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All Journal JurTI (JURNAL TEKNOLOGI INFORMASI) CCIT (Creative Communication and Innovative Technology) Journal
Tutik Maryana
Universitas AMIKOM Yogyakarta
Computer Science & IT

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Comparison Analysis of Best First Search Algorithm with A * (star) in determining the closest route in the district Sleman Tutik Maryana; Ripto Sudiyarno; Kusrini Kusrini
CCIT Journal Vol 13 No 1 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1522.128 KB)

Abstract

There are various pathfinding algorithms that have advantages and disadvantages of each algorithm. The purpose of this study is to compare the best-first search pathfinding greedy algorithm with A * (Star) in terms of determining the shortest route in a tent search. The method used in this study is an analytical method for analyzing what algorithms can be applied in track search. Then, the method continued with the design method for the best-first search and A * greedy algorithm, the user interface for the algorithm testing application. The next method is the implementation method, which is the best-first greedy algarithm search and A * implemented in the algorithm testing application. The last method is the method of testing algorithms that will be compared. The conclusions will be drawn from the results of comparison algorithms. The result of this study is the acquisition of a distance comparison between thegreedy best-first search algorithm with A *. The conclusion of this study is that the A * algorithm is able to provide the shortest and optimal route results compared to the BFS algorithm.
Analisys Of Demand and Optimization Of Medicine Prediction Using ABC Analysis and SVR Method In The “MORBIS” Aplication Tutik Maryana; Kusrini Kusrini; Hanif Al Fatta
CCIT (Creative Communication and Innovative Technology) Journal Vol 13 No 2 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.078 KB) | DOI: 10.33050/ccit.v13i2.1098

Abstract

The problem that occurs in hospitals regarding the processing of drug supplies is about the condition of out of stock medicines because hospitals spend around 33% of the total investment in one year only for the investment costs of drugs. To deal with the above problems the hospital must have good logistics management, one way of managing it is by doing good planning. In this research, the writer will use ABC Analysis and Support Vector Regression (SVR) algorithm. For the use of these methods, the following ABC Analysis will be used for the drug classification process, namely by dividing the torch into three main groups based on interests, namely groups A, B and C. Henceforth, the writer will use the SVR motedo to calculate drug predictions. The results that the authors get from this study are ABC analyys classify drugs. Into three groups namely group A with a total of 276 items with a percentage of 22.96% of the total number of items, group B with a total of 396 items with a percentage of 33.11% and C with a total of 528 with a percentage of 43.94% with a total of 1202 drug items. Prediction testing is done by taking a sample of five drugs derived from group classification. The SVR calculation process is done by comparing linear scaling and z normalization preprocessing methods. The result of this research is that MAPE shows that preprocessing with linear scaling produces a better value than compared to z nomrlization and calculation with ABC analysis.
ANALISIS PERBANDINGAN PREDISKSI OBAT DENGAN MENGGUNAKAN METODE ABC ANALISYS DAN SVR PADA APLIKASI “MORBIS” Tutik Maryana; Kusrini Kusrini; Hanif Al Fatta
(JurTI) Jurnal Teknologi Informasi Vol 3, No 2 (2019): DESEMBER 2019
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v3i2.1016

Abstract

Permasalahan rumah sakit mengenai pengolahan persediaan obat adalah kondisi obat yang habis, dikarenakan rumah sakit dalam satu tahun mengeluarkan 33% dari biaya investasi untuk investasi obat. Untuk mengtasi permasalahan diatas rumah sakit harus memiliki pengeloaan logistic dengan baik, cara pengelolaan adalah dengan melakukan perencanaan yang baik. Penulis akan memakai algoritma ABC Analysis dan SVR. ABC Analysis akan digunakan untuk proses klasifikasi obat yaitu dengan cara membagi obat manjadi tiga kelompok utama berdasarkan kepentingan yaitu kelompok A, B dan C. Penulis akan menggunakan metodo SVR untuk menghitung prediksi obat. Hasil penelitian ini adalah ABC analisys dapat membagi  obat. Menjadi tiga bagian  yaitu kelompo A 276  item dengan presentase 22,96% dari jumlah item keseluruhan, kelompok B sejumlah 396 item dengan presentase 33,11% dan C sejumlah 528 dengan presenrase 43,94% dengan kesluruhan obat adlah 1202 item obat. Pengujian prediksi dilakukan dengan cara mengambil sample lima obat dari hasil klasifikasi. Proses perhitungan SVR adalah membandingkan metode preprocessing linier scaling dan z normalization. Hasil dari penelitian tersebut adalah MAPE menunjukan bahwa  dengan menambahkan preprocessing dengan linier scaling dapat membuat proses SVR lebih optimal dari pada menggunakan z nomrlization dan perhitungan dengan klasifikasi ABC analisys.
IMPLEMENTASI ALGORITMA APRIORI DAN FORWARD CHAINING UNTUK MENENTUKAN MAKANAN YANG TEPAT PADA PENDERITA DIABETES Agatha Deolika; Victor Saputra Ginting; Tutik Maryana; Ripto Sudiyarno; Kusrini Kusrini
(JurTI) Jurnal Teknologi Informasi Vol 3, No 2 (2019): DESEMBER 2019
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.566 KB) | DOI: 10.36294/jurti.v3i2.1080

Abstract

Abstract - The high number of diabetes patients in Indonesia is increasing. Some of the factors that cause diabetes in Indonesia include family history, obesity, aging, lack of activity and diet. Too much food containing sugar is also one of the emergences of diabetes. Most diabetics often have complications of diabetes disease and that is based on the criteria of a patient. Therefore, it is necessary to conduct research on the rule or dependence of the disease based on patient criteria and determination of diet for diabetics. In this study using a combination of a priori methods to determine the rule of disease and forward chaining to determine patient food. Based on the research tests conducted, it can be concluded that the combination of 2 methods produces a pretty good which in the a priori method uses a minimum value of support 2 and a minimum of confidence 10 and produces 10 rules with 3 combinations of items, as well as forward chaining tests that use 30 data produces an accuracy of 83 %.Keywords - Apriori Algorithm, Forward Chaining, Diabetes Abstrak - Tingginya jumlah pasien diabetes yang  terjadi di Indonesia semakin meningkat. Beberapa faktor penyebab penyakit diabetes di Indonesia anatara lain riwayat keluarga, obesitas, pertambahan usia, kurangnya aktivitas dan pola makan. Terlalu banyak makan yang mengandung gula juga merupakan salah satu munculnya penyakit diabetes. Kebanyakan penderita diabetes sering sekali terjadinya kompliksi penyait diabetes dan itu berdasarkan kreteria seorang pasien. Maka dari itu perlu dilakukan penelitian mengenai rule atau keterhungungan penyakit berdasarkan kriteria pasien dan penentuan pola makan bagi penderita penyakit diabetes. Pada penelitian ini menggunakan kombinasi metode apriori untuk menetukan rule penyakit dan forward chainning untuk mentukan makanan pasien. Berdasarkan pada pengujian penelitian yang dilakukan dapat diambil kesimpulan Kombinasi 2 metode ini menghasilkan cukup bagus yang mana pada metode apriori menggunakan nilai minimal support 2 dan minimal confidence 10 dan menghasilkan 10 rule dengan 3 kombinasi item, serta pengujian forward chaining yang menggunakan 30 data menghasilkan akurasi 83% .Kata Kunci - Algoritma Apriori, Forward Chaining, Diabetes
Co-Authors Agatha Deolika Hanif Al Fatta Kusrini Kusrini Ripto Sudiyarno Victor Saputra Ginting