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All Journal Journal of Environmental Engineering and Sustainable Technology Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JOURNAL OF APPLIED BUSINESS ADMINISTRATION Indonesian Journal of Electrical Engineering and Computer Science
Muhammad Tanzil Furqon
Fakultas Ilmu Komputer , Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Social Sciences

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Implementasi Bagging Naive Bayes untuk Klasifikasi Stenosis Left Anterior Descending (LAD), Left Circumflex Artery (LCX) dan Right Coronary Artery (RCA) dalam Diagnosis Coronary Artery Disease (CAD) Amalia Luhung; Muhammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Coronary Artery Disease (CAD) is a disease that occurs due to the accumulation of atherosclerotic plaque that causes blockage (stenotic) in the tunica intima lining of coronary arteries. The coronary arteries are Left Anterior Descending (LAD), Left Circumflex Artery (LCX), and Right Coronary Artery (RCA). Stenosis in coronary arteries can cause heart attacks and even death. Diagnosis needs to be done quickly to reduce the impact of CAD so, a system was built to help find out LAD, LCX, and RCA stenosis through classification. Classification is done to classify patients' coronary arteries into normal or stenotic classes using the Bagging Naive Bayes method. This method allows the classification to be carried out by several predictor models made based on bootstrap by sampling with replacement to get aggregate results. The steps taken to implement this method are preprocessing, bootstraping, Naive Bayes classification, voting. The highest accuracy in the LAD classification obtained was 0.7573 when the classification was done using 200 data, 25 bootstrap samples (T), and the classification was carried out with all features. Its result ​​of precision, sensitivity and specificity are 0.8065, 0.7938, and 0.7012. In LCX classification the highest accuracy achieved is 0.7282 when the classification is done using 200 data, T = 1, and the classification is done with the features selected. Precision, sensitivity, and specificity result are 0.9042, 0.7262, and 0.7368. Whereas in the RCA classification the highest accuracy achieved is 0.7282 when the classification was carried out using 150 data, T = 1, and the classification was carried out with the results of the selection of precision, sensitivity and specificity values ​​0.9242, 0.7262, and 0.7368. The intended feature selection method is Pearson's chi-squared and One-way ANOVA.
Klasifikasi Stress berdasarkan Elektrodermal Activity (EDA) menggunakan Seleksi Fitur Information Gain dan Metode LVQ2 Hanifah Khoirunnisak; Fitra Abdurrachman Bachtiar; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Untuk dipublikasikan di Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Pengembangan Aplikasi Pendeteksi Kesalahan Dalam Membaca Al-Qur'an Berbasis Android Menggunakan Speech Recognition Dengan Menerapkan Metode Jaro Winkler Distance Rifaldi Raya; Ahmad Afif Supianto; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Al-Qur'an is the holy book which is owned by Muslims. This book is the main reference in living life for Muslims throughout the world. In order to become a good Muslim, each person must practice the contents of the Al-Qur'an. Before being able to practice it, of course a Muslim must be able to read and understand the contents of the Al-Quran. The process of learning to read the Al-Qur'an requires a lot of time and also a teacher as a guide. Regular practice is one solution so that the learning process to read the Al-Qur'an can be completed quickly. However, the teacher as a guide cannot always be there to accompany a student in learning to read the Al-Qur'an. From these problems, the author offers a way, namely an error detection application in reading the Al-Qur'an that can be used as a student training medium without time constraints. The writer developed this application using the Jaro Winkler Distance method as a method of comparison and assessing reading errors. This application makes use of Google's Speech Recognition to convert the voice input entered by the user to the depth of Arabic text. The results of the conversion in the form of Arabic text will be compared with the original text from the Qur'an using the Jaro Winkler Distance method. At the testing stage, the authors found that this method was very incompatible with the object of the Qur'an because the results of the accuracy testing carried out were very low.
Prediksi Penjualan Metal Roof menggunakan Metode Backpropagation (Studi Kasus: PT Comtech Metalindo Terpadu) Vandi Cahya Rachmandika; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The manufacturing industry in Indonesia has developed rapidly in line with technological developments in Indonesia. The manufacturing industry that has experienced an increase is the printed goods industry. In this research, one of the printed goods industries is PT Comtech Metalindo Terpadu is a metal roof sales industry. PT Comtech Metalindo Terpadu has a problem regulating the supply of metal roof raw materials. In this case, predicting metal roof sales can find out sales at a certain period, so that it can help to regulate raw material inventory or purchase of raw materials. This study uses the Backpropagation method to predict sales of metal roofs, and to evaluate the predictive error value will use the Mean Absolute Precentage Error (MAPE). The smallest MAPE value obtained from this study is 5.76% with the neuron input value 3, the hidden neuron value 100, the initial weight range value in the range -0.5 to 0.5, the learning rate value 0.2, and the epoch value 150.
Pembentukan Daftar Stopword menggunakan Term Based Random Sampling pada Analisis Sentimen dengan metode Naive Bayes (Studi Kasus: Kuliah Daring di Masa Pandemi) Raditya Rinandyaswara; Yuita Arum Sari; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Pengembangan Sistem Berbasis Web pada Bisnis Jasa Seni Lukis Hugo Ghally Imanaka; Muhammad Tanzil Furqon; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The painting service business is a business that provides the creation of fine art in the form of paintings. Zona Karikatur, Dokter Desain, and Creative are a few examples of digital painting services providers in Indonesia. In their development, these companies find problems in several things such as production processing, ordering, suitability of customer demand, and financial data collection. Therefore, a web for painting service business management was created to help and overcome problems such as managing the order processing, production, and financial data collection to make it more efficient. Waterfall model and object-oriented approach was chosen to build this system. Requirement analysis of this research produces 5 actors, 52 functional requirements, and 1 nonfunctional requirement. This system has been tested using unit testing, integration testing, validation testing, and compatibility testing. Unit testing and integration testing use the whitebox testing techniques, and those have valid results. The implementation of program code on this system uses the Go language. Validation testing uses the blackbox testing technique and it has a validity percentage of 100%. Compatibility testing was carried out using the Crossbrowsertesting tool, it shows that the system can run well on various browsers and devices. Despite this, it has a fatal problem with Internet Explorer 11. Through this development, it produces a system that can manage the painting service business.
Exponential Smoothing untuk Peramalan Jumlah Penjualan Hijab Vie Hijab Store Eky Cahya Pratama; Muhammad Tanzil Furqon; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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In the modern era like today, advances in information technology have penetrated into various fields, one of which is in the industrial sector which can assist in the decision-making process to forecasting something that will happen in the future. Vie Hijab Store is a home-based business, such as a sewing house, which is concerned in the production and sale of hijab, which has problems stocking fabric as raw material. The process of forecasting the number of sales will be very helpful in regulating the decision-making process when stocking goods. In this study, the method used for forecasting Exponential Smoothing which consists of Single Exponential Smoothing (SES), Double Exponential Smoothing (DES), Triple Exponential Smoothing (TES) methods. Referring to one of the test results on the 4th increase period data sample which represents the situation of an increase in the second year of the Hajj month obtained from the dataset, the best parameter values for khimar products in the TES method are alpha = 0,9, beta = 0,9 and gamma = 0,1 which resulted in a MAPE of 11.47%. As for pashmina products in the TES method with alpha = 0.4, beta = 0.9 and gamma = 0.8 which resulted in a MAPE of 9,22%. Based on the results of all the tests of the three methods, if a comparison is made, it is shown that the majority of the best results are obtained when using the Triple Exponential Smoothing method. Therefore, the Triple Exponential Smoothing method was chosen as the best method for forecasting the number of hijab sales.
Klasifikasi Masa Panen Varietas Unggul Kedelai menggunakan Support Vector Machine (SVM) Abas Saritua Gultom; Muhammad Tanzil Furqon; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Soybean is an agricultural commodity that is very much needed in Indonesian, because soybeans are widely consumed in various food products, soybeans are also used as industrial raw materials. Soybean farmers need to know what type of soybean plant is included in the seeds to be planted, so that the increase in soybean production is maintained. To facilitate the process, data from various types of soybeans will be used. The research will be conducted using the SVM (Support Vector Machine) method because the SVM method can generalize high without having to have additional datasets. In this study, there were 6 variables and objects belonging to 3 classes, namely early age, medium age, and deep age. The best test results use a polynomial degree 2 kernel, using the lamda (λ) value of 10, Constant 1, Epsilon 0.01 and iter max of 10. Based on various tests and scenarios that have been carried out, the best evaluation value is generated in tests using K-Fold Cross Validation with a value of K = 5 and produces an accuracy value of 56.666%.
Peramalan Jumlah Produksi Padi menggunakan Metode Backpropagation Dwi Yana Wijaya; Muhammad Tanzil Furqon; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Paddy a crop that produces rice is a is the most important product for the people of Indonesia. Rice at an affordable price for the community is one of the important factors to maintain national resilience and government stability. In this case, forecasting rice production can be used as a consideration for the government to take a policy because forecasting rice production can provide an overview of information in the form of the number of products produced in the future. This study uses the Backpropagation method to forecast the amount of rice production and to evaluate the error value using the Mean Absolute Percentage Error (MAPE). Forecasting paddy production is carried out in several provinces such as DKI Jakarta, West Java, North Sumatra, Riau, and Banten. This study resulted in the smallest MAPE value with a value of 7.39%. This value is generated from data from the province of West Java with 10 neurons as input neurons, 3 hidden neurons, with initial weight and bias range value from -0.8 to 0.8, a learning rate value of 0.6, and an epoch of 50 times.
Prediksi Harga Beras menggunakan Metode Least Square Brillian Ghulam Ash Shidiq; Muhammad Tanzil Furqon; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Basic ingredients are something that must be fulfilled in order to support the survival of all humans, one of the main ingredients is rice. Rice is a major commodity of staples needed by humans in several countries in the world. As a result, if the price of the staple food of rice experiences erratic price fluctuations (fluctuations) which can cause a reduction in the purchasing power of people with low incomes, the rice mills stop operating to avoid losses. Therefore, to avoid and reduce the risk of food security problems in the future, we need a system that can be able to predict the prices of rice so that it can help reduce the risk of loss and can ensure that rice prices can be reached by the wider community. In making this system, of course, a periodic data method (time series) is needed that can process real data in order to predict the price of rice staples correctly. In this study the method used is the Least Square method. This method can predict rice prices by using data in the past to be used as forecasting guidelines in the future. From the prediction results, the smallest error search calculation (error) is carried out using MAPE (Mean Absolute Percentage Error). The data used in this study were 132 data. Which consists of 132 training data and 12 test data the latest data. After the prediction process is carried out the result from the prediction prices of rice for 12 months in 2021 are obtained. The results of the prediction of rice prices for 12 months in 2021 are obtained. The test results from this prediction are in the form of the smallest error value (error) which is considered very good in accuracy to predict rice prices using the least square method, which is 5%.
Co-Authors Abas Saritua Gultom Abu Wildan Mucholladin Achmad Arwan Achmad Ridok Adinda Chilliya Basuki Adinugroho, Sigit Agus Wahyu Widodo Ahmad Afif Supianto Akhmad Eriq Ghozali Al-Mar'atush Shoolihah Aldion Cahya Imanda Amalia Luhung Andini Agustina Anindya Celena Khansa Kirana Anjelika Hutapea Annisya Aprilia Prasanti Annisya Aprilia Prasanti Ardisa Tamara Putri Arief Andy Soebroto Arif Indra Kurnia Arina Rufaida Arinda Rachman Arjun Nurdiansyah Arya Perdana Arynda Kusuma Dewi Aryo Pinandito Aryu Hanifah Aji Asfie Nurjanah Audi Nuermey Hanafi Ayu Anggrestianingsih Barik Kresna Amijaya Bayu Rahayudi Bayu Rahayudi Bossarito Putro Brillian Ghulam Ash Shidiq Budi Darma Setiawan Candra Dewi Cusen Mosabeth Daniel Alex Saroha Simamora David Bernhard Defanto Hanif Yoranda Dendry Zeta Maliha Destin Eva Dila Purnama Sari Desy Andriani Diajeng Sekar Seruni Dian Eka Ratnawati Dwi Yana Wijaya Dyan Dyanmita Putri Dyang Falila Pramesti Dzar Romaita Edy Santoso Eko Ari Setijono Marhendraputro Eky Cahya Pratama Elan Putra Madani Erwin Bagus Nugroho Evilia Nur Harsanti Fadhilla Puji Cahyani Fahmi Achmad Fauzi Fajar Pradana Fatwa Ramdani, Fatwa Fernando Parulian Saputra Fikar Cevi Anggian Firdaus Rahman Fitra Abdurrachman Bachtiar Gabriel Mulyawan Ghulam Mahmudi Al Azis Guntur Syafiqi Adidarmawan Hangga Eka Febrianto Hanifa Maulani Ramadhan Hanifah Khoirunnisak Hugo Ghally Imanaka Humam Aziz Romdhoni I Gusti Ngurah Ersania Susena Imam Cholissodin Iman Harie Nawanto Imaning Dyah Larasati Inas Hakimah Kurniasih Indra Eka Mandriana Indri Monika Parapat Indriana Candra Dewi Indriati Indriati Inggang Perwangsa Nuralam Issa Arwani Jojor Jennifer BR Sianipar Julita Gandasari Ariana Jumerlyanti Mase Kevin Nadio Dwi Putra Khaira Istiqara Laila Diana Khulyati Lailil Muflikhah Listiya Surtiningsih Luthfi Faisal Rafiq M. Ali Fauzi Mahardhika Hendra Bagaskara Mahendra Data Maria Sartika Tambun Marji Marji Masayu Vidya Rosyidah Mochamad Ali Fahmi Muh. Arif Rahman Muhamad Fahrur Rozi Muhammad Aghni Nur Lazuardy Muhammad Iqbal Mustofa Muhammad Rafif Al Aziz Muhammad Riduan Indra Hariwijaya Muhammad Wafiq Naufal Sakagraha Kuspinta Nindy Deka Nivani Novanto Yudistira Nur Kholida Afkarina Nurdifa Febrianti Nurudin Santoso Nurul Hidayat Nurul Hidayat Nurul Ihsani Fadilah Ofi Eka Novyanti Oky Krisdiantoro Pangestuti, Edriana Pricielya Alviyonita Priyambadha, Bayu Putra Pandu Adikara Putri Indhira Utami Paudi R Moh Andriawan Adikara Raden Rafika Anugrahning Putri Raditya Rinandyaswara Rahman Syarif Randy Cahya Wihandika Ratna Ayu Wijayanti Restia Dwi Oktavianing Tyas Ridho Ghiffary Muhammad Rifaldi Raya Rifwan Hamidi Rimba Anditya Kurniawan Riski Nova Saputra Riza Rizqiana Perdana Putri Rizal Setya Perdana Robbiyatul Munawarah Romlah Tantiati Satrio Hadi Wijoyo Setyoko Yudho Baskoro Silvia Aprilla Sutrisno Sutrisno Tania Oka Sianturi Taufan Nugraha Teri Kincowati Tryse Rezza Biantong Ulva Febriana Vandi Cahya Rachmandika Vania Nuraini Latifah Vera Rusmalawati Vianti Mala Anggraeni Kusuma Weni Agustina Wildan Afif Abidullah Wildan Ziaulhaq Wildan Ziaulhaq Wilis Biro Syamhuri Yuita Arum Sari