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All Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika ILKOM Jurnal Ilmiah Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Teknologi Informasi Indonesia
Sukrianto, Darmanta
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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ANALYSIS OF SLOW MOVING GOODS CLASSIFICATION TECHNIQUE: RANDOM FOREST AND NAïVE BAYES Jollyta, Deny; Gusrianty, Gusrianty; Sukrianto, Darmanta
Khazanah Informatika Vol. 5 No. 2 December 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v5i2.8263

Abstract

Classifications techniques in data mining are useful for grouping data based on the related criteria and history. Categorization of goods into slow moving group or the other is important because it affects the policy of the selling. Various classification algorithms are available to predict labels or class labels of data. Two of them are Random Forest and Naïve Bayes. Both algorithms have the ability to describe predictions in detail through indicators of accuracy, precision, and recall. This study aims to compare the performance of the two algorithms, which uses testing data of snacks with labels for package type, size, flavor and categories. The study attempts to analyze data patterns and decides whether or not the goods fall into the slow moving category. Our research shows that Random Forest algorithm predicts well with accuracy of 87.33%, precision of 85.82% and recall of 100%. The aforementioned algorithm performs better than Naïve Bayes algorithm which attains accuracy of 84.67%, precision of 88.33% and recall of 92.17%. Furthermore, Random Forest algorithm attains AUC value of 0.975 which is slightly higher than that attained by Naïve Bayes at 0.936. Random Forest algorithm is considered better based on the value of the metrics, which is reasonable because the algorithm does not produce bias and is very stable.
N-gram and Kernel Performance Using Support Vector Machine Algorithm for Fake News Detection System Jollyta, Deny; Gusrianty, Gusrianty; Prihandoko, Prihandoko; Sukrianto, Darmanta
ILKOM Jurnal Ilmiah Vol 15, No 3 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i3.1770.398-404

Abstract

The modern technological advancements have made it simpler for fake news to circulate online. The researchers have developed several strategies to overcome this obstacle, including text classification, distribution network analysis, and human-machine hybrid methods. The most common method is text categorization, and many researchers offer deep learning and machine learning models as remedies. An Indonesian language fake news detection system based on news headlines was developed in this work using the Support Vector Machine (SVM) kernel and n-gram. The objective of this research is to identify the model that produces the best performance outcomes. The system deployment on the web will employ the model that produces the greatest outcomes. According to the research findings, the linear kernel SVM algorithm produces the best results, with an accuracy value of 0.974. Furthermore, the bigram feature used in the development of a classification model does not increase the precision of fake news identification in Indonesian. Utilizing the unigram function yields the most accurate results.
Implementasi Sistem Informasi Notulen Rapat Dan Penugasan Pegawai Pada Dinas Pangan, Tanaman Pangan Dan Hortikultura Muhammad, Muhammad; Oktarina, Dwi; Sukrianto, Darmanta; Purjumatin, Purjumatin
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.5931

Abstract

The minutes of the meeting are recordings made as a conclusion of the discussions that take place in the meeting process, while the appointment of officials is the assignment of duties to officials in accordance with their respective fields. The current recordings of the minutes of the meeting are still done manually; the minutes are recorded closely at the meeting and are stored in the archive of the notes until they are stacked and vulnerable to damage. The current staff assignment is still done manually by the chief of the service, who makes the staff appointment letter, then prints the staff assignments and gives them to the staff through the staff and general officers department, so it will take quite a long time. The methods used in the minutes of the meeting and the appointment of staff are prototype methods where data collection techniques are used, including interviews and observations, whereas the design methods in this design are described as using case diagrams, activity diagrams, sequence diagrams, and class diagrams. The objective of the research is to transform the manual system into a web-based system that can be accessed online as well as to provide ease in managing the minutes of meetings and staff appointments at the Food Plant and Horticulture Service.
Implementasi Framework Laravel Seleksi Pengajuan Bantuan Pendidikan Pada Baznas Kota Pekanbaru Sukrianto, Darmanta; Oktarina, Dwi; Prasetyo, Prasetyo
Jurnal Teknologi Informasi Indonesia (JTII) Vol 9 No 1 (2024): Jurnal Teknologi Informasi Indonesia (Mei)
Publisher : JURNAL TEKNIK INFORMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30869/jtii.v9i1.1324

Abstract

Bantuan pendidikan adalah dukungan atau bantuan yang diberikan kepada individu atau kelompok yang membutuhkan untuk mengakses pendidikan. Pada BAZNAS Kota Pekanbaru terdapat program bantuan pendidikan. Proses dalam mengajukan bantuan pendidikannya saat ini masih menggunakan cara konvensional yaitu peserta harus datang menanyakan bantuan, lalu kembali lagi untuk mengumpulkan berkas persyaratan bantuan pendidikan sehingga peserta harus mengeluarkan biaya untuk transportasi dan memerlukan waktu yang cukup lama. Metode yang digunakan dalam pengajuan bantuan pendidikan adalah metode prototype dimana teknik pengumpulan data yang digunakan antara lain wawancara dan observasi. Metode desain pada langkah perancangan ini digambarkan dengan menggunakan use case diagram, activity diagram, sequence diagram, class diagram. Perancangan aplikasi menggunakan bahasa pemograman PHP dengan framework laravel dan MySQL sebagai database. Tujuan dari penelitian ini adalah membangun sistem informasi seleksi penerima pengajuan bantuan pendidikan berbasis web yang mempermudah bagi BAZNAS Kota Pekanbaru, dan mempercepat proses pengolahan data yang valid dalam sistem informasi seleksi penerima pengajuan bantuan pendidikan berbasis web bagi BAZNAS Kota Pekanbaru.
Co-Authors Deny Jollyta Dwi Oktarina Gusrianty, Gusrianty Muhammad Muhammad Prasetyo Prasetyo Prihandoko Prihandoko Purjumatin Purjumatin