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All Journal TEKNIK INFORMATIKA Sainteks Jurnal Pseudocode SMATIKA Jurnal Ilmiah KOMPUTASI Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer Jurnal SOLMA Prosiding Seminar Nasional Teknoka Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Sisfokom (Sistem Informasi dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer IJID (International Journal on Informatics for Development) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Linguistik Komputasional Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science FIKROH: JURNAL PEMIKIRAN DAN PENDIDIKAN ISLAM Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Teknosains : Jurnal Sains,Teknologi dan Informatika Infotech: Journal of Technology Information Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer Sibatik Journal : Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer SmartComp Fikroh: Jurnal Pemikiran dan Pendidikan Islam JURNAL TEKNIK INFORMATIKA DAN KOMPUTER Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Cosmic Jurnal Teknik BHAKTI JIVANA
Firman Noor Hasan
Universitas Muhammadiyah Prof. Dr. Hamka
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Evaluasi Penggunaan Aplikasi Getcontact Sebagai Perlindungan Modus Penipuan Dengan Metode User Experience Questionnaire Pavita, Rachma; Hasan, Firman Noor
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5544

Abstract

Era digital saat ini, para penipu menggunakan teknologi untuk keuntungan pribadi. Berpura-pura sebagai orang terdekat atau bahkan karyawan bank adalah salah satu taktik yang sering digunakan. Namun, aplikasi bernama GetContact muncul untuk mengatasi penipuan ini. Aplikasi ini dapat mencari nomor telepon dan menemukan panggilan dan pesan singkat dari kontak yang tidak dikenal. Metode User Experience Questionnaire (UEQ) digunakan dalam penelitian aplikasi GetContact untuk mengukur tingkat kepuasan pengguna dengan berbagai kriteria, seperti daya tarik, efisiensi, ketepatan, stimulasi, dan kebaruan. Hasil penelitian menunjukkan bahwa aplikasi ini memiliki beberapa keuntungan dalam mendeteksi dan menghindari modus penipuan dengan nomor yang tidak dikenal, tetapi ada beberapa kelemahan yang perlu diperbaiki. Dengan nilai sebesar 0.69, ketepatan deteksi nama pada nomor telepon masih dapat ditingkatkan. Selain itu, fitur seperti daya tarik, efisiensi, stimulasi, dan kebaruan aplikasi kurang dari rata-rata. Meskipun aplikasi ini menawarkan kemampuan untuk mengakses informasi dan membantu pengguna menemukan nomor telepon, pengalaman pengguna kurang memuaskan. Namun, penelitian ini menemukan bahwa penggunaan GetContact dapat membantu mengidentifikasi dan mencegah modus nomor tidak dikenal. Aplikasi ini memiliki kelemahan, tetapi masih memiliki potensi untuk berkembang dan memberikan pengalaman pengguna yang lebih baik di masa mendatang.
ANALYSIS OF PUBLIC SENTIMENT RELATED TO THE FAILURE OF INDONESIA TO HOST U-20 USING MULTINOMIAL NAÏVE BAYES CLASSIFIER Zaini, Fachri; Sari, Jessica Windi; Hasan, Firman Noor
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1209

Abstract

The case of Indonesia's failure to host the U-20 World Cup in 2023 has become a hot topic of discussion in Indonesia. The rejection of the Israel U-20 national team and security factors by FIFA are considered the main reasons for the cancellation. This raises many issues and controversies from various parties. In this study, sentiment analysis using the Naive Bayes algorithm was conducted. Researchers use the naive bayes algorithm because this algorithm has high accuracy with simple calculations. The data obtained in this study came from 250 tweets of Twitter data with a ratio of training and test data of 7:3. The results showed good data classification with 97.26% accuracy, 93.33% precision, and 100% recall. In conclusion, the classification model developed can describe public sentiment related to Indonesia's failure in the U-20 World Cup well.
Business Intelligence Visualisasi Data Penerimaan Mahasiswa Baru Menggunakan Tableau di Universitas ABC Anhari, Tirta; Alim, Endy Sjaiful; Rizkiawan, M. Asep; Hasan, Firman Noor; Aulia, Muhammad Fathan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 6, No 1 (2025): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v6i1.570

Abstract

This study aims to analyze the application of Business Intelligence (BI) using Tableau in the new student admission process at ABC University. Tableau is used to visualize admission data for the period 2021 to 2023, including the number of applicants, geographic distribution, and course preferences. The research methodology involves data collection, cleaning, and integration which is then visualized in an interactive dashboard. The results showed a decrease in the number of applicants during the study period, with the lowest applicants in 2024. Geographic distribution analysis shows that DKI Jakarta and West Java provinces still dominate, indicating the need for expansion in conducting promotions and also data-based marketing strategies. In addition, the shift in the interest of applicants from Communication Science study programs to Pharmacist and Management Professions is an important finding, indicating a changing trend in prospective students' preferences for the fields of Communication Science and Business. This study concludes that the implementation of BI using Tableau provides significant benefits in improving the efficiency of decision-making, expanding the range of admissions, and strengthening the competitiveness of ABC University amid changing educational trends. The findings contribute to the literature related to BI implementation in the education sector and recommend further development to optimize university management in the future
Implementation of User Sentiment with Naïve Bayes Algorithm to Analyze LinkedIn Application Regarding Job Vacancies in the Play Store Al Ghozi, Dhiyauddin; Hasan, Firman Noor
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7879

Abstract

Mobile applications have become an important part, one of which is the LinkedIn application which is a mobile application that focuses on the recruitment process, job search and as a professional networking platform which is now increasingly relevant, especially in Indonesia. The methodology involves data collection, data preprocessing, data labeling, and application of the Naïve Bayes algorithm. Sentiment analysis can be used as a reference to improve the quality of an application and the level of user satisfaction as well as knowing the number of positive and negative sentiments in user feedback. The 999 data obtained were then divided into 60% training data and 40% test data. In this analysis, negative sentiment outweighs positive sentiment, with a total of 539 negative reviews and 460 positive reviews. Based on evaluation using the confusion matrix, accuracy results were 95.74%, precision was 100%, and recall was 91.46%. This research aims to provide insight into the communication and interaction patterns of LinkedIn users in relation to job opportunities and overall sentiment towards the platform.
Analisis Sentimen Calon Presiden 2024 di Media Sosial X Menggunakan Naive Bayes dan SMOTE Sunata, Muhamad Hafidz Ardian; Irwiensyah, Faldy; Hasan, Firman Noor
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7708

Abstract

In the era of digital advancement, the utilization of social media has surged, enabling individuals to express their viewpoints openly. This research underscores the utilization of social media platform X as the primary avenue for users to express their opinions, particularly on political matters, notably within the framework of the presidential election. Sentiment analysis techniques, specifically employing the Naïve Bayes algorithm and the Synthetic Minority Oversampling (SMOTE) method, have been the central focus of inquiry to infer people's inclinations toward presidential candidates. Despite numerous antecedent studies, deficiencies persist in terms of precision and data imbalance. This study endeavors to enhance the efficacy of sentiment analysis by integrating the Naïve Bayes approach with SMOTE. By scrutinizing tweets on social media X spanning from December 12, 2023, to March 31, 2024, the data is categorized into positive and negative sentiments. The findings reveal that employing SMOTE bolstered accuracy to 88% for the Ganjar-Mahfud dataset, whereas accuracy without SMOTE languished at approximately 69% for the Anies-Imin dataset. Out of 1589 tweets conveying positive sentiments, approximately 27.7% were directed towards Anies-Imin, 28.7% towards Prabowo-Gibran, and 43.5% towards Ganjar-Mahfud. The preponderance of negative sentiments was aimed at Anies-Imin (41.5%) and Prabowo-Gibran (40.8%).
Rancang Bangun Sistem Informasi Akademik Siswa Berbasis Web: (STUDI KASUS : SMPN 103 JAKARTA) Pamungkas, Dimas; Noor Hasan, Firman
Cosmic Jurnal Teknik Vol 2 No 1 (2025): Februari
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosmic.v2i1.1073

Abstract

SMPN 103 Jakarta merupakan sebuah sekolah yang sudah berdiri sejak tahun 1974 dan mulai beroperasional pada tahun 1978, yang beralamat di Jl. RA.Fadillah Komplek Kopassus, kelurahan cipayung, kecamatan Pasar Rebo, pada saat pihak masih menggunakan cara manual dalam melakukkan input data absensi dan data absensi serta data nilai masih belum terdigitalisasi dengan baik sehingga menyulitkan guru dalam melakukan monitoring siswa bedasarkan data absensi dan data nilai, maka tujuan dari penelitian ini adalah merancang aplikasi sistem informasi akademik siswa berbasis web yang dapat dgunakan guru untuk melakkukan monitoring siswan, dalam membangun sistem ini peneliti menggunakan metode prototyping, dengan bahasa pemrograaman PHP, dan framework Laravel. Hasil dari penelitian ini sebuah aplikasi sistem informasi akademik siswa yang mudah digunakan dalam penggunaan aplikasi.
Analisis Sentimen Tanggapan Masyarakat Terhadap Penutupan TikTok Shop Menggunakan Metode Naïve Bayes Fadli, Khairul; Hasan, Firman Noor
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.6060

Abstract

E-commerce has become an important role in driving the economy, many business actors, especially MSMEs, depend on selling their products online. E-commerce continues to experience extraordinary growth, many breakthroughs have been made to improve its systems and services. One of them is social commerce which utilizes social interactions from social network users, for example TikTok Shop. However, the government changed regulations regarding social commerce which resulted in the closure of TikTok Shop operations in Indonesia, which many reactions and opinions from the public. Therefore this research was conducted with aim of analyzing public sentiment towards the closure of TikTok Shop. This research uses 1233 data taken and collected from social media X in the range September to December 2023. This research also uses the Naïve Bayes Classifier algorithm method with a training data to test data ratio of 80:20. This research resulted in accuracy of 90,24%, precision of 74,33%, and recall of 100%. The large number of negative sentiments in this sentiment analysis shows the public’s disappointment with the policy changes carried out by the government which resulted in the closure of TikTok Shop operations in Indonesia.
Utilization of the FP-Growth Algorithm on MSME Transaction Data:Recommendations for Small Gifts from The Padang Region Firman Noor Hasan; Riyan Ariyansah
JURNAL TEKNIK INFORMATIKA Vol 17, No 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37966

Abstract

The existence of adequate transaction data turns out to have a similar sales transaction pattern for MSMEs, so it would be a shame if it were left like that. Moreover, this data can be used to increase efficiency in MSMEs in the culinary sector, one of which is as a recommendation for small gifts. The study uses the Association Rules technique, whereas fp-growth is used to obtain a combination of elements. The goal is to facilitate MSMEs' ability to suggest small gifts to clients. The fp-growth algorithm calculation was implemented to process 2043 data originating from transaction data in MSMEs, with the specified minimum support value being 15%, while the minimum confidence value determined was 55%. The results of the trial obtained the two best rules, namely, "If a customer buys a list of small gifts from Balado Sanjai Chips, then the customer will buy Jangek Crackers" and "If a customer buys Jangek Crackers, then the customer will buy Sanjai Balado Chips".
Analisa Kinerja Algoritma Random Forest dan XGBoost dalam Klasifikasi Penyakit Cacar Monyet (Monkeypox) Krisna, Mohammad Dito Dwi; Hasan, Firman Noor
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.7167

Abstract

Monkeypox is a contagious disease that requires prompt and accurate handling, particularly in the diagnostic process. However, identifying symptomps manually often takes time and is prone to error. In response to this challenge, this study aims to develop a machine learning based classification model to support a more efficient diagnosis process. This research applies two machine learning algorithms XGBoost regression and Random Forest regression to classify patients as infected or uninfected with monkeypox based on clinical symptoms. The study focuses on assessing how well each algorithm can distinguish between positive and negative cases, especially when dealing with imbalanced data or overlapping features. The dataset used consists of 25.000 entries sourced from Kaggle, each containing clinical indicators related to monkeypox. Before modeling, the data underwent exploratory data analysis (EDA) and preprocessing, including handling missing values. Furthermore, cross-validation and parameter tuning techniques were implemented to optimize model performance. The results indicate that XGBoost outperformed Random Forest, achieving 68% accuracy, 69% precision, 89% recall, and a 78% F1-score. In contrast, Random Forest yielded slightly lower scores. Both models were evaluated using the ROC curve, where each reached an AUC values of 0.60. This suggests that wile both models show potential, their ability to clearly distinguish between classes positive and negative remains limited and can be improves in future work.
Penerapan FP-Growth dan Random Forest dalam Analisis Data Penjualan Makanan Ringan Afandi, Irfan Ricky; Wahyuningtyas, Irma; Fathurrohman, Sewin; Hasan, Firman Noor
InComTech : Jurnal Telekomunikasi dan Komputer Vol 15, No 1 (2025)
Publisher : Department of Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/incomtech.v15i1.30260

Abstract

Penelitian ini bertujuan untuk menganalisis pola pembelian produk makanan ringan serta memprediksi penjualan produk dengan menggunakan pendekatan data mining dan machine learning. Dalam industri makanan ringan yang semakin kompetitif pemahaman mendalam tentang pola perilaku konsumen dan tren penjualan produk sangat penting untuk pengambilan keputusan bisnis yang lebih efektif serta peningkatan profitabilitas perusahaan. Tantangan utama dalam penelitian ini adalah mengidentifikasi variabel yang relevan dalam dataset penjualan untuk mengungkap pola asosiasi antar produk dan menghasilkan prediksi penjualan yang akurat. Metodologi yang digunakan dalam penelitian ini melibatkan algoritma FP-Growth untuk menemukan asosiasi produk yang sering dibeli bersamaan serta algoritma Random Forest untuk memprediksi penjualan berdasarkan data historis. Hasil penelitian dari penerapan algoritma FP-Growth mampu mengidentifikasi sembilan aturan asosiasi yang potensial untuk diterapkan dalam sistem rekomendasi produk untuk menyediakan rekomendasi produk yang lebih personal kepada konsumen. Selain itu, model prediksi menggunakan Random Forest menunjukkan performa yang baik dengan nilai Mean Absolute Error (MAE) sebesar 23,54, Root Mean Squared Error (RMSE) sebesar 36,36 dan R-squared sebesar 0,86 dengan keseluruhan menunjukkan tingkat akurasi yang cukup baik. Penelitian ini memberikan kontribusi penting dalam optimasi stok dan strategi pemasaran berbasis data. Penelitian lanjutan disarankan menggunakan data yang lebih bervariasi dan periode waktu yang lebih panjang untuk meningkatkan akurasi prediksi.
Co-Authors Abdillah, Allif Rizki Abdul Syakir Achmad Ramadhan Achmad Sufyan Aziz Afandi, Irfan Ricky Affandi, Irfan Ricky Afikah, Prista Afnan Sabili, Dian Ainurrafik Agus Fikri Agus Fikri Ahmad Rizal Dzikrillah Ahmad Rizal Dzikrillah Ahmad Roshid Ahmad Syahril Ahmad Syahril Al Ghozi, Dhiyauddin Alfandi Safira Alim, Endy Sjaiful Allif Rizki Abdillah Allif Rizki Abdillah Ammar Rusydi Ananda Prasta Warasati Janah Ananda, Ridha Faiz Andika Saputra Andriani, Vivi Anhari, Tirta Anwar Hidayat Ari Wibowo Arief Wibowo Arien Bianingrum Rossianiz Arvin Rafialdo Aulia, Muhammad Fathan Avorizano, Arry Azhar Haikal Anwar Azhar Haikal Anwar Bagas Kembar Rezkyllah Bahrul Rozak Bahrul Rozak Dan Mugisidi Dandie Triyanto Desty Afni Dewi Mayangsari Dian Ainurrafik Afnan Sabili Dian Ainurrafik Afnan Sabili Diana Fitri Lessy Diana Fitri Lessy Dimas Febriawan Dimas Febriawan Dimas Febriawan Dion Parisda Ray Djeli Moh Yusuf Doni Gunawan Rambe E Erizal Erizal Erizal Erizal Erizal Estu Sinduningrum Estu Sinduningrum Fachri Zaini Fadli Al Gani Fadli Hardiyanto Putra Fadli, Khairul Faisal Parsakh Nursyamsi Faisal Parsakh Nursyamsyi fajar sidik Fajar Sidik Faldy Irwiensyah Faldy Irwiensyah Faldy Irwiensyah, Faldy Farhan Bias Purnama Putra Farhan Nufairi Farhan Nufairi Fathurrohman, Sewin Fauzan Setya Ananto Fauzi Kurniawan Fayakun Kun Febriandirza, Arafat Febriawan, Dimas Hafizh Dhery Al Assyam Handika, Yusuf Hanif, Isa Faqihuddin Hardyatman, Intan Diah Hazbi Santoso Hibatullah Faisal Hibatullah Faisal Hibatullah Faisal Hilmi Ammar Hilmy Zhafran Muflih I Ketut Sudaryana, I Ketut Ibnu Suhada Indra Ramadhan Indra Ramadhan Indriyanti, Prastika Intania Widyaningrum Irawati Irawati Irfan Ricky Affandi Isnan Wisnu Prastiyo Kamayani, Mia Krisna, Mohammad Dito Dwi Kurniyati Nur Lathifah Dini Rachmawati Lingga Lingga Lingga Lita Astri Pramesti Luqman Abdur Rahman Malik Luthfi Akbar Ramadhan M. Asep Rizkiawan Meliyawati MILASARI, LISA ASTRIA Mohammad Akhdaan Juliandra Muchammad Sholeh Muchammad Sholeh Muflih, Hilmy Zhafran Muhamad Saiful Arif Muhammad Abid Fajar Muhammad Ardhi Ryan Saputra Muhammad Ikhwan Muhammad Ikhwan Muhammad Rafly Al Fattah Zain Muhammad Ridwan Muhammad Rifansyah Mukti, Avis Tantra Mutiara Zahra Arifin Nisa Qonita Rizkina Nofendri, Yos Nugroho, Dendy Aprilianto Nunik Pratiwi Oktarina Heriyani Pamungkas, Dimas Panji Islami Anakku Pavita, Rachma Pranata, Ananda Bagas Prisilia Talakua Prista Afikah Purnamaningsih, Ine Rahayu Putri, Kirana Alyssa Rafli Erlangga Rahman Malik, Luqman Abdur Rahmatullah, Ahmad Faiz Ramadhita, Nindia Fitri Ramzah, Harry Reisa Inayah Rian gustini Ridwan Maulana Subekti Rika Nurhayati Riyan Ariyansah Rizki Alamsyah Rizki Kamelia Rizky Ramdhani Rosalina Rozak, Bahrul Saputra, Ramadani Sari, Jessica Windi Sari, Laila Atikah Setiawan, Ahmat Simamora, Silvia Damayanti Sinduningrum, Estu Sistani, Muhammad Ghiffar Siti Nurhaliza Sri Fitriani Sunata, Muhamad Hafidz Ardian Syahri, Alfi Tasya Rizki Salsabilla Tia Anggita Sari Transiska, Dwi Wahyu Stiyawan Wahyuningtyas, Irma Wanda Aulia Widyastuti Andriyani Windi Al Azmi Wulandari, Sania Zahra, Khofifah Humaeroh Az Zaini, Fachri Zuhri Halim Zuhri Halim, Zuhri