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Rancang Bangun Sistem Informasi untuk Toko Online Berbasis Aplikasi Android Desty Afni; Firman Noor Hasan
Prosiding Seminar Nasional Teknoka Vol 6 (2021): Prosiding Seminar Nasional Teknoka ke - 6
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

Petshop adalah salah satu tempat untuk menjual kebutuhan hewan peliharaan seperti menjual peralatan dan perlengkapan untuk hewan peliharaan. Saat ini sistem penjualan yang digunakan oleh Klinik Petshop “wine” masih menggunakan cara manual, dimana para pelanggan harus datang langsung ke toko untuk membeli kebutuhan hewan peliharaan. Pada penulisan ini bertujuan untuk mempermudah klinik petshop “wine” dalam mengelola transaksi jual-beli peralatan dan perlengkapan hewan peliharaan secara online, dan memberikan informasi mengenai cara perawatan hewan serta jual-beli hewan peliharaan. Metode yang digunakan dalam penelitian ini ialah metode waterfall. Hasil yang diperoleh dalam penelitian ini adalah telah dibangun aplikasi petshop wine berbasis android yang terbukti dapat mempermudah costumer dalam membeli perlengkapan dan peralatan hewan peliharaan terbukti dari hasil uji efektivitas sistem diperoleh sebesar 91,33%, lalu untuk hasil uji efektivitas yang dilakukan oleh admin sebesar 83,17%, responden yang menyatakan bahwa aplikasi ini telah dikategorikan sesuai atau telah efektif layak diterapkan pada petshop wine.
Implementasi Business Intelligence Untuk Menganalisis Data Penyakit Diabetes Menggunakan Platform Tableau Muhamad Saiful Arif; Kurniyati Nur; Ridwan Maulana Subekti; Reisa Inayah; 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

Diabetes is a chronic metabolic disorder with multi-etiology characterized by high levels of sugar and is the result of insufficiency of insulin function present in the human body. The purpose of this article is to visualize and find out the rate of diabetes cases around the world based on the age range of the dataset that has been concentrated by implementing Business Intelligence to display confirmed case data, both in pregnancy, Body Mass Index (BMI), and blood pressure. The motto used is to process the world dataset from the www.kaggle.com data platform, this dataset is processed using the tableau desktop platform. The results of this article are in the form of reports in the form of Dashboards such as the number of confirmed cases both in pregnancy, Body Mass Index (BMI), and blood pressure that exist in the world and can be used to support a decision making. The interface display of the processed dataset is the result of an interestingly formed analysis, using an interactive Dashboard provided by tableau so that the data can be displayed attractively.
ANALISIS SENTIMEN TERHADAP APLIKASI COFFEE MEETS BAGEL DENGAN ALGORITMA NAÏVE BAYES CLASSIFIER Andika Saputra; Firman Noor Hasan
SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan Vol. 2 No. 2 (2023): January
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sibatik.v2i2.579

Abstract

Di era modern dengan kemajuan teknologi yang sangat pesat ini, tercipta banyak aplikasi yang dapat membantu beragam kebutuhan manusia saat ini. Salah satu nya adalah aplikasi online dating atau aplikasi pencari jodoh online. Banyaknya pihak yang melihat peluang bisnis dari membuat aplikasi online dating ini dengan memanfaatkan latar belakang manusia untuk mencari jodoh. Aplikasi online dating menjadi fenomena sosial di kalangan masyarakat mulai dari kalangan muda sampai yang tua, mereka yang belum menemukan jodohnya mencoba untuk menggunakan aplikasi online dating ini sebagai alternatif untuk mendapatkan jodoh lebih mudah. Kegiatan online dating berbeda dengan mencari pasangan yang umumnya secara konvensional, hubungan yang tercipta melalui aplikasi online dating tergantung pada daya tarik pengguna dan gaya komunikasi penggunanya. Aplikasi online dating telah memiliki banyak digemari setelah kemunculan dan cara kerjanya yang membuat pengguna bertemu dengan banyak orang baru lalu menjalin banyak hubungan pertemanan. Fenomena tersebut membuat situs dan aplikasi online dating ini menjadi wadah bagi orang-orang yang ingin menjalin pertemanan dan menemukan pasangan.
Analisa Visualisasi Data Kematian Yang Disebabkan Oleh Penyakit Hiv Dan Malaria Diseluruh Dunia Dengan Metode Business Intelligence Menggunakan Dashboard Tableau Mutiara Zahra Arifin; Bagas Kembar Rezkyllah; Fadli Hardiyanto Putra; Rizky Ramdhani; 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

HIV and Malaria are diseases that claim many victims in all parts of the world. Although in some countries there are treatments that can reduce mortality rates, not all countries have these treatments. So there are still many deaths from these two diseases. This study will analyze data visualization from kaggle in the form of dashboards and visualizations using the story feature available on Tableau, with the aim of this research being able to find out how many people die due to HIV and Malaria worldwide. Of all that, a method called Business Intelligence uses an interactive dashboard option provided by Tableau to be used as a decision making tool, which can then be converted into a visualization which will later be combined into an information dashboard. This study obtained the results of the BI dashboard display starting from the number of HIV and Malaria death cases worldwide, the distribution of death cases worldwide and countries with the highest number of death cases. This research yielded accurate results, namely the number of deaths from HIV was 36,364,419 people and the number of deaths from malaria was 25,342,676 people, the country with the most HIV deaths came from South Africa and the country with the most Malaria deaths came from Nigeria, and a comparison of the results of HIV deaths and Malaria in Indonesia.
Implementasi Business Intelligence Untuk Menganalisis Data Destinasi Wisata di Indonesia Menggunakan Platform Tableau Diana Fitri Lessy; Lita Astri Pramesti; Rafli Erlangga; Muhammad Rafly Al Fattah Zain; 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

Tourist destinations are one of the main choices that can be made in spare time. Indonesia is a country that is famous for its beauty, so it attracts many tourists to visit. The purpose of this study focuses on visualizing tourist destination data in Indonesia by implementing Business Intelligence to display places, prices and ratings from five cities in Indonesia. The method of this research is to process a dataset of tourist destinations in Indonesia from www.kaggle.com using the Tableau platform. The results of this study are in the form of reports in the form of dashboards such as places, prices and ratings from five cities in Indonesia which are used in the decision-making process to make it easier and more systematic. The data display from the results of the analysis that has been carried out produces an attractive and interactive dashboard provided by Tableau.
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.
Utilization of Data Mining on MSMEs using FP-Growth Algorithm for Menu Recommendations Firman Noor Hasan; Achmad Sufyan Aziz; Yos Nofendri
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 2 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2166

Abstract

Existing transaction data is only recorded and stored as a sales transaction memorandum, so it has not been utilized optimally. The data is only stored and used as transaction history. The availability of a lot of data and having a pattern of sales transactions that are similar to MSME Cafe Over Limit will be utilized by using data mining science. This research uses the association rules method. Implementation of fp-growth to get item combinations. The purpose of this research is to make it easier for MSMEs to determine menu recommendations for customers. The fp-growth algorithm is used to process as many as 2038 transaction data with a minimum support value of 10%, while for a minimum confidence value of 50%. So that there are 3 rules, namely "if you order Mariam chocolate cheese milk then the customer will order Kopsus Overlimit", from this rule it will form a support value of 10.79%, using a confidence value of 54.19% and a lift ratio of 0.93. Furthermore "if you order Kopsus Overlimit then you will order tofu at grandma's house", from the rule it will produce a support value of 34.69%, with a specified confidence value of 59.76%, so the lift ratio value is 1.15. The last rule "if you order tofu at grandma's house, the customer orders Kopsus Overlimit", from the rule that occurs, the support value is 34.69%, with a confidence value of 66.7% and a lift ratio of 1.15. The results of the study found the two best rules, namely "if the customer orders over-limit Kopsus, he will order tofu at grandma's house" and "if he orders tofu at grandma's house, the customer orders over-limit Kopsus". Based on the results of the rules formed, it can be concluded that only two rules can be categorized as valid and can be used as a reference in food and beverage menu recommendations at MSME Cafe Over Limit. So the results of this study can be useful to be applied to MSMEs, especially in terms of menu recommendations.
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