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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Sutrisno Sutrisno
Fakultas Ilmu Komputer , Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Penentuan Varietas Padi Unggul yang Akan Ditanam Berdasarkan Potensi Hasil Menggunakan Metode Analytic Hierarchy Process-Weighted Product (AHP-WP) Tunggul Prastyo Sriatmoko; Nurul Hidayat; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The increasing population in Indonesia every year, which results in increased demand for food in Indonesia. While the increase in production of the country's agricultural production is still lacking, resulting in the government doing imports to meet food needs. Therefore, an effort is needed to improve better production, especially in rice, which is the staple food of the Indonesian population, one way to increase production is by planting seeds of superior varieties of rice. However, many criteria need to be considered in choosing which rice varieties are suitable to choose from in making choices. From these problems, there are several methods that can be implemented in solving problems with a system that is able to provide advice on the type of rice planted using the Analytic Hierarchy Process (AHP) method to give weights and the Weighted Product (WP) method is used to calculate alternative ranks and take values the highest as a final recommendation. In the testing phase with an accuracy method comparing the results of recommendations from the system compared to recommendations from experts, the resulting accuracy rate is 90.19607843%, so that it can be concluded that the AHP and WP methods can be used in recommending superior types of rice because they have high accuracy values above 90% nearing perfect from expert data.
Sistem Perkiraan Penggunaan Listrik Rumah Tangga Menggunakan Logika Fuzzy (Studi Kasus: PLN Area Pasuruan) Mochamad Ali Fahmi; Muhammad Tanzil Furqon; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In one of Indonesia's regions, Pasuruan, in recent years there has been a rapid increase in economic growth, resulting in a large increase in electricity demand to exceed the scenario originally planned by the government. The electricity system in the city of Pasuruan itself is a complex electricity system where there are difficulties in estimating the amount of electricity that can affect the readiness of the generating unit to provide electricity supply to consumers. Based on these constraints, it is necessary to estimate long-term electricity use, especially for the household sector in planning the addition of new power plants, expansion of the distribution network and planning requirements for the operation of electricity generation, so that the power generated is in accordance with load requirements. In this study Fuzzy Logic method is used to estimate or forecast. Data that were used as many as 70 historical data from January 2012 to October 2017 obtained from PLN Pasuruan Area. The results of the implementation and accuracy testing in this study got the best parameter value with the lowest MSE value of 1.602823095 and MAPE 3,84%. The test is done to get the best number of fuzzy sets at 16, while the worst value is 7 fuzzy sets.
Klasifikasi Citra Jenis Makanan dengan Color Moments, Morphological Shape Descriptors, dan Gray Level Coocurrence Matrix menggunakan Neighbor Weight K-Nearest Neighbor Muhammad Abdan Mulia; Yuita Arum Sari; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The level of development of human growth depends on food consumed daily. The good condition of the human body comes from healthy and hygienic food. Recognizing a food becomes a problem for visitors or tourists who are visiting a food place that has no known nutrient levels and ingredients. To overcome this problem, research needs to be done to classify a food image. Morphological Shape Descriptors (MSD), Color Moments (CM), and Gray Level Co-ocurence Matrix (GLCM) features with Haralick have been shown to produce good features for classification. The Neighbor Weight K-Nearest Neighbor method is also an alternative to the image classification process.Based on the test results from k-fold cross validation with k = 10 and the evaluation method in the form of accuracy, obtained maximum accuracy of 0.86 with parameter values ​​E = 11 and k = 3 in the case of training data amounting to 530 images of single food which has been pre-processing. This shows that the classification of food images based on the extraction of textural features such as form (MSD), color (CM), and texture (GLCM) results in relatively better accuracy. In addition, the combination of the use of these three features affects the results of accuracy. This is indicated by testing which shows that the results of relative accuracy are better achieved in features of a combination of textures, shapes, and colors.
Implementasi TOPSIS Pada Sistem Rekomendasi Pemilihan Lapangan Tenis Di Malang Berbasis Lokasi Heru Budiyanto; Ratih Kartika Dewi; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Many people, especially in Malang city, like to play sports in tennis courts, so more tennis courts are spread out in Malang. However, with so many places in the tennis court, sometimes many people do not know which one is better for training. Seeing this problem, the researchers built a recommendation system for tennis courts in Malang. This system was developed using the Android-based native mobile development model so that it can be reached by many people. With this application, the community can get recommendations on suitable tennis courts based on their location using GPS. The recommendation system for the tennis court was designed using the TOPSIS method with 3 criteria data, namely the distance from the user's location using haversine calculations, tennis court prices per hour, and rating. The results of functional testing, the system built has fulfilled the functional requirements with a 100% valid value, Testing the algorithm validation between manual calculations and system calculations shows a 100% match in the form of alternative sequences and the value of each alternative, and Rank Consistency Testing by reducing and the addition of criteria is 2 criteria and 4 criteria compared to the initial criteria to get a consistent ranking result.
Deteksi Plagiarisme pada Artikel Berita Berbahasa Indonesia menggunakan BM25 Dina Dahniawati; Indriati Indriati; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the cases that had tarnished the world of journalism was the plagiarism that had been carried out by a journalist related to the news articles he wrote. Plagiarism was not given strict observation, so that the reuse of all news articles could be carried out freely in the past. But as time goes by, news agencies are no longer able to ignore the case of plagiarism, so detection of plagiarism is very important to implement. The method used to detect plagiarism in this study is BM25. The process of calculating plagiarism using BM25 begins with text preprocessing, searches for term frequency value, inverse document frequency, weighting using BM25, then calculating the percentage of plagiarism. Testing is done by changing the threshold value by 75%, 50%, and 25%. Then the results of plagiarism calculations using BM25 will be compared with the results of cosine similarity. The average results from BM25 are closer to the threshold with a difference of 6.12%, 9.77%, and 10.01%. These results prove that BM25 works better than cosine similarity which has a difference of 14.25%, 26.43% and 32.36% of the threshold. The average value of precision from BM25 for each threshold is 0.87, 0.80, and 0.63.
Prediksi Rating pada Reveiw Produk Kecantikan Menggunakan Metode Contextual Valence Shifters dan Regresi Linear Nanda Firizki Ananta; Mochammad Ali Fauzi; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

At present there are various kinds of beauty products. With a variety of products, the selection of beauty products in accordance with the needs must be done to get the best results. One way to choose beauty products for consumers is to look at reviews along with ratings of the products to be purchased. But with the existence of various review sources, it is not uncommon for the review not to be accompanied by a rating, making it difficult for the consumers to see whether the product to buy is a good product or not. Therefore, this research aims to categorize the review into a rating so that it is easier for consumers to determine the selected product. The system built in this research uses the Contextual Valence Shifters and Linear Regression methods and the use of n-grams includes taking the word bigram, trigram, and review sentences. In system testing, the highest results for the tolerance 0 testing model are 21,6% for bigram and trigram, the tolerance 1 test model the highest accuracy is 66,5% for bigram and for sentiment review is 62,4% for bigram. From the results of the tests, the use of n-gram especially bigram had a positive impact on the results of system accuracy.
Prediksi Volume Impor Beras Nasional menggunakan Metode Support Vector Regression (SVR) Cindy Inka Sari; Budi Darma Setiawan; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In Indonesia domestic rice production and rice imports are needed in order to attain national rice consumption. As the number of people increases and imported rice are consumed continuously, therefore Indonesia depends on rice imports from other countries. Prediction is needed to control the volume of national rice imports because excessive imports will cause negative losses and impacts. Support Vector Regression (SVR) is used to predict the volume of national rice imports. The data used in the prediction are data on consumption, production, volume of rice imports 1 year earlier as bebas variables and data on the volume of national rice imports in the period 1971 - 2016 as terikat variables. Tests carried out using 9 test data obtained the best parameters Sigma (σ) = 0.07, Lambda (λ) = 0.4, Constanta Learning Rate (cLr) = 0.01, Kompleksitas (C) = 10, Epsilon (ε) = 0.0004, the number of Iterations = 2000 and the number of training data = 37. The evaluation results were measured using Mean Absolute Presentage Error (MAPE). The best MAPE value produced is included in the sufficient category of 32.2748
Pengenalan Citra Jenis Makanan Menggunakan Klasifikasi Naive Bayes Dengan Ekstraksi Fitur Hue Saturation Intensity Color Moments Dan Morphological Shape Descriptors Ian Lord Perdana; Yuita Arum Sari; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The process of determining some kind of food become important because it will determine the food that will be processed in the system that recorded the food for health and diet purpose. The process of determining food consist of preprocessing process and then changing the color model of the image from RGB to HSI. The next process is color feature extraction with Color Moment method that will generate the mean feature, standard deviation feature, and skewness feature from every color channel. Then, for shape feature extraction will using Morphological Shape Descriptors that will generate the length feature, width feature, diameter feature, and aspect ratio feature from the image. After the feature get extracted from the image, do the classification process with Naive Bayes Method with the help of LogSumExp for the probability calculation. The result in the testing of the effect of testing data generate 78% accuracy value when using 100 testing data. The result in the testing the effect of image dimension generate 81% accuracy value when using 300x300 pixel image for testing. The result in the testing the effect of number feature used generate 83% accuracy value when using feature from Color Moment only. The conclusion is, the feature extraction Color Moment and Morphological Shape Descriptors with Naive Bayes classification can be used to determine the kind of some food.
Temu Kembali Citra Makanan Menggunakan Color Histogram Dan Local Binary Pattern Chindy Putri Beauty; Yuita Arum Sari; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Technology makes it easier for humans. One of them is the ease of finding food on the internet. However, in general, search engines are available using text queries with image file names, a textual based approach. It is difficult to be done on large-scale imagery. Image search based on visual image content commonly known as image retrieval system based on content or Content Based Image Retrieval (CBIR) can be used as a solution. Food image has different colors and textures. The texture feature extraction method used in this research is Local Binary Pattern (LBP) and for the color feature extraction is Color Histogram. The image used is 444 data, 413 data as data training and 31 data as data testing. Based on feature extraction, similarity can be calculate using Euclidean distance. The result get by calculating Mean Average Precision (MAP). The best MAP obtained when the n value is 2 with MAP 0,919354 which n is the number of document that displayed on result. For the feature comparison testing, the use of color features only provides better results than using the texture feature or both features
Prediksi Rating Otomatis pada Review Produk dengan Metode Contextual Valence Shifters, K-Nearest Neighbor (K-NN), dan Regresi Linear Ahmad Galang Satria; Mochammad Ali Fauzi; Sutrisno Sutrisno
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

The growing use of communication media makes information easy to obtain including information on products provided in online stores. The rating feature on the website is a way to see the quality of the product to be purchased so as not to make a wrong choice when purchasing a product that can have a bad impact. Abundant data about product reviews in various online sources are useful as study material for producers in improving product quality. The existence of review data that is found without accompanying the rating makes it difficult for producers to determine the review into a particular sentiment. In this study can accelerate the determination of reviews into sentiment in the form of rating. This study uses a linear regression method and k-nearest neighbor as a prediction method and the method of weighting the contextual valence shifter based on the lexicon dictionary after pre-processing. The use of n-gram includes unigram, bigram, and trigram aimed at increasing the accuracy of the system. The greatest percentage is obtained at tolerance 1 with the results obtained by trigrams greater than bigram or unigram with linear regression method, namely 77% accuracy while k-NN gets 75% accuracy at k = 20 and k = 30. The test results show the use of n-grams, especially bigram and trigram has a positive impact on the results of system accuracy.
Co-Authors Abas Saritua Gultom Achmad Dwi Noviyanto Adinugroho, Sigit Aditya Negara Aditya Sudarmadi Agi Putra Kharisma Agus Prayogi Ahmad Galang Satria Anandita Azharunisa Sasmito Andi Amaliyah Maryama Arthur Julio Risa Ashshiddiqi Axel Iskandar Budi Darma Setiawan Candra Dewi Chalid Ahmad Aulia Chindy Putri Beauty Cindy Inka Sari Danastri Ramya Mehaninda Deby Chintya Dewi Syafira Dhavin Putra Alamsyah Dhimas Tungga Satya Dina Dahniawati Dita Sundarningsih Dyah Ayu Wahyuning Dewi Edy Santoso Endah Utik Wahyuningtyas Enny Trisnawati Fajar Pradana Faraz Dhia Alkadri Febriyani Riyanda Filan Maula Andini Firhad Rinaldi Saputra Fran's Dwi Saputra Atmanagara Galih Aulia Rahmadanu Heru Budiyanto Ian Lord Perdana Imam Cholissodin Imam Farouqi Faisal Inas Nabila Indri Monika Parapat Indriati Indriati Jeowandha Ria Wiyani Jodi Irjaya Kartika Karuniawan Susanto Kukuh Wicaksono Wahyuditomo M. Ali Fauzi Mahardhika Hendra Bagaskara Marji Marji Miracle Fachrunnisa Almas Mochamad Ali Fahmi Mochamad Rafli Andriansyah Mohamad Yusuf Arrahman Muhammad Abdan Mulia Muhammad Alfian Nuris Shobah Muhammad Hafidzullah Muhammad Tanzil Furqon Nanda Firizki Ananta Nurul Hidayat Putra Pandu Adikara Putri Indhira Utami Paudi Rachmad Faqih Santoso Rachmad Ridlo Baihaqi Rahmatsyah Rahmatsyah Rakhmadina Noviyanti Randy Cahya Wihandika Ratih Kartika Dewi Rayindita Siwie Mazayantri Rekyan Regasari Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Indah Rokhmawati Rezza Hary Dwi Satriya Rich Juniadi Domitri Simamora Riski Adam Elimade Rizal Maulana Sabrina Nurfadilla Safira Dyah Karina Siti Utami Fhylayli Supraptoa Supraptoa Thariq Muhammad Firdausy Tibyani Tibyani Tri Halomoan Simanjuntak Tunggul Prastyo Sriatmoko Wayan Firdaus Mahmudy Widya Amala Sholikhah Yose Parman Putra Sinamo Yuita Arum Sari