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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA
Santiary, Putri Alit Widyastuti
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Intra-class deep learning object detection on embedded computer system Santiary, Putri Alit Widyastuti; Swardika, I Ketut; Dewi, Dewa Ayu Indah Cahya; Sugirianta, Ida Bagus Ketut
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp430-439

Abstract

Implementation of artificial intelligence tends to be portable, mobile and embeds in embedded computer system (EBD). EBD is a special-purpose computer with limited capacity in a small-form size. Deep learning (DL) had known as cutting edges for object recognition. With DL, object feature extraction analysis is omitted. DL requires large computing resources and capacity. Implement DL algorithm on EBD goal to achieves high detection accuracy and high-efficiency resources. Hence, be able to cope with intra-class variations, and image disturbances. By those challenges and limitations, this study reports the performance of EBD to recognize an object which has high variations in their class, through an optimal raw-input dataset. The raw-input dataset performed optimization process with a supervisor. Yield is the proper optimal input dataset in size. The performance results observed begin from training dataset until evaluation stage of DL. The comparison performs in efficiency resources, loss, validation-loss, timesteps, and detection accuracy by multiclass confusion matrix analysis. This study shows through this purpose method efficient resources are highly archived. Shorter timesteps ensure training stage is successful, and detection accuracy is perfectly archived. In addition, this study proves DL method archived great performances in classifying object that has identical structure.
Modelling spatio-temporal energy consumption from nighttime radiance satellite dataset Swardika, I Ketut; Santiary, Putri Alit Widyastuti
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 13 No. 3 (2023): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v13i3.166-175

Abstract

National electricity consumption increases in line with continuous population growth and other socio-economic factors. The national electric power capacity goal develops largely for industrial manufacture and new settlement. The electrification- ratio on the target; is based on the accessibility of electricity services. The spatial distribution of electricity services coverage over the Indonesian territory is insufficient, particularly over the remote area that is out of electric services. Modeling by spatial (location) and temporal (year) to estimate electricity or energy consumption is necessary to develop using a low-light nighttime satellite dataset, therefore spatial boundaries can be accomplished. The modeling procedure starts by preparing the data frame of the independent variable input (amount of radiance) and the dependent variable output (the consumption of electricity or energy). The modelling method uses the curve-fitting approach where the indicator results by evaluating the R-square and RMSE values. The output model function is used to convert radiances into electrical power consumption units with a certain degree of accuracy. The selection of the input-output variable was achieved after variable analysis with the highest R-square outcome. Results indicate that the model functions in a polynomial form and correlations between variables are not simple. The selection of various model functions did not change the degree of correlation. The accumulative of energy radiances as independent variable input provides the optimum correlation result. The energy consumption from street lighting, in general, offers appropriate information that can be seen from satellites. The model function can be applied to a narrower spatial scale by input variable constraints.
Sistem Pendukung Keputusan Penentuan Lokasi Wisata dengan Metode Topsis Santiary, Putri Alit Widyastuti; Ciptayani, Putu Indah; Saptarini, Ni Gusti Ayu Putu Harry; Swardika, I Ketut
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 5 No 5: Oktober 2018
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3250.396 KB) | DOI: 10.25126/jtiik.2018551120

Abstract

Bali merupakan salah satu tujuan wisata favorit. Di Bali terdapat banyak lokasi wisata yang menawarkan berbagai kelebihannya masing-masing. Setiap kawasan wisata menawarkan wahana dan keunggulannya masing-masing. Hal ini seringkali menjadikan wisatawan bingung untuk menentukan lokasi wisata, agar mampu memaksimalkan waktu kunjungan, biaya serta kepuasan yang diperoleh. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan (SPK) untuk penentuan lokasi wisata dengan metode TOPSIS dan fuzzy. Metode ini akan memberikan pembobotan kriteria sesuai dengan kondisi/preferensi pengguna, dan kemudian melakukan pengolahan pada data yang bersifat rasa/fuzzy. Metode TOPSIS akan memberikan perankingan alternatif yang menjamin kedekatan dengan kriteria benefit dan menjauhkannya dari kriteria yang bersifat cost. Implementasi sistem dilakukan dengan menggunakan database MySQL dan bahasa PHP. SPK yang dibangun mampu menghasilkan rekomendasi dengan memberikan perankingan lokasi wisata kepada pengguna sesuai preferensinya. Sistem yang dibangun diuji dengan menggunakan 17 alternatif dan 3 kriteria yang terdiri dari 1 kriteria cost dan 2 benefit. Eksperimen yang dilakukan berhasil memberikan perankingan yang berbeda terhadap 15 alternatif dan hanya 2 alternatif dengan ranking yang sama yaitu pada ranking ke-5 dan ke-6 karena skor keduanya sama pada setiap kriteria. AbstractBali is one of the favorite tourist destinations. In Bali there are many tourist destinations that offer their respective advantages. Each tourist area offers its own attraction and advantages. This often makes tourists confused to determine tourist destinations to maximize visit time, costs and satisfaction obtained. This study aims to build a decision support system (DSS) for determining tourist destinations with TOPSIS and fuzzy methods. This method will provide criteria weighting in accordance with the conditions/preferences of the user, and then perform processing on fuzzy data. The TOPSIS method will provide an alternative ranking that guarantees proximity to benefit criteria and keeps them from the cost criteria. System implementation was done using a MySQL database and PHP language. The DSS able to produce recommendation that provides users with a ranking of tourist destinations according to their preferences. The system built was tested using 17 alternatives and 3 criteria consisting of 1 cost criterion and 2 benefi criteria. Experiments carried out successfully gave different ranks to 15 alternatives and only 2 alternatives with the same ranking were ranked 5th and 6th because of both alternatives have the same score at each criterion.
Co-Authors Dewa Ayu Indah Cahya Dewi Harry Saptarini, Ni Gusti Ayu Putu I Ketut Swardika Putu Indah Ciptayani Sugirianta, Ida Bagus Ketut