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Deteksi Gerak Otot Frontalis Berbasis Citra 3 Dimensi Menggunakan Gray Level Co-Occurrence Matrix (GLCM) Wibowo, Hardianto; Hery Purnomo, Mauridhi; Mulyanto Yuniarno, Eko
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 1, No 2, August-2016
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (707.04 KB) | DOI: 10.22219/kinetik.v1i2.25

Abstract

Ekspresi wajah atau mimik merupakan salah satu dari hasil gerak otot pada wajah. Dalam kamus besar bahasa Indonesia, ekspresi merupakan pengungkapan atau proses menyatakan, yaitu memperlihatkan atau menyatakan maksud, gagasan perasaan dan lain sebagainya. Ekspresi wajah atau mimik dipengaruhi oleh saraf tujuh atau nervuse facialis. Dalam penelitian yang dilakukan paul ekman didapat sebuah standarisasi ekspresi dalam format pergerakkan yang disebut dengan Facial Action Coding System (FACS). Dalam penelitiannya paul ekman menyatakan enam ekspresi dasar yaitu bahagia, sedih, terkejut, takut, marah dan jijik. Dalam anatomy otot, bahwa setiap otot yang bergerak pasti terjadi kontraksi, dan pada saat terjadi kontraksi, otot akan mengembang atau mengelembung. Otot dibagai menjadi tiga bagian yaitu origo dan insersio sebagai ujung otot dan belly sebagai titik tengah otot, jadi setiap terjadi gerakkan maka otot bagian beli akan mengembang atau menggelembung. Teknik pengambilan data yaitu dengan merekam data dalam bentuk 3D, setiap terjadi kontraksi maka otot bagian beli akan mengelembung dan data inilah yang akan diolah dan dibandingkan. Dari pengolahan data ini akan didapat kekuatan maksimum kontraksi yang akan dipakai sebagai acuan untuk besaran pergeseran otot khususnya pada otot frontalis. Dalam deteksi pergerakkan akan menggunakan metode gray level co-occurrence matrix (GLCM), dan akan didapatkan pula besaran pergeseran otot secara maksimal. Dari hasil pengujian didapatkan nilai pergeseran pergerakkan otot sebesar 1,367 4,460.
Gamification And GDLC (Game Development Life Cycle) Application For Designing The Sumbawa Folklore Game ”The Legend Of Tanjung Menangis (Crying Cape)” Husniah, Lailatul; Pratama, Bayu Fajar; Wibowo, Hardianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 4, November 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (679.726 KB) | DOI: 10.22219/kinetik.v3i4.721

Abstract

Sumbawa is popularly known as one of the regions in Indonesia, having a well- known folklore among the Sumbawa people, entitled the legend of Tanjung Menangis (Crying Cape). However, Tanjung Menangis is commonly recognized for its beauty than the stories contained. Therefore, a research is carried out by developing a game that is employed as a tool to introduce the story of Tanjung Menangis Legend as effort to preserve the original story of the mainland Sumbawa. The media game is chosen due to its favoured technology by children and adolescent as the target users of this research. This study applies Game Development Life Cycle (GDLC) method in the development stage which consists of several stages includinng: pre-production, production, testing, and post-production by adding an element of gamification. The game is tested on students at Labangka Elementary School in Sumbawa district in an age range of 10-15 years. After playing the game, the majority of respondents states that students gain knowledge about the Legend of Tanjung Menangis as reported from the results of the t- test with a probability value of 7.369x10-41, which is far below the value of α = 0.05. This result means that there was an increase in user knowledge of application. The test results also showed that all respondents agreed that the game of The Legend of Tanjung Menangis was used as one of the media used to introduce the story of the original Sumbawa people. In addition, the testing results as conducted with playtesting and gameflow test achieved good grades, with a range of values 4.5-4.81 of the seven elements tested, including: Concentration, Challenge, Player Skills, Control, Clear Goals, Feedback, and Immersion.
GAME EDUKASI ROTI MOCAF BERBASIS ANDROID Cahyono, Eko Budi; Firmansyah, Tino; Suharso, Wildan; Wibowo, Hardianto
SINTECH (Science and Information Technology) Journal Vol 1 No 2 (2018): SINTECH Journal Edition Oktober 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (832.512 KB) | DOI: 10.31598/sintechjournal.v1i2.303

Abstract

The understanding of the Indonesian people about the importance of abundant raw materials is very lacking, this is evidenced by the many understandings that mocaf (cassava flour) is a raw material that cannot be processed properly and attractively so that it does not become a trend. Indonesia is one of the countries producing cassava although cassava is not a staple food. People need to know and understand the extent to which cassava can be processed into cassava flour, and cassava flour into bread. This study designs and builds applications that are educational to provide understanding to the community, especially for school-age children, considering that the main education is when compulsory children are elementary, middle and high school. In this study the Game Development Life Cyle (GDLC) method is used which consists of the stages of initiation, pre production, production, testing. In this study playtesting evaluation was carried out for 20 respondents with a play time of 10-15 minutes, covering aspects of concentration in addition to functional testing. Concentration aspects are valued at 4,15.
Monitoring Walking Devices For Calorie Balance In Patients With Medical Rehabilitation Needs Andhyka Kusuma, WAK, Wahyu; Sari, Zamah; Fitriani, Diah Ayu; Norhabibah, Siti; Ubay, Sabrina Nurul; Wibowo, Hardianto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.931 KB) | DOI: 10.11591/eecsi.v5.1613

Abstract

This article presents a measurement system intended to monitor human footsteps. The goal is to guide the users medical rehabilitation incorrect use to prevent dangerous situations and maximize comfort. Indicators of risk in question: the imbalance of movement in motor coordination and the number of calories to be burned for medical rehabilitation patients by balancing the patient's needs. Measurements are made by placing the sensor on one of the patient's legs. The main sensor accelerometer used in this study. The measurement system comes with an application link that allows patients and therapists to monitor the activity. Calibration and experimental results are presented in this article.
Correlation Between Bruto Domestic Products (Gdp) With Duty Schools Wibowo, Hardianto; Iswatiningsih, Daroe; Suharso, Wildan; Firdausi, Fachrunnisa
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.421 KB) | DOI: 10.11591/eecsi.v5.1718

Abstract

This study aims to analyze the linkage of dropout rates with Gross Domestic Product (GDP). The data source of this research is the Central Bureau of Statistics (BPS), with data acquisition of GDP and drop out rate of elementary, junior and senior high school year 2008 until 2011. Data obtained through quantitative approach with secondary data source. The connectedness value between school dropout and GDP at primary level was 0.7294 in 2008, 0.7225 in the year of 2009, 0.4393 in 2010 and 0.3878 in 2011. While the relationship between the number of dropouts and GDP of junior high school level is 0.6095 in 2008, 0.6238 in 2009, 0.3605 in 2010 and 0.2467 in 2011. while the relationship between the drop out rate and GDP of the SMA level was 0.6061 in 2008, 0.5965 at in 2009, 0.5321 in 2010 and 0.2606 in 2011.
ANALISIS KOINTEGRASI PASAR MODAL IN- DONESIA DENGAN PASAR MODAL AMERIKA SERIKAT DAN PASAR MODAL EROPA MENGGUNAKAN PENDEKATAN JOHANSEN COINTEGRATION TEST (Studi Kasus pada saat terjadi Krisis Ekonomi di Amerika Serikat dan Eropa tahun 2008 - 2012) Wibowo, Hardianto
JURNAL BISNIS STRATEGI Vol 21, No 1 (2012): Juli
Publisher : Magister Manajemen, Fakultas Ekonomika dan Bisnis Undip

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (482.831 KB) | DOI: 10.14710/jbs.21.1.112-141

Abstract

By understanding the cointegration between one capital market with other capital markets,  it can assist investors in determining which of the capital  market  will be used to form the International diversification in order to provide a potential advantage.  In research on the cointegration of capital markets has been done by Fratzscher (2002), Murtini and Ekawati (2003), Karim, Kassim, dan Arip (2010), Srikanth and Aparna (2012), by taking a few sample of some of the capital market in the world revealeddifferent results, instead of giving rise to a research gap. Therefore, it is necessary to do a deeper study because a different result occured after the economic crisis of United States and Europe in 2008. Research problem to be studied is to analyze the cointegration between the Indonesian capital market with the U.S. capital markets (DJIA) and the European capital markets (FTSE 100, IBEX 35 and ATHEX).This reseach method uses quantitative research. The sample of research is the data from IHSG, DJIA index, FTSE 100 index,  IBEX 35 index, and ATHEX index that limited in weekend closing data during the observation period between 2008-2012. Data analysis techniques using Johansen Cointegration Test, Augmented Dickey-Fuller (ADF) Test and Granger Causality Test within 5% significance.The results of this study would be indicate that the Indonesian capital market has been cointegrated  with U.S. stock market (DJIA), UK stock market  (FTSE 100), Spain stock market (IBEX 35) and Greek capital market (ATHEX). Indeed, the Indonesian Capital Market connected to U.S. and Europe Capital Markets have a causal relationship. 
Performance Comparisson Human Activity Recognition Using Simple Linear Method Kusuma, Wahyu Andhyka; Sari, Zamah; Minarno, Agus Eko; Wibowo, Hardianto; Akbi, Denar Regata; Jawas, Naser
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (731 KB) | DOI: 10.22219/kinetik.v5i1.1025

Abstract

Human activity recognition (HAR) with daily activities have become leading problems in human physical analysis. HAR with wide application in several areas of human physical analysis were increased along with several machine learning methods. This topic such as fall detection, medical rehabilitation or other smart appliance in physical analysis application has increase degree of life. Smart wearable devices with inertial sensor accelerometer and gyroscope were popular sensor for physical analysis. The previous research used this sensor with a various position in the human body part. Activities can classify in three class, static activity (SA), transition activity (TA), and dynamic activity (DA). Activity from complexity in activities can be separated in low and high complexity based on daily activity. Daily activity pattern has the same shape and patterns with gathering sensor. Dataset used in this paper have acquired from 30 volunteers.  Seven basic machine learning algorithm Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosted and K-Nearest Neighbor. Confusion activities were solved with a simple linear method. The purposed method Logistic Regression achieves 98% accuracy same as SVM with linear kernel, with same result hyperparameter tuning for both methods have the same accuracy. LR and SVC its better used in SA and DA without TA in each recognizing.
Analisa Data Pesawat Terbang Menggunakan Metode Elimination Void Data dan Smoothing Data Chandranegara, Didih Rizki; Arifianto, Sofyan; Wibowo, Hardianto
POROS TEKNIK Vol. 12 No. 1 (2020)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/porosteknik.v12i2.874

Abstract

Perkembangan transportasi udara saat ini semakin meningkat, sehingga data yang disediakan juga semakin banyak. Oleh karena itu perlu dilakukan analisa-analisa terkait data penerbangan yang ada. Sehingga hasil analisa tersebut sangat berguna sebagai bahan evaluasi pihak otoritas penerbangan. Penelitian ini melakukan analisa terhadap data pesawat yang di sebarkan secara periodik menggunakan sistem yang bernama Automatic Dependent Surveillance-Broadcast (ADS-B). Hasil dari penelitian ini menunjukkan bahwa data penerbangan yang sangat besar dapat direduksi sehingga dapat menghemat ruang penyimpanan data dari pihak tertentu tanpa mengurangi informasi yang di peroleh sebelumnya.
ClusterMix K-Prototypes Algorithm to Capture Variable Characteristics of Patient Mortality With Heart Failure Novidianto, Raditya; Wibowo, Hardianto; Chandranegara, Didih Rizki
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 2, May 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i2.1209

Abstract

Cardiovascular Disease (CVD) is one of the leading causes of many death worldwide, leading to heart failure incidence. The World Health Organization (WHO) says the number of people dying from cardiovascular disease from heart failure each year has an average of 17,9 million deaths each year, about 31 percent of the total deaths globally. Identify the mortality factors of heart failure patients that need to be formed, which reduces death due to heart failure. One of them is by using variable mortality due to heart failure by applying the k-prototypes algorithm. The clustering result is formed 2 clusters that are considered optimal based on the highest silhouette coefficient value of 0,5777. The results of the study were carried out as segmentation of patients with variable mortality of heart failure patients, which showed that cluster 1 is a cluster of patients who have a low risk of the chance of mortality due to heart failure and cluster 2 is a cluster of patients with a high risk of mortality due to heart failure. The segmentation is based on the average value of each variable of heart failure mortality factor in each cluster compared to normal conditions in serum creatine variables, ejection fraction,  age,  serum sodium, blood pressure, anemia,  creatinine phosphokinase,  platelets, smoking, gender, and diabetes.
Combined scaled manhattan distance and mean of horner’s rules for keystroke dynamic authentication Didih Rizki Chandranegara; Hardianto Wibowo; Agus Eko Minarno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14815

Abstract

Account security was determined by how well the security techniques applied by the system were used. There had been many security methods that guaranteed the security of their accounts, one of which was Keystroke Dynamic Authentication. Keystroke Dynamic Authentication was an authentication technique that utilized the typing habits of a person as a security measurement tool for the user account. From several research, the average use in the Keystroke Dynamic Authentication classification is not suitable, because a user's typing speed will change over time, maybe faster or slower depending on certain conditions. So, in this research, we proposed a combination of the Scaled Manhattan Distance method and the Mean of Horner's Rules as a classification method between the user and attacker against the Keystroke Dynamic Authentication. The reason for using Mean of Horner’s Rules can adapt to changes in values over time and based on the results can improve the accuracy of the previous method.