Garuda - Garba Rujukan Digital

p-Index From 2019 - 2024

1.564

P-Index

This Author published in this journals

All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Perfecting a Video Game with Game Metrics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Pekommas Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Seminar Nasional Informatika (SEMNASIF) Edu Komputika Journal Journal of Information Technology and Computer Science IJID (International Journal on Informatics for Development) Jurnal Akuntansi dan Bisnis IJITEE (International Journal of Information Technology and Electrical Engineering) Journal of Computer System and Informatics (JoSYC) Water Circulation Monitoring System in The Vanname Shrimp Cultivation based on Internet of Thing Jurnal Nasional Teknik Elektro dan Teknologi Informasi Proceeding ISETH (International Summit on Science, Technology, and Humanity) Electrician : Jurnal Rekayasa dan Teknologi Elektro

Indriana Hidayah

Department Of Electrical Engineering And Information Technology, Faculty Of Engineering, Universitas Gadjah Mada, Bulaksumur, Yogyakarta 55281,

Author-ID : 2453157

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Social Sciences Other

Published : 24 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3

Sistem Pakar Berbasis Aturan untuk Otomatisasi Penyusunan Angka Kredit Instruktur Berbasis Web Cahyani Windarto; Hanung Adi Nugroho; Indriana Hidayah
Jurnal Pekommas Vol 17, No 2 (2014): Agustus 2014
Publisher : BBPSDMP KOMINFO MAKASSAR

Efisiensi penyelenggaraan birokrasi telah menjadi salah satu parameter penilaian kinerja kelembagaan. Intelligent Penyusunan Angka Kredit (iPAK) merupakan sistem cerdas dalam penyusunan angka kredit instruktur yang diaplikasikan dengan pendekatan rule based untuk mendapatkan angka kredit yang mencerminkan prestasi kerja instruktur. Aturan disusun berdasarkan persyaratan angka kredit yang tercantum dalam peraturan perundangan dan pengalaman praktek penyusunan angka kredit. Kegiatan administrasi dalam penyusunan angka kredit berupa pengumpulan dokumen memberikan peluang mengoptimalkan penggunaan kertas dengan penerapan metoda six sigma untuk menghilangkan pemborosan dan kesalahan pencetakan. Prototipe aplikasi iPAK (Intelligent Penyusunan Angka Kredit) dibangun dengan bahasa pemrograman PHP, database MySQL dan CSS untuk tampilan antar muka. Implementasi otomatisasi penyusunan angka kredit akan meningkatkan sigma level dari 2,81 menjadi 4,53 yang artinya kontrol dan penggunaan teknologi telah meningkat.

Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining Saucha Diwandari; Adhistya Erna Permanasari; Indriana Hidayah
Journal of ICT Research and Applications Vol. 12 No. 1 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.1.4

Visitor interaction with e-commerce websites generates large amounts of clickstream data stored in web access logs. From a business standpoint, clickstream data can be used as a means of finding information on user interest. In this paper, the authors propose a method to find user interest in products offered on e-commerce websites based on web usage mining of clickstream data. In this study, user interest was investigated using the PIE approach coupled with clustering and classification techniques. The experimental results showed that the method is able to assist in analyzing visitor behavior and user interest in e-commerce products by identifying those products that prompt visitor interest.

Sistem Pakar Deteksi Minat Untuk Pemilihan Jenjang Karir Menggunakan Metode Certainty Factor M. Tsana'uddin Farid; Hanung Adi Nugroho; Indriana Hidayah
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

Interests have an important role in the career path because interests will affect a person's performance, passion and abilities during their educational studies. The problem that occurs is that based on a survey conducted by the Indonesian Career Center Network, it was found that 87% of students in Indonesia felt that they were wrong in deciding which major they were taking. This problem is because the majors they take do not match their interests. This problem can be prevented by detecting interest early on so that career paths can be planned appropriately. This study aims to provide a solution to this problem by building an interest detection expert system to support career path selection. Certainty Factor methods are used in determining the output of the expert system to be built with the adaptation of the interest test tool, called RIASEC. Testing is done by comparing the system output results with expert consultation. The test results showed that the expert detection system was able to answer the interest with an accuracy of 93%. Based on the test results, the solution in interest detection expert system could be used as a reference assessment in planning career path choices

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2014.1170202

Tinjauan Pustaka Sistematis: Implementasi Metode Deep Learning pada Prediksi Kinerja Murid Muhammad Haris Diponegoro; Sri Suning Kusumawardani; Indriana Hidayah
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The use of machine learning, which is one of the implementations in the field of artificial intelligence, has penetrated into various fields, including education. By using a combination of machine learning techniques, statistics, and databases, educational data mining can be carried out to find out the patterns that exist in a particular dataset. One use of educational data mining is to predict student performance. The results of student performance predictions can be used as an instrument for monitoring and evaluating the learning process so that it can help determine further steps in order to improve the learning process. This study aims to determine the state of the art implementation of deep learning which is part of machine learning in the context of educational data mining, especially regarding student performance predictions. In this study, a systematic literature review is presented to determine the variation of deep learning techniques or algorithms used and their performance. Twenty scientific publications were found and the average performance achieved in making predictions was 89.85%. The majority of the techniques used are Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) with demographic, behavioral, and academic data features.

Regresi Linear untuk Mengurangi Bias Sistem Penilaian Uraian Singkat Silmi Fauziati; Adhistya Erna Permanasari; Indriana Hidayah; Eko Wahyu Nugroho; Bobby Rian Dewangga
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 3: Agustus 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

This study is aimed to improve the performance of a short essay scoring system. The improvement is executed by integrating a simple linear regression to the output of a combined cosine similarity method (with weighted term frequency using Term Frequency –Inverse Document Frequency (TF-IDF) method) and term-matching mechanism.The linear regression is conducted by taking the short essay score (resulting from the combined cosine similarity and termmatching) as a regressor variable. In order to demonstrate the effectivenessof the proposedscoring system, the performance of the scoring system is measured relative to manual scoring by a lecturer.The results show that prior to linear regression, the scoring system tends to give higher score(biased score) compared to the manual score,which is problematic. The following scoring system with linear regression tackles this problem as the scoring bias is significantly reduced, that is, no tendency to givehigher or less scorecompared to the manual score.That the scoring bias is significantly reduced using a simple approach, linear regression,is expected to contribute in the acceleration of implementingautomatedessay scoring system on online learning technologiessuch as e-learning.

Metode Imputasi pada Data Debit Daerah Aliran Sungai Opak, Provinsi DI Yogyakarta Fahmi Dhimas Irnawan; Indriana Hidayah; Lukito Edi Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 4: November 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The data availability of water resources in Indonesia has several complex problems related to the perfection of data. The problems taking place when collecting data in several Indonesian agencies are the accuracy and completeness of the data. There are several methods that can be used to handle missing value imputation, such as k-Nearest Neighbors Imputation (k-NNi) and Multivariate Imputation by Chained Equation (MICE). This study seeks to compare and find the most appropriate method using the Opak watershed dataset in Special Region of Yogyakarta. The characteristics of the Opak watershed lies in its fan shape that provides a lower concentration-time and produces a higher flow. The results of the statistical validation comparison showed that the most consistent average value of RMSE and MAE was the k-NNi method with a value of k = 28. As for the comparison of R-Squared values, the k-NNi method with a value of k = 28 obtained the best average value with 80%, followed by the k-NNi method of k = 7 as the default k value with a percentage of 73%. Among the applied methods, the MICE comparison method obtained the lowest average percentage value with 63%.

Pengukuran Kepuasan Pengguna E-Learning Menggunakan Metode Evaluasi Heuristik dan System Usability Scale Emi Iryanti; La Ode Mohamad Zulfiqar; Sri Suning Kusumawardani; Indriana Hidayah
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 3: Juni 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022924631

Pandemik COVID-19 yang terjadi saat ini mempengaruhi banyak aspek kehidupan termasuk pendidikan, dimana pembelajaran dilakukan dari rumah untuk mengurangi resiko penularan virus corona dengan menerapkan e-learning. Hal ini yang membuat implementasi e-learning harus baik, oleh karenanya harus dilakukan evaluasi agar e-learning mudah digunakan. Salah satu aspek penting yang harus dievaluasi yakni dari sisi usability-nya dimana dapat diketahui kepuasan pengguna dari sisi “kebergunaan”nya. Penelitian ini menggunakan dua metode evaluasi usability yaitu System Usability Scale (SUS) dan evaluasi heuristik (HE) digunakan untuk hal ini. Penggunaan kedua metode ini dilakukan untuk mendapatkan hasil evaluasi yang lebih mendalam agar dapat dilakukan perbaikan oleh pihak terkait. Dalam evaluasi usability menggunakan HE, evaluator yang dipilih adalah lima user expert yang ahli dalam bidang usability (tiga orang) ahli dalam bidang IT dan pengembangan pembelajaran (dua orang), sedangkan lingkup evaluasi pada penelitian ini yaitu proses login, edit profile, organisasi perkuliahan, dan aktivitas perkuliahan. Sedangkan pada evaluasi menggunakan kuesioner SUS diperoleh skor 63,3 (grade C-) dengan 162 responden, dengan hasil uji realibitas sebesar 0,818 dan uji validitas semua item pertanyaan di atas 0,129 yang berarti bersifat realible dan valid. Hasil evaluasi usability menggunakan HE, didapatkan bahwa terdapat satu prinsip yang dianggap sebagai permasalahan mayor oleh user expert yaitu prinsip user control and freedom, dimana sistem (e-learning) tidak memfasilitasi fungsi undo dan redo yang menyebabkan pengguna kebingungan apabila dengan sengaja/tidak memilih menu yang tidak dikehendaki. AbstractThe COVID-19 pandemic affects many aspects including education, where learning is carried out from home to reduce the risk of coronavirus transmission by implementing e-learning. One important aspect that must be evaluated is from the usability side, where we can find out the user satisfaction from the "usability" side. This study uses two usability evaluation methods, namely the System Usability Scale (SUS) and the heuristic evaluation (HE). The use of these two methods is carried out to obtain more in-depth evaluation results so that related parties can improve them. In the usability evaluation using HE, the selected evaluators are five user experts who are experts in the field of usability (three people) who are experts in the field of IT and learning development (two people), while the scope of evaluation in this study is the login process, edit profile, lecture organization, and lecture activities. While the evaluation using the SUS questionnaire obtained a score of 63.3 (grade C-) with 162 respondents. The results of the usability evaluation using HE, it was found that there is one principle that is considered a major problem by user experts, namely the principle of user control and freedom, where the system (e-learning) does not facilitate the undo and redo functions which causes confusion if the user click unwanted menu.

Penerapan Metode Certainty Factor Dalam Diagnosis Gangguan Depresi Septian Rico Hernawan; Hanung Adi Nugroho; Indriana Hidayah
Journal of Computer System and Informatics (JoSYC) Vol 3 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i2.643

Globalization can cause several problems and pressures of mind for both individuals and groups. Various kinds of problems can certainly lead to psychological disorders, one of which is depression. Indonesia itself is one of the countries with a high number of people with depressive disorders. Depressive disorder itself can have many consequences ranging from lack of enthusiasm to even death. Facing these serious problems, the government should be able to address the mental disorder that is currently happening. However, the reality is still far from this. Inadequate infrastructure, equality problems for each region, and shortages of experts are the main problems at this time. The expert system is considered to be a solution in solving these problems. Web-based expert systems can replace the role of experts in the process of initial diagnosis of depressive disorders, patients can also access them easily. The calculation method implemented is the Certainty Factor method. This method is considered suitable in the diagnosis of depression. The implementation of the CF method in the diagnosis of depression can provide a confidence level of up to 94.9%. The expert system is expected to be able to eliminate human errors, speed up the diagnostic process, make it easier for health workers, and provide standards for related parties in handling mental disorders

Improving Data Quality and Data Governance Using Master Data Management: A Review Sanny Hikmawati; Paulus Insap Santosa; Indriana Hidayah
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 3 (2021): September 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.66307

Master data management (MDM) is a method of maintaining, integrating, and harmonizing master data to ensure consistent system information. The primary function of MDM is to control master data to keep it consistent, accurate, current, relevant, and contextual to meet different business needs across applications and divisions. MDM also affects data governance, which is related to establishing organizational actors’ roles, functions, and responsibilities in maintaining data quality. Poor management of master data can lead to inaccurate and incomplete data, leading to lousy stakeholder decision-making. This article is a literature review that aims to determine how MDM improves the data quality and data governance and assess the success of MDM implementation. The review results show that MDM can overcome data quality problems through the MDM process caused by data originating from various scattered sources. MDM encourages organizations to improve data management by adjusting the roles and responsibilities of business actors and information technology (IT) staff documented through data governance. Assessment of the success of MDM implementation can be carried out by organizations to improve data quality and data governance by following the existing framework.

Co-Authors Adhistya Erna Permanasari Astrie Kusuma Dewi Bobby Rian Dewangga Cahyani Windarto Diah Priyawati Ebedia Hilda Am Eko Nugroho Eko Wahyu Nugroho Emi Iryanti Fachrul Budi Prayoga Fahmi Dhimas Irnawan Faizal M. Priyowibowo Hanung Adi Nugroho Hanung Adi Nugroho Hanung Adi Nugroho Indah Soesanti Intan Sulistyaningrum Sakkinah La Ode Mohamad Zulfiqar Lukito Edi Nugroho M. Arifin Hidayat M. Tsana'uddin Farid Muhammad Haris Diponegoro Nasrokhah Noviati Paulus Insap Santosa Rio Jumardi Ripto Mukti Wibowo Sanny Hikmawati Saucha Diwandari Septian Rico Hernawan Shindy Arti Silmi Fauziati Sri Kustanti Sri Suning Kusumawardani Stefani, Brillian Stefani, Brillian Tari Mardiana Teguh Bharata Adji Widiyanti, Tanty Yanuar Winarno Winarno

Title

Found 24 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 24 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 24 Documents
Search