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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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Implementasi High Order Fuzzy Time Series Multifactor pada Prediksi Harga Ayam Broiler di Pasar Malang Fanny Aulia Dewi; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malang is the second largest population after Surabaya in East Java Province. Malang, which has increased its population every year, has resulted in the need for staples, especially broiler chicken meat, to increase. Broiler chicken meat is one of the sources of nutritious animal protein. Broiler chicken meat can be consumed by all levels of society so that there is an increase in demand every year. The availability of broiler chicken meat must always be fulfilled in the market and must pay attention to the price too. Broiler chicken meat prices on religious holidays (such as Eid al-Fitr, Eid Al-Adha, Christmas) there is a very striking increase compared to prices on normal days. The traders who need information about the price of broiler chickens every day in order to arrange sales so as not to miss. Therefore, a settlement is needed in forecasting the price of chicken using 72 data obtained from BPS in the period January 2013-December 2018. Based on the results of this study, the best MSE is 1,430 based on the highest number of orders.
Prediksi Permintaan Semen Dengan Metode Fuzzy Time Series Yosendra Evriyantino; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cement is a material that is used as an adhesive for solid materials namely bricks or concrete blocks into a strong and sturdy unit, usually used for making houses, walls, foundations, roads, or other buildings. In Indonesia, cement production is quite high. In 2017, the total cement production in Indonesia has reached 107.9 million tons. However, high cement production in Indonesia is not matched by the number of requests. As a result, Indonesia experienced an oversupply of cement which caused the price of cement in the market to experience a decline. Therefore, research on predicting cement demand needs to be done as a solution for cement producers in estimating the amount of cement that needs to be produced. In this study, discussing the Fuzzy Time Series method used to predict the amount of demand for cement. The data used is data collected from PT. Semen Indonesia from 2006 to 2018 for each month. From the test results, the smallest MAPE error value was obtained at 10.42% with a parameter value of 80 intervals for 24 test data and 96 training data.
Penerapan Algoritma Support Vector Regression Pada Peramalan Hasil Panen Padi Studi Kasus Kabupaten Malang Dhan Adhillah Mardhika; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Rice is one of the important resources in human life, in several surveys it was found that more than 59% of the world's population used rice from rice as food staple. But in another theory stated that the human population will continue to develop exponentially while it is difficult to be followed by the growth of food products, especially in this case rice. Support Vector Regression (SVR) method is a method that will be used in this study, this method has been used in several previous studies such as forecasting gold prices and forecasting electricity consumption. In this study we will focus on testing whether the Support Vector Regression (SVR) method is suitable for use in predicting rice yields, using a number of predetermined parameters, and by applying changes to the parameters, namely the number of iterations, Complexity, Epsilon, Sigma, cLR , Lambda. The best results obtained in this study reached MAPE error rate of 10.133%, these results were achieved with the following parameter values, Number of iterations: 50, Complexity: 1, Epsilon: 0.01, Sigma: 1, cLR: 0.1, Lambda: 1
Pengembangan Aplikasi Daily Quest: Aplikasi Untuk Menangani Kemalasan Pada Anak Menggunakan Platform Android Aditya Putra Pratama; Agi Putra Kharisma; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Laziness in children often arises due to lack of motivation in doing something. In psychology, studies state that laziness in children arises due to the absence of habits in regular learning. To increase motivation, parents need to give a gift so that children have the will to do something. This is done to start getting children used to doing things. The provision of daily activity is a tool to get children used to doing daily activities. This research uses the Waterfall software development method. The method is chosen because the functional requirements of the system have been defined from the beginning and have no change. Tests conducted on the Daily Quest application are validation, usability, and compatibility testing. In validation testing results in a 100% success rate. Usability testing results in a success rate of 82.8% for the parent system and 91.6% for the child system. The system usability scale (SUS) method produces an average value of 66 in the parent system, classifying it into the C grade category, which is marginal. Whereas in the child system produces an average value of 73, classified into the category grade B- that is acceptable. In system compatibility testing, the Daily Quest application can only run well on Android Lollipop 5.0 (API level 21 or greater).
Analisis Sentimen Review Produk Smartphone Pada Dokumen Twitter Berbahasa Indonesia Menggunakan Metode K-Nearest Neighbor Dan Pembobotan Jumlah Likes Siti Robbana; Indriati Indriati; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is popular social media in great demand because it provides information needed by many internet users. Such information can be in the form of opinions, questions or review of a product's good or bad. Diverse smartphone product reviews make it difficult for companies to know people's interests and opinions on the smartphone product. To find a solution for this problem, sentiment analysis system is needed on tweets about smartphone products. This research conducted a sentiment analysis with the K-Nearest Neighbor (textual) method to carry out the classification process and add weighting features to the number of likes (non-textual). The result of combining intellectual and non-textual weighting with certain constants is α constans and β constans will produce a class of positive and negative sentiments. The data was used is taken from Twitter in the form 300 data tweets of smartphone product reviews. The test results of 210 training data and 90 test data with textual weighting obtained an accuracy of 91.01%, using only non-textual weighting of 68.53% and combining textual and non-textual weighting resulted an accuracy of 94.38%
Klasifikasi Citra Kue Tradisional Indonesia Berdasarkan Ekstraksi Fitur Warna RGB Color Moment Menggunakan K-Nearest Neighbor Fida Dwi Febriani; Yuita Arum Sari; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Food is one of the needs in primary needs which is very important for humans. These needs must be met every day, but the human tendency for food needs changes with the times. Society in general will choose fast food that is ready to be served rather than choosing traditional food. In this day and age, most people tend to capture the moment when they want to enjoy a food that will be consumed. Taking pictures (photos) is one way, from which the images are obtained an image on food. The image will display several different colors, so the color will be a feature that can be used for extraction. One method used to extract color features in images is Color Moment. This feature will produce three main values namely mean, standard deviation, and skewness. In addition, this feature together with the K-Nearest Neighbor (K-NN) algorithm will classify the extracted colors based on training data taken as many as k values. In this study, there are 29 Indonesian traditional cake objects that will be used, where the test scenario is divided into 29 classes, 8 classes, 5 classes, and 3 classes. By using the K-NN method and the Color Moment feature, the highest evaluation value obtained is 60% for the test scenario of 3 classes.
Analisis Sentimen Kebijakan Pemindahan Ibukota Republik Indonesia dengan Menggunakan Algoritme Term-Based Random Sampling dan Metode Klasifikasi Naive Bayes Akhmad Sa'rony; Putra Pandu Adikara; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The capital city relocation policy of the Republic of Indonesia that was announced by President Joko Widodo last August caused many pros and cons in the community, especially in the social media environment. In this study, sentiment analysis of the policy is done using data obtained from Twitter. The system development process includes data scraping, preprocessing, Raw Term Frequency calculation and classification using the Naive Bayes method. In preprocessing, the filtering process is done using the Term-Based Random Sampling algorithm to create a stoplist. The testing process is done by 2 methods, parameter testing and multiclass confusion matrix testing. Parameter testing is done by changing the percentage of term of the training data used as a stoplist, ranging from 0 percent to 60 percent, while the confusion matrix is ​​used to calculate the value of accuracy, precision, recall, and f-measure. Based on the confusion matrix test results, the system gets the best macroaverage value in the classification with a stoplist of 20 percent with an accuracy macroaverage value of 0,94, precision macroaverage value of 0,945, recall macroaverage value of 0,94, and f-measure macroaverage value of 0,938.
Penentuan Model Lajur pada Self-Driving Car menggunakan Hough Transform dan Kuantisasi Warna K-Means Pupung Adi Prasetyo; Randy Cahya Wihandika; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Technology continues to develop to the phase where human daily activities can be carried out by artificial intelligence. Research on artificial intelligence keeps on competing to produce more advanced program to simplify things. Nowadays artifial intelligence tools can be found in various application, one of them is self-driving car. This topic is one of the most widely researched topic due to its various division of functionality. The most frequently discussed functionality is the defining of navigation lane model. The lane model which is the navigation direction of a self-driving car must be visually determined based on the road markings, which also the navigation direction directions of public vehicles. Therefore, this study will determine the lane model visually using image processing methods. By only using image processing, the resulting precision can reach an average value of 88.45% in various road conditions. Therefore, it can be concluded that the visual image processing can be used to determine the lane model in a self-driving car.
Prediksi Keputusan Pelanggan Menggunakan Extreme Learning Machine Pada Data Telco Customer Churn Daris Hadyan Tisantri; Randy Cahya Wihandika; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this modern era many company and institution compete to sell their services like internet and telecommunication that use subscription system to sell their services. Because of that, company must compete via marketing strategy. Main factor for customer to continuously extend their subscription is loyalty. Loyalty have directly proportional with business performance. Because of marketing factor and customer loyalty, many customers changed or stopped their subscription from one and another similar company and makes some company lost their customer and revenue. If company or institution can predict churn, they can anticipate so that customer didn't churn. In this research, the dataset that used for this research is from Kaggle sourced from IBM Sample Data Sets. This dataset consists of 7043 data that have 20 features with two classes yes if the customer churn and no if the customer is not churn. After that, the feature on the dataset that not used will be eliminated with Pearson correlation. After that the data will be trained on Extreme Learning Machine to predict customer will churn or not. Result of this research is the system can get accuracy 76,96%, precision churn 65,45%, precision non churn 78,65%, recall churn 29,38%, recall non churn 94,19%
Ekstraksi Ciri untuk Klasifikasi Jenis Kelamin berbasis Citra Wajah menggunakan Metode Compass Local Binary Patterns Muhamad Wahyu Budi Santoso; Randy Cahya Wihandika; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Humans can quickly and make accurate predictions from visual images. Among facial tasks, gender classification is one that has an important role and is probably the easiest and fastest way to achieve. This time, the use of computers continues to grow so that a system similar to human capabilities is built, namely the gender recognition based on facial images. Some applications that require a gender recognition system such as, application of human-computer interaction interface (adjusting software behavior concerning the gender of the user), and demographic data collection to determine trends and product recommendations in the store based on gender. The use of accessories on facial images such as glasses, earrings, and hats that can make a person's gender difficult to recognize is a challenge in doing gender classification based facial image by the system. Compass Local Binary Patterns (CoLBP) as one of the image processing methods used in feature extraction for gender classification based face images. CoLBP utilizes the Kirsch Compass Mask to improve the performance of Local Binary Patterns (LBP) in the feature extraction process. In this research using the Color FERET dataset containing photos of faces (with accessories and without accessories) and the Random Forest classification method for the evaluation process. In the test results, the best accuracy average is 91.8%. From this research, can be concluded that the CoLBP method provides good feature extraction performance and accessories on the face give an influence on the reducing quality of the feature extraction by the CoLBP method.
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