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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
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

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Klasifikasi Hoaks Menggunakan Metode Maximum Entropy Dengan Seleksi Fitur Information Gain Albert Bill Alroy; Putra Pandu Adikara; Sigit Adinugroho
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

In 2016, Indonesia has 132 million internet users. This number increase to 143 million users in 2017. Internet user can access many things such as chatting services, social media, and e-commerce. There are many people who intentionally make false information known as Hoax. Hoax are information or news that contains uncertain facts or events that have not occured. The problem of spreading Hoax can be reduced by making a system that can classify whether a news is a Hoax or not. The method used in this research is Maximum Entropy with Information Gain Fiture Selection. The amount of data used in this research is 600 articles in Indonesian. There are 372 news articles classified as facts and 228 news articles classifed as Hoax. The amount of best results accuracy in this research is 0,8 with information information gain fiture selection (threshold = 50%), 1 precision, 0,8 recall, and 0,89 f-measure.
Klasterisasi Data Titik Api Menggunakan Metode Self Organizing Map di Wilayah Jawa Dika Perdana Sinaga; Putra Pandu Adikara; Yuita Arum Sari
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 events of forest fires can occur naturally or artificial that impact environmental damage and loss of all aspects. Indonesia's wildfires are increasing annually. This is because Indonesia has many peatlands and rainfall in the dry season is less than half the normal rainfall or known as the El Nino Southern Oscillation (ENSO) phenomenon. Early indications forest fires can be known through a fire point (hotspot). In the years 2010 to 2018 found 14.070 fire points in Java region. One way to detect land fires is to divide the data of the fire points into groups using the Self Organizing Map (SOM) method. To measure the quality of the formed cluster, the Silhouette Coefficient (SC) algorithm is used. Based on the test results obtained the highest SC value of 0.248945455 with the value of neuron count is 3, alpha value is 0.1, maximum epoch value is 18 and the value of reduction of learning rate is 0.1. In 2017 the resulting SC value was 0,23416068940874324. The result is that East Java region has a big chance of land fires if seen from the point of fire that appears and confidence value.
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.
Optimasi Feeder Vehicle Routing Problem pada Distribusi Pengiriman Barang dengan menggunakan Multiple Travelling Salesman Problem dan Algoritme Genetika Maya Novita Putri Riyanto; Imam Cholisoddin; Putra Pandu Adikara
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

The increase in population is directly proportional to the increase in demand for goods. The sales block is a concept of shipping goods by dividing the area based on the number of fleets, but the number of goods in the Motorcycle fleet is depleted, so the goods must be taken to the Car fleet, this problem is called the Feeder Vehicle Routing Problem. Researchers will optimize the Feeder Vehicle Routing Problem (FVRP) on the distribution of freight shipments using Multiple Traveling Salesman Problems (MTSP) and Genetic Algorithms. In the Genetic Algorithm chromosome representation based on the MTSP concept, a cluster division is made to map the shipping routes, including the destination Shop, the condition of reloading or not reloading, the selection of the Car to reload, the Position of the Car, and the time interval for changing the reloading items. Crossover Reproduction Stage uses Partial Mapped Crossover and Extended Intermediate Crossover, while the reproduction of mutations using the method. Calculate distance values ​​using the Haverseine Formula, then calculate fitness values ​​and save with Elitism. The test results get the greatest fitness value 1.35926 assessment of population size 50, Cr value of 0.5 and Mr 0.6 in generation 100, besides fitness convergence is available at around values ​​1.25 to 1.3. Producing with a size of 50, or more than 50, and producing 100, and a value of Cr 0.5 and Mr 0.5, resulting in a fitness value of 1.266594973.
Analisis Sentimen Terhadap Rating dan Ulasan Film dengan menggunakan Metode Klasifikasi Naive Bayes dengan Fitur Lexicon-Based Nadhif Sanggara Fathullah; Yuita Arum Sari; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 2 (2020): Februari 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Film is a work of art which liked a lot by movie fans today. The types of films are very diverse and each type of film has its own fans. Every fan has their own assessment of the film they like. Rating becomes an assessment of a film with a certain scale. In addition, the review becomes a translation of fan ratings of the film. The assessment aspects contained in the review include the delivery of stories, shooting techniques, actors, visual effects, etc. In the review itself there are criticisms or comments that contain sentiment towards the film. Sentiment analysis can help film fans determine whether a film has positive or negative sentiments. In order to get the sentiment analysis result, the Naive Bayes Classification Method is used with Lexicon-Based features selection. In the classification process, the appearance of sentiment words are calculated as well as the rating features to determine the sentiment class. Based on the test results, the value of accuracy, precision, and recall has a result of 0.9, 0.9, and 0.9 respectively by selecting the feature in the form of deletion of stopword while the value of accuracy, precision, and recall has a result of 1, 1, and 1 respectively by selecting features in the form of Lexicon-Based.
Analisis Sentimen Mass Rapid Transit Jakarta dengan Naive Bayes Classifier dan Deteksi Target Opini Berbasis Aturan pada Twitter Dhanika Jeihan Aguinta; Putra Pandu Adikara; 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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Abstract

Untuk dipublikasikan di 5th International Conference on Sustainable Information Engineering and Technology (SIET)
Analisis Sentimen Mengenai Produk Toyota Avanza Menggunakan Metode Learning Vector Quantization Versi 3 (LVQ 3) dengan Seleksi Fitur Chi Square, Lexicon-Based Features serta Normalisasi Min-Max Jonathan Reynaldo; Putra Pandu Adikara; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 3 (2020): Maret 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Car is a means of transportation used by peoples with some excellence and comfort values for better driving experience. Toyota as the manufacturer of Toyota Avanza needs people's opinions to upgrade their products. Opinions from social media need to be classified as positive, neutral or negative opinions so sentiment analysis is needed. For analyzing a sentiment, Learning Vector Quantization 3 (LVQ 3) is used in this research. Chi Square feature selection, lexicon-based features and min-max normalization are used in this research too. Evaluation using confusion matrix with 240 training data and 60 testing data results the accuracy of 38,33% using features from Chi Square feature selection, 33,33% using lexicon-based features, and 36,67% using both of Chi Square feature selection and lexicon-based features.
Peringkasan Artikel Berbahasa Indonesia Menggunakan TextRank dengan Pembobotan BM25 Yurdha Fadhila Hernawan; Putra Pandu Adikara; 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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Abstract

Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Deteksi Perundungan Siber (Cyberbullying) pada Instagram Menggunakan Metode Naive Bayes Classifier dengan Lexicon Based Features Salsabila Insani; Putra Pandu Adikara; Sigit Adinugroho
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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Abstract

Untuk dipublikasikan di 5th International Conference on Sustainable Information Engineering and Technology (SIET)
Analisis Sentimen Layanan Astra Honda Motor Menggunakan Metode Naive Bayes dan Identifikasi Aspek pada Layanan Menggunakan DBSCAN Naufal Akbar Eginda; Putra Pandu Adikara; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 3 (2020): Maret 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In today's era, transportation is one of the most vital needs. according to BPS Indonesia (badan pusat statistik) in 2017, motorbikes are the most owned form of transportation in Indonesia. one of the most commonly used motorbike brand is honda. astra honda motor provides a range of services available to its customers. of all their services, honda's customers would surely have a number of opinions or feedbacks regarding their services, whether they are positive or negative. in order to classify and identify aspects of the public opinion, naive bayes with lexicon-based features are implemented to classify them and dbscan is implemented to cluster them by taking the top 3 terms generated from each document. the dataset used in this paper consists of 100 datas divided into an equal set of each class, and 25 datas for testing in which 13 are classified positive and 12 are negative. the result of the classification process applying naive bayes with lexicon-based features is a precision value of 53%, recall of 63%, f-measure of 58% and 60% of accuracy. While, the result of the aspect identification came down to 41,4% for precision, 80,5% for recall, 54,6% for f-measure and a mere 37,6% for its accuracy level. as for the cluster evaluation with silhouette coefficient, the best parameter values using dbscan is an epsilon of 0.1 along with minpts of 1.
Co-Authors Adani, Rafi Malik Ade Kurniawan Adinda Chilliya Basuki Adinugroho, Sigit Adiyasa, Bhisma Adriansyah, Rachmat 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