Article Per Year (5 Year)
p-Index From 2021 - 2026
3.178
P-Index
This Author published in this journals
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

Published : 66 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 66 Documents
Search

 1   2   3   4   5 
PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT UNGGUL SAPI BALI MENGGUNAKAN METODE K-NEAREST NEIGHBOR Indra Ekaristio P; Arief Andy Soebroto; Ahmad Afif Supianto
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 1 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.329 KB) | DOI: 10.21776/ub.jeest.2015.002.01.7

Abstract

Bali cattle is an Indonesian native cattle that have a characteristic of the color of his skin. Bali cattle skin color can indicate the quality of the Bali cattle. The classification of the quality of Bali cattle directly is difficult because the human eye has a limited ability to see colors. A decision support system that is able to classify the quality of Bali cattle is based on a digital image of the skin color can help to overcome these limitations. The system will classify Bali cattle into three classes, namely Good (Seeds Superior), Average and Poor. System applying the K-Nearest Neighbor algorithm for the classification process is based on the average features and standard deviation of the red, green, and blue (RGB). This research tested a method to obtain the best value of K, the best image size, and the amount of training data best that will be used. Male Bali cattle using a value of K = 3, image size = 128×128 pixel, and the amount of training data = 45. While the female Bali cattle using a value of K = 6, image size = 64×64 pixel, and the amount of training data = 30. The results of testing the accuracy of the system for male Bali cattle is 100%, while the results of testing the accuracy of the system for female Bali cattle is 66.67%.
An Overview Of Learning Support Factors On Mathematic Games Ahmad Fairuzabadi; Ahmad Afif Supianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 2, May 2019
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.305 KB) | DOI: 10.22219/kinetik.v4i2.761

Abstract

 In this study, we examined the factors in game design that were used by developers to support the interests of mathematics learning. The aim is to overcome the lack of empirical evidence about the impact of factors in the game on learning outcomes, identify how the design of in-game activities affects learning, and develop an overview of general recommendations for designing mathematics education games. This study tries to illustrate the impact of game design factors in mathematics education games on the objectives and results of game-based learning.
Review of Technique and Algorithm for Educational Data Mining: Trend and Challenge in Games Design Ulfatun Nadifa; Fitra Abdurracman Bachtiar; Ahmad Afif Supianto; Herman Tolle
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 1, February 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i1.1349

Abstract

This study reviews techniques and algorithm models often used in the analysis of educational data mining. The review in this study is based on previous studies to provide researchers knowledge about trends and challenges analysis Educational data mining in game design meaningful. However, there is a lot of games design developed without analysis Educational data mining which then will not answer the student problem. The analysis needed periodic data and developing the game required actual student conditions, this is a combination inseparable. Determine Research questions, Search Terms, and filtering for the selection and analysis of the article review. There are some student problems on analysis review, namely prediction student performance, student behavior, student at-riks, and student dropout. The number of Articles in the study was 33 with 21 Articles of research and 12 of Article review. The number of studies 8 with percent 38% used techniques Confusion matric with 33% percent used algorithms Decision Tree in 7 of studies. The section in this study consists of techniques evaluation, model selection, outcome, subject, and algorithm method. Which are recommended techniques and algorithms for analysis Educational data mining and in ideal game design to further research.
Determinant of Effective Family Communication among First-Grade High School Adolescents Aged 15 - 16 Years: A Multi-Centre Cross-sectional Study Heni Dwi Windarwati; Retno Lestari; Ridhoyanti Hidayah; Ahmad Afif Supianto; Satrio Agung Wicaksono; Niken Asih Laras Ati; Mira Wahyu Kusumawati; Dewa Ayu Anggi Gharbelasari; Ridwan Sofian; Phat Prapawichar
Jurnal Keperawatan Padjadjaran Vol. 10 No. 2 (2022): Jurnal Keperawatan Padjadjaran
Publisher : Faculty of Nursing Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jkp.v10i2.2009

Abstract

Background: Family communication can become a support system for adolescents. Ineffective communication in the family causes emotional problems and poor psychological well-being in adolescents. Purpose: This study aimed to analyze the determinant factor of effective family communication in adolescents. Methods: This was a cross-sectional multi-centre design with 357 participants aged 15-16 from fve high schools in Indonesia. We used the convenience sampling method to select participants. Communication in the family questionnaire, Rosenberg Self Esteem Instrument, Depression Anxiety Stress Scale (DASS-21), and the Scale for Suicide Ideation (SSI) questionnaires were used to measure communication within the family, selfesteem, stress, anxiety, depression, and suicide ideation, respectively. Data were analyzed using Chi-square and binary logistics regression. Results: Most of the adolescents were male (52.1%), had harmonious families (96.6%), had economic status above the minimum wage (65.5%), had high self-esteem (88.5%), and had high social support (67.8%). However, in terms of mental health problems, as many as 47.3%, 74.2%, 72%, and 30.5% of adolescents experienced stress, anxiety, depression, and suicidal ideation, respectively. The multivariate analysis concluded that gender (AOR: 0.499; 95% CI: 0.294-0.847) and socioeconomic status (AOR: 0.2.162; 95% CI: 1.296-3.608) were signifcantly correlated with family communication. Conclusion: Males adolescents are more likely to have ineffective family communication than female adolescents. Also, adolescents with a family socioeconomic status below the minimum wage have a greater risk of ineffective family communication. Therefore, it is essential to improve family communication through assertive communication training in adolescents and families in the educational and community setting.
Komparasi Metode Data Mining K-Nearest Neighbor Dengan Naive Bayes Untuk Klasifikasi Kualitas Air Bersih (Studi Kasus PDAM Tirta Kencana Kabupaten Jombang) Maulana Aditya Rahman; Nurul Hidayat; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (538.647 KB)

Abstract

Water is a chemical compound that is needed for the survival of living things on earth. The widest area on planet earth is water that covers almost 71% of the region on earth. Water is also a very important substance on earth that is needed by all living things from plants, animals and humans. It takes the supervision and processing of the environment around the water source so as to produce clean water quality in accordance with the standard of clean water quality and meet the standard of water that is suitable for human consumption. To determine the classification of clean water quality there are many methods that can be used. To choose the best classification method, it can be comparated between several methods. This study comparing the K-Nearest Neighbor and Naive Bayes methods. Based on several studies, the K-Nearest Neighbor and Naive Bayes methods are quite good and yield a high degree of accuracy. Based on the test result, the average accuracy value of K-Nearest Neighbor method is 82.42% and the average accuracy of Naive Bayes method is 70.32%. It can be concluded that the best method for water quality classification is K-Nearest Neighbor method.
Pemilihan Alternatif Tanaman Obat Terhadap Penyakit Hipertensi Menggunakan Metode Analytical Network Process (ANP) dan Simple Multi Attribute Rating Technique (SMART) Linda Pratiwi; Indriati Indriati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.595 KB)

Abstract

Medicinal plants contain active substances aims for healing and preventing of various types of diseases. Various types of medicinal plants each has certain criteria which result in difficulty in determining the alternative medicinal plants as the best priority. This research aims to select alternative medicinal plants which have nutritious substances for hypertension disease treatment. Not only nutritious substances, but also considering the price, availability and taste of the plant. Hypertension is a disease caused by high blood pressure. The selection of alternative medicinal plants for hypertension disease using Analytical Network Process (ANP) and Simple Multi Attribute Rating Technique (SMART) method. Analytical Network Process (ANP) method is used for determining the weights of each of the supporting criteria and Simple Multi Attribute Rating Technique (SMART) method is used for ranking of alternative medicinal plants selection. This research uses 10 data of medicinal plants to be tested. The result of Analytical Network Process (ANP) and Simple Multi Attribute Rating Technique (SMART) method use Spearman Rank correlation test with rs = 0.964 that means a relationship system and expert approach perfectly.
Identifikasi Penyakit Mata Menggunakan Metode Learning Vector Quantization (LVQ) Entra Betlin Ladauw; Dian Eka Ratnawati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.131 KB)

Abstract

Taking care and maintaining healthy eyes are very important for human, because eyes are one of the senses that help human to do daily activities. Eyes that give visual information to human, cannot be separated from the threat of many eyes diseases. The diseases can attack from small to big scale. Unfortunately, eyes diseases are usually considered not to have such potential to harm human, so eyes health often to be ignored by people in general. Therefore, in this paper a system to identify eyes diseases has been developed using Learning Vector Quantization (LVQ) method. This method can give classification to a pattern that represent specific class, which will move to a nearer position to corresponding class when the classification data point is true. In this research, there are 21 symptoms and 9 eyes diseases that processed in training and testing processes, where the data were divided into training data and testing data. In training process, LVQ method did some stages to get final weight. The weight will be used in testing process. Using LVQ method, obtained parameter values are α = 0.4, Dec α = 0.8, Min α = 0.00001, Max Epoch = 25, training data = 100 data (80%) and data test = 25 data (20%). From accuracy testing for this system, the result show 82.80% average accuracy and 92% highest accuracy, that means this system works fine. So, it can be concluded that LVQ method can be used for eyes diseases identification.
Peramalan Debit Bendungan Dengan Menggunakan Metode Backpropagation dan Algoritme Genetika Beta Deniarrahman Hakim; Indriati Indriati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (521.985 KB)

Abstract

Dam discharge forecasting is needed to plan water allocation plans for various needs such as for Hydropower plant, flood control and irrigation. Artificial neural network in this case backpropagation method has a learning method to change the weight of the value of the architecture of the artificial neural network.#Genetic algorithms can optimize the#weight of artificial neural networks to avoid the occurrence of a minimum local which is a weakness of backpropagation. Genetic algorithms will optimize the weight#of the artificial neural network so individuals which are produced as a weight representation with the best fitness value resulting from the optimization process with the genetic algorithm then used as the initial weight of the artificial neural network backpropagation method. The data used as input data is the dam discharge time series data the previous months. The data used is monthly debit data from 2008 to 2017. Input data will be processed to produce an output value which is the forecasted value of the dam discharge in the next month. The optimal training parameters for genetic algorithm and backpropagation training are the population size=100, the generation=100, Cr and Mr combination 0,6 and 0,4, the number of iterations=500, the value of learning rate=0,7. The test results using optimal parameters get the MSE value=0,04188
Query Expansion Pada LINE TODAY Dengan Algoritme Extended Rocchio Relevance Feedback Chandra Ayu Anindya Putri; Indriati Indriati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.742 KB)

Abstract

LINE TODAY provides access to up-to-date news contents. Data on LINE TODAY are used to be able to do search engine feature. Query Expansion technique will be very useful if it is to be combined with search engine system where the queries inputted by users are combined with additional queries from the system. These additional queries will make queries generated by users more specific. In addition, users feedback (user judgement/explicit relevance feedback) assessing on each news can minimize ambiguous queries. The process begins with preprocessing technique consisting of several stages which are cleansing, case folding, tokenization, filtering, and stemming. And then, term weighting and cosine similarity. The next process is calculated using the Extended Rocchio Relevance Feedback method which is a traditional method from Rocchio Relevance Feedback to generate an additional queries. The results are obtained from implementation and testing process of Query Expansion on LINE TODAY with Extended Rocchio Relevance Feedback Algorithm resulted an average Precision value of 0.53308, Recall value of 0.81708, F-Measure value of 0.59553, and Accuracy value of 0.9574. The accuracy value obtained with Extended Rocchio Relevance Feedback method based on user judgement increase by 2% compared to automated search by the method of Rocchio Relevance Feedback.
Implementasi Metode Backpropagation Untuk Peramalan Luas Area Terbakar di Hutan dengan Inisialisasi Bobot Nguyen-Widrow Afrizal Aminulloh; Sigit Adinugroho; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (346.969 KB)

Abstract

Forest fires are a serious event that must be watched out for areas dominated by forest areas. In forest fires, there are several factors that can affect the occurrence of fires such temperature, humidity, rain, wind, and others. This paper implements the backpropagation method to predict the area of the fire. The input used is a factor that influences the occurrence of 7 forest fires. The process of backpropagation method begins with normalizing input data with a range based on the activation function used, after that initialization is weighted and can use the Nguyen-Widrow algorithm, feeds the feedforward and continues to the next process, feedbackward with the MSE requirement less than the error or iteration limit. less than the same as the maximum iteration, if the requirements have been met the output will be normalized, will get a forecasting value, and the last process calculates the results of MSE and SMAPE as a result of the success of the forecasting process. Based on the results of the tests that have been done, it is obtained that the optimal parameters are 5 hidden layer neurons, 0.1 learning rate, and maximum 1500 iterations. The highest average SMAPE result from this study is 49,1796 and the lowest SMAPE average is 31,4492 which shows that the backpropagation method can be used to forecast burn areas in the forest.
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