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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Community Empowerment
Randy Cahya Wihandika
Fakultas Ilmu Komputer , Universitas Brawijaya
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

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Optimasi Penjadwalan Jam Kerja Part Time menggunakan Algoritme Genetika (Studi Kasus: Haga Coffee Shop Malang) Angky Christiawan Rongre; Budi Dharma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 5 (2020): Mei 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Haga coffee shop is a coffee shop that provides various types of drinks using coffee as a basic ingredient besides that there are various kinds of drinks besides coffee such as chocolate and green tea and has three outlets. Haga coffee shop also opens part time for students who want to fill their free time between lectures free time between classes and additional allowance also adds expertise in the work world to make part time according to the choices of many students. This makes the manager of Haga coffee shop required to be able to make part-time work schedules that are not convoluted with the lecture schedules of their employees or students. Scheduling is the activity of finding a path that is in line with expectations in order to create an optimized visit schedule. Genetics algorithms is one method in finding solutions to scheduling problems that are often used by researchers. Genetic algorithms were used for 8 employees of Haga coffee shop with a population of 150, the number of generation 50 and combinaton Cr 0,2 & Mr 0,9 were the besst fitness values.
Analisis Sentimen pada Ulasan Pengguna MRT Jakarta Menggunakan Metode Neighbor-Weighted K-Nearest Neighbor dengan Seleksi Fitur Information Gain Firda Oktaviani Putri; Indriati Indriati; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The existence of the MRT Jakarta is expected to reduce the number of private transportation uses, which causes the congestion rate in the Jakarta area to continue to increase. Reviews from MRT Jakarta users help MRT Jakarta in improving its services, because good service quality can attract people to use MRT as public transportation for traveling. However, at this time, MRT Jakarta's official social media accounts had not yet found a feature to sort reviews between positive and negative reviews. If this is done manually it will take time, therefore it is necessary to carry out an automation process in the selection of these reviews. This automation process is known as sentiment analysis. In this study, the sentiment analysis system uses a combination of the Neighbor-Weighted K-Nearest Neighbor (NWKNN) classification method with the Information Gain feature selection. Tests conducted in this study using 5-Fold Cross Validation. The test results reach the optimal point at the 5th Fold, when the k value = 100, the exponent value = 2, and the threshold value for feature selection = 100% (without feature selection and without using stopword removal), with values of precision, recall, f- measure, and accuracy is 1; 0.94; 0.97; and 0.97.
Penerapan Latent Dirichlet Allocation (LDA) dengan Term Frequency-Inverse Document Frequency (TF-IDF) untuk Ekstraksi Aspek pada E-Commerce Satyawan Agung Nugroho; Fitra Abdurrachman Bachtiar; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Deteksi Pergerakan Arah Mata menggunakan Convolution Neural Network berdasarkan Facial Landmark Muhammad Amin Nurdin; Randy Cahya Wihandika; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The movement of the human eye can be useful in various fields, for example in security systems, health, transportation and design interface. In the design interface systems, eye movement used as an interactive system. The system can interact and responses to users by using eye movements. The video-based eye tracking method has the advantage of being practical and convenient during the detection process. This study uses the Convolution Neural Network (CNN) algorithm because it will utilize the advantages of the CNN method to classify and have the most significant results in object recognition. The results of this study indicate that the CNN model that good to use in the classification of eye direction based on facial landmarks is with 2 layers contain 32 filters and 64 filters, batch size 16 in image augmentation with 20 fully connected layers resulting loss value of 0.08, with an accuracy of 0.98 and 8.62 seconds in training time. Test results on videos taken 50 frames randomly three times, resulting in an average accuracy 0.95.
Pengembangan Sistem Informasi Lowongan Kerja menggunakan Web Semantik (Studi Kasus : Unit Pengembangan Karir dan Kewirausahaan Universitas Brawijaya) Fachril Rachma Zulfidar; Achmad Arwan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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In the recruitment process at the University of Brawijaya's Career and Entrepreneurship Development Unit (UPKK UB), information on job vacancies from companies can only be accessed on the web page UPKK UB. This results in a lack of spread of information obtained by applicants looking for work. Vacancies in a company are sometimes not properly announced. Thus, applicants who have competencies according to the needs of the position cannot get information easily. With the use of technology web semantics in the job vacancy information system being developed, information spread can be done easily. Web semantics used because web semantics has advantages in data openness. Information owned by a system can be used or shared by other systems. In addition to the advantages of web semantic in data integration, with web semantic computers it is possible to search, combine, and process content web based on meanings understood by humans. The development method used in this system is the waterfall method. This system has been tested using unit testing, integration testing, and validation testing. Based on the tests carried out, the system gets 100% valid results in unit, integration, and validation tests. The system also gets 100% valid results in compatibility testing because it is able to run well in the browser environment under test.
Analisis Sentimen Pada Ulasan Pengguna Aplikasi Mandiri Online Menggunakan Metode Modified Term Frequency Scheme Dan Naive Bayes Eka Putri Nirwandani; Indriati Indriati; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Digital distribution service is a container for various applications that can be downloaded at any time. In addition to applications on Digital distribution service, there are also application reviews that contain comments from certain application users. The review contains a very large number of negative comments or positive comments. Due to the large number of reviews, the digital distribution service shares these reviews using ratings with inappropriate review content. To solve the problem of mismatch between the content of the review and the rating given by the user, a sentiment analysis is needed. This study uses the Naive Bayes method and the Modified Term Frequency Scheme. Naive Bayes method was chosen because it works well in document classification by estimating the required parameters. Used 1,500 data consisting of 627 positive reviews and 873 negative reviews. Preprocessing process is carried out, weighting using the Modified Term Frequency Scheme and document classification using the Naive Bayes method. In the 5-fold test, the average of the method used was accuracy 83%, recall 86%, precision 76%, f-measure 77,70% with the 3rd fold being the best fold with accuracy 85%, recall 84,50%, precision 81,34%, f-measure 82,88%.
Prediksi Cuaca Kota Denpasar menggunakan Algoritma ELM dengan Optimasi Quantum Delta Particle Swarm Optimization Adam Sulthoni Akbar; Candra Dewi; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Weather is an important factor for beach visitors on the island of Bali, especially in the city of Denpasar. Clear weather, is the perfect weather to visit the beach. To make tourist not come to beach when weather it's rainy, a weather prediction is needed, so tourists can determine the right time to visit the beach in the city of Denpasar. Weather is a natural phenomenon that occurs in a relatively short period of time. Weather data is collected via satellite, and can be used to predict the weather in the future. In this research, the weather data used were temperature, wind speed, humidity and air pressure. To make these predictions, an artificial neural network using the Extreme Machine Learning method is used, with the optimization of the Quantum Delta Particle Swarm Optimization. With 5 hidden neuron, the result of accuracy from ELM is 39%, otherwise, with QDPSO optimization with 10 particles, 42 iterations, and g value 0,96, have result 100% accuracy.
Klasifikasi Aritmia Dari Hasil Elektrokardiogram Menggunakan Metode Support Vector Machine Qurrata Ayuni; Randy Cahya Wihandika; Novanto Yudistira
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Arrhythmia (heart rhythm disorder) is a disorder of the cardiac elektrophysology caused by disruption of the conduction system as well as impaired formation and delivery of electrical impulses. Some factors that influence arrhythmia include age, blood pressure, height and weight. This arrhythmia can be recognized by using a cardiac record or electrocardiogram (ECG). Numerical data generated by ECG has many features that are not easily processed manually. Computer assistance with certain machine learning techniques can be used to automatically recognize diseases. One method of machine learning is support vector machine (SVM). In this study, a system was designed to classify arrhythmias using support vector machine (SVM) methods. The most optimal accuracy value or accuracy that has the highest value indicates that the system is in accordance with expectations, so that the support vector machine method is able to measure the accuracy of the classification of arrhythmias based on electrocardiogram results with RBF kernel function of 92%.
Pengembangan Sistem Informasi Manajemen dan Prediksi Permintaan Pemesanan Bibit Parfum Pada Toko Blossom Perfume Berbasis Web Fachrur Rozy; Faizatul Amalia; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Business people use many technological developments in their business, one of which is the management information system. The perfume business is a business that is available in various regions. Blossom Perfume is a shop that runs a famous perfume business in the Kisaran area, Asahan Regency, North Sumatra. Blossom Perfume is currently still using manual methods in transaction data and checking the stock of perfume seeds at each outlet as well as the estimated demand for seed stock in the following month. To solve this problem, a management information system was developed that supports Blossom Perfume in writing sales transactions and optimizing information. The development process in this system uses the waterfall model method. The main features contained in this management system are adding transaction data, viewing transaction history, viewing seed stock at each outlet and predicting orders for perfume seeds. This system is expected to make it easier for owners to manage their business. In making predictions, this system uses the Single Exponential Smoothing (SES) method. The choice of this algorithm is because it requires little past data by assuming fluctuations in data around the average value that still pay attention to patterns or trends. Web-based system with Codeigniter (CI) framework. Testing on this system uses the Whitebox method for unit testing and integration and the Blackbox method for testing validation. Reusability testing was also carried out using the System Usability Scale (SUS) method with a final score of 88.3 (acceptable).
Penentuan Kualitas Biji Kopi Menggunakan Local Ternary Patterns Dan RGB-HSV Color Moment Dengan Learning Vector Quantization Fajri Eka Saputra; Randy Cahya Wihandika; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coffee cultivation in Indonesia is still done by very traditional methods, like wise in determination of its quality level by sorting it out still done by human operators by considering its size and density, which means determination of coffee bean's quality level is very depended on the operator's ability, so that is susceptible to mistakes and non-technical factors that accompany it. The quality level of coffee bean itself is divided to 6 grades that is grade 1 to grade 6 for each variant. One of the methods that can be done to ease determination of the quality of coffee beans is by processing its image by extracting texture feature by using Local Ternary Patterns(LTP) method, color feature with HSV and RGB Color Moment, and utilizing classification algorithm Learning Vector Quantization (LVQ). This method is considered as a breakthrough in coffee bean's grade determination because the cost is cheaper but still gives decent results considered in a relatively short time. In this study, the image data used is as many as 150 data with 30 data on grade 1 through 5 because the data availability was not up to grade 6. This study results a system that was able to classify the quality of coffee beans with an accuracy rate of 84,4%. Two of the entered quality cases were successfully predicted with 100% correctness, namely grade 1 and 5.
Co-Authors Achmad Arwan Achmad Ridok Achmad Yusuf Adam Hendra Brata Adam Sulthoni Akbar Adinugroho, Sigit Aditya Putra Pratama Agi Putra Kharisma Agung Nurjaya Megantara Agus Wahyu Widodo Akhmad Sa'rony Amar Ikhbat Nurulrachman Anang Hanafi Angky Christiawan Rongre Ani Enggarwati Ardisa Tamara Putri Ardiza Dwi Septian Arif Pratama Arynda Kusuma Dewi Barlian Henryranu Prasetio Bayu Kusuma Pradana Bayu Laksana Yudha Bayu Rahayudi Budi Darma Setiawan Budi Dharma Setiawan Candra Dewi Chandra Tio Pasaribu Cindy Cunday Cicimby Cornelius Bagus Purnama Putra Cusen Mosabeth Dani Devito Daris Hadyan Tisantri Denny Sagita Rusdianto Devinta Setyaningtyas Atmaja Dhan Adhillah Mardhika Dhanika Jeihan Aguinta Diajeng Sekar Seruni Dian Eka Ratnawati Dimi Karillah Putra Dito Rizki Pramudeka Dizka Maryam Febri Shanti Dwi Rahayu Eka Putri Nirwandani Emma Wahyu Sulistianingrum Ersya Nadia Candra Fachril Rachma Zulfidar Fachrur Rozy Faizatul Amalia Fajri Eka Saputra Fanny Aulia Dewi Fera Fanesya Fida Dwi Febriani Fikri Hilman Firda Oktaviani Putri Fitra Abdurrachman Bachtiar Frisma Yessy Nabella Gilang Widianto Aldiansyah Glenn Jonathan Satria Gregorius Ivan Sebastian Hafiz Ari Putra Hamim Fathul Aziz Heykhal Hafiddhan Rachman I Gusti Ngurah Ersania Susena Imam Cholissodin Indriati Indriati Irnayanti Dwi Kusuma Jonathan Reynaldo Kevin Haidar Kevin Nastatur Chatriavandi Koko Pradityo Lailil Muflikhah Lalu Muhammad Ivan Natania Latifa Nabila Harfiya M. Rikzal Humam Al Kholili Moh. Dafa Wardana Mohammad Rizky Hidayatullah Muchlas Mughniy Muh. Arif Rahman Muhamad Ilham Dian Putra Muhamad Wahyu Budi Santoso Muhammad Alif Fahrizal Muhammad Amin Nurdin Muhammad Faiz Abdul Hamif Muhammad Ihsan Diputra Muhammad Shidqi Fadlilah Muhammad Tanzil Furqon Muhammad Tegar Kanugroho Naufal Akbar Eginda Nindy Deka Nivani Nova Amynarto Novanto Yudistira Nur Wahyu Ningtyas Nurul Hidayat Nurul Muslimah Pindo Bagus Adiatmaja Pupung Adi Prasetyo Puspita Sari Putra Pandu Adikara Putu Gede Pakusadewa Qurrata Ayuni Raden Rafika Anugrahning Putri Ratih Kartika Dewi Rayindita Siwie Mazayantri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rizal Setya Perdana Rizky Nur Ariyanti Ruri Armandhani Sarah Najla Adha Satria Dwi Nugraha Satyawan Agung Nugroho Sema Yuni Fraticasari Sevtyan Eko Pambudi Sigit Adinugroho Siti Robbana Sukma Fardhia Anggraini Supraptoa Supraptoa Sutrisno Sutrisno Tahajuda Mandariansah Threecia Agil Regitasari Tifo Audi Alif Putra Tri Kurniawan Putra Utaminingrum, Fitri Valen Novandi Kanasya Vandi Cahya Rachmandika Winda Cahyaningrum Yosendra Evriyantino Yosua Christopher Sitanggang Yudha Prasetya Anza Yuita Arum Sari Yurdha Fadhila Hernawan