cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Saepul Bahri
Contact Email
saeful.sel@bsi.ac.id
Phone
+6281210914656
Journal Mail Official
jurnal.larik@bsi.ac.id
Editorial Address
Jl. Raya Cemerlang No.8, Sukakarya, Kec. Warudoyong, Kota Sukabumi, Jawa Barat 43135
Location
Kota adm. jakarta barat,
Dki jakarta
INDONESIA
Ladang Artikel Ilmu Komputer
Published by Universitas Bina Sarana Informatika
ISSN : -     EISSN : 28081730     DOI : https://doi.org/10.31294/larik.v2i2
Core Subject : Science,
Computer Science & IT
Jurnal Larik : Ladang Artikel Ilmu Komputer adalah jurnal yang berisi artikel penelitian dan studi ilmiah dalam bidang ilmu komputer dan Informatika khususnya sistem otomasi, kecerdasan buatan, pembelajaran mesin dan penambangan data.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 27 Documents
 1   2   3 
Pengembangan Sistem Forecasting Penjualan Pada Aplikasi Point of Sales Menggunakan Metode Trend Least Square Ita Yulianti; Ami Rahmawati
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 1 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (620.371 KB) | DOI: 10.31294/larik.v2i1.1153

Abstract

The use of cash register as evidence of technology utilization in business activities is not enough to help the sustainability of a business, because it has not fully controlled data collection, especially in terms of information about the development of income and inventory planning. Therefore, for the sake of the business sustainability, the strategy is needed, one of which is to build a system that can manage the transaction process equipped with sales forecasting features that can display product predictions according to market needs. To build a system of data collection techniques, the waterfall system development model and the implementation of the Least Square trend method. Of the three research methods that are applied, the contribution produced is in the form of a desktop-based Point of Sales (POS) system with Java programming languages equipped with additional features, namely sales prediction. Based on the application of the system it is proven that the use of the Trend Least Square method is very appropriate to use because it can display the prediction results of sales for the coming period with predictive error rates of only 0.0067% and this system also helps optimize service activities to customers and can help sales management in terms of Provision of products.
Pencarian Criteria Splitting Terbaik Pada Algoritma C4.5 Untuk Mengukur Pemilihan Pembelajaran Pada Era Pendemi Covid-19 Siti Masripah; Dewi Ayu Nurwulandari; Rizal Amegia Saputra
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 1 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.664 KB) | DOI: 10.31294/larik.v2i1.1292

Abstract

The condition of the 2022 pandemic is still ongoing and has entered the 2nd year of the learning system that is still not 100% offline and is still being done online. The online learning system certainly makes parents, educators and students have to pay extra and extra understanding because not all of them can overcome these two things. Classification in determining the choice of learning becomes very important because online learning reaps the pros and cons in the community. In this study, the dataset was obtained from the results of a survey of parents, educators, students and students, and as many as 283 respondents had been collected to measure learning choices in the Covid-19 Pandemic Era. Data processing uses the Rapid miner application by applying the C4.5 Data Mining Classification Algorithm method, in the experimental process the split criteria comparison process is carried out on the C4.5 algorithm, namely Information Gain, Gini Index and Gain Ratio. The two highest accuracy values obtained are 85.88% for the Gain Ratio and Information Gain, while the Gini Index is 8.24%, for the AUC value the highest value is 0.80 in the Gain Ratio, followed by the Information Gain of 0.783 and the Gini Index of 0.784. Based on the comparison results, the Split gain ratio criterion is included in the Good classification category, because it has a value between 0.80 - 0.90.
Klasifikasi Data Penjualan Mengunakan Algoritma K-Means Dan Analytic Hierarchy Process Yosep Nuryaman; Bibit Sudarsono; Ummi Faddillah; Ayuni Asistyasari
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 1 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.877 KB) | DOI: 10.31294/larik.v2i1.1371

Abstract

With the Covid 19 which has hit the last few years, sales in various fields have a negative impact, including Supermarket X, which has experienced a decline in various branches in various regions. For consideration, they evaluate the sales of these branches. By classifying the existing sales data, it is hoped that they will be able to see which self-service branch group x is not doing well, which one is already good. However, it is necessary to have a good classification technique so that evaluations are carried out based on good calculation results. Therefore, the author tries to use the K-Mean Algorithm and the AHP Algorithm to classify the existing sales data. The K-Mean Algorithm and the AHP Algorithm are algorithms that are able to cluster a set of data. By clustering the stores based on the proximity of the sales results for the last 2 years which has gone up and down using these 2 algorithms, we will be able to see which stores are classified as good and which are not. Based on the comparison results from the calculation results, it was found that the best results were using the K-Mean algorithm with k2 in the 3rd literacy with a ratio of 0.04926
Analisis Perbandingan Efektifitas White-Box Testing dan Black-Box Testing Dede Wintana; Denny Pribadi; Moh Yusup Nurhadi
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 1 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (647.37 KB) | DOI: 10.31294/larik.v2i1.1382

Abstract

This research, will descibe about comparison of black-box testing with manual testing. Researcher will compare how efficient is white-box testing and manual testing. In usage which one is better and which one is worse. This research will compare them by data to show how efficient they ares. The research also show the chart of white-box and manual testing comparison. The complete result will described as journal seen describing below.
Kombinasi Tomek-Link Dan Smote Untuk Mengatasi Ketidakseimbangan Kelas Pada Credit Card Fraud Wahyu Nugraha; Deni Risdiansyah; Deasy Purwaningtias; Taufik Hidayatulloh; Satia Suhada
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.131 KB) | DOI: 10.31294/larik.v2i2.1789

Abstract

Increasing online trading activities or e-commerce has become a trend today. As a result the most common crime is credit card fraud or carding. There are approximately 1,000 cases of fraud in one million transactions so that data is collected in the form of datasets of credit card fraud risk. In some cases, minority classes are more important to identify than the majority class as in the case of credit card transactions. In this study to deal with the problem of class imbalances on credit card fraud risk datasets, the proposed resampling method is the Tomek-Link and SMOT data level with the C5.0 classification model. This research was conducted to improve the accuracy of AUC in the C5.0 classification algorithm model. The results showed that the proposed method was able to increase the AUC value of 0.134 compared to without the resampling method.
Klasifikasi Kebutuhan Produk Ecoprint Menggunakan Metode Clustering K-Means Lestari Yusuf; Sakti Sudirman
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (673.986 KB) | DOI: 10.31294/larik.v2i2.1797

Abstract

Mencari tahu tingkat minat tertinggi konsumen produk ecoprint berdasarkan data daerah, data usia, data jenis kelamin, dan data jenis produk. Data jenis produk antara lain sepatu sport, sepatu boots, sepatu flat pria, sepatu falt wanita, dan tas. Dalam mencari tahu tingkat peminat tertinggi dari pembelian produk, penelitian ini menerapkan data mining dengan metode algoritma Clustering K- Means dan implementasi data menggunakan aplikasi Rapidminer. Pada hasil akhir penelitian dengan menerapkan metode algoritma Clustering K-Means, cluster dikelompokkan menjadi 3 yaitu cluster 1 berjumlah 73 data, cluster 2 berjumlah 15 data, dan cluster 3 berjumlah 12 data. Dari cluster yang didapat menghasilkan 3 kategori peminatan yaitu sangat diminati, diminati, kurang diminati. Produk yang sangat diminati konsumen terbanyak adalah sepatu sport dan sepatu flat wanita kemudian produk tas dan sepatu flat pria dan yang terendah adalah produk sepatu boots. Produk ini sangat diminati oleh kalangan perempuan dan kurang diminati oleh kalangan laki-laki. Dengan rentan usia konsumen yang sangat berminat yaitu kalangan usia 25 sampai 50 tahun, rentan usia yang kurang berminat kalangan usia 18-25 dan 50 keatas. Asal daerah konsumen yang sangat berminat yaitu daerah Pulau Jawa, Kota Jakarta, dan sekitarnya, sedangkan asal daerah konsumen yang kurang berminat yaitu Sumatera
Perancangan Program Absensi Kehadiran Siswa Berbasis Web Devy Ferdiansyah; Nur Syafitri
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.238 KB) | DOI: 10.31294/larik.v2i2.1815

Abstract

Absensi merupakan hal yang wajib dilakukan untuk siswa. Dalam melakukan absensi masih menggunakan cara manual. Oleh karena itu, diperlukan suatu sistem absensi siswa yang dapat melakukan pendataan, dan pengelolaan data agar dapat dilakukan secara cepat, efisien, dan akurat. Pembuatan sistem absensi siswa ini dilakukan dengan cara pengumpulan data, observasi. Sistem ini dibuat dengan menggunakan Bahasa pemrograman PHP dan MYSQL untuk pengelolaan database. Sebagai hasil dari tugas akhir ini adalah dibuatnya website Sistem Informasi Absensi siswa. Data siswa, data guru, jadwal pelajaran, data absensi, absensi menggunakan website siswa. Dengan adanya website ini, diharapkan proses absensi akan lebih efisien dan dapat dipantau dengan mudah oleh guru dan oleh admin..
Information Retrieval Pemetaan Peta Jalan Penelitian Perguruan Tinggi Berbasis Dokumen Publikasi Ilmiah Dosen Agung Wibowo; Rusda Wajhillah
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.188 KB) | DOI: 10.31294/larik.v2i2.1816

Abstract

The quality of research needs to be directed and classified for improvement. A college roadmap must accordance interest and expertise from it lecturers. Therefore, be the duty of every college to create a strategic plan and pre-eminent research. Faculty of information technology in most all College has produced many scientific publications. Publication document of scientific papers is one example of unstructured documents. Its contents form of writing style, mostly defined by the author language. Generally, the document title only determined the maximum number of words. The main objective of the information retrieval system is to determine the documents keywords from the query provided by the user in a group of documents. TF/IDF Algorithm (Term Frequency – Inversed Document Frequency) and the Vector Space Model algorithm is several methods of the algorithm that can utilize on text mining in analysing phases as options document classification determination-based solutions words that often appear on the document title. This paper can help decision makers to determine, assess, adapt research roadmap to College. The depiction of a tree model using long-term roadmap makes it easier to read and understand.
Algoritma C4.5 Untuk Menentukan Kelayakan Pemberian Kredit (Studi kasus: Bank Mandiri Taspen Kantor Kas Sukabumi) Taufik Hidayatulloh; Anisa Fajria; Rida Nutria Lestari; Neng Sella Zakiatun Nufus
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 2 No 2 (2022): Desember 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (826.731 KB) | DOI: 10.31294/larik.v2i2.1836

Abstract

Menurut UU No.10 tahun 1998 menyatakan bahwa kredit adalah penyediaan uang atau, berdasarkan persetujuan atau kesepakatan pinjam meminjam antar bank dengan pihak lain yang mewajibkan pihak peminjam untuk melunasi hutangnya setelah jangka waktu tertentu dengan pemberian bunga. Kelancaran dalam pembayaran kredit sangat berpengaruh terhadap profit perusahaan atau perbankan yang merupakan sumber penghasilan utama yang dimiliki perusahaan. Proses pemberian kredit kepada konsumen/nasabah adalah hal yang tidak mudah, karena harus mempertimbangkan beberapa faktor. Maka dari itu tujuan penelitian ini adalah membuat sistem penunjang keputusan dalam menentukan factor kriteria konsumen dalam melakukan kredit. Studi kasus dilakukan di Bank Mandiri Taspen Sukabumi. Permasalahan pada penelitian ini adalah sering terjadi pembayaran kredit macet oleh nasabah, maka dari itu penelitian ini menggunakan metode Algoritma C4.5 decision tree digunakan untuk memprediksi macet atau tidaknya pembayaran kredit oleh nasabah. Penelitian ini menggunakan data set yang memiliki kriteria penentu, yaitu hasil Approve dan Reject, status pegawai, jaminan, jenis kredit, usia, gaji, persyaratan, kesehatan, dan SIUP. Dari hasil penelitian yang menggunakan 258 data private nasabah bulan November dan Desember 2021 di Bank Mandiri Taspen Kantor Kas Sukabumi menghasilkan evaluasi bahwa Algoritma C4.5 akurat diterapkan untuk memprediksi macet atau tidaknya pembayaran kartu kredit nasabah dengan tingkat akurasi sebesar 93,75% untuk data training 0.9 dan testing 0.1, selain itu didapatkan tingkat akurasi 96,77% untuk data training 0.8 dan testing 0.2.
Penerapan Metode Clustering Dalam Upaya Pencegahan Penyakit Demam Berdarah Menggunakan Algoritma K-Means (Studi Kasus: Kota Tasikmalaya) Muhamad Rivalda
Ladang Artikel Ilmu Komputer Vol 3 No 1 (2023): Juli 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dengue fever is a contagious disease transmitted by the Aedes Aegypti mosquito, and this disease occurs continuously throughout the year, causing outbreaks and deaths. In Indonesia, public awareness in maintaining cleanliness and lack of anticipation of people infected with Dengue Fever, so Dengue Fever is a disease easily infected for all ages. The research methodology used in this study used the clustering method. The goal is to cluster and evaluate the k-means algorithm model to determine the algorithm's accuracy in classifying Dengue Fever disease. K-Means Clustering, K, which means a constant for the desired number of clusters, while Means which means the average of the data groups in the cluster. Therefore, research using the K-Means Algorithm will group the areas in Tasikmalaya City according to the rate of occurrence of dengue cases so that they are precisely and quickly targeted in efforts to prevent Dengue Fever. The formula used in the K-Means algorithm has four stages, namely: Determining the number of clusters, calculating distances, grouping data, and calculating the center of the cluster. The benefits of this research are that it can speed up the process of prevention efforts in Dengue Fever, know efforts to prevent Dengue fever quickly and precisely, clustering systems for prevention efforts and can reduce mortality, and add insight for readers who want to learn about clustering and K-Means algorithms.

Page 2 of 3 | Total Record : 27

 1   2   3 

Filter by Year

2021 2023


Reset
Filter By Issues
All Issue Vol. 3 No. 2 (2023): Desember 2023 Vol 3 No 2 (2023): Desember 2023 Vol 3 No 1 (2023): Juli 2023 Vol 2 No 2 (2022): Desember 2022 Vol 2 No 1 (2022): Juli 2022 Vol 1 No 2 (2021): Desember 2021 Vol 1 No 1 (2021): Juli 2021