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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Majalah Ilmiah Teknologi Elektro Jurnal Teknologi Informasi dan Komputer
I Wayan Agus Surya Darma
Institut Bisnis Dan Teknologi Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences

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Peramalan Jumlah Kunjungan Wisatawan Menggunakan Triple Exponential Smoothing I Wayan Agus Surya Darma; I Putu Eka Giri Gunawan; Ni Putu Sutramiani
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2020.v08.i03.p06

Abstract

Bali merupakan salah satu destinasi pariwisata terbaik di dunia. Berdasarkan berita resmi statistik yang dipublikasikan oleh Badan Pusat Statistik Bali, jumlah kunjungan wisatawan mancanegara ke Bali pada bulan Juni 2019 mencapai 549.751 kunjungan. Peramalan kunjungan wisatawan merupakan faktor yang sangat penting untuk menentukan kebijakan tempat tujuan wisata, meminimalkan ketidakpastian dan resiko investasi. Hal ini merupakan hal yang sangat penting karena sektor pariwisata merupakan tulang punggung ekonomi di Bali. Penelitian ini mengangkat topik bagaimana mengimplementasikan metode Triple Exponential Smoothing pada proses peralaman jumlah wisatawan. Kami menggunakan data historis kunjungan wisatawan ke Bali yang diperoleh dari Badan Pusat Statistik Provinsi Bali. Hasil peramalan dievaluasi menggunakan mean absolute error untuk menunjukan rata-rata kesalahan dalam perhitungan peramalan. Rata-rata Mean Absolute Error yang dihasilkan pada peramalan ini adalah 18 dengan hasil evaluasi terbaik dengan menggunakan Alpha 0.9, Beta 0 dan Gamma 0.8.
EKSTRAKSI FITUR AKSARA BALI MENGGUNAKAN METODE ZONING I Wayan Agus Surya Darma; I K. G. Darma Putra; Made Sudarma
Jurnal Teknologi Elektro Vol 14 No 2 (2015): (July - December) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (214.435 KB) | DOI: 10.24843/MITE.2015.v14i02p09

Abstract

Feature extraction is an important process in character recognition system. The purpose of this process is to obtain special feature from a character image. This paper is focuses on how to obtain special feature from a handwritten Balinese character image using zoning. This algorithm dividing Balinese character image into multiple regions, then a special feature on each region resulting the data extracted feature. The test result in this paper generates a various  semantic and direction feature data. This is because this paper using handwritten Balinese character. Furthermore, the features that produced in this paper can be used on Balinese character image recognition process
Implementasi Zoning dan K-Nearest Neighbor dalam Pengenalan Karakter Aksara Wrésastra I Wayan Agus Surya Darma
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 10, No. 1 April 2019
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (401.763 KB) | DOI: 10.24843/LKJITI.2019.v10.i01.p02

Abstract

Balinese script is an important aspect that packs the Balinese culture from time to time which continues to experience development along with technological advances. Balinese script consists of three types (1) Wrésastra, (2) Swalalita and (3) Modre which have different types of characters. The Wrésastra and Swalalita script are Balinese scripts which grouped into the script criteria that are used to write in the field of everyday life. In this research, the zoning method will be implemented in the feature extraction process to produce special features owned by Balinese script. The results of the feature extraction process will produce special features owned by Balinese script which will be used in the classification process to recognize the character of Balinese script. Special features are produced using the zoning method, it will divide the image characters area of ??Balinese scripts into several regions, to enrich the features of each Balinese script. The result of feature extractions is stored as training data that will be used in the classification process. K-Nearest Neighbors is implemented in the special feature classification process that is owned by the character of Balinese script. Based on the results of the test, the highest level of accuracy was obtained using the value K=3 and reference=10 with the accuracy of Balinese script recognition 97.5%.
IMPLEMENTASI SUPPLY CHAIN MANAGEMENT PADA E-COMMERCE SEBAGAI STRATEGI PENGEMBANGAN UMKM JAJANAN DODOL KHAS BULELENG I Wayan Agus Surya Darma; I Gusti Agung Indrawan; Ni Putu Sutramiani
Jurnal Teknologi Informasi dan Komputer Vol 6, No 2 (2020): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.92 KB)

Abstract

ABSTRACTPenglatan Village is a village that is the biggest dodol production center of Buleleng in the largestdistrict of Buleleng which is distributed to all regencies in Bali, even Buleleng dodol is also an icon oftypical souvenirs of Buleleng to be taken outside of Bali. Conventional trading has been carried out bymicro and small and medium enterprises (UMKM) entrepreneurs in the village of Penglatan who arecraftsmen of Buleleng dodol. Dodol craftsmen in the village of Penglatan, which is a home industrythat sells dodol products to collectors, then collectors distribute dodol products typical of Buleleng toall districts in Bali. This causes the home industry in the village of Penglatan difficult to developbecause it can not handle direct requests. Another problem faced is the difficulty of the craftsmen incalculating the need for raw materials in producing dodol typical of Buleleng when there is an order.Implementation of supply chain management in e-commerce that was developed to manage the supplyof dodol raw materials in accordance with orders that enter the system. This is expected to help dodolcraftsmen in the village of Penglatan in determining the need for raw materials needed to produceorders and provide electronic-based trading media. Determination of raw material requirements forproducing dodol is calculated by applying the concept of master requirements planning. Thedeveloped system can help MSMEs in managing sales transactions and calculating raw materialrequirements in producing dodol.Keywords: Supply Chain Management, Material Requirement Planning, E-Commerce, Dodol KhasBuleleng.ABSTRAKDesa Penglatan merupakan desa yang menjadi sentra produksi dodol khas Buleleng terbesar dikabupaten Buleleng yang disalurkan ke seluruh kabupaten di Bali, bahkan dodol Buleleng jugamenjadi ikon oleh-oleh khas Buleleng untuk dibawa ke luar Bali. Perdagangan secara konvesionaltelah dilakukan oleh pelaku Usaha Mikro Kecil dan Menengah (UMKM) di desa Penglatan yangmenjadi pengrajin dodol Buleleng. Pengrajin dodol di desa Penglatan yang merupakan industri rumahtangga yang menjual produk dodolnya ke pengepul, kemudian pengepul mendistribusikan dodol khasBuleleng ke seluruh kabupaten di Bali. Hal ini menyebabkan industri rumah tangga di desa Penglatansulit berkembang karena tidak bisa menangani permintaan langsung. Permasalahan lainnya yangdihadapi adalah sulitnya pengrajin dalam memperhitungkan kebutuhan bahan baku dalammemproduksi dodol khas Buleleng ketika ada pesanan. Implementasi supply chain management padae-commerce yang dikembangkan untuk mengelola pasokan bahan baku dodol sesuai dengan pesananyang masuk ke sistem. Hal ini diharapkan dapat membantu pengrajin dodol di desa Penglatan dalammenentukan kebutuhan bahan baku yang diperlukan dalam memproduksi pesanan dan memberikanmedia perdagangan berbasis elektronik. Penentuan kebutuhan bahan baku untuk memproduksi dodoldihitung dengan menerapkan konsep master requirement planning. Sistem yang dikembangkan dapatmembantu UMKM dalam mengelola transaksi penjualan dan menghitung kebutuhan bahan bakudalam memproduksi dodol.Kata kunci: Supply Chain Management, Material Requirement Planning, E-Commerce, Dodol KhasBuleleng.
Batik’s Pattern Recognition and Generation: Review and Challenges Dewa Made Sri Arsa; Anak Agung Ngurah Hary Susila; Desak Ayu Sista Dewi; Ni Putu Sutramiani; I Wayan Agus Surya Darma
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 10 No 2 (2022): Vol. 10, No. 2, August 2022
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2022.v10.i02.p04

Abstract

Batik is one of cultural heritage acknowledged by UNESCO. Intelligence system comes as one of solution to take parts on preservation programs of this heritage. This study explores the current state of the art in application of artificial intelligence on Batik images. This research provides a systematic investigation and present the current progress and hot issues in recognition and generation area for Batik images. Furthermore, this research also presents several Batik data sets and their state of the art. As a result of the review, we are projecting several future works in the discussion.
Handwritten Balinese Script Recognition on Palm Leaf Manuscript using Projection Profile and K-Nearest Neighbor Ni Putu Sutramiani; I Wayan Agus Surya Darma; Dewa Made Sri Arsa
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 10 No 3 (2022): Vol. 10, No. 3, December 2022
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2022.v10.i03.p02

Abstract

This paper presents a simple approach to the handwritten Balinese script characters recognition in palm-leaf lontar manuscripts. The Lontar manuscript is one of the cultural heritages found in Bali. Lontar manuscripts are written using a pengrupak, which is a kind of knife for writing on palm leaves. To give color to the results of the writing, candlenut is used so that the writing appears clear. In this paper, we apply the projection profile at the segmentation stage to get the handwritten Balinese script characters in the lontar manuscript. The palm leaf manuscript that we use is the Wariga Palalubangan palm leaf. The recognition process is carried out by implementing K-Nearest Neighbor in the recognition process. The recognition was made on the Wianjana script obtained from lontar manuscripts using 720 images consisting of 18 classes as dataset training. The test results showed that the level of recognition accuracy was obtained by 52% in the characters of handwritten Balinese scripts derived from lontar manuscripts and 92% in the characters of handwritten Balinese scripts on paper.
Optimization Strategy on Deep Learning Model to Improve Fruit Freshness Recognition I Gusti Agung Indrawan; Putu Andy Novit Pranartha; I Wayan Agus Surya Darma; I Putu Eka Giri Gunawan
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 14 No 1 (2023): Vol. 14, No. 1 April 2023
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2023.v14.i01.p01

Abstract

The high fruit production during the harvest season is a challenge in the process of sorting fresh fruit and rotten fruit in plantations. Automatic fruit freshness classification based on deep learning can speed up the sorting process. However, building a model with high accuracy requires the right strategy based on the dataset's characteristics. This research aims to apply optimization strategies to deep learning models to improve model performance. The optimization strategy is implemented by optimizing the model using fine-tuning strategy by selecting the best parameters based on learning rate, optimizers, transfer learning, and data augmentation. The transfer learning process is applied based on the dataset's characteristics by training some parameters with a size of 30% and 60%, which were tested in four scenarios. The fine-tuning strategy is applied to three Deep Learning models, i.e., MobileNetv2, ResNet50, and InceptionResNetV2, which have various parameter sizes. Based on test results, fine-tuning strategy produces the best performance up to 100% with a learning rate of 0.01, the SGD optimizers on the InceptionResNetV2 model are trained on 60% of the parameters.
Co-Authors Anak Agung Ngurah Hary Susila Arsa, Dewa Made Sri Desak Ayu Sista Dewi I Gusti Agung Indrawan I ketut Gede Darma Putra I Putu Eka Giri Gunawan Made Sudarma Ni Putu Sutramiani Putu Andy Novit Pranartha