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Optimasi Travelling Salesman Problem Pada Angkutan Sekolah Dengan Algoritme Particle Swarm Optimization M. Khusnul Azhari; Imam Cholissodin; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Currently, The implementation of school transport has been done a lot of school, private and even the government. One of them is MI Salafiyah Kasim school. Although the school transport system has been implemented for years, there are obstacles such as students who are delivered not always the same every day, the driver delays in delivering to the destination, the school driver who always prioritizes personal experience and fund of transportation operations that are still unstable . To overcome these problems, the authors use the Particle Swarm Optimization Algorithm in the optimization to get the order of delivery of students with the shortest route that can be passed by the school driver. The results of this study compared actual sample data one day delivery with the system that has been designed. Of the five experiments applied to each kloter, three of them are able to produce a better route recommendation than the usual driver. Once reviewed overall, the system is considered to work well and produce a fairly optimal solution.
Implementasi Algoritme Improved Particle Swarm Optimization Untuk Optimasi Komposisi Bahan Makanan Untuk Memenuhi Kebutuhan Gizi Penderita Penyakit Diabetes Melitus Gregorius Dhanasatya Pudyakinarya; Imam Cholissodin; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diabetes Mellitus is one of the diseases with the highest number of casualties in Indonesia. The high diabetics in Indonesia are due to the lack of public knowledge about healthy food controls that result in poor diet. As a result, many people have not met the balance of nutritional intake that is the most important part in managing a good and healthy diet. Information on the right diet is needed for diabetics to improve their health condition. The Particle Swarm Optimization (PSO) algorithm is often used in performing optimization cases with good and optimal results, in particular, there is development to Improved Particle Swarm Optimization (IPSO) which further improves PSO performance. Therefore, this study designs an optimization system for the composition of food ingredients for the nutritional needs of people with Diabetes Mellitus using Improved-PSO algorithm. The results obtained from this study are optimized Improved-PSO parameters that are population number = 150, acceleration coefficient value = 2, 1, and convergent system on iteration to 550. In addition, from the results of global analysis shows that the nutrient calculation of the system can meet the nutritional needs of patients with a difference of tolerance ± 10% of expert calculations.
Implementasi Data Mining untuk Prediksi Mahasiswa Pengambil Mata Kuliah dengan Algoritme Naive Bayes Indra Kurniawan Syahputra; Fitra Abdurrachman Bachtiar; Satrio Agung Wicaksono
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Faculty of Computer Science of Brawijaya University's academic division has tasks for scheduling and determining courses every semester offered for students. However, the scheduling process has some problems such as, many of classes are offered while the students who are interests in that course are very low or vice verca. Therefore, a system is needed that can predict students will take a course or not. One of the solutions is using data mining classification. Based on student's attributes values, grade points, grade point average, semester credit units, cumulative semester credit units, and the semester is used to classify whether the student will take certain courses. Result of the classification divided into two classes that are ‘Yes' for student who take the class and No class for student who put off the class. Classification process is performed using Naive Bayes Classification (NBC) algorithm. The process used data from the odd semester in 2014 to even semester in 2015 for training and from odd semester in 2016 for testing. Prediction result using two courses as sample, the result of accuracy score for Customer Relationship Management course is 85,88%, while for Wireless Network course is 44,92%. The output of this research is a web-based dashboard that displays a comparison of actual dan predict values of each course in certain year and semester.
Prediksi Produktivitas Padi Menggunakan Jaringan Syaraf Tiruan Backpropagation Gandhi Ramadhona; Budi Darma Setiawan; Fitra A. Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Rice is very important for human beings, especially to the ASEAN community. Indonesia is one of the ASEAN countries that cultivate rice. In 2015, Indonesia ranked as the third-highest in terms of the world's largest rice producer. However, Indonesia still have to import rice every year due to its high demand and to fulfil Indonesian's per-capita consumption. The other reason is the different amount of harvest on each areas resulting in a scarcity of rice because the country can not be able to optimize the farming techniques that are used. This research use the methods of backpropagation neural network to predict the results of the rice productivity. In its implementation, the data is normalized using the min - max normalization and weighting initialization using Nguyen - Widrow. Based on the results of testing the parameters for the method of backpropagation, shows the most minimum RMSE i.e. 8.6918 with parameter values learning rate = 0.8, hidden layer neurons, hidden = 3 = 4 with the number of epoch 10000 against 135 training and 13 test data. Based on result of 5 fold cross validation against the stability testing data gets an average RMSE of 8.2126.
Perbandingan Holt's dan Winter's Exponential Smoothing untuk Peramalan Indeks Harga Konsumen Kelompok Transportasi, Komunikasi dan Jasa Keuangan Achmad Fahlevi; Fitra Abdurrachman Bachtiar; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Consumer Price Index (CPI) is one of the most commonly used indicators in measuring the inflation rate. CPI's group of Transportation, Communication and Financial Services have the second largest proportion on living cost with 19.15%. As the group who categorize as administered price (the price are ruled by the government), forcasting this group would help some parties involved in taking neccessery decision and avoiding significant inflation rate. In this research, forecasting were performed using two Exponential Smoothing method which is, Holt's Exponential Smoothing and Winters Exponential Smoothing. This method was evaluated by calculating average error rate using Mean Absolute Percentage Error (MAPE) method. There will be 120 data from January 2017 until December 2017 that used which taken from Bank Indonesia official websites. The results of the test was the best parameter value for Holt's Exponential Smoothing which is 𝛼 = 0.7 dan β = 0.1 and for Winters Exponential Smoothing 𝛼 = 0.1, β = 0.4 dan γ = 0.8. And from this parameter's value, MAPE's value obtained for Holt's Exponential Smoothing which 0.474% and for Winters Exponential Smoothing is 1.503%. Both of them got MAPE value under 10% that can be categorize as very good on forcasting CPI group of Transportation, Communication and Financial Services. And can be conclude either that Holt's Exponential Smoothing have better accuration rather than Winters Exponential Smoothing in Cosumer Price Index's group of Transportation, Communication and Financial Services.
Prediksi Kredit Macet Berdasarkan Preferensi Nasabah Menggunakan Metode Klasifikasi C4.5 pada Koperasi Simpan Pinjam Mitra Raya Wates Iqbal Taufiq Ahmad Nur; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bad credit is the main problem that faced by financial institutions, especially cooperatives in Indonesia. This problem is also happened in KSP Mitra Raya Wates that does not use credit analyst and the decision making process is using an intuitive approach and based on existing experience that owned by KSP Leader. The survey process conducted at KSP Mitra Raya Wates also cannot guarantee that the loans made by customers are free from credit risk, considering there are customers who have bad credit from a total of all customers who have received loans. KSP Mitra Raya Wates needs a system that capable of supporting decision to detect credit quality early on. C4.5 method can be used to predict customers' credit quality by generating rule in form of decision tree. The results of confusion matrix have accuracy of 94.5946. While based on the ROC curve, it generated AUC value of 0.9689. The level of usability generated by utilizing SUS is 82.5. The output is dashboard visualization with several graphs containing the percentage, time-series and trend of total submissions that have been made and also forms that can be used by KSP Mitra Raya Wates to make predictions of customer credit application and also dataset entry into the system.
Analisis Sentimen Opini Pelanggan Terhadap Aspek Pariwisata Pantai Malang Selatan Menggunakan TF-IDF dan Support Vector Machine Yoga Tika Pratama; Fitra Abdurrachman Bachtiar; Nanang Yudi Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Department of Tourism and Culture (Disparbud) of Malang Regency requires the customer's perspective in the process of monitoring and evaluation of management and development activities of South Malang beach tourism. But Disparbud neither have the data about the customer's opinion, nor the application of technology on data processing and data analysis that capable of providing information about customer's perspective on aspects of South Malang beach tourism. The customer's perspective can be obtained from customer's opinions in the form of review that available on the web platform. Web Scraping is a method for extraction of customer's opinion data sourced from the web platform. To get the information about customer's perspective on aspects of South Malang beach tourism could be done by performing Aspect Level Sentiment Analysis on the customer's opinion data. One of many classification methods is the Support Vector Machine, which can be used to classify sentiments in sentiment analysis process. This research managed to get 674 customer's opinion data in Bahasa Indonesia ranged from 2013 to 2018 for 43 tourist attractions of South Malang beach tourism sourced from TripAdvisor. The tests that have been conducted on the results of the sentiment classification for all aspects resulted good results in an average of 85% on accuracy, 85% on precision, 87% on recall, and 85% on F1-Score. The output of this research is in form of data visualization in the form of Dashboard consisted of 4 Dashboards which contains results from the process of sentiment analysis on the customer opinions to aspects of South Malang beach tourism.
Evaluasi dan Rekomendasi Tampilan Website E-Complaint Universitas Brawijaya Pada Perangkat Bergerak Menggunakan Metode Heuristic Evaluation Wahyu Satriyo Wibowo; Hanifah Muslimah Az-Zahra; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Usability issues of Brawijaya University's E-Complaint website, particularly any of those issues faced by mobile device users due to less responsive display, receive considerable attention because they affect user's perspective on the website. Thus, a usability evaluation was done by applying heuristic evaluation method to fix the issue faced by the users. These experts relied on provided 13 heuristic mobile checklists to conduct the evaluation. Usability assessment was also conducted on the user's side by utilizing System Usability Scale (SUS) and it was complemented with interview with 8 respondents who were categorized into 2 groups: Brawijaya's scholars and general public. The heuristic evaluation highlighted 66 issues in total which were then summarized into 27 issues including issues found during interview with the respondents. Those results were then used for revision. UB's E-Complaint website display improvement was based on the collected guidelines, expert solutions, and user feedback. This improvement lowered the number of issues found by the experts, from 66 into 29 issues with average severity rating of 1,80 (it was previously 2,84). User satisfaction was also improved from SUS score of 44.38 into 72.5 and was supported by positive responses received from the interviews. SUS score indicated that there were some improvements in adjective rating from “OK” to “Good”, in grade scale from “F” to “C”, and in acceptability from “not acceptable” into “acceptable”.
Peringkasan Multi-Dokumen Berbasis Clustering pada Sistem Temu Kembali Berita Online Menggunakan Metode K-Means Amalia Kusuma Akaresti; Mochammad Ali Fauzi; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The growing number of online news sites resulted in an explosion of information and information redundancy occurred. On this issue it takes the search engine to make it easier for users to find information, but users still have to read it one by one, therefore it needs also a summary system. Therefore a summary system is required to facilitate Internet users avoid getting the same information from different sources. In this study, multi-document clustering based on online news retrieval system using K-Means method. The process of searching system using Cosine Similarity method and on the summary using K-Means Clustering method. The results show that the optimum results in the recall system are Recall 71%, Presicion 65.82%, F-Measure 66.35% and on Recall system of Recall 37.3%, Presicion 18%, F-Measure 19.2%.
Evaluasi Kualitas Website Terhadap Kepuasan Masyarakat Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis (IPA) (Studi Kasus pada Website disperkim.malangkota.go.id Dinas Perumahan dan Kawasan Permukiman Kota Malang) Ikrom Septian Hadi; Satrio Hadi Wijoyo; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The purpose of this study to obtain results of the evaluation of website use WebQual disprekim.malangkota.go.id 4.0 and get advice on website disperkim.malangkota.go.id using the guidelines and methods of science. The method used in the evaluation of the Department of Housing and Settlement website Malang was that WebQual 4.0 to 3 dimensions as well as methods lmportance and Performance Analysis (LPA), which consists of a conformance level analysis, gap analysis, and analysis of LPA quadrant. The results of the analysis of the quality of Website Department of Housing and Settlement Region Malang shows that the website has a concordance rate of <100% is equal to 94.53%, means that the Website performance level Department of Housing and Settlement Region Malang is still below the level of interest or not in accordance with user expectations. Average Average value gap (GAP) on the Website of Housing and Settlement Region Malang were negative (<0) is equal to -0.24, the results showed that the level of performance Website Department of Housing and Settlement Region Malang is still lacking and has not met expectations users
Co-Authors AA Sudharmawan, AA Abidatul Izzah Abu Wildan Mucholladin Achmad Arwan Achmad Basuki Achmad Fahlevi Achmad Firmansyah Sulaeman Achmad Hanim Nur Wahid Achmad Ridok Adam Hendra Brata Adam Syarif Hidayatullah Adam Syarif Hidayatullah Adinugroho, Sigit Aditya Rachmadi Aditya Rachmadi, Aditya Admaja Dwi Herlambang, Admaja Dwi Admi Rut Sinana Afida, Latansa Nurry Izza Afifurrijal Afifurrijal Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Fairuzabadi Ahmad Foresta Azhar Zen Aisyah Awalina Aisyah Awalina Aisyatul Maulidah Aisyatul Maulidah Akhmad Lazuardi Alaikal Fajri Nur Alfian Aldi Fianda Putra Alfi Nur Rusydi Alfin Taufiqurrahman Alfirsa Damasyifa Fauzulhaq Alhasyimi, Dana Mustofa Alifi Lazuardi Gunawan Amalia Kusuma Akaresti Andi Alifsyah Dyasham Anggit Chalilur Rahman Anita Rizky Agustina Anita Rizky Agustina Anjasari, Ni Luh Made Beathris Anjumi Kholifatu Rahmatika Annuranda, Ramansyah Eka Apriyanti -, Apriyanti Ardi Wicaksono ari kusyanti Arieftia Wicaksono Aulia Akhrian Syahidi Aulia Dewi Savitri Aulia Nurrahma Rosanti Paidja Aulia Septi Pertiwi Azhar Izzannada Elbachtiar Azzam Syawqi Aziz Baharudin Yusuf Widiyanto Barlian Henryranu Prasetio Bayu Aji Firmansyah Bayu Sutawijaya Benni A. Nugroho Bere, Stevania Biabdillah, Fajerin Bianca Pingkan Nevista Bintang Fajrianti Brahma Hanif Farhansyah Budi Darma Setiawan Budi Setiawan Cahya, Reiza Adi Cinthia Vairra Hudiyanti Dariswan Janweri Perangin-Angin Dary Ardiansyah Haryono Dea Zakia Nathania Dedi Romario Delpiero, Rangga Raditya Desy Setya Rositasari Dika Imantika Dimas Angga Nazaruddin Dinda Adimanggala Dito William Hamonangan Gultom Diva Fardiana Risa Diva Fardiana Risa Djoko Pramono Dona Adittia Dyah Ayu Wulandari Dyah Ayu Wulandari Dzar Romaita Eka Devi Prasetiya Eka Yuni Darmayanti Eko Laksono Eko Setiawan Elok Nuraida Kusuma Dewi Fabiansyah Cahyo Kuncoro Pradipta Faizatul Amalia Fajar Pradana Fajar Pradana Fajerin Biabdillah Faranisa, Puspa Ayu Fardan Ainul Yaqiin Farhan Setya Dhitama Farid Syauqi Nirwan Fasya Ghassani Hadiyan Fatwa Ramdani, Fatwa Ferdian Maulana Akbar Ferry Ardianto Rismawan Ficry Agam Fathurrachman Fikar Mukamal Gandhi Ramadhona Giga Setiawan Gregorius Dhanasatya Pudyakinarya Gultom, Dito William Hamonangan Gunawan, Alifi Habib Bahari Khoirullah Haikal, Raihan Hanif Prasetyo Maulidina Hanifah Khoirunnisak Hanifah Muslimah Az-Zahra Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haryowinoto Rizqul Aktsar Hasyir Daffa Ibrahim Hayashi, Yusuke Herman Tolle Heryana, Ana Hirashima, Tsukasa Holiyanda Husada Hutamaputra, William Ihza Razan Alghifari Ikhsan Putra Arisandi Ikrom Septian Hadi Ilham Pambudi Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra K. Syahputra Indra Kurniawan Syahputra Indriati Indriati Indriati Indriati Intan Yusuf Habibie Iqbal Taufiq Ahmad Nur Irfani, Ilham Irma Nurvianti Irwan Suprianto Issa Arwani Ivqonnada Al Mufarrih Joseph Ananda Sugihdharma Joseph Ananda Sugihdharma Julia Ferlin Kartiko, Erik Yohan Katrina Puspita Kevin Gusti Farras Fari&#039; Utomo Kharis Alfian Kharis Alfian Kresna Hafizh Muhaimin Krisnabayu, Rifky Yunus Krisnandi, Dikdik Kuncahyo Setyo Nugroho Kurnia Fakhrul Izza Kusumo, R. Budiarianto Suryo Lailil Muflikhah Ludgerus Darell Perwara Luthfi Afrizal Ardhani M Reza Syahputra A M. Ali Fauzi M. Khusnul Azhari M. Raabith Rifqi M. Sofyan Irwanto Mar'i, Farhanna Marvel Timothy Raphael Manullang Mawarni, Marrisaeka Michael Stephen Lui Moch Irfan Prayudha Adhianto Mochamad Chandra Saputra Mochamad Havid Albar Purnomo Mochammad Dearifaldi Al Ikhsan Mochammad Dearifaldi Al Ikhsan Moh Iqbal Yusron Mufidatun Nuha Muh. Edo Aprillia Andilala Muhammad Ferdyandi Muhammad Ifa Amrillah Muhammad Tanzil Furqon Muhammad Taufik Dharmawan Muhammad Wafi Muhammad Wafi Muhammad Zulfikarrahman Nabila Leksana Putri Nabila Lubna Irbakanisa Nadifa, Rahajeng Mufti Nainggolan, Cesilia Natasya Nanang Yudi Setiawan Nanang Yudi Setiawan Nanang Yudi Setyawan Nanda Ajeng Kartini Nanda Samsu Dhuha Nasita Ratih Damayanti Naufal Fathirachman Mahing Nourman Hajar Novanto Yudistira Novi Sunu Sri Giriwati Novianti, Siska Nur Wahyu Melliano Hariyanto Nurafifah Alya Farahisya Nurul Hidayat Oddy Aulia Rahman Nugroho Okta Dwi Ariska Ovy Rochmawanti Pamungkas, Gilang Alif Pradana , Fajar Priyambadha, Bayu Pryono, Muhammad Adam Puras Handharmahua Putra Pandu Adikara Rafif Taqiuddin Rafif Taqiuddin Rafly, Andi Raga Saputra Heri Istanto Rahman, Rafli Rahmat Adi Setiawan Ramadhan, Muhammad Fitrah Randy Cahya Wihandika Randy Cahya Wihandika Ratih Kartika Dewi Refi Fadholi Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renavitasari, Ivenulut Rizki Diaz Retno Indah Rokhmawati Retno Indah Rokhmawati, Retno Indah Revanza, Muhammad Nugraha Delta Reza Syahputra Rezka Aditya Nugraha Hasan Rezky Dermawan Rhobith, Muhammad Rian Nugroho Ridwan Adi Setiabudi Riski Darmawan Riza Setiawan Soetedjo Rizal Setya Perdana Rizkey Wijayanto Rizkia Desi Yudiari Rizky Adinda Azizah Rizky Muhammad Faris Prakoso Robi Dwi Setiawan Rona Salsabila Said Atharillah Alifka Alhabsyi Samuel Arthur Satrio A. Wicaksono Satrio Agung Wicaksono Satrio Agung Wicaksono Satrio Hadi Wijoyo Satrio Hadi Wijoyo Satyawan Agung Nugroho Satyawan Agung Nugroho Shinta Aprilisia Sifaunnufus Ms, Fi Imanur Sintiya, Karena Siswahyudi, Puad Siti Mutdilah Sofyanda, Erika Yussi Sri Wulan Utami Vitandy Sueddi Sihotang Sugihdharma, Joseph Ananda Sulandri Sulandri Sza Sza Amulya Larasati Taufik Hidayat Timothy Julian Titus Christian Ubaydillah, Achmad Afif Utaminingrum, Fitri Vasha Farisi Sarwan Halim Very Sugiarto, Very Vivy Junita Wahyu Ardiansyah, Mohammad Wahyu Satriyo Wibowo Wahyudi, Hafif Bustani Wayan F. Mahmudy Wayan Firdaus Mahmudy Welly Purnomo Whita Parasati Wicky Prabowo Juliastoro Windy Adira Istiqhfarani Wiratama Ahsani Taqwim Wirdhayanti Paulina Yoga Tika Pratama Yudi Muliawan Yuita Arum Sari Zainal Arifien Zayn, Afta Ramadhan