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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Systemic: Information System and Informatics Journal Community Empowerment
Putra Pandu Adikara
Universitas Brawijaya
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Optimasi Susunan Bahan Makanan untuk Ibu Hamil Kurang Energi Kronis (KEK) Menggunakan Algoritme Genetika Ika Oktaviandita; Imam Cholissodin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Women during pregnancy are advised to maintain nutritional adequacy, especially energy and protein. Inadequate nutrition intake will cause pregnant women at risk of Chronic Lack of Energy or in Indonesian called as Kurang Energi Kronis (KEK). In this research given recommendations of the composition of foodstuffs that have balanced nutrition with minimal price using genetic algorithm. The process of finding a solution is to perform a combination of chromosomes and then processed using genetic operators (crossover, mutation, and selection). Crossover process using one cut point method, mutation method used is exchange mutation, and selection process using selection elitism method. Need of parameters of genetic algorithm are population size, Crossover rate (Cr), Mutation rate (Mr), and number of generations. In this system obtained the best optimization results on the population size of 100 population with average fitness value 17.744, Cr value of 0.5 and the value of Mr of 0.5 with average fitness value 17.983, and on the number of generations 100 generated average Average fitness value of 17.962. The results obtained recommendations of the composition of foodstuffs for 7 days along with the costs to be incurred. However, these results still do not meet the maximal needs during pregnancy.
Klasifikasi Penyimpangan Tumbuh Kembang pada Anak Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Afrizal Rivaldi; Putra Pandu Adikara; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Humans during life must experienced a phase of growth and development. This growth and development phase is very influential on the quality of child growth. The critical period of growth and development occurs in the first years of a child's life. At an early age, the process of growing physical, mental, and psychological development is very fast so that requires more attention from parents. In the development phase may occur disorders where the process of growth and development of children obstructed or unnatural. Development disorders are often encountered autism, ADHD, and Down syndrome. This study will classify development disorders based on symptoms that appear using Neighbor's Nearest K-Neighbor (NWKNN). The NWKNN method is the development of the KNN method, which is weighted on each class to be classified. In this research will be classify various types of development disorderds that include autism, ADHD, Down syndrome and normal. The results of this study indicate that the NWKNN method can classify well by using 80 training data and 20 test data, K = 10, and E = 4 with 95% up to accuracy. This study also proved NWKNN method which has 3% average of accuracy better than KNN method in doing classification of growth and development of child.
Prediksi Harga Emas Batang Menggunakan Feed Forward Neural Network Dengan Algoritme Genetika Dimas Fachrurrozi Azam; Dian Eka Ratnawati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Investment is an activity to buy goods, with the purpose to be sold to other investors until they reach a high enough value. There are many types of investments, one of which is gold. Some people who are just starting out in investing find it difficult in deciding to buy and sell gold. Many losses will be obtained if the investor missteps in selling or buying gold. Based on the problem, the researcher intends to help the investor by proposing gold price prediction system using feed forward neural network (FFNN) with genetic algorithm. The genetic algorithm method is used to optimize the existing weights to be used with the forward neural network feed model to process the price prediction. From the test result, the total of 126 training data, and the total of 54 testing data, the CR value 0.3 and the MR value 0.7, the number of pop size is 250, the number of generations are 200, yields an average mean root mean square error (RMSE) of 0.304587%.
Klasifikasi Dokumen Sambat Online Menggunakan Metode K-Nearest Neighbor dan Features Selection Berbasis Categorical Proportional Difference Nur Hijriani Ayuning Sari; Mochammad Ali Fauzi; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sambat Online is a platform to facilitate the suggestions, criticisms, complaints or questions from public to the Government of Malang through provided websites or via short messages. Incoming complaints, will be categorized into various fields of SKPD. To make it easier to organize the text and increase the efficiency of the administrator in sorting out and define the field of SKPD, an intelligent systems that can classify documents according to its SKPD's field is needed. K-Nearest Neighbor (K-NN) is a method of classification that will be used to find similarities between documents. Feature selection method used in this research is Categorical Proportional Difference (CPD) to measure the degree of contribution of a word. Started from collecting the test documents and training documents, continue to the preprocessing stage and selection features, weighting, and then do the classification, and analysing the results of the classification system by value of accuracy, precision, recall, and F-Measure. The result is the most optimal performance is the use of k = 1 with featured as much as 100% of 91.84%, which shows better value compared to the featured selection due to the removal of the term with low CPD value.
Implementasi Metode Backpropagation untuk Mengenali Teks pada Natural Scene Image Imam Ghozali; Tibyani Tibyani; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Text in images contain useful information. Text detection in Natural Scene Image (NSI) becomes an important part of research on text information extraction (TIE). For getting information on the NSI there are various challenges, such as determining the text region in a complex background to recognize various kinds of text that has a variety of shapes, sizes, colors and others. The results of TIE can be implemented in many ways, one of them system can to help blind people to recognize product label or recognize text is around them. To recognize text on the NSI is a composite of two research topics, the first topic is determination of the text region or text detection and second topic is recognizing character of text or character recognition. In this research will focus on recognizing character using backpropagation method. Results of tests is 44.00%, this is influenced by the features extracted from the results of image binerization, many image data has a noise.
Optimasi Vehicle Routing Problem With Time Windows (VRPTW) Pada Rute Mobile Grapari (MOGI) Telkomsel Cabang Malang Menggunakan Algoritme Genetika Moch. Khabibul Karim; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sales Operation and Outlet (SOO) is one of Telkomsel's divisions. Sales Operation in transportation field is called Mobile Grapari (MOGI). Mogi operates every day, looking for sales points, but those points hasn't been effective in sales operation. The previous system was a manual scheduling by coordination between one MOGI with the other, causing occuring problem which is an empty point. This problem also leads to scheduling ineffectiveness at sales point which gives less than optimal results. One of causes is Vehicle Routing Problem with Time Windows (VRPTW). To overcome this problem, an optimization method called genetic algorithm is applied. Genetic algorithm is applied for solving point routes and sales profits. The test is performed to find the parameters that produce the best fitness value. The result of the test shows that the best population size is 450 with 2700 generation iteration and the combination of crossover and mutation rate are 0,2 and 0,9 respectively. Through this test, we get the best selection method that is elitism selection. The fitness value of best parameters is 0,5581. The effective route solution that is generated on Monday, First Car is in Arjosari (Terminal Area), Singosari (Samsat Singosari), and Karang Ploso Rest Area. Second Car is in Gadang (Terminal Hamidrusdi), Sudimoro (Pujas front SM Futsal Zone), and Kawi Atas Street. Third Car is located in Merjosari (Lap. Merjosari), Sigura-gura Street, (Home Aston Printer) and Tlogomas (Ruko Kopi Sosial) with Rp. 5.114.167.00 profit and Rp. 35.584.167,00 for a week.
Penerapan Algoritme Genetika Untuk Penjadwalan Latihan Reguler Pemain Brass Marching Band (Studi Kasus: Ekalavya Suara Brawijaya) Marina Debora Rindengan; Imam Cholisoddin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Marching band is an extracurricular where the players are required to work together in a team in order to give a good appearance. The rehearsals require a lot of times with many players. A poor schedule of marching band rehearsal or conflict of schedule between players can cause problems in doing the rehearsals. Data schedule of each player is taken from Marching Band Ekalavya Suara Brawijaya, and national holiday from September 2016 until December 2016. After getting the data, process of genetic algorithm that start from chromosome representation to time and practice day, and then do the process of extended intermediate crossover and reciprocal exchange mutations for new offspring that will be selected by elitism selection for next generation. The optimal schedule is obtained through testing, the largest average fitness score is 1 on the population size 130, the number of generation is 140, and combinations of cr and mr is 0,5.
Analisis Sentimen pada Review Konsumen Menggunakan Metode Naive Bayes dengan Seleksi Fitur Chi Square untuk Rekomendasi Lokasi Makanan Tradisional Novan Dimas Pratama; Yuita Arum Sari; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Consumer reviews at a restaurant are very influential in the quality of the restaurant itself. Many of the consumers pour critics or opinions through the internet media. The purpose of this study was to analyze the opinion sentiment from traditional food consumers as well as provide location recommendations with the desired keywords. Naive Bayes is a machine learning technique that is often used to classify text data. Chi Square is a feature selection used to calculate the level of a feature's dependencies on a class. In this study, Chi Square method gives value to the feature which is then sorted and selected according to percentage tested. Selected features are used for the classification process using the Naive Bayes method. The result of classification accuracy with 25% feature selection is 81%, with 50% feature selection is 80% and with 77% feature selection is 80%. From this test it can be concluded that feature selection is not so influential on the result value accuracy. It can be seen the difference of the accuracy value between using feature selection and without using a feature selection that is not very significant.
Implementasi Named Entity Recognition Pada Factoid Question Answering System Untuk Cerita Rakyat Indonesia Yulia Kurniawati; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Regional legend or folklore is a story that developed among the various cultures of Indonesia that have been down and down inherited. Folklore is a story of the past that is believed to be the true event, usually the folktale is the origin of a place. The lack of an attractive means of introducing folklore is one of the reasons for the lack of interest of Indonesian folklore. In addition, the level of understanding of children who are still less than adults cause them to easily forget the story of the people when they are less understood to the story of the people of Indonesia. This study aims to facilitate the children in understanding the story. Therefore, the researcher makes question answering system by using Named Entity Recognition method. The classification of named entity in this research using naive bayes method. In this research used four named entity to recognize the next word will be candidate for answers such as product, person, location and none. Where none is an entity. In addition, the type of question that can be asked on the question answering system is Factoid Question is a question that the answer is a short and solid fact not a description. The data used are five folk stories of Indonesia obtained from the internet and the classification of Named Entity has a precision value of 34.22%, the accuracy of NE classification of 64.65% and recall 13.13% while for question answering accuracy system obtained accuracy of 16.7%.
Pembangkitan Aturan Pengenalan Emosi Pada Twitter Menggunakan Metode Fuzzy-C Means Farid Rahmat Hartono; Yuita Arum Sari; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this digital era, social media users are growing more rapidly and more mediasocial applications. One of the most widely used social media today is Twitter, with users reaching over hundreds of millions of people in the world. Twitter is a mobile or desktop application where users can create an article that can reflect their emotions through a short text form status with a maximum of 140 characters. With so many active users up to now then on every status created by Twitter users can reflect their emotions. It takes a pesikolog to see an emotion from the status of people in social media because there is no automatic system to determine one's emotions through its status on Twitter. The system in this research is made using Fuzzy C-Means (FCM) method. The FCM method can be used to generate rules that can replace the role of a psychologist to determine a person's emotions from a status he or she creates on Twitter's social media. The Term Frequency & Invers Document Frequency (TF-IDF) weighting method in text mining is used to process textual data into numerical data to be able to be processed by FCM. Based on the test results, this system produces an highest accuracy of 70% so it can be concluded that the FCM method is good used in the formation of a person's emotional determination of a status on social media Twitter.
Co-Authors Adani, Rafi Malik Ade Kurniawan Adinda Chilliya Basuki Adinugroho, Sigit Adiyasa, Bhisma Afrizal Rivaldi Agi Putra Kharisma, Agi Putra Agus Wahyu Widodo Ahmad Fauzi Ahsani Akhmad Sa'rony Al Farisi, Faiz Aulia Al Huda, Fais Albert Bill Alroy Alimah Nur Laili Allysa Apsarini Shafhah Alqis Rausanfita Alvandi Fadhil Sabily Amaliah, Ichlasuning Diah Amar Ikhbat Nurulrachman Ananda Fitri Niasita Anang Hanafi Andina Dyanti Putri Andre Rino Prasetyo Anggraheni, Hanna Shafira Ani Budi Astuti Annisa Alifia Annisa, Zahra Asma Arsya Monica Pravina Aulia Jasmin Safira Aulia Rahma Hidayat Avisena Abdillah Alwi Azhar, Naziha Baliyamalkan, Mohammad Nafi' Barbara Sonya Hutagaol Bayu Andika Paripih Bayu Rahayudi Bryan Pratama Jocom Budi Darma Budi Darma Setiawan Candra Dewi Candra Dewi Dahnial Syauqy Daisy Kurniawaty Danang Aditya Wicaksana Dayinta Warih Wulandari Deri Hendra Binawan Dhanika Jeihan Aguinta Dheby Tata Artha Dian Eka Ratnawati Dika Perdana Sinaga Dimas Fachrurrozi Azam Dwi Suci Ariska Yanti Dwi Wahyu Puji Lestari Dyva Pandhu Adwandha Edy Santosa Eka Dewi Lukmana Sari Elmira Faustina Achmal Evilia Nur Harsanti Faiz Aulia Al Farisi Farid Rahmat Hartono Fattah, Rafi Indra Fayza Sakina Maghfira Darmawan Febriarta, Renaldy Dwisma Ferdi Alvianda Ferly Gunawan Ferly Gunawan Firdaus, Agung Firmansyah, Ilham Fitra Abdurrachman Bachtiar Franklid Gunawan Galih Nuring Bagaskoro George Alexander Suwito Gilang Widianto Aldiansyah Glenn Jonathan Satria Guedho Augnifico Mahardika Haekal, Firhan Imam Hanson Siagian Hendra Pratama Budianto Hernawan, Yurdha Fadhila Hibatullah, Farras Husain Husein Abdulbar Ichsan Achmad Fauzi Ika Oktaviandita Imam Cholisoddin Imam Cholissodin Imam Ghozali Imanuel Juventius Todo Gurning Indah Mutia Ayudita Indriati Indriati Indriati Indriya Dewi Onantya Ivan Fadilla Ivan Ivan Jesika Silviana Situmorang Jojor Jennifer BR Sianipar Jonathan Reynaldo Junda Alfiah Zulqornain Karina Widyawati Karunia Ayuningsih Katherine Ivana Ruslim Khalisma Frinta Krishnanti Dewi Laila Restu Setiya Wati Lailil Muflikhah Laksono Trisnantoro Lubis, Saiful Wardi Lusiyana Adetia Isadi Luthfi Mahendra M. Aasya Aldin Islamy M. Ali Fauzi Maghfiroh, Sofita Hidayatul Makrina Christy Ariestyani Marina Debora Rindengan Maya Novita Putri Riyanto Mayang Arinda Yudantiar Mayang Panca Rini Melati Ayuning Lestari Moch. Khabibul Karim Moh. Dafa Wardana Mohammad Fahmi Ilmi Mohammad Toriq Muh. Arif Rahman Muhammad Faiz Al-Hadiid Muhammad Fajriansyah Muhammad Iqbal Pratama Muhammad Nurhuda Rusardi Muhammad Rizaldi Muhammad Rizky Setiawan Muhammad Tanzil Furqon Muhammad Taufan Muthia Azzahra Nadhif Sanggara Fathullah Nadia Siburian Nanda Agung Putra Nanda Cahyo Wirawan Naufal Akbar Eginda Naziha Azhar Niluh Putu Vania Dyah Saraswati Novan Dimas Pratama Novanto Yudistira Nur Hijriani Ayuning Sari Nurul Hidayat Panjaitan, Mutiharis Dauber Panji Husni Padhila Pengkuh Aditya Prana Prais Sarah Kayaningtias Prakoso, Andriko Fajar Pretty Natalia Hutapea Putri Rahma Iriani Radita Noer Pratiwi Rahma Chairunnisa Raissa Arniantya Randy Cahya Wihandika Randy Cahya Wihandika Randy Ramadhan Ravindra Rahman, Azka Renata Rizki Rafi` Athallah Renaza Afidianti Nandini Restu Amara Rezky Dermawan Rhevitta Widyaning Palupi Ridho Agung Gumelar Riza Cahyani Rizal Maulana, Rizal Rizal Setya Perdana Rizal Setya Perdana Rosy Indah Permatasari Sagala, Revaldo Gemino Kantana Salsabila Insani Salsabila Rahma Yustihan San Sayidul Akdam Augusta Santoso, Nurudin Sigit Adinugroho Sigit Adinugroho Silaban, Gilbert Samuel Nicholas Silvia Ikmalia Fernanda Sindy Erika Br Ginting Sri Indrayani, Sri Sutrisno Sutrisno Tania Malik Iryana Taufan Nugraha Thariq Muhammad Firdausy Tibyani Tibyani Tirana Noor Fatyanosa, Tirana Noor Uke Rahma Hidayah Utaminingrum, Fitri Vergy Ayu Kusumadewi Vinesia Yolanda Vivin Vidia Nurdiansyah Wijanarko, Rizqi Yerry Anggoro Yohana Yunita Putri Yoseansi Mantharora Siahaan Yosua Dwi Amerta Yuita Arum Sari Yuita Arum Sari Yuita Arum Sari Yulia Kurniawati Yurdha Fadhila Hernawan Yure Firdaus Arifin Zahra Asma Annisa