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All Journal Jurnal Pekommas Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MITRA: Jurnal Pemberdayaan Masyarakat Data Science: Journal of Computing and Applied Informatics
Ika Nurlaili Isnainiyah
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Public Health

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Data Warehouse Development for UPN “Veteran” Jakarta Library (Perancangan Data Warehouse pada Perpustakaan UPN “Veteran” Jakarta) Henki Bayu Seta; Theresia Wati; Ika Nurlaili Isnainiyah
Jurnal Pekommas Vol 2, No 2 (2017): Oktober 2017
Publisher : BBPSDMP KOMINFO MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2017.2020206

Abstract

This article presents the design and development of data warehouse on UPN "Veteran" Jakarta campus library. The method was done by conducting observation and analysis of current system, continued by applying the nine steps (Nine-Step Methodology) to design snowflake schema. The results consist of data warehouse that provides global, relevant, and integrated information that can be seen from various points of view and is expected to support the decision making processes on UPN "Veteran" Jakarta campus library.Artikel ini menyajikan hasil dari proses desain dan pengembangan data warehouse untuk perpustakaan kampus Universitas Pembangunan Nasional “Veteran” Jakarta. Metode analisis dilakukan melalui observasi terhadap kondisi eksisting sistem, kemudian dilanjutkan dengan mengimplementasikan Nine-Step Methodology untuk mendesain skema Snowflake. Hasil penelitian ini adalah sebuah data warehouse yang menyajikan informasi yang menyeluruh, relevan dan terintegrasi dan dapat ditinjau dari berbagai sudut pandang, yang diharapkan dapat bermanfaat untuk menunjang proses pengambilan keputusan oleh pihak perpustakaan kampus Universitas Pembangunan Nasional “Veteran” Jakarta.
Analisis Manajemen Risiko Keamanan Data Sistem Informasi (Studi Kasus: RSUD XYZ) Nurhafifah Matondang; Ika Nurlaili Isnainiyah; Anita Muliawatic
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (326.756 KB) | DOI: 10.29207/resti.v2i1.96

Abstract

This paper describes the implementation of OCTAVE Allegro method to evaluate several aspects related to information security risks of the information technology applied in a health institution. The evaluation was conducted at RSUD XYZ and referred to five impact areas: reputation and customer confidence, finance, productivity, security and health, and also penalties and punishment. The results show that the impact area of reputation and customer confidence has the highest risk assessment result among other areas. The overall result and discussion presented in this paper certainly does not violate the code of ethics for RSUD XYZ.
Education of Internet Marketing for Traditional Craftsmen of Baduy Suharyati Suharyati; Ika Nurlaili Isnainiyah
MITRA: Jurnal Pemberdayaan Masyarakat Vol 3 No 2 (2019): MITRA: Jurnal Pemberdayaan Masyarakat
Publisher : Institute for Research and Community Services

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/mitra.v3i2.843

Abstract

Regulation of the Minister of Home Affairs of the Republic of Indonesia No.1 of 2013 explain that the Indonesian government continues to strive to alleviate poverty and improve the welfare of the population through community empowerment activities. The 4.0 industrial revolution era triggered the digital technology trend, especially the internet to support product marketing, e.g. by reducing marketing costs and labor costs. However, the lack of technological knowledge is undeniable on a number of Indonesian population, such as MSME entrepreneurs of Outer Baduy traditional craftsmen in the Kanekes village. Government support is needed through ongoing activities with higher education institutions to provide education and assistance on product marketing (internet marketing). Community service held by lecturers from the Faculty of Economics, UPN Veteran Jakarta, aims to empower and raise the knowledge of the Outer Baduy community regarding internet marketing education and practice using social media. The approach used in this activity consists of talks, module creation, tutorials and practice on product marketing strategies using social media such as Instagram and Facebook. Based on the questionnaire analysis results, it is identified that the understanding of social media features for the promotion, networking and marketing expansion from participants has reached 68,57%. Keywords: internet marketing; social media; Instagram; Baduy
A Web-Based Diabetes Prediction Application Using XGBoost Algorithm Herlambang Dwi Prasetyo; Pandu Ananto Hogantara; Ika Nurlaili Isnainiyah
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 2 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i2-6290

Abstract

One of the diseases that is generally characterized by symptoms of an increase in glucose levels in the blood and is one of the body diseases classified as chronic is diabetes. Diabetes suffered by a person from time to time can cause serious damage to other organs such as blood vessels, kidneys, heart and nerves. Machine learning provides various data mining algorithms that can be used to assist medical experts. The accuracy of machine learning algorithms is a measure of the effectiveness of decision support systems. Prediction of diabetes can be seen from the patient's medical record data, therefore the author wants to create a diabetes prediction system independently through a website-based application system. This application system will be combined with data observation, namely the science of data mining using the XGBoost algorithm. The dataset is divided into training data by 80% and testing data by 20%. Before the data modeling was carried out, we carried out various parameter setting scenarios with the hope of evaluating and evaluating the implementation to be applied, the parameters we adjusted were colsample_bytree, gamma, learning_rate, max_depth, n_estimators, reg_alpha, reg_lambda, and subsample. After sharing the data and tuning parameters, the resulting model by applying the XGBoost algorithm has an accuracy of 74.67%, the resulting precision value is 57.40%, the resulting recall value is 65.94%, the resulting specificity value is 78, 50%.
MobileNets-V1 Architecture for Web Based Fish Image Classification Herlambang Duwi Prasetyo; Pandu Ananto Hogantara; Ika Nurlaili Isnainiyah
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 2 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i2-6291

Abstract

Recently, the research study about fish identification become a very challenging to researchers. Climate and environmental changes have a major impact on fish species and their environment. To identify fish using manual process is time consuming and need effort to gather samples in different environment. The identification of fish species is performed by using feature extraction and a series of features. Generally, the characteristic is divided into two groups namely general characteristics and anatomical features. General characteristics is characteristic that can be seen directly without the aid of tools. The characteristics include color, texture, and fiber direction. Although, manual is performed by expert but is possible that identification is not accurate. Therefore, to overcome the problem, we create a web-based application for identifying fish by using image as input. We use 10 class data with 300 images for each class. Then, we split into training and testing with 80:20 ratio. The application was developed by using the MobileNets- V1 model. The proposed method has accuracy on 89 %, that obtain from training score is 91.04%, validation is 88,96%. This score is higher than other methods that used in this application. Total time for computation process is about 127 minutes.
Co-Authors Anita Muliawati Henki Bayu Seta Herlambang Duwi Prasetyo Herlambang Dwi Prasetyo Iin Ernawati Matondang, Nurhafifah Pandu Ananto Hogantara Suharyati Suharyati Theresiawati Widiastiwi, Yuni Zaidiah, Ati