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All Journal Jurnal Mantik Jurnal Responsif : Riset Sains dan Informatika semanTIK
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Universitas Bina Sarana Informatika
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PENERAPAN PENERAPAN TEKNIK PSO OVER SAMPLING DAN ADABOOST J48 UNTUK MEMPREDIKSI CACAT SOFTWARE Sugiono; Andi Taufik; Ricky Faizal Amir
Jurnal RESPONSIF: Riset Sains & Informatika Vol 2 No 2 (2020): Jurnal Responsif : Riset Sains dan Informatika
Publisher : LPPM Universitas BSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jti.v2i2.249

Abstract

Perangkat lunak yang bermutu ditentukan oleh jumlah cacat yang ditemukan pada saat proses pengujian. Proses perbaikan perangkat lunak setelah terdistribusi memiliki resiko yang lebih tinggi. Beberapa metode telah diujikan untuk memprediksi cacat pada perangkat lunak. Secara umum dataset software metrics telah digunakan sebagai acuan. Dataset software metrics bersifat tidak seimbang sehingga berpengaruh terhadap tingkat akurasi pemrediksi cacat perangkat lunak. Pada tahapan pra pemrosesan, digunakan metode Particle Swarm optimization (PSO) untuk mengatasi masalah polusi data serta metode Random Over Sampling (ROS) untuk menangani ketidak seimbangan kelas pada dataset. Metode yang diusulkan pada penelitian ini yaitu algoritma decision tree J48 yang dioptimalkan dengan teknik adaboost. Dataset software metrics yang digunakan pada penelitian ini bersumber pada dataset PROMISE repository. Hasil penelitian menunjukan bahwa penggunaan teknik adaboost pada algoritma decision tree J48 layak digunakan sebagai metode untuk memprediksi cacat pada perangkat lunak dengan nilai akurasi mencapai 93,507% dan nilai AUC mencapai 0,935
Grouping of Covid-19 Affected Areas in Bogor City Using The K-Means Algorithm Zulia Imami Alfianti; Sugiono; Mochammad Abdul Azis; Ahmad Fauzi
Jurnal Mantik Vol. 4 No. 4 (2021): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2021.1142.pp2336-2341

Abstract

Clustering plays an important role in processing big data, making predictions and overcoming anomalies in data, identical characteristics in data sets are grouped using iterative techniques. Because data is always evolving from day to day, very large data sets with little can be identified into interesting patterns by grouping, special methods are needed to handle it. In December 2019 there was an outbreak of acute respiratory syndrome caused by coronavirus 2 infection that occurred in Wuhan and on February 12, 2020, the World Health Organization officially named the disease Corona Virus 2019 (Covid 19). This research will conduct clustering of areas affected by Covid 19 in the City of Bogor. The clustering was done using the K-Means method and dividing the data into 3 clusters, namely the low-impact cluster, the medium-impact cluster and the high-impact cluster. The results showed that from 68 urban villages in the city of Bogor, 45% of the area was in the low-affected category, 35.29% of the area was in the medium-affected category and 19.12% of the area was in the high-affected category.
Optimization of Tree Algorithms by Resampling and Ensembling in Deffect Prediction Software: Frans Edward Schaduw; Sugiono Sugiono; Syaiful Anwar
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The level of defects in a software will always be linear with the quality of the resulting software. In the development process, developers need to predict the level of defects in a software to produce better software. In this study, the Particle Swarm optimization (PSO) method was used to optimize the data at the preprocessing stage, the Random Over Sampling (ROS) method to balance the classes in the dataset and the ensemble technique to maximize the performance of the J48 algorithm. The dataset used in this study uses the PROMISE repository dataset. The results showed that the integration of the PSO+ROS+J48+Bagging algorithm resulted in an average accuracy value of 92.378% and an AUC value of 0.924. This shows that the combination of PSO, ROS and J48 methods with Bagging Technique is feasible to be used as an algorithm to predict the defect level of a software
Maximum Information Securing Techniques With Vigenere Custom-Based Encryption Sugiono; Ahmad Fauzi; Dini Nurlaela; Lestari Yusuf
Jurnal Mantik Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i2.2695

Abstract

The Vigenere algorithm is one of the classic encryption algorithms that is easy to understand and apply in the process of securing information. By using the vigenere table we can easily read messages that have been encrypted. However, the vigenere algorithm is also an algorithm that is difficult to solve, this is because to be able to solve a cipher text, a key is needed. With a character transition technique based on the sequence of characters in a certain key so that the transition form of the character becomes unstable and difficult to guess. The vigenere method in general is still not optimal because it only relies on keys to secure information, while the vigenere table used is still a standard alphabet that has been applied by vigenere and is still incase sensitive or case sensitive. In this study we will maximize the use of the vigenere algorithm by randomizing the predetermined vigenere alphabet table so that a key and table form are needed to be able to solve a ciphertext
Application of Menu Ordering Information System Design at Kawas Truck Café with WEB Design Rahdian Kusuma Atmaja; Hari Sugiarto; Priyono Priyono; Sugiono Sugiono; Ade Setiawan
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Kawas Truck Cafe is a business entity engaged in the culinary field. The cafe does not yet have an information system that can assist in various processes in it, such as the ordering process, and sales transactions and reports. This can cause problems such as human error in the ordering process. The use of stationery and paper when recording menu orders results in overlapping orders, unordered delivery of orders. The report process at this cafe still uses conventional methods in recording and storing order transaction data. So to overcome these problems, the author makes a computerized system for ordering menus at the Kawas Truck cafe to be more efficient. In making this web, the author uses programming languages ??such as PHP, HTML, javascript, css, jquery with several features such as login, menu data, customer data, user data, sales transactions, orders, and reports that can be accessed by company owners and cashiers. By creating a computerized system, the author can help the ordering process, sales to reporting at Kawas Truck Cafe, to achieve effective business activities and time efficiency in company activities.
Implementation of a web-based laundry application with the laravel framework for laundry Aisy Laundry Muhammad Faisal; Priyono; Riswandi Ishak; Elin Panca Saputra; Tino Dwiantoro; Sugiono; Dyah Ayu Astuti; Muhammad Amir Hasan
Jurnal Mantik Vol. 7 No. 1 (2023): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i1.3753

Abstract

Aisy Laundry is a laundry service business located in Tambun, South Bekasi. The administrative service process at the site is still manual, paper and books are still used for recording transaction data and preparing reports. the purpose of this research is to complement the needs of users or users who can make it easier to do input so as to optimize the time used. in that place they still use paper and books, they still record transaction data in making reports. Paper media is susceptible to damage, tearing, loss and humidity, making it difficult to find the required data, a time-consuming process, and errors often occur during recording. Therefore, a laundry service application program was created. The development of this program uses the waterfall method, namely creating a database using a programming language and designing software using the web-based Laravel Framework by creating several features such as logins, User Data, Customer Data, Laundry Service Data, Account Data, Payment Transaction Data and Transaction Report Data. With this program, it can be a solution to help facilitate transaction creation and reporting, as well as increase the effectiveness and efficiency of an optimal work system at Aisy Laundry.
Data Mining Berbasis Machine Learning Untuk Analitik Prediktif Dalam Kelulusan Ridwansyah Ridwansyah; Muhammad Iqbal; Henny Destiana; Sugiono Sugiono; Abdul Hamid
SemanTIK : Teknik Informasi Vol. 10 No. 2 (2024): SemanTIK : Teknik Informasi
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v10i2.67

Abstract

Akreditasi perguruan tinggi menjadi salah satu indikator utama kualitas pendidikan, di mana tingkat kelulusan mahasiswa merupakan salah satu komponen penilaian yang sangat diperhatikan. Tingkat kelulusan yang rendah dapat berdampak negatif pada reputasi institusi, serta tantangan bagi mahasiswa dalam kelulusan tepat waktu. Tujuan penelitian untuk mengembangkan model prediktif kelulusan mahasiswa menggunakan berbagai algoritma machine learning yang sebelumnya belum pernah dilakukan pada dataset yang sama. Metode seperti LDA, RIDGE, LR, GBC, DUMMY, KNN, DT, NB, SVM, dan QDA diaplikasikan untuk memprediksi kelulusan. Hasil menunjukkan bahwa LDA memberikan kinerja terbaik dengan akurasi 86,20%, diikuti oleh Ridge dan LR. Model LDA menunjukkan performa unggul seperti recall dan F1-Score, menjadikannya model paling efektif untuk prediksi kelulusan. Dengan ini kontribusi yang didapat sangat signifikan dalam analitik prediktif pendidikan, terutama dalam hal meningkatkan tingkat kelulusan mahasiswa dan mendukung pencapaian akreditasi yang unggul. Hasil yang didapat diharapkan akan digunakan oleh perguruan tinggi untuk mengidentifikasi risiko akademik lebih dini dan memberikan intervensi yang tepat, sehingga dapat meningkatkan kualitas pendidikan dan tingkat kelulusan mahasiswa
Co-Authors Abdul Hamid Ade Setiawan Akrom, Akrom Andi Taufik Dini Nurlaela Dyah Ayu Astuti Frans Edward Schaduw Hari Sugiarto - UBSI Henny Destiana Lestari Yusuf Mochammad Abdul Azis Muhammad Amir Hasan Muhammad Faisal Muhammad Iqbal Panca Saputra, Elin Priyono Priyono Priyono Purwoko, Agus Rahdian Kusuma Atmaja Ricky Faizal Amir Ridwansyah Ridwansyah Riswandi Ishak Tino Dwiantoro Zulia Imami Alfianti