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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Buletin Udayana Mengabdi Jurnal SPEKTRUM Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Pekommas Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Information Technology and its Utilization
G M Arya Sasmita
Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Analisa Pola Belanja Konsumen serta Prediksi Stok Barang Berbasis Web I Made Dwi Cahaya Putra; Gusti Made Arya Sasmita; Ni Kadek Dwi Rusjayanthi
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 3 (2023): Volume 9 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i3.67154

Abstract

Data mining merupakan teknik pengolahan data dalam jumlah besar menggunakan berbagai algoritma serta sistem untuk menghasilkan sebuah informasi yang berguna. Tujuan dari penelitian ini adalah untuk membuat sebuah sistem berbasis web dengan mengimplementasikan teknik data mining yang dapat digunakan dalam mempermudah melakukan asosiasi terhadap barang dan prediksi stok barang. Penelitian ini dilakukan dengan menggunakan dua metode asosiasi yaitu dengan algoritma FP-Growth dan apriori serta dua metode prediksi yaitu dengan algoritma regresi linier dan Support Vector Regression (SVR). Proses asosiasi dari 2658 data transaksi menggunakan metode FP-Growth dan apriori sama-sama menghasilkan jumlah aturan asosiasi berdasarkan nilai minimum support dan confidence yang sama. Proses prediksi 10 jenis barang menggunakan regresi linier dan SVR menghasilkan tingkat akurasi yang berbeda-beda tiap produknya sehingga metode dengan akurasi tertinggi dipilih pada setiap produk. Rata-rata tingkat kesalahan prediksi dengan MAPE dari 10 produk menggunakan metode regresi linear sebesar 12,09% sedangkan metode SVR sebesar 11,51%, sehingga metode SVR memiliki akurasi yang lebih baik untuk diterapkan pada Timbul Jaya Petshop. Hasil dari asosiasi dan prediksi dapat dimanfaatkan untuk merancang strategi bisnis kedepannya. 
SARIMA with Sliding Window Implementation for Forecasting Seasonal Demand Data Made Rama Pradipta; Gusti Made Arya Sasmita; Anak Agung Ngurah Hary Susila
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 1 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i1.59971

Abstract

Demand forecasting is an essential part of business process management. A comparison of methods is needed to get the best model to provide good forecasting results. Difficulties in meeting consumer demands and predicting these requests using demand data at companies CV. ABCD is the main problem in this research. The SARIMA and decomposition methods are used for comparison and search for the best model before forecasting. SARIMA  with a windowing size of 56, indicating the smallest MAPE value of 3,91%. The value <10%, so it can be said to produce an excellent forecasting value. Forecasting results with SARIMA  show a meeting between actual and forecasting data in 2022. Therefore, it can be said the forecasting results for 2023 and 2024 can be used as a reference for the company CV. ABCD to meet customer demand and avoid stock shortages.
Application Design of the Medicines Usage Prediction Based on Backpropagation Neural Network Method and PHP I Putu Arya Dharmaadi; Gusti Made Arya Sasmita
Journal of Information Technology and Its Utilization Vol 2 No 2 (2019)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.2.2.2537

Abstract

The development of information technology makes many organizations utilizing it in their business process. For example, hospitals use certain information systems in medicine management. We observe that most medicines applications do not provide the drug usage prediction feature so that this situation causes the hospital staff being difficult in providing enough medicines. Therefore, in this experimental research, we developed an application in the form of a simple design for helping the hospitals in predicting daily medicine usage. This application also provides medicines stock management and doctor diagnosis features. The Brainy library is used to facilitate implementing the backpropagation neural network method in PHP programming language. We choose PHP because this server script is widely used in information system development. We demonstrated that the mock-up as the result of this development is able to work properly. For further study, we suggest expanding this mock-up become a full hospital information system that covers many functions in medical centers.
Co-Authors Anak Agung Ketut Agung Cahyawan Wiranatha Anak Agung Ngurah Hary Susila Andika Pradita Putera Arsa, Dewa Made Sri Ayu Wirdiani Cardian Althea Stephanie Lahallo Dwi Putra Githa Dwi Rusjayanthi, Dwi Eka Candyasa Pratyaswara Gede Haris Premana Wibawa Gede Sukadarmika Gerlan A Manu Gusti Agung Ayu Putri Gusti Agung Mayun Kukuh Jaluwana Gusti Ngurah Sanditya Riantama I Dewa Nym. Nurweda P., I Gede Ary Suta Sanjaya I Gede Nengah Bayu Darmawan I Gst Putu Agus Wawan Adi Putra I Gusti Agung Sagotri Mahadewi I Gusti Ngurah Indra Saputra I Gusti Ngurah Made Putra Eryawan I Ketut Adi Purnawan I ketut Gede Darma Putra I Made Agus Dwi Suarjaya I Made Dwi Cahaya Putra I Made Sukarsa I Made Sunia Raharja I Made Sunia Raharja I Made Sutha Negara I Md. Agus Ana W. M.Ti I Nengah Simpen I Nyoman Adi Wardiana I Nyoman Piarsa I Putu Agung Bayupati I Putu Aris Richard Hernanda I Putu Arya Dharmaadi I Putu Cahya Prawira I Putu Indra Permana I Wayan Dharma Satriawan I.Gst. Agung Bagus Mega Putra Ida Ayu Putu Wipra Astiti Ida Ayu Shinta Dewi Paramitha Imelda Rizky Purba Kadek Adi Praptha Kadek Suar Wibawa Lady Hasiani Siahaan Lie Jasa Linawati Linawati Made Bagus Winanda Radityatama Made Rama Pradipta Mentari Harmadya Nyoman Putra Sastra Putu A Bayupati Putu Eka Suputra Putu Wira Buana Setyo Hadi Kusumo Veranita Lamrotua Sihombing Yulius C. N. Bless Zebedeus Cheyso