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All Journal Journal of Environmental Engineering and Sustainable Technology Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Keperawatan Padjadjaran Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Ahmad Afif Supianto
Fakultas Ilmu Komputer - Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Mechanical Engineering Neuroscience Nursing Public Health

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Prediksi Kelulusan Mahasiswa Berdasarkan Kinerja Akademik Menggunakan Pendekatan Data Mining Pada Program Studi Sistem Informasi Fakultas Ilmu Komputer Universitas Brawijaya Ryan Dwi Pambudi; Ahmad Afif Supianto; Nanang Yudi Setiawan
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

Late graduation is a problem that often encountered in university's academic environment. This is also experienced in University of Brawijaya Information System study program which average students accepted in the Information Systems study program is 213 students, whereas the average students that graduate is only less than 99 students. This imbalancy will be certainly causing disadvantage to the academicians and students. So based on this problem t is necessary to predict the students who are indicated not to graduate on time so that further action can be given. One of the tasks that can be used to predict graduation in data mining can use the type of task classification. By utilizing one of the classification algorithm methods namely Naive Bayes, probability patterns will be generated on each attribute that can be used to determine whether students graduate on time or not. From data of students that collected totaling 1354 data, the data is then carried out pre-processing for the mining process on a system developed on a web-based using Weka CLI. Information from graduation predictions is displayed on the dashboard according to the needs of the Head of the SI Department. Test Results Black-box shows a valid system according to defined needs. While the results of usability testing with the System Usability Scale(SUS) produce a value of 57.5 which is classified as an Adjective rating Good.
Optimasi Peramalan Metode Backpropagation Menggunakan Algoritme Genetika pada Jumlah Penumpang Kereta Api di Indonesia Mohammad Birky Auliya Akbar; Indriati Indriati; Ahmad Afif Supianto
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 train is a kind of massive land transport with a lot of users, base on the results presented by Statistics for Safety Index and service reached 4.09 from 5 in year 2014, also supported by the fact that exposed by the daily Tempo (www.bisnis.tempo.co) indicating that the train users from time to time inCreased. However, with the inCrease in the number of passengers on top of the train without any prediction will be bad for the train in Indonesia. For this need a method of predicting the results that can be answerable, using popular methods such as artificial neural network Backpropagation and optimizations to do in determining the initial weights (W) with Using numbered variables 800 for the population, 20 for a number of generations, the composition of the value of Mr = 0.3 and Cr = 0.7, with the main variant of the Backpropagation artificial neural network that consists of multiple iterations is 100 and a value of Alpha is 0.9, also with dataset on a monthly basis, start from January 2006 to June 2017 in timeseries form data, with 100 training data pattern as initial data and 10 pattern of test data of last data. So the result is the level of precision based on error value (MSE) results 0.065869861 from the results of the hybridization method backpropagation artificially neural networks using a genetic algorithm, while without using the hybridization error value is 0.072517977.
Prediksi Kelulusan Mahasiswa Berdasarkan Kinerja Akademik Menggunakan Metode Modified K-Nearest Neighbor (MK-NN) Imaning Dyah Larasati; Ahmad Afif Supianto; Muhammad Tanzil Furqon
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 the Brawijaya University FILKOM Informatics Engineering study program, the academic performance of students in terms of study period is still a problem. In FILKOM's academic database, there are student academic data. The data can be carried out data mining by predicting students' graduation in the 5th semester. K-NN is a good method for predicting graduation. However, there is a method that has better accuracy than K-NN has been found in other cases, that is MK-NN. Therefore, this study using M-NN method for predict students' graduation based on academic performance by testing includes testing the effect of k value, the number of training data and the composition of training data. Furthermore, comparing the accuracy produced by MK-NN and K-NN methods. The highest accuracy of testing the effect of the value of k is when k = 5, which is equal to 82%. The highest accuracy from testing the effect of number of training data and the composition of training data reached 85,25% and 84%. From the comparison of the accuracy of MK-NN and K-NN it was concluded that MK-NN produced better accuracy than K-NN.
Prediksi Kinerja Akademik Mahasiswa Pada Mata Kuliah Pemrograman Dasar dengan Algoritme Backpropagation Aldous Elpizochari; Ahmad Afif Supianto; Bayu Rahayudi
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

Basic programming course is one of the courses taken by new students and usually some of those students have difficulties understanding the basic concepts of programming. This study aims to identify students who are struggling on the course at the earliest possible time by using factors that can be collected before any test or evaluation is taken so that the lecturer can provide additional assistance for students who encounter such difficulties. The classification method proposed in this study is Neural Network Backpropagation. Tests will be done to find out whether the proposed method can solve the problem of this study and to find out the best value for parameters such as the number of hidden neurons and hidden layer and learning rate for this study. Some test scenarios are also used in this study such as using all of the data features, using PCA with 85%, 90%, 95% variance, and using only significant features based on Pearson correlation. The test results of this study revealed that the proposed method can be used to solve the problem in this study, with the highest average accuracy of 0.74 in two scenarios, the PCA with 95% variance and using only significant features scenario. Test results also show that the parameters which produce the best result is 7 hidden neurons in one hidden layer and learning rate value of 0.7.
Implementasi Algoritme Association Rule Untuk Pencarian Perilaku Pengguna Internet Dalam Mengakses Sebuah Website Menggunakan Metode Modified-Apriori Adhitya Pratama Wijayakusuma; Nurul Hidayat; Ahmad Afif Supianto
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 search pattern is one of the ways that you can use to specify the search in the form of recommendations suggest that appears on the internet user's browser, by looking at how often the Web sites visited by the users simultaneously other Internet. Research on the hidden patterns that are found in the database into a field that is in great demand these days. In the hidden pattern, there is some useful information. Large-scale data will have difficulty when analyzed with simple data analysis so that it takes a special technique to be able to analyze large scale data, i.e. data mining. The results of the analysis will result in a sistem that would later figure out patterns of internet users accessing a website from the results of analysis of the association between websites that are frequently opened simultaneously, after knowing the pattern It then can be used as a recommendation sistem search. So, in this study using a sales transaction data to determine patterns of sales by using Association Rule algorithm and Modified-a priori from data mining. Association Rule is a method for finding interesting relationships hidden in data by using the calculation of the value of the support and confidence. Algortime Modified-a priori is the development of the a priori algorithms searching frequent itemset with joining processes (join) and pruning (prune) and produce a faster time efficiency using hash compared with the a priori algorithms. The technique used is the hash with the hash map. The data used in this research is the internet user search data retrieved from history browser internet users as much as 20 users with the number of transactions by as much as 300 transactions. The results of this research have the minimum value of the highest support i.e. 34.11% and generates the rule amounted to 2. Minimum confidence highest i.e. 80.00% and generates the rule amounted to 3. The length of the itemset that is formed are 2-and 3-itemset. Obtained as a rule that has a lift ratio of more than 1.
Pengembangan Sistem Informasi Manajemen Akademik Sekolah Menengah Atas (Studi Kasus pada SMA Sejahtera 1 Depok) Ammar Burhanuddin Sayuti; Ahmad Afif Supianto; Welly Purnomo
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

Sejahtera 1 Depok Senior High School is one of the educational institutions in Depok city under the auspices of the family sejahtera bandung foundation. Main tasks Sejahtera 1 Senior High School is practice the learning process, evaluate of study result students, and graduate qualified students with the required standards. However, there are several things such as the process of registration new students is still manually, and the process of evaluate students, the distribution of ratings for student report is very complex. Therefore the need for information systems that can help deal with the problem. Development of school academic management information systems using waterfall model. Which is conducted phase is requirement analysis, design, implementation, and testing. After the result of the User Acceptance Test given to the BPTIK teacher as a admin (the percentage of UAT by 90%), the teacher as student assessor (the percentage of UAT by 90%), and prospective student as registrant (the percentage of UAT by 85%).
Aplikasi Data Mining Untuk Memprediksi Kelulusan Mahasiswa Menggunakan Algoritme C4.5 Febrian Pandu Widhianto; Ahmad Afif Supianto; Nanang Yudi Setiawan
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

Brawijaya University Faculty of Computer Science had many students. The Information system study program from the generation 2011 to 2018 has 1817 college students, but the number of students who graduate and enter is disproportionate, so that students who do not graduate on time can reduce accreditation from major, faculty or university. Based on that, the amount of data available can be used as an algorithm in data mining to predict students graduates. The C4.5 algorithms are one of the algorithms that can be used in predicting students graduation by producing a rule in the form of a decision tree. The data used in this study is student academic data from semester 1 - 4. Using the algorithm C4.5 generated accuracy by 90.9%, while ROC's curve of AUC values is 0.8232. the usability value produced from SUS is 67.5. The output generated by a dashboard display with some graphic that contains the graduation percentage, the graduation recapitulation of each generation and the value details of students, is also a form for data input that can be used by the head of program information system study program to predict by uploading collective data or linear data.
Aplikasi Data Mining Untuk Klasifikasi Kesiapan Skripsi Menggunakan Algoritma Apriori Mohammad Malik Abdul Azis; Ahmad Afif Supianto; Nanang Yudi Setiawan
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

Thesis is a mandatory thing that must be done by a student to get a bachelor's degree. Based on the PSIK data from the Faculty of Computer Science, Brawijaya University, from 192 data, 96 students completed the thesis according to the specified time 95 other students did not complete the thesis according to the specified time span of 6 months. So based on these problems a system is needed that can explore knowledge - new knowledge and can help make decisions using data mining. In this study using one of the data mining tasks namely Association Rule Mining using the Apriori algorithm produces rule patterns that can be used as parameters for the prediction of thesis readiness. The collected data supports 540 academic program data records of 2013 - 2014 Information System study students and 192 FILKOM APPS data records that contain progress data for student thesis in 2018, then pre-processing to use the usage pattern using Apriori with WEKA tools. The results of testing the system using a black box show valid results so that it can be concluded that the system is made according to requirements. Then to test usability obtained a value of 67.5 which belongs to the predicate D for Scale Scale and Marginal Height for the Acceptance Range.
Analisis Sentimen Opini Mahasiswa Terhadap Saran Evaluasi Kinerja Dosen Menggunakan TF-IDF dan Support Vector Machine. Achmad Firmansyah Sulaeman; Ahmad Afif Supianto; Fitra Abdurrachman Bachtiar
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

Lecturers especially in institution should always need to improve their knowledge and effective and efficient teaching methods that can be well received by students. Evaluation on the quality of teaching and academic standardization needs to be done so that the objectives of the teaching goal can be achieved. Brawijaya University especially Computer Science Faculty implements of filling the online questionnaire due to evaluating lecturers' performance at each semesters. The opinion data that held by the UJM Team of Information Systems Department is still no processed by using data analysis classification technology that is able to provide information about student perspectives. Sentiment analysis using Support Vector Machine in combining with Term Frequency Inverse Document Frequency as word weighting can be used as a method in classification of student opinion data. This research managed to used student opinion data in bahasa for 3 last semesters in 2017 and 2018. The test that have been conducted on the results of classification show the average of 82% on Accuracy. Data visualization become an output of this research based on the classification result with displaying 3 different pages of sentiment analysis lecturers performance evaluation on each semester. The average result of usability test show result in 70, which means receives a good visualization dashboard at it self.
Pengembangan Sistem Informasi Praktik Kerja Industri (Prakerin) Menggunakan V-Model Studi Kasus: SMKN 2 Malang Mochamad Bachtiyar Eko Cahyo Putro; Ahmad Afif Supianto; Djoko Pramono
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

Malang State Vocational High School 2 every year carries out industrial work practices (internship). In the internship activities, the school has difficulty, because the industrial work practice data management process was managed manually. This resulted in several difficulties, one of which was in the registration of apprenticeship, the head of the department had difficulty recording data for all students who enroll in apprenticeship, because the head of the department needed to visit classes according to his department to provide a list of Business / Industrial World that can be chosen by students., then the head of the department needs to record the data of the students and where students want to carry out internship. Based on these problems, a web-based Prakerin Information System was built. In the system development process, the SDLC method will be used is V-model. The results of the requirements analysis are strongly approved by the user, evidenced by the results of User Acceptance Testing (UAT), with a system that can run in accordance with the expected system functionality as evidenced by system testing. The system is implemented using the PHP programming language and MySQL database management system. Implementation of the system is in accordance with the results of the design made, because the results of unit testing are all sample functions in accordance with the flow of design sequence diagrams and the system has a well structured and written code, high testability, and less cost and effort, then integration testing produces a valid percentage of 100% which means the system has been well integrated.
Co-Authors Abdul Harris Wicaksono Achmad Firmansyah Sulaeman Adhitya Pratama Wijayakusuma Adinugroho, Sigit Admaja Dwi Herlambang Afrizal Aminulloh Ahmad Fairuzabadi Aldous Elpizochari Ammar Burhanuddin Sayuti Anam, Syaiful Andi Reza` Perdanakusuma Anggie Tamara Blanzesky Annisa Salamah Rahmadhani Arief Andy Soebroto Bayu Rahayudi Beta Deniarrahman Hakim Bilal Benefit Candra Dewi Carlista Naba Chandra Ayu Anindya Putri Dewa Ayu Anggi Gharbelasari Dian Eka Ratnawati Dito William Hamonangan Gultom Dityo Kukuh Utomo Diva Devina Djoko Pramono Entra Betlin Ladauw Fadhyl Farhan Alghifari Fawwaz Roja Mahardika Febrian Pandu Widhianto Feri Setyo Efendi Fitra Abdurrachman Bachtiar Fitra Abdurracman Bachtiar Galih Wisnu Murti Gede Jaya Widhi Aryadi Hafizh Yuwan Fauzan Haryo Setowibowo Herman Tolle Hilmi Rezkian Aziz Dama Ignatius Chandra Christian Imaning Dyah Larasati Indra Ekaristio P Indriati Indriati Iqbal Setya Nurfimansyah Izza Isma Komang Candra Brata Lestari, Retno Linda Pratiwi Lutfi Fanani Lutfi Putra Gusrinda Mardiani Putri Agustini Maulana Aditya Rahman Mira Wahyu Kusumawati Mochamad Bachtiyar Eko Cahyo Putro Mochammad Izzuddin Mohammad Birky Auliya Akbar Mohammad Malik Abdul Azis Muhammad Aminul Akbar Muhammad Hasan Johan Alfarizi Muhammad Tanzil Furqon Nabila Divanadia Luckyana Nanang Yudi Setiawan Nanda Samsu Dhuha Ni Wayan Surya Wardhani Niken Asih Laras Ati Niken Hendrakusma Wardani Novira Azpiranda Nur Aenun Marjan Nur Laita Rizki Amalia Nur Sa'diyah Nur Shafiya Nabilah Salam Nurul Hidayat Onky Prasetyo Phat Prapawichar Puras Handharmahua Rafid Agung Pradana Retno Indah Rokhmawati Ridhoyanti Hidayah Ridwan Sofian Rifaldi Raya Rifky Yunus Krisnabayu Riska Agustia Risqi Auliatin Nisyah Rizka Awaliyah Nurul Putri Rosa Nur Madinah Rudi Gunawan Ryan Dwi Pambudi Santi Yunika Sufiana Satrio Agung Wicaksono Satrio Hadi Wijoyo Sri Wulan Utami Vitandy Tibyani Tibyani Tri Berlian Novi Ulfatun Nadifa Vito Ramadhan Welly Purnomo Widhy Hayuhardhika Nugraha Putra Willy Aditya Nugraha Windarwati, Heni Dwi Yusi Tyroni Mursityo Yustinus Radityo Pradana