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All Journal Jurnal Informatika Jurnal Ilmiah Matrik JURNAL ILMIAH INFORMATIKA Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat METIK JURNAL Building of Informatics, Technology and Science Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika ILKOMNIKA: Journal of Computer Science and Applied Informatics JATI (Jurnal Mahasiswa Teknik Informatika) IJITEE (International Journal of Information Technology and Electrical Engineering) Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sains Komputer dan Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Jurnal Informatika Terpadu International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Jurnal Informatika Teknologi dan Sains (Jinteks) Sci-Tech Journal Sewagati: Jurnal Pengabdian Masyarakat Indonesia Safari : Jurnal Pengabdian Masyarakat Indonesia Adopsi Teknologi dan Sistem Informasi Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Jurnal Informatika Polinema (JIP) GEMBIRA (Pengabdian Kepada Masyarakat) Buffer Informatika JSE Journal of Science and Engineering Jurnal Abdimas Mahakam
Naufal Azmi Verdikha
Teknik Informatika, Universitas Muhammadiyah Kalimantan Timur
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Peningkatan Pelayanan Administrasi Masyarakat di Desa Loa Duri Ulu Menggunakan Sistem Informasi Berbasis Web (SIMPELDES) Faldi Faldi; Naufal Azmi Verdikha; Intan Kinanthi Damarin Tyas
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol 7 No 3 (2022): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v7i3.2859

Abstract

Administrative control is a way for an institution to archive or discipline its administration correctly. Loa Duri Ulu Village is one of the villages located in Loa Janan District, Kutai Kartanegara Regency, East Kalimantan. Currently, the service administration system in the village of Loa Duri Ulu is still manual. Every community that needs documents related to a population still has to come to the village office to take care of these documents and record them into a book manually to impact the village office in carrying out their duties. This community service aims to overcome administrative service problems in Loa Duri Ulu Village by creating an administrative service information system. In this research-based community service, an iterative model strategy is used in the Software Development Life Cycle (SDLC), including several stages. This method consists of 5 stages: Planning Stages, Analysis Stages, Web Design Stages, SIMPELDES web Implementation Stages, and Maintenance Stages. The result of this service is that a web called the SIMPELDES web has been created and designed where this web has service features for various types of inputting and archiving letters in Loa Duri village. With an administrative application system and community service that is connected to the community database, it will be faster to get the required letters, both new letters, and old ones.
Study of Undersampling Method: Instance Hardness Threshold with Various Estimators for Hate Speech Classification Naufal Azmi Verdikha; Teguh Bharata Adji; Adhistya Erna Permanasari
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (969.833 KB) | DOI: 10.22146/ijitee.42152

Abstract

A text classification system is needed to address the problem of hate speech in social media. However, texts of hate speech are very hard to find in social media. This will make the distribution of training data to be unbalanced (imbalanced data). Classification with imbalanced data will make a poor performance. There are several methods to solve the problem of classification with imbalanced data. One of them is undersampling with Instance Hardness Threshold (IHT) method. IHT method balances the dataset by eliminating data that are frequently misclassified. To find those data, IHT requires an estimator, which is a classifier. This research aims to compare estimators of IHT method to solve imbalanced data problem in hate speech classification using TF-IDF weighting method. This research uses the class ratio of dataset after undersampling, time of the undersampling process, and Index of Balanced Accuracy (IBA) evaluation to determine the best IHT method. The results of this research show that IHT method using the Logistic Regression (IHT(LR)) has the fastest undersampling process (1.91 s), perfectly balance dataset with the class ratio is 1:1, and has the best of IBA evaluation in all estimation process. This result makes IHT(LR) be the best method to solve the imbalanced data problem in hate speech classification.
KOMPARASI ALGORITMA KLASIFIKASI UNTUK MENENTUKAN EVALUASI KINERJA TERBAIK PADA STATUS AKREDITASI SEKOLAH/MADRASAH KALIMANTAN TIMUR BERDASARKAN IASP 2020 Taghfirul Azhima Yoga Siswa; Naufal Azmi Verdikha
Jurnal Informatika Teknologi dan Sains Vol 4 No 3 (2022): EDISI 13
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.33 KB) | DOI: 10.51401/jinteks.v4i3.1807

Abstract

Indonesia mulai beradaptasi pada era revolusi industri 4.0 ke era society 5.0 dengan penerapan teknologi modern dan penciptaan peluang baru pada semua aspek kehidupan. Selain pengembangan infrastruktur, rencana pemindahan Ibu Kota Negara (IKN) ke Provinsi Kalimantan Timur (KALTIM) juga menjadi catatan penting dalam kesiapan sumber daya manusia yang berkualitas yang dapat dilihat dari mutu pendidikan dengan status akreditasi sekolah. Penelitian ini bertujuan untuk melakukan komparasi terhadap beberapa algoritma klasifikasi seperti C4.5, Naïve Bayes, K-Nearest Neighbor (K-NN), Support Vector Machine (SVM) dan  Logistic Regression untuk mencari kinerja terbaik dalam klasifikasi status akreditasi sekolah/madrasah provinsi Kalimantan Timur berdasarkan IASP 2020. Tahap preprocessing membagi data dilakukan menggunakan metode cross validation yang bersumber pada data BAN S/M KALTIM tahun 2020-2021 berjumlah 295 record. Kemudian dilakukan evaluasi kinerja algoritma untuk mencari nilai Accuracy, Precision dan Recall menggunakan confusion matrix. 
KOMPARASI METODE E-SERVQUAL DAN EUCS UNTUK MENGANALISIS TINGKAT KEPUASAN DOSEN DALAM PERKULIAHAN ONLINE PADA MASA PANDEMI COVID-19 BERBASIS LMS DI UMKT Taghfirul Azhima Yoga Siswa; Naufal Azmi Verdikha
Jurnal Ilmiah Matrik Vol 23 No 3 (2021): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v23i3.1525

Abstract

Universitas Muhammadiyah Kalimantan Timur (UMKT) merupakan universitas yang mengusung konsep IT-Based Paperless University berupaya menerapkan perkuliahan online yang ideal dengan menggunakan Learning Management System (LMS) berbasis website / mobile yang bekerja sama dengan Openlearning.com Australia. Harapannya proses belajar mengajar dapat dilakukan kapan saja dan dimana saja tanpa dibatasi ruang dan waktu namun tetap mengedepankan standar dan kualitas perkuliahan yang sesuai dengan aturan yang berlaku. Penelitian ini dilakukan dengan cara menyebarkan kuesioner kepada responden yaitu dosen sebagai pengguna LMS Openlearning dan dilakukan pemilihan responden dengan teknik random sampling dan rumus slovin sehingga didapatkan 114 orang untuk dijadikan sampel dalam penelitian ini. Kuesioner yang disebarkan terdiri dari dua instrumen yaitu berdasarkan dimensi metode EUCS dan E-ServQual. Tujuan dari penelitian ini adalah untuk mengetahui persentase tingkat kepuasan dosen dalam menerapkan openlearning untuk proses perkuliahan online yang diukur dengan komparasi analisis pendekatan metode EUCS dan E-ServQual serta gap antara kedua kuesioner tersebut, sehingga harapannya dapat memberikan hasil rekomendasi bagi Universitas Muhammadiyah Kalimantan Timur untuk mengevaluasi keberhasilan perkuliahan online yang sudah berjalan. Hasil penelitian menunjukan bahwa tingkat kepuasan dosen UMKT dalam perkuliahan online berbasis LMS Openlearning menggunakan metode EUCS sebesar 78,33% dengan selisih sebesar 9,98% sedangkan saat menggunakan metode E-ServQual tingkat kepuasan pengguna sebesar 73,15% dengan selisih sebesar 8%. Dari hasil analisis komparasi kedua metode tersebut didapatkan persentase kepuasan pengguna menggunakan metode EUCS lebih tinggi daripada metode E-ServQual walaupun memiliki range kategori yang sama yakni puas.
The application of particle swarm optimization (PSO) to improve the accuracy of the naive bayes algorithm in predicting floods in the city of Samarinda Faldi Faldi; Trisha NurHalisha; Wawan Joko Pranoto; Hendra Saputra; Asslia Johar Latipah; Sayekti Harits Suryawan; Naufal Azmi Verdikha
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 3 (2023): September : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i3.148

Abstract

This study focuses on the implementation of Particle Swarm Optimization (PSO) to enhance the accuracy of the Naive Bayes algorithm in predicting floods specifically in the city of Samarinda. The aim is to improve the efficiency and precision of flood prediction models in order to mitigate the impact of flooding in the area. The results of this research highlight the effectiveness of PSO in optimizing the Naive Bayes algorithm, showing promising potential for more accurate flood prediction and proactive measures in Samarinda. The accuracy value obtained from testing using the Naive Bayes method alone is 91.12%. However, there is an improvement in accuracy after conducting testing with the optimization technique based on Particle Swarm Optimization (PSO) and the Naive Bayes algorithm. The conducted testing achieved an accuracy value of 94.38%. This accuracy result is higher compared to testing without optimization.
Pembuatan Aplikasi Persediaan Barang Berbasis Web Pada PT. Bayan Resources Tbk Ririn Wahyuni; Muhammad Taufiq Sumadi; Naufal Azmi Verdikha
SAFARI :Jurnal Pengabdian Masyarakat Indonesia Vol. 4 No. 1 (2024): Januari : Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/safari.v4i1.1148

Abstract

This research aims to design and implement a web-based Goods Inventory Information System at PT Bayan Resources Tbk. The company faces challenges in inventory management, such as stock uncertainty, variations in order cycle time, and operational efficiency levels that need to be improved. Waterfall method is used as a framework for system development, with stages of requirement analysis, design, implementation, testing, and maintenance. The system is designed to improve operational efficiency through integration of inventory data, order management, and item tracking. The result is a web-based application with features such as a secure login page, informative dashboard, master data management, efficient input of incoming and outgoing goods, and careful user control. With the implementation of dark mode, the system gives users the flexibility to customize the display according to their preferences. Users can easily access, track, and analyze inventory data, supporting faster and more accurate decision-making for the company.
Pelatihan Instalasi Dasar Sistem Operasi Linux Versi Debian Pada Siswa SMK Muhammadiyah Loa Janan Zayni Zayni; Muhammad Taufiq Sumadi; Nauval Azmi Verdikha
SEWAGATI: Jurnal Pengabdian Masyarakat Indonesia Vol. 2 No. 4 (2023): Desember : Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/sewagati.v2i4.1125

Abstract

The community service program at SMK Muhammadiyah Loa Janan focuses on installing the Debian Linux operating system and virtualization using Virtualbox. Over a three-month period, three study groups were involved by dividing two training sessions per day. The implementation method involves theory and practice with emphasis on a basic understanding of Debian Linux operating system installations. This outline reflects the challenges of students' lack of technical skills in the face of technological advances. The solution is intensive training with the support of guest teachers from the Informatics Engineering Study Program. Integrated implementation methods include material introduction, practice, and evaluation. The results noted an increase in students' understanding and skills in Debian Linux installations, with recommendations for additional resources.
Evaluasi Support Vector Machine Dengan Optimasi Metode Genetic Algorithm Pada Klasifikasi Banjir Kota Samarinda Evitasari, Yuliana Dilla; Pranoto, Wawan Joko; Verdikha, Naufal Adzmi
Jurnal Sains Komputer dan Teknologi Informasi Vol. 6 No. 1 (2023): Jurnal Sains Komputer dan Teknologi Informasi
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/jsakti.v6i1.5462

Abstract

Banjir merupakan bencana alam yang sering terjadi di Indonesia, terutama di kota Samarinda yang terletak di Kalimantan Timur. Penelitian ini bertujuan untuk meningkatkan akurasi dengan menerapkan metode seleksi fitur menggunakan Genetic Algorithm (GA). Melalui analisis data banjir kota Samarinda, ditemukan bahwa terdapat tiga atribut yang paling berpengaruh terhadap terjadinya banjir, yaitu kelembapan, lamanya penyinaran matahari, dan kecepatan angin. Selanjutnya, penelitian ini menggunakan algoritma Support Vector Machine (SVM) untuk mengklasifikasikan data banjir. Dengan menerapkan seleksi fitur menggunakan GA, hasil pengujian menunjukkan peningkatan akurasi algoritma SVM sebesar 13.45%. Sebelum penerapan seleksi fitur, akurasi SVM hanya mencapai 52,71%, namun setelah penerapan seleksi fitur menggunakan GA, akurasi meningkat menjadi 66,16%. Hasil ini membuktikan bahwa seleksi fitur dengan menggunakan GA efektif dalam meningkatkan akurasi prediksi banjir. Kesimpulan dari penelitian ini adalah seleksi fitur menggunakan GA dapat mengidentifikasi atribut-atribut yang paling berpengaruh terhadap terjadinya banjir di kota Samarinda. Penerapan seleksi fitur ini menghasilkan peningkatan signifikan dalam akurasi algoritma SVM untuk prediksi banjir.
Analisis Pengaruh Gain Ratio Untuk Algoritma K-Nearest Neighbor Pada Klasifikasi Data Banjir di Kota Samarinda Sari, Septa Intan Permata; Pranoto, Wawan Joko; Verdikha, Naufal Azmi
Jurnal Sains Komputer dan Teknologi Informasi Vol. 6 No. 1 (2023): Jurnal Sains Komputer dan Teknologi Informasi
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/jsakti.v6i1.5472

Abstract

Berdasarkan data yang diperoleh dari BMKG dan BPBD Kota Samarinda, diketahui bahwa telah terjadi bencana banjir pada periode tahun 2019 - 2020 di Kota Samarinda. Penelitian ini bertujuan untuk melakukan klasifikasi data banjir di Kota Samarinda menggunakan algoritma K-Nearest Neighbor dan pembagian data menerapkan teknik 5-Fold Cross-Validation serta perhitungan rumus jarak Euclidean Distance. Kemudian, dilakukan seleksi fitur pada algoritma KNN menggunakan metode Gain Ratio guna mengetahui pengaruhnya terhadap akurasi dari KNN. Hasil penelitian menunjukkan bahwa peningkatan akurasi tertinggi setelah menerapkan Gain Ratio didapatkan oleh K=7 dengan persentase kenaikan akurasi sebesar 5,95%, diikuti oleh K=5 dengan persentase kenaikan akurasi 5,81%, K=3 dengan persentase kenaikan akurasi 5,68%, K=9 sebesar 3,61%, K=11 sebesar 2,44%, dan K=13 sebesar 1,23%. Hanya ada satu akurasi yang tidak mengalami peningkatan atau penurunan akurasi, yaitu K=15.
Analisis DistilBERT dengan Support Vector Machine (SVM) untuk Klasifikasi Ujaran Kebencian pada Sosial Media Twitter Azmi Verdikha, Naufal; Habid, Reza; Johar Latipah, Asslia
METIK JURNAL Vol 7 No 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.583

Abstract

Hate speech is a significant issue in content management on social media platforms. Effective classification of hate speech plays a crucial role in maintaining a safe social media environment, combating discrimination, and protecting users. This study evaluates a hate speech classification model using SVM with linear and polynomial kernels. The dataset used consists of labeled Indonesian-language tweets. The importance of developing an effective classification model to address hate speech has led to the utilization of DistilBERT as a feature extraction method. However, DistilBERT has high-dimensional features, necessitating dimensionality reduction to reduce model complexity. Therefore, in this study, the PCA dimensionality reduction method is implemented with various scenarios of dimensionality, namely 10, 20, 30, 40, and 50. Evaluation is performed using F1-Score, and the entire study is evaluated using 10-fold cross-validation. The evaluation results indicate that in the scenario with a linear kernel, the model achieves the highest F1-Score of 0.75 in the 50-dimensional scenario. Meanwhile, in the scenario with a polynomial kernel, the model achieves the highest F1-Score of 0.7857 in the 50-dimensional scenario. These findings demonstrate that the use of a polynomial kernel with 50 dimensions yields the best performance in classifying hate speech.
Co-Authors Abdul Rahim Achmad, Arda Fahmi Adhistya Erna Permanasari Ahmad Ilham Ahmad Ridhani Mubaraq Alam, Fajar Amru Omar Arbansyah Arbansyah Aspianur Asslia Johar Latipah Assliah Johar Latipah Bulan Suci Cahayawati Dwiagam, Junianda Haris Evitasari, Yuliana Dilla Fahrezi, Irqi Anbi Fajar Alam Faldi Faldi Faldi Faldi Fattah, Mi'raj Fendy Yulianto Fiqri, Mohammad Hiqmal Fitri Damayanti Habid, Reza Hasudungan, Rofilde Hendra Saputra Hery Tri Waloyo Hidayati Ramadhani, Novia Husni Thamrin Ikram, Muhammad Ilham, Muhammad Fauzan Nur Johar Latipah, Asslia Latipah, Asslia Johar Muhamad Ridwan Muhamad Wahyu Tirta Muhammad Fauzan Nur Ilham Muhammad Najeri Al Syahrin Muhammad Taufiq Sumadi Muhammad Taufiq Sumadi Muthmainnah Muthmainnah Nuraini, Nabila Nurdiansyah, Rendy Octaviany, Dinda Nur Pranata, Aditya Pranata, Ricky Albin Rahmad Fahrozi, Mu. Aldi Reza Andriyanti Ridhoi, Reno Ririn Wahyuni Rudiman Rudiman, Rudiman Sari, Septa Intan Permata Sayekti Harits Suryawan Susanto, Muhammad Riza Radyaka Syahrandi, Akmal Taghfirul Azhima Yoga Siswa Takhta Perlawanan Putra Sinawang Teguh Bharata Adji Tri Wahyudi Trisha NurHalisha Tyas, Intan Kinanthi Damarin Wawan Joko Pranoto Wawan Joko Pranoto Wisnu Ismunandar Zayni Zayni