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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
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisis Sentimen Komentar Netizen Terhadap Pembubaran Konser NCT 127 Menggunakan Metode Naive Bayes Nisa Qonita Rizkina; Firman Noor Hasan
Journal of Information System Research (JOSH) Vol 4 No 4 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i4.3803

Abstract

The present rate of technological advancement has resulted in the rapid spread of information, which is easily available through social media platforms such as Twitter. Users of Twitter can send and read content in the form of text or videos using the facilities that Twitter itself offers. Numerous Twitter users have commented on the NCT 127 concert's recent dissolution, which has drawn both supportive and critical remarks. A dataset of 2451 tweets was created by gathering information from Twitter using the keyword "nct" between November 4 and November 6, 2022. The data was subsequently cleaned, yielding a total of 2451 useable data points. Labeling and the Naive Bayes algorithm were then applied to the data. The goal of this study was to count the number of favorable and unfavorable tweets and evaluate how well the Naive Bayes algorithm was applied. According to the trials done, there were 559 favorable remarks and 1,892 negative ones. The accuracy of the evaluation tests was 82.01%. Additionally, the analysis of negative sentiment produced a f1-score of 79.21%, a recall of 68.52%, and precision of 93.84%. Contrarily, the evaluation of positive attitude produced a f1-score of 84.15%, a recall of 95.50%, and a precision of 75.21%. The Naive Bayes method, it may be inferred, can categorize and process with a very consistent accuracy that approaches near-perfect outcomes.
Analisis Sentimen Masyarakat Terhadap Perilaku Korupsi Pejabat Pemerintah Berdasarkan Tweet Menggunakan Naive Bayes Classifier Abdul Syakir; Firman Noor Hasan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6648

Abstract

The corrupt behavior of government officials is a problem that worries the public and threatens the integrity of the government system. In today's digital era, social media is an important means for the public to voice their opinions and sentiments on social issues, including the corruption of government officials. This study aims to analyze public sentiment toward the corrupt behavior of government officials based on tweet data on social media using the Naïve Bayes Classifier method. Tweet data is taken from social media Twitter related to corruption cases involving government officials within a certain period. The data is then processed to remove irrelevant elements and extract the sentiments contained in the tweets The Naïve Bayes Classifier method is applied to classify these tweets of positive, negative, or neutral sentiment toward corrupt behavior from government officials. The results of this study conclude that the public is very angry, disappointed, and has a low level of trust in corrupt behavior committed by government officials. Proven by the most dominant sentiment category is negative sentiment with 224 data and 95 data fall into the positive sentiment category.
Implementasi Teknik Clustering untuk Meningkatkan Performa Aplikasi Node JS Bahrul Rozak; Erizal Erizal; Firman Noor Hasan
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 4 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i4.4532

Abstract

Permasalahan yang sering kali muncul pada aplikasi berbasis server side, adalah request request dan response dalam jumlah yang besar. Proses request serta response akan terus berlanjut selama pengguna berinteraksi dengan aplikasi, Jika hal ini terus berlanjut maka penggunaan sumber daya (resource) yang berlebih pada CPU dapat menjadikan perfoma aplikasi tidak optimal bahkan dapat menimbulkan crash, yang berdampak pada layanan dan kualitas aplikasi. Oleh karena itu, diperlukan teknik untuk menangani permasalahan tersebut. Metode yang diimplementasikan pada penelitian ini ialah membuat aplikasi berbasis server side dengan dua spesifikasi yaitu dengan module cluster dan tanpa module cluster, selanjutnya kedua aplikasi dengan spesifikasi yang berbeda, masing-masing akan dilakukan tahap pengujian performa serta monitoring, kemudian dilakukan proses analisa hasil perbandingan untuk mendapatkan kesimpulan. Module cluster akan membantu untuk melakukan teknik clustering, teknik clustering ialah mengelompokkan proses yang sama serta sering dieksekusi. Dengan teknik ini beban kerja pada CPU akan terdistribusi, sehingga memberikan peningkatan performa aplikasi.
Pandemi Covid-19 Serta Pengaruhnya Terhadap Aktivitas Ibadah Dan Nilai-Nilai Al Islam Kemuhammadiyahan Firman Noor Hasan
Fikroh: Jurnal Pemikiran dan Pendidikan Islam Vol. 14 No. 2 (2021): Fikroh: Jurnal Pemikiran dan Pendidikan Islam
Publisher : Program Studi Pendidikan Agama Islam (PAI) Sekolah Tinggi Agama Islam Al Azhar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37812/fikroh.v14i2.192

Abstract

During the Covid-19 pandemic, the government implemented WFH (Work From Home), LFH (Learn From Home), and PFH (Pray From Home), so as to have a changing impact on human behavior both in terms of economy, quality of worship, learning, and others. This study aims to determine the worship activities carried out by respondents and their relationship to their practice of Al-Islamic Kemuhammadiyahan values in their daily lives in the midst of the COVID-19 pandemic. The results of the research obtained from 87 respondents indicated that the religious activities and activities of practicing the Islamic values of Kemuhammadiyahan that were carried out by respondents in the midst of the COVID-19 pandemic situation, actually decreased and also greatly influenced the decrease in the practice of the Islamic values of Kemuhammadiyahan. This is also influenced by other variables that were not included in this study, such as appeals and regulations from the Regional Government / Pemprov regarding PSBB (Large-Scale Social Restrictions), as well as recommendations from the Central Government to reduce activities & activities outside the home such as work, study, crowds, and others.
Analisis Sentimen Ulasan Pengguna Aplikasi Ajaib Menggunakan Metode Naïve Bayes Hilmy Zhafran Muflih; Allif Rizki Abdillah; Firman Noor Hasan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1303

Abstract

Developments occurring in the investment sector have made people interested in starting to invest. Currently, investments can be made easily using applications on smartphones, such as the Ajaib application. The Ajaib application offers comfort in making investments with the features, security and convenience provided to users, so that various reviews emerge from users in the form of negative or positive sentiments after using the Ajaib application. From the various reviews given, there are still some people who are still hesitant to use the Ajaib application because of the reviews given by people who have used it. The reviews given by users encouraged researchers to conduct research regarding user views after using the Ajaib application with the Naïve Bayes algorithm. The research was carried out to determine the number of negative and positive sentiments from existing reviews regarding the Ajaib application. Researchers collected 500 data through a scraping process on Google Playstore in the Ajaib application. The results obtained in research on sentiment analysis using the Naïve Bayes algorithm method were 44.2% or 221 positive sentiments and 55.8% or 279 negative sentiments from the 500 sentiment data that had been analyzed. The evaluation process was carried out using a confusion matrix to evaluate the Naïve Bayes algorithm method. The results of the evaluation process obtained an accuracy value of 74.44%.
Klasifikasi Sentimen Terhadap Aplikasi Identitas Kependudukan Digital Menggunakan Algoritma Naïve Bayes dan SVM Faisal Parsakh Nursyamsyi; Firman Noor Hasan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1517

Abstract

The Ministry of Home Affairs announced the implementation of an application to keep up with technological and information developments while utilizing digitalization in an effort to increase the efficiency of public services to the community in terms of population data under the name Digital Population Identity (IKD). The Digital Population Identity Application will represent identity data information in digital form. There have been 5 million users who have downloaded the application and around 33 thousand people have provided reviews regarding their satisfaction after using the application. However, implementing the Digital Population Identity application still has pros and cons. There are various user sentiments given based on reviews regarding their satisfaction after using the application. From this problem. The researcher tried to conduct sentiment classification research using the Naïve Bayes algorithm and Support Vector Machine using RapidMiner Studio to determine the public's response to their satisfaction with the Digital Population Identity application by pulling review data on the Digital Population Identity application. Sentiment in review data will be divided into positive sentiment and negative sentiment. The stages carried out in the research process are data collection, data labeling, data cleaning, word weighting with TF-IDF, SMOTE Upsampling, and Cross Validation to accommodate the two classification algorithms, apply model, and performance. As a result of the analysis process that has been carried out, the Support Vector Machine algorithm has quite good performance with an accuracy value of 80.46%, precision of 0.73, and recall of 0.96%. Meanwhile, Naïve Bayes has an accuracy value of 80.22%, precision of 0.73 and recall of 0.94. Both algorithms can carry out the classification process well in the analysis process in the Digital Population Identity application
Perancangan Sistem Inventory Spare Part Elektronik Berbasis Web Application (Studi Kasus: Maspion Service Center) Luqman Abdur Rahman Malik; Rizki Kamelia; Firman Noor Hasan
Jurnal Teknik Informatika dan Komputer Vol. 2 No. 1 (2023): Jurnal Teknik Informatika dan Komputer
Publisher : UHAMKA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v2i1.11167

Abstract

This study aims to simplify and speed up the making of spare part stock reports at the Maspion Service Center and to avoid the risk of data recording errors that occur during spare part stock data collection. The method used in this research is the waterfall method. The researcher aims to design a spare part stock inventory system at the Maspion Service Center in order to simplify and speed up the making of spare part stock reports at the Maspion Service Center without recording in the ledger. The testing method used by the researcher is the Blackbox testing method. The results obtained in the design of this system are proven to be able to avoid the risk of data recording errors that occur during data collection of spare part stock, with the existence of a spare part stock database that is not possible with the same type of spare part twice
Perbandingan Akurasi Metode Naïve Bayes Classifier dan Lexicon Based Pada Analisis Sentimen Respon Masyarakat Tentang Kebijakan Kenaikan Harga Minyak Goreng Faldy Irwiensyah; Firman Noor Hasan
Jurnal Teknik Informatika dan Komputer Vol. 2 No. 1 (2023): Jurnal Teknik Informatika dan Komputer
Publisher : UHAMKA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v2i1.11500

Abstract

Cooking oil is a basic need for Indonesian people. Indonesia experienced a shortage of oil in March 2022. This was a hot topic of discussion on social media Twitter last March, many people thought positively or negatively. However behind it all, there are differences in the assessment of parties who feel the pros and cons, various parties have different points of view. In this article, we conduct a sentiment analysis of public responses regarding the scarcity of cooking oil using a dataset obtained from the Twitter digital platform. This article aims to classify tweets related to the scarcity of cooking oil into positive and negative sentiments using a machine learning strategy with the Naive  Bayes and lexicon based methods. This algorithm was chosen to make it easier for interested users to compare methods and find out how accurate it is, which is where the level of accuracy obtained from the lexicon method is 42% and the method using the naïve Bayes classifier is 72%. Shows the results of the analysis related to the scarcity of cooking oil for the highest level of accuracy, namely the method that uses the naïve Bayes classifier compared to the method that uses lexicon based
Visualisasi Dashboard Business Intelligence Untuk Analisa Ketersediaan Tenaga Kesehatan Pada Saat Covid-19 Di Jakarta Menggunakan Tableau Panji Islami Anakku; E Erizal; Firman Noor Hasan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 4 (2023): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i4.251

Abstract

The Covid-19 pandemic in 2020 witnessed a significant increase in cases worldwide, claiming numerous lives. Despite having a substantial number of healthcare workers in several hospitals in DKI Jakarta, there remained a shortage of healthcare personnel during the Covid-19 outbreak. Consequently, there were still many deaths attributed to both diseases. This study aims to analyze self-data visualization from opendatajakarta in the form of a dashboard and utilize the storytelling feature available in Tableau for visualization. The research aims to determine the number of healthcare workers during the major Covid-19 outbreak in DKI Jakarta. To achieve this, the study employs a method called Business Intelligence using the interactive dashboard options provided by Tableau as a decision-making tool, which will be transformed into visualizations and combined into an information dashboard. The research obtained results in the form of a Business Intelligence dashboard displaying the number of healthcare workers in DKI Jakarta.
Implementasi Business Intelligence Untuk Menganalisis dan Memvisualisasikan Data Penumpang Bus Transjakarta Menggunakan Tableau Anwar Hidayat; Zuhri Halim; Firman Noor Hasan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 3 (2023): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i3.224

Abstract

The existence of transportation facilities such as the Transjakarta bus will make it easier for human activities to move from one place to another. This Transjakarta bus is used as an alternative choice of means of transportation by many people in Jakarta. Because Transjakarta buses use special lanes that allow faster travel. The purpose of this study is to analyze Transjakarta passenger data by implementing a Business Intelligence system to display the number of passengers by type of bus, the number of passengers by route, the most favorite type of bus, the total number of passengers, the average passenger and the top five bus routes. The research method used is dataset processing, namely data for Transjakarta bus passengers in 2021 sourced from data.jakarta.go.id and the data is processed using Tableau tools. The results of this research report are in the form of a dashboard, such as the number of passengers as many as 120,308,547 people and the average passenger is 81,676 people. It is hoped that reports made in the form of data visualization and dashboards can be used in decision making. 
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