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THE URBAN PLANNING CONCEPT BASED ON SMART CITY APPROACH Muhammad Bakri; Anita Ahmad Kasim
International Journal on Livable Space Vol. 3 No. 2 (2018): Resilient Built Environment
Publisher : Jurusan Arsitektur - FTSP - Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/livas.v3i2.3014

Smart City comes as a strategy to reduce the problem due to rapid urban growth and urbanization. The concept of Smart City is needed to ensure the conditions of a habitable City in the context of rapidly growing urban population growth. The urgency of this challenge prompted many cities to begin to find smarter ways of managing urban areas. One way to make the concept of the smart city is to make the city an icon that is sustainable and livable. This study aims to provide the necessary information in building and developing a city through the smart city approach. This paper clarifies the meaning of the word "smart" in the city context through an approach based on an in-depth literature review of the relevant study. This study will identify the main factors and characteristics that characterize smart cities. The method used to obtain various factors and the characteristics of the Smart City in the arrangement of a region is done by studying various kinds of the literature of various concepts and components in the Smart City. The results obtained in this study there is a concept of Smart City in urban planning by mapping various factors and characteristics in the Smart City. Keywords: Smart City, Urban planning, smart city characteristic

Quadratic Support Vector Machine For The Bomba Traditional Textile Motif Classification Nuraedah Nuraedah; Muhammad Bakri; Anita Ahmad Kasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1004-1014

The Bomba textile is one of the textile fabrics in Indonesia used in a province called Sulawesi Tengah. Bomba Textile has a unique pattern and has a philosophical meaning in human life in Sulawesi Tengah. Bomba Textile has many motif patterns and varied colors. The problem in this research is the difficulty in classifying every The Bomba textile motif in each class. Data classification is needed to recognize the motif of each Bomba textile pattern and to cluster it into the appropriate class. The features used to classify the Bomba textile motif is the textural feature. Texture features obtained from Gray-Level Co-occurrence matrices (GLCM) method consisting of energy, contrast, homogeneity and correlation with four angles 0°, 45°, 90°, and 135°. This research will implement Quadratic Vector Machine (QSVM) method with texture feature on Bomba textile pattern. The use of a single texture feature with angles 90° has an accuracy of 90.3%. The incorporation of texture features by involving all features at all angles can improve the accuracy of the classification model. This research produces a model of motif classification on the Bomba textile which has the classification accuracy of 94.6% and error rate of 5.4%.

THE URBAN PLANNING CONCEPT BASED ON SMART CITY APPROACH Muhammad Bakri; Anita Ahmad Kasim
International Journal on Livable Space Vol. 3 No. 2 (2018): Resilient Built Environment
Publisher : Jurusan Arsitektur - FTSP - Universitas Trisakti

Smart City comes as a strategy to reduce the problem due to rapid urban growth and urbanization. The concept of Smart City is needed to ensure the conditions of a habitable City in the context of rapidly growing urban population growth. The urgency of this challenge prompted many cities to begin to find smarter ways of managing urban areas. One way to make the concept of the smart city is to make the city an icon that is sustainable and livable. This study aims to provide the necessary information in building and developing a city through the smart city approach. This paper clarifies the meaning of the word "smart" in the city context through an approach based on an in-depth literature review of the relevant study. This study will identify the main factors and characteristics that characterize smart cities. The method used to obtain various factors and the characteristics of the Smart City in the arrangement of a region is done by studying various kinds of the literature of various concepts and components in the Smart City. The results obtained in this study there is a concept of Smart City in urban planning by mapping various factors and characteristics in the Smart City. Keywords: Smart City, Urban planning, smart city characteristic

Artificial Intelligent for Human Emotion Detection with the Mel-Frequency Cepstral Coefficient (MFCC) Anita Ahmad Kasim; Muhammad Bakri; Irwan Mahmudi; Rahmawati Rahmawati; Zulnabil Zulnabil
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15435

Emotions are an important aspect of human communication. Expression of human emotions can be identified through sound. The development of voice detection or speech recognition is a technology that has developed rapidly to help improve human-machine interaction. This study aims to classify emotions through the detection of human voices. One of the most frequently used methods for sound detection is the Mel-Frequency Cepstrum Coefficient (MFCC) where sound waves are converted into several types of representation. Mel-frequency cepstral coefficients (MFCCs) are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The primary data used in this research is the data recorded by the author. The secondary data used is data from the "Berlin Database of Emotional Speech" in the amount of 500 voice recording data. The use of MFCC can extract implied information from the human voice, especially to recognize the feelings experienced by humans when pronouncing the sound. In this study, the highest accuracy was obtained when training with epochs of 10000 times, which was 85% accuracy.

The Management of School Operational Assistance (SOA) through Tax Administration at Tojo Una Una’s Financial and Asset Management Agency Muhammad Iqbal Bakri; Andi Mattulada; Muhammad Ikbal Abdullah; Fikry Karim; Abdul Kahar; Muliati; Muhammad Din; Femilia Zahra; Andi Chairil Furqan
Research Horizon Vol. 2 No. 4 (2022)
Publisher : Publindo Akademika

School Operational Assistance (SOA) is a government program that provides funding for personnel operational costs for basic education units as implementing compulsory learning programs. This study aims to analyze the management of School Operational Assistance (SOA) through tax administration at Tojo Una Una’s Financial and Asset Management Agency, Central Sulawesi Province, Indonesia. The approach that will be taken in implementing community service activities is through an explanation of the management of the SOA fund treasurer and the person in charge of the principal of each school in the Tojo Una Una Regency, the duties and authorities of the SOA fund treasurer. Pre and post-tests were tested using the Compare Means Paired- Sample T-Test analysis with the statistical analysis tool SPSS because the data came from the same subject. The results highlight that the management of SOA funds has not been fully effective because several factors that lead to the achievement of the objectives of managing funds have not been achieved, including planning, implementation, and accountability aspects. Therefore, to improve technical capabilities and skills in the management of SOA funds, especially related to SOA tax administration, it is necessary to carry out service in the form of socialization related to SOA tax administration, which will be framed in an effective communicative, and relaxed manner.

Automatic Identification of Herbal Medicines Based on Medicinal Plant Leaf Images Using the Scale Invariant Feature Transform (SIFT) Features Anita Ahmad Kasim; Muhammad Bakri; Chairunnisa Lamasitudju; Ahmad Fachrozi
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar

Background: A few people prefer to consume medicinal plants compared to modern medicine. This is because modern medicine contains chemicals which over time can have a bad impact on the kidneys, and medicinal plants are also considered cheap treatments. Meanwhile, in our current environment, there are plants that grow and have certain benefits, but some people don't know whether these plants are herbal medicinal plants or not. By utilizing technology, people can find out about herbal medicinal plants based on the leaves by photographing them on an Android smartphone. Method: The method used to extract features from the leaf image is Scale Invariant Feature Transform (SIFT). Aim: This research aims to recognize leaves whose images have been photographed or uploaded. The system will identify herbal medicinal plants using the leaf image of the plant using the Scale Invariant Features Transform (SIFT) method. Result: Feature Extraction and Support Vector Machine (SVM). With this system, it is hoped that users will be able to identify herbal medicinal plants that may grow in the surrounding environment. Based on the description in the background above, the problem formulation in this research is how to identify herbal medicinal plants using leaf images using Android-based SIFT feature extraction. Conclusion: The results of the confusion matrix test explain that this system has an average accuracy of 77%, which means that this system is quite good at identifying leaf images, even though the error rate is quite high at 23%.Keywords—Medicinal Plant Leafs, SVM, SIFT

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