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All Journal Jurnal Pseudocode SMATIKA Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal SOLMA Prosiding Seminar Nasional Teknoka Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Linguistik Komputasional Jurnal ICT : Information Communication & Technology FIKROH: JURNAL PEMIKIRAN DAN PENDIDIKAN ISLAM Zonasi: Jurnal Sistem Informasi Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Infotech: Journal of Technology Information Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN) KLIK: Kajian Ilmiah Informatika dan Komputer Sibatik Journal : Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan SmartComp Fikroh: Jurnal Pemikiran dan Pendidikan Islam JURNAL TEKNIK INFORMATIKA DAN KOMPUTER
Firman Noor Hasan
Universitas Muhammadiyah Prof. Dr. Hamka
Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Implementasi Business Intellegence untuk Menganalisis Hasil Panen dan Produktivitas Padi di Indonesia Menggunakan Tableu Ahmad Roshid; Fauzi Kurniawan; Intania Widyaningrum; Tasya Rizki Salsabilla; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 7 (2022): Proceeding of TEKNOKA National Seminar - 7
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

Indonesia is an agricultural country where the majority of the population works in agriculture. Agriculture has an important role in Indonesia in developing the local economy as well as meeting basic human needs. One of Indonesia's largest agricultural products is rice. During the process of collecting data on agricultural products, especially rice, with a large amount of recorded data such as harvested area and annual productivity, it can cause errors in compiling information for the analysis process as well as for evaluation by the ministry of agriculture. Thus, the purpose of this research is to find out how much the harvested area and productivity of rice harvests in Indonesia have increased or decreased. The method used in this article is to process a dataset of harvested area, production, and productivity of rice by province in Indonesia from www.bps.go.id using Tableau. The results of this article are a visualization of a dataset of harvested area and rice productivity by province in Indonesia that can be used for policy making by the ministry of agriculture.
Implementasi Business Intelligence Untuk Menvisualisasi Data Kekerasan Di Provinsi Jawa Barat Menggunakan Tableau Farhan Bias Purnama Putra; Rizki Alamsyah; Mohammad Akhdaan Juliandra; Isnan Wisnu Prastiyo; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 7 (2022): Proceeding of TEKNOKA National Seminar - 7
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

Penelitian ini membahas business intelligence dalam perannya memvisualisasikan data kekerasan di wilayah Provinsi Jawa Barat. Business Intelligence adalah system yang di gunakan untuk mengumpulkan, menyimpan, dan menganalisis data yang di hasilkan. Data yang terkumpul akan di tampilkan dalam format laporan yang mudah dipahami, komprehensif dan akurat. Dimana data kekerasan diolah dengan tool Tableau dan digunakan untuk melihat hasil pola visual pada data kekerasan berdasarkan tahun, jumlah korban, jenis kelamin tempat kejadian, kabupaten/kota dan bentuk kekerasan, serta jenis pelayanan yang di berikan untuk korban. Tableau merupakan perangkat lunak yang bisa menampilkan data dalam bentuk visual yang menarik. Hasil visualisasi yang didapatkan dalam Tableau dilakukan untuk memvisualisasikan data dalam bentuk dashboard grafis berdasarkan pola data demografi seperti tahun, jumlah korban, jenis kelamin, tempat kejadian, kabupaten/kota, bentuk kekerasan, dan jenis pelayanan untuk menganalisis data yang dapat di gunakan untuk evaluasi pemerintah Jawa Barat.
Implementasi Business Intelligence Untuk Menganalisis Data Jumlah Penduduk Di DKI Jakarta Menggunakan Platform Tableau Hibatullah Faisal; Faisal Parsakh Nursyamsi; Indra Ramadhan; Lingga; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 7 (2022): Proceeding of TEKNOKA National Seminar - 7
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

In Indonesia, especially in the province of DKI Jakarta, population growth continues to increase every year. Data regarding population growth in the province of DKI Jakarta is an important factor for consideration in decision making based on the visualization results on the data. The purpose of this article is to visualize population growth data from 2019 to 2021 in the province of DKI Jakarta by implementing a Business Intelligence system to display the results of the development of the number of population growth that has been recorded in 2019 to 2021 in the province of DKI Jakarta. The method is to process the population dataset in the DKI Jakarta province from www.data.jakarta.go.id using Tableau. The results are in the form of reports in the form of dashboards such as total population data, the number of population growth by year and city in the DKI Jakarta province which can be used to support a decision making. Display data generated from the results of the analysis will be visualized with an interactive dashboard with Tableau so that it is easy to understand.
Analisis Sentimen Tingkat Perbandingan Efisen antara Kendaraan BBM denganKendaraan Listrik Menggunakan Algoritma Naives Bayes Arvin Rafialdo; Achmad Ramadhan; Ananda Prasta Warasati Janah; Azhar Haikal Anwar; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 7 (2022): Proceeding of TEKNOKA National Seminar - 7
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

The most widely used energy sources today are fossil fuels, one of which is oil, especially Indonesia isstill very dependent on fossil energy, almost 95% of Indonesia's energy needs are still supplied by fossils.Along with the times, many studies are trying to find alternative energy sources, one of which is electric vehicles, as an alternative to the use of fossil energy. Therefore, researchers classify public sentiment and understanding of fuel-oil and electric vehicles using the Naïve Bayes method to compare vehicle efficiency levels. Based on the results of the study, it was found that oil-fueled vehicles with electricity using the Naïve Bayes method yielded 50 results for each data. Fuel-fueled vehicles give positive and negative results, namely 30 and 20. Meanwhile, electric vehicles give positive and negative results of 43 and 7. It can be concluded that public sentiment towards electric vehicles is more efficient than oilfueledvehicles.
Implementasi Business Intelligence Menggunakan Tableau Untuk Visualisasi Data Dampak Bencana Banjir di Indonesia Dandie Triyanto; Muchammad Sholeh; Firman Noor Hasan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.769

Abstract

Indonesia is a region prone to natural disasters, one of which is flooding. The purpose of this study was to visualize the impact areas of the natural flood disaster in all provinces of Indonesia by implementing business intelligence, which displays the number of submerged houses, damaged houses, and public facilities, as well as the number of dead, missing, and injured victims. The method of this research was obtained in the form of a dataset sourced from the National Disaster Management Agency from January 1, 2008, to January 31, 2023, using the business intelligence platform Tableau Public. The results of the research are in the form of reports and dashboards that display data visualization for flood-affected provinces in Indonesia. In conclusion, based on the visualization results obtained, the province that experienced the impact of the flood disaster was West Java with the highest number of 1,538,125, and based on all cities and districts in February 2021, there were 221,715 The most damaged houses and public facilities, namely 4,929 houses and 76,795 public facilities; and the most flood victims, namely 173 missing victims in 2010, 500 dead victims in 2010, and 69,656 injured victims in 2008.
Analisis Sentimen Ulasan Pelanggan Pada Aplikasi Fore Coffee Menggunakan Metode Naïve Bayes Tia Anggita Sari; Estu Sinduningrum; Firman Noor Hasan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.884

Abstract

Evolution of the coffee shop enterprise in Indonesia is progressing rapidly, because coffee consumption in Indonesia continues increasing every year. In selecting the application to be used usually consider security, convenience and many promotions. But some users are still hesitant in using an application because some of the reviews are displayed, then from that problem a research is carried out using sentiment analysis to produce a classification on customer satisfaction with fore coffee using the Naïve Bayes Algorithm. The stages of this research consist of collecting data from web scraping, data preprocessing, The utilization of TF-IDF data weighting, coupled with the successful deployment of the Naive Bayes algorithm, leads to a heightened level of precision while ensuring a straightforward and prompt workflow. Results of data processing and application of algorithms. Process results data processing carried out there are 1801 data, the highest number of sentiments is positive sentiment of 1163 and 315 negative sentiments. This shows that from 1801 data comments that users the fore coffee application likes the services provided by the fore coffee baristas, but there are also the community who don't like the waiter given by the barista. The accuracy value that has been obtained after processed using the naïve Bayes algorithm, a percentage of 74.28% is obtained which can be seen that the data can be used as a basis for fore coffee in considering decision making.
Pelatihan Sertifikasi Microsoft Office Specialist (MOS) Bagi Siswa-Siswi SMK Islam Malahayati Jakarta Firman Noor Hasan; Djeli Moh Yusuf; Fayakun Kun
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 3 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i3.13582

Abstract

Educators who have competence in certain areas of expertise will guide their students to have competency in those areas of expertise. Competency in the field of expertise is obtained through a certification exam. The main purpose of competency certification is to ensure a person is competent in their area of expertise through the learning stage as well as the work experience stage. Certifications are usually issued by institutes, organizations, or professional associations that oversee certain professional competencies. This activity is motivated by the following: (1) In general, teachers and students do not know about the importance of competency certification, which is not only recognized nationally but is also recognized on an international scale. (2) In general, teachers and students do not know how to use Microsoft Office tools in accordance with international standards (SI). (3) There are still many students who do not have competency certification, both at the national and international levels. (4) Students do not know the international competency certification exam methods that use the CBT system and simulators that are connected in real-time. This community service activity is in the form of a training method for Microsoft Office Specialist International competency certification, which is divided into several stages. The results of the evaluation questionnaire filled out by the participants resulted in 52.23% feeling very satisfied, while 44.06% of the participants felt agreeable, satisfied, and helped through community service and mentoring activities.
Analisis Sentimen Terhadap Kandidat Calon Presiden Berdasarkan Tweets Di Sosial Media Menggunakan Naive Bayes Classifier Allif Rizki Abdillah; Firman Noor Hasan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 01 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i01.750

Abstract

This research is to analyze the sentiments of the Indonesian people about the presidential candidates who are likely to advance in the 2024 presidential election from tweets on the Twitter application. Tweets on Twitter are written, typed and published by Indonesian netizens about the candidates who are likely to advance in the 2024 presidential election. In this study, researchers used tools, namely RapidMiner Studio to collect tweet data from Indonesian netizens about the candidates. Furthermore, the researcher uses the Naïve Bayes Classifier algorithm to determine whether a statement or sentiment has a positive or negative value which is carried out using Rapid Miner tools as well. Of the four candidates that the researchers examined, Anies got 74% positive sentiment 26% negative sentiment, then followed by Sandi, namely 57% positive sentiment 43% negative sentiment, Ganjar received 53% positive sentiment 47% negative sentiment and Prabowo received 32% positive sentiment. 68% negative sentiment. The conclusion of this research is to find out which candidates are liked or favored by the Indonesian people from the results of sentiment analysis using the Naïve Bayes algorithm and the tools used, namely Rapid Miner.
The Influence of Simping Clamshell Addition on Disc Brake Pad Mechanical Properties Agus Fikri; Firman Noor Hasan; Riyan Ariyansah
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 5 Nomor 2 Tahun 2023
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v5i2.4984

Abstract

The brake pads made from asbestos are environmentally hazardous due to the friction and abrasion occurring during braking, resulting in the release of airborne asbestos fibers. These fibers pose various health risks to humans and contribute to environmental pollution. This study aims to analyze the influence of adding clamshell waste material on the mechanical properties of motorcycle disc brake pads. The research utilized an experimental approach, conducting tensile and friction tests on six samples with different compositions: 100% brake pads, 40% brake pads, 60% simping clamshell, 60% brake pads, 40% simping clamshell, 20% brake pads, 80% simping clamshell, 50% brake pads, 50% simping clamshell, and 100% brake pads. The results indicate that the sample comprising 50% used brake pads and 50% simping clamshell exhibited the smallest difference in thickness, measuring 0.05 mm or 0.59%, indicating the strongest adhesive strength and wear resistance compared to other variations. Thus, a higher simping clamshell composition sacrifices some tensile strength but offers improved elasticity, benefiting specific braking conditions.
Analisis Sentimen Twitter Terhadap Perpindahan Ibu Kota Negara Ke IKN Nusantara Menggunakan Orange Data Mining Hafizh Dhery Al Assyam; Firman Noor Hasan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.957

Abstract

This study uses text mining which involves changing unstructured text to be structured and can be processed by a computer. In order to recognize important new patterns and ideas, several analytical techniques are used, including the text clustering method, Naive Bayes, and Support Vector Machines (SVM). Text Clustering analysis technique, which involves cluster analysis of text-based documents, can assist in categorizing and understanding unstructured text data using machine learning technology and Natural Language Processing (NLP) used in this process. This study aims to evaluate the community's response to the relocation of the national capital to Kalimantan. after going through the cleansing process, namely cleaning punctuation and characters, Transform Case, namely changing letters to lowercase, Tokenization is the process of dividing text sentences or paragraphs into certain parts, Stopwords Reducing the index in the text by removing some verbs, adjectives and other adverbs . The results of the analysis will be displayed in the form of a word cloud with words dominated by Indonesian and then Indonesian and distribution tables. The researcher collects 100 data via Twitter to become a dataset. The results of sentiment analysis with the Naive Bayes Classifier algorithm obtained results, namely 6 forms of emotion which were dominated by surprise (80%) and joy (50%), sadness (15% Sadness), fear (Fear) 10%, disgust (Disgust). ) 0% , angry (Anger) 0%.
Co-Authors Achmad Ramadhan Agus Fikri Ahmad Faiz Rahmatullah Ahmad Rizal Dzikrillah Ahmad Rizal Dzikrillah Ahmad Roshid Ahmad Syahril Alfandi Safira Allif Rizki Abdillah Allif Rizki Abdillah Allif Rizki Abdillah Ananda Bagas Pranata Ananda Prasta Warasati Janah Andika Saputra Ari Wibowo Arief Wibowo Arien Bianingrum Rossianiz Arvin Rafialdo Avis Tantra Mukti Avorizano, Arry Azhar Haikal Anwar Azhar Haikal Anwar Bagas Kembar Rezkyllah Bahrul Rozak Bahrul Rozak Dan Mugisidi Dandie Triyanto Desty Afni Dian Ainurrafik Afnan Sabili Dian Ainurrafik Afnan Sabili Diana Fitri Lessy Diana Fitri Lessy Dimas Febriawan Dion Parisda Ray Djeli Moh Yusuf Erizal Erizal Estu Sinduningrum Estu Sinduningrum Estu Sinduningrum Estu Sinduningrum Fadli Hardiyanto Putra Faisal Parsakh Nursyamsi Faisal Parsakh Nursyamsyi fajar sidik Fajar Sidik Faldy Irwiensyah Faldy Irwiensyah Farhan Bias Purnama Putra Farhan Nufairi Farhan Nufairi Fauzan Setya Ananto Fauzi Kurniawan Fayakun Kun Febriandirza, Arafat Hafizh Dhery Al Assyam Harry Ramzah Hibatullah Faisal Hibatullah Faisal Hilmy Zhafran Muflih Hilmy Zhafran Muflih I Ketut Sudaryana Ibnu Suhada Indra Ramadhan Indra Ramadhan Intania Widyaningrum Irawati Irawati Irfan Ricky Affandi Irfan Ricky Affandi Isa Faqihuddin Hanif Isnan Wisnu Prastiyo Kurniyati Nur Lingga Lita Astri Pramesti Luqman Abdur Rahman Malik Luthfi Akbar Ramadhan Meliyawati Mia Kamayani Mohammad Akhdaan Juliandra Muchammad Sholeh Muchammad Sholeh Muhamad Saiful Arif Muhammad Abid Fajar Muhammad Ikhwan Muhammad Ikhwan Muhammad Rafly Al Fattah Zain Muhammad Ridwan Mutiara Zahra Arifin Nisa Qonita Rizkina Nofendri, Yos Nunik Pratiwi Prastika Indriyanti Prista Afikah Rafli Erlangga Reisa Inayah Rian gustini Ridwan Maulana Subekti Rika Nurhayati Riyan Ariyansah Rizki Alamsyah Rizki Kamelia Rizky Ramdhani Sri Fitriani Tasya Rizki Salsabilla Tia Anggita Sari Wahyu Stiyawan Wanda Aulia Windi Al Azmi Zuhri Halim