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Asep Saepulrohman
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INDONESIA
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Published by Universitas Pakuan
ISSN : 16937554     EISSN : 26543990     DOI : 10.33751
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Scientific Journal of Computer and Mathematical Science (Jurnal Ilmiah Ilmu Komputer dan Matematika) is initiated and organized by Department of Computer Science, Faculty of Mathematics and Science, Pakuan University (Unpak), Bogor, Indonesia to accommodate the writing of research results for the academics and institutions other. Komputasi journal was originally launched in 1992, and published online since 2007 with ISSN version p-ISSN: 1693-7554 and version of the daring of e-ISSN: 2654-3990 in 2018 (SK No. 0005.26543990/JI.3.1/SK.ISSN/2018.10-15 October 2018 (starting Vol. 16, No. 1, January 2019). The journal is a publication media for original manuscripsts related information technology development and science written in Bahasa Indonesia which is published twice times a year (January and July).
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Articles 15 Documents
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Search results for , issue "Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika" : 15 Documents clear
PELUANG HUBUNGAN KARAKTERISTIK MAHASISWA BARU DENGAN MOTIVASINYA MASUK ILMU KOMPUTER Syarif Hidayatullah; Muhamad Saad Nurul Ishlah
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (280.421 KB) | DOI: 10.33751/komputasi.v17i2.2149

Abstract

Various motivational factors can influence prospective new students at Pakuan University (Unpak) when choosing a Computer Science Department as their majors. In order to be able to compete for better quality, Unpak is expected to be able to improve its excellent service, so that the needs and desires of the new students when deciding to join the Computer Science Department can be fulfilled. In this study, a survey of new students from the Department of Computer Science about their motivation to join the Department is conducted to find out what new students want when they decide to join. Furthermore, based on the survey, the Chi-Square method and Bayes method are used to get the probability of the relationship between the characteristics of new students and their motivation to go to the College when choosing the Department. The results show that there is a significant relationship between the characteristics of new students with motivation, which can be seen from the Gender, Regional Origin, Previous Information about Computer Science program and Computer Science Program Media including those that are combined in the above categories, except for Gender. It shows the greatest opportunity occurred in the characteristics of new students to the motivation of 1; 0.806; 0.750 and 0.742.
KAMUS DIGITAL TANAMAN OBAT MENGGUNAKAN ALGORITMA ROCCHIO BERBASIS MOBILE Arie Qur’ania; Triastinurmiatiningsih -; Nazar Muhamad Ikhbal
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.157 KB) | DOI: 10.33751/komputasi.v17i2.2145

Abstract

Digital dictionaries have been widely used to facilitate word processing and word search through digital media such as mobile phones. Society generally knows the efficacy and how to mix medicinal plants from the experience of previous parents or through books and writings. Searching through books or writings requires a short time compared to searching through digital media, one of which is a digital dictionary. The research aims to create a digital dictionary of mobile-based medicinal plants which has a search facility based on the words entered, for example, the contents of the medicinal plants. The digital dictionary application of medicinal plants uses a search method with the Rocchio algorithm with relevance feedback techniques to check the proximity of the query to the average document relevant to the level of similarity calculation through the stages of tokenizing, filtering, stemming, and Term Weighting with a total data of 200 medicinal plants.
IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI Nadya Febrianny Ulfha; Ruhul Amin
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.622 KB) | DOI: 10.33751/komputasi.v17i2.2150

Abstract

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.  
ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE Wahyu Supriyatin
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (438.096 KB) | DOI: 10.33751/komputasi.v17i2.2146

Abstract

Object tracking one of computer vision. Computer vision similar to human eye function. The difficulty is to detect presence an object and object tracking application made. Object tracking used in aircraft, track cars, human body detectors at airports, a regulator the number of vehicles pass and navigation tools on robots. This study is to identify objects that pass in frame. This research also count the number of objects that pass in one frame. Object tracking done by comparing two algorithms namely Horn-Schunck and Lucas-Kanade. Both algorithms tested using the Source Block Parameter and Function Block Parameter. The test carried out with video resolution 120x160 and the position camera is 2-4 m. The object tracking test is conducted in the duration of 110-120 seconds. Stages tracking object was thresholding, filtering and region successfully obtain object binary video. The Lucas-Kanade has faster in identifying objects compared to the Horn-Schunck algorithm.
IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI Nadya Febrianny Ulfha; Ruhul Amin
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.36 KB) | DOI: 10.33751/komputasi.v17i2.2156

Abstract

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.
KOMPRESI FILE MENGGUNAKAN ALGORITMA LEMPEL ZIV WELCH (LZW) Aries Suharso; Jejen Zaelani; Didi Juardi
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (969.729 KB) | DOI: 10.33751/komputasi.v17i2.2147

Abstract

In the field of information technology, data communication is closely related to file delivery. The size of the file is sometimes a constraint in the delivery process. Large files will take longer delivery times compared to files with smaller sizes. Therefore, to handle the problem, one of them by means of compression. This study uses an experimental method with a waterfall development model with analysis, design, coding, and testing. This application applies the Ziv Welch Lempel (LZW) algorithm. The Ziv Welch Lemp Algorithm (LZW) is included in the lossless compression technique, which is a compression technique that does not change the original data. The result of a compression assessment used the Lempel Ziv Welch (LZW) algorithm shows the average rate of compression ratio and for all types of text files by 51.04% with an average of 2.56 seconds, for an image file type of 37.26% with an average time of 0.44 seconds. Based on the average percentage of the compression ratio for all file types tested using the LZW algorithm (Lemp Ziv Welch) is 40.40% with an average time required is 1.81 seconds.
Cover Editorial Page Editorial Page
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1300.032 KB) | DOI: 10.33751/komputasi.v17i2.2157

Abstract

Hal Editorial
PERBANDINGAN KINERJA METODE PRA-PEMROSESAN DALAM PENGKLASIFIKASIAN OTOMATIS DOKUMEN PATEN Budi Nugroho; Asep Denih
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (280.07 KB) | DOI: 10.33751/komputasi.v17i2.2148

Abstract

This paper presents a performance analysis and comparison of several pre-processing methods used in automatic patent classification with graph kernels for Support Vector Machine (SVM). The pre-processing methods are based on the data transform techniques, namely data scaling, data centering, data standardization, data normalization, the Box-Cox transform and the Yeo-Johnson transform. The automatic patent classification is designed to classify an input of patent citation graphs into one of 10 possible classes of the International Patent Classification (IPC). The input is taken with various background conditions. The experiments showed that the best result is achieved when the pre-processing method is data normalization, achieving a classification accuracy of up to 85.33.15% for the KEHL and 93.80% for the KVHL. In contrast, for the KEHG, the preprocessing method application decreased the accuracy.
IMPLEMENTASI DATA MINING PENJUALAN OBAT DALAM MEMPREDIKSI STOK BARANG MENGGUNAKAN METODE ALGORITMA APRIORI Ruhul Amin
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v17i2.1679

Abstract

PT. Kimia Farma adalah suatu perusahaan yang bergerak dalam bidang industri farmasi Indonesia, Kimia Farma sangat diperhitungkan kiprahnya khususnya dalam pembangunan kesehatan masyarakat Indonesia. Dalam persaingan didunia bisnis, khususnya Apotek, para pengembang menemukan suatu strategi jitu yang dapat meningkatkan penjualan obat. Salah satu cara mengatasinya adalah dengan tetap tersediaannya berbagai jenis obat yang dibutuhkan oleh konsumen. Penerapan Algoritma Apriori dapat membantu dalam kandidat kombinasi item, jika memenuhi parameter support dan confidence maka hasil tersebut dapat membantu dalam pola pembelian obat.
ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE Wahyu Supriyatin
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v17i2.2002

Abstract

Computer vision same function as human eye, the ability to see or look objects passing by. Object tracking is one of computer vision. Object tracking aims is to recognize and identifying object pass and determine how many.This research was conducted by comparing the two algorithms in Optical Flow, the Horn-Schunck and the Lucas-Kanade algorithm. The test was carried out using two videos obtained from the Matlab library. The resolution of the video used in this study is same, 120x160. The camera used to pick up the objects in this study is placed in one position. The test is carried out using simulation parameters specified in each algorithm. Both algorithms successfully recognize and detect objects and can count how many objects are in a frame. In the same testing duration time simulation makes the Lucas-Kanade algorithm have a faster total record time than Horn-Schunck in recognizing and detecting of objects.

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