry out teaching and learning activities at schools or universities. Based on this, the Ministry of Education and Culture has issued an appeal to stop face-to-face teaching and learning activities at schools and universities and replace them with distance or online learning. Resulting in teaching and learning activities to be less than optimal for students or students, there is dissatisfaction with the distance or online learning system, the purpose of this study is to measure the level of student satisfaction with online lectures by applying data mining techniques, classifying the level of online learning satisfaction using an online learning approach. k-NN algorithm and Decision Tree with 100 questionnaire data that has been collected from active students who carry out online lectures with an accuracy rate of 96.00% from the k-NN algorithm and a satisfied precision value of 95.51%, a satisfied recall value of 98.84% on a precision value the dissatisfied class is 90.91%, the recall value of the dissatisfied class is 71.43%. While the accuracy results using the Decision Tree algorithm approach is lower with an accuracy of 95.00%. based on research results that the level of student satisfaction with distance learning or online is quite high.

COMPARATIVE ANALYSIS OF THE K-NEAREST NEIGHBOR ALGORITHM ON VARIOUS INTRUSION DETECTION DATASETS Andri Agung Riyadi; Fachri Amsury; Tiska Pattiasina; Jupriyanto Jupriyanto
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i1.147

Because we have flaws in developing security rules, inadequate computer system settings, or software defects, security in computer networks can be vulnerable. Intrusion detection is a computer network security method that detects, prevents, and blocks unauthorized access to confidential information. The IDS method is intended to defend the system and minimize the harm caused by any attack on a computer network that violates computer security policies such as availability, confidentiality, and integrity. Data mining techniques were utilized to extract relevant information from IDS databases. The following are some of the most widely utilized IDS datasets NSL-KDD, 10% KDD, Full KDD, Corrected KDD99, UNSW-NB15, ADFA Windows, Caida, dan UNM have been used to get the accuracy rate using the k-Nearest Neighbors algorithm (k-NN). The latest IDS dataset provided by the Canadian Institute of Cybersecurity contains most of the latest attack scenarios named the CICIDS2017 dataset. Preliminary experiment shows that the approach using the k-NN method on the CICIDS2017 dataset successfully produces the highest average value of intrusion detection accuracy than other IDS datasets.

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