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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Economic Journal of Emerging Markets Jurnal Ilmiah Poli Rekayasa Proceedings of KNASTIK Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal NERS Scientific Journal of Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) POLYGLOT Emerging Science Journal Syntax Literate: Jurnal Ilmiah Indonesia JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) International Journal of New Media Technology Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) International Journal of Supply Chain Management Poltekita : Jurnal Ilmu Kesehatan Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Informatika Jurnal Informatika Ekonomi Bisnis Journal of Applied Data Sciences Walisongo Journal of Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Action Research Literate (ARL) Jurnal Indonesia Sosial Teknologi Jurnal Informatika Ekonomi Bisnis Jurnal Sistem Informasi International Journal of Education, Language, Literature, Arts, Culture, and Social Humanities The Indonesian Journal of Computer Science Malahayati International Journal of Nursing and Health Science Jurnal Komtika (Komputasi dan Informatika)
Achmad Nizar Hidayanto
Fakultas Ilmu Komputer, Universitas Indonesia
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Data Quality Management Maturity Measurement of Government-Owned Property Transaction in BMKG Wibisono, Septian Bagus; Hidayanto, Achmad Nizar; Nugroho, Widijanto Satyo
CommIT (Communication and Information Technology) Journal Vol 12, No 2 (2018): CommIT Vol. 12 No. 2 Tahun 2018
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v12i2.4470

Abstract

Government-Owned Property (GOP) management, including the bookkeeping of GOP transaction, is part of GOP Officer responsibility to ensure the quality of transaction data. This responsibility also applies to GOP Officer in Indonesian Agency for Meteorological, Climatological and Geophysics ‘Badan Meteorologi, Klimatologi, dan Geofisika’ (BMKG). GOP data as the source for the Central Government Financial Report is expected to be well-maintained. It must be presented as accurate as possible, although there are still inaccurate data presented in the latest BMKG GOP Report. This qualitative research using document study and some interview sessions aims to measure how well the Data Quality Management (DQM) maturity of GOP transaction in BMKG using Loshin’s Data Quality Maturity model. Thus, the result of maturity assessment is analyzed to recommend and implement DQM activities from the Data Management Body of Knowledge (DMBOK). The purpose is to improve GOP DQM. The research shows that the level of DQM maturity is at a repeatable level to defined level. Moreover, 52 maturity characteristics need to be followed through with DQM activities.
PERBANDINGAN ALGORITMA KLASIFIKASI DALAM PENDETEKSIAN PENYAKIT KANKER Hidayanto, Achmad Nizar; Hapsari, Ika Chandra; Jiwanggi, Meganingrum Arista; Fitria, Diane
Proceedings of KNASTIK 2010
Publisher : Duta Wacana Christian University

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

Abstract

Kanker merupakan salah satu penyakit pembunuh teratas. Menurut  data dari WHO tahun 2008, kanker menyebabkan 12,6% kematian di dunia setelah penyakit jantung dan infeksi. Salah satu kesulitan dalam pendeteksian penyakit kanker adalah perlunya pasien untuk melakukan berbagai macam uji lab sebelum mereka divonis terkena penyakit kanker atau tidak. Penelitian ini bertujuan untuk melakukan deteksi penyakit kanker berdasarkan hasil uji lab yang sudah dilakukan oleh pasien. Terdapat empat hasil uji lab yang dipergunakan sebagai variabel untuk melakukan klasifikasi. Untuk melakukan deteksi penyakit kanker ini, digunakan beberapa algoritma klasifikasi yang sudah disediakan oleh SPSS Clementine 11.1 atau Weka 3.6.0, yaitu  Neural Network, C5.0, Logistic, Classification via Regression, dan LogitBoost. Algoritma Neural Network  sendiri  terdiri dari 6 metode, yaitu Dynamic ,Prune, Exhaustive Prune, Quick, RBFN dan Multiple. Percobaan dilakukan sebanyak sepuluh kali untuk masing-masing algoritma atau metode. Pada tiap percobaan, terdapat dua kali treatment terhadap data yang diolah.  Hasil percobaan menunjukkan bahwa  algoritma Neural Network dengan metode Prune menghasilkan hasil yang terbaik dalam mendeteksi penyakit kanker.
Immutability of Distributed Hash Model on Blockchain Node Storage Rahardja, Untung; Hidayanto, Achmad Nizar; Lutfiani, Ninda; Febiani, Dyah Ayu; Aini, Qurotul
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.29444

Abstract

The blockchain system uses hash functions. Hash is used in the blockchain to mark each block of data. Hash function algorithms map a string that is usually hexadecimal of any size to a sequence of fixed-size bits. This journal will discuss the distributed hash model for immutable blockchain node storageThe methodology used in the preparation of this research is mind mapping and literature review, namely the collection of scientific journals, articles and ebooks. Storage of nodes on the blockchain using a distributed hash model. The distributed hash model only stores a portion of the block data at each node, and the block data is taken as a resource. A hash connects each block with the previous on the blockchain, so the entire blockchain transaction cannot be changed or deleted. For further research will expand the research topic regarding storage immutability on the blockchain so that it becomes more complete and detailed.
Immutability of Distributed Hash Model on Blockchain Node Storage Rahardja, Untung; Hidayanto, Achmad Nizar; Lutfiani, Ninda; Febiani, Dyah Ayu; Aini, Qurotul
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.29444

Abstract

Purpose: The blockchain system uses hash functions. Hash is used in the blockchain to mark each block of data. Hash function algorithms map a string that is usually hexadecimal of any size to a sequence of fixed-size bits. This journal will discuss the distributed hash model for immutable blockchain node storage. Methods: The methodology used in the preparation of this research is mind mapping and literature review, namely the collection of scientific journals, articles, and e-books. Result: Storage of nodes on the blockchain using a distributed hash model. The distributed hash model only stores a portion of the block data at each node, and the block data is taken as a resource. A hash connects each block with the previous on the blockchain, so the entire blockchain transaction cannot be changed or deleted. Novelty: For further research will expand the research topic regarding storage immutability on the blockchain so that it becomes more completed and detailed.
Improving Hierarchical Decision Approach for Single Image Classification of Pap Smear Dwiza Riana; Yudi Ramdhani; Rizki Tri Prasetio; Achmad Nizar Hidayanto
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (755.324 KB) | DOI: 10.11591/ijece.v8i6.pp5415-5424

Abstract

The single image classification of Pap smears is an important part of the early detection of cervical cancer through Pap smear tests. Unfortunately, most classification processes still require accuracy enhancement, especially to complete the classification in seven classes and to get a qualified classification process. In addition, attempts to improve the single image classification of Pap smears were performed to be able to distinguish normal and abnormal cells. This study proposes a better approach by providing different handling of the initial data preparation process in the form of the distribution for training data and testing data so that it resulted in a new model of Hierarchial Decision Approach (HDA) which has the higher learning rate and momentum values in the proposed new model. This study evaluated 20 different features in hierarchical decision approach model based on Neural Network (NN) and genetic algorithm method for single image classification of Pap smear which resulted in classification experiment using value learning rate of 0.3 and momentum of 0.2 and value of learning rate of 0.5 and momentum of 0.5 by generating classification of 7 classes (Normal Intermediate, Normal Colummar, Mild (Light) Dyplasia, Moderate Dyplasia, Servere Dyplasia and Carcinoma In Situ) better. The accuracy value enhancemenet were also influenced by the application of Genetic Algorithm to feature selection. Thus, from the results of model testing, it can be concluded that the Hierarchical Decision Approach (HDA) method for Pap Smear image classification can be used as a reference for initial screening process to analyze Pap Smear image classification.
A non-negative matrix factorization based clustering to identify potential tuna fishing zones Devi Fitrianah; Hisyam Fahmi; Achmad Nizar Hidayanto; Pang Ning-Tan; Aniati Murni Arymurthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5458-5466

Abstract

Many nonnegative matrix factorization based clusterings are employed in discovering pattern and knowledge. Considering the sparseness nature of our data set about the daily tuna fishing data, we attempted to utilize a clustering approach, which is based on non-negative matrix factorization. Adding sparseness constraint and assigning good initial value in the modified NMF method, a proposed algorithm Direct-NMFSC yielded better result cluster compared to other methods which are also utilizing sparse constraint to their approaches, SNMF and NMFSC. The result of this study shows that Direct-NMFSC has 5.376 times of iteration number less than NMFSC in average with 531.97 as the CH index result. The determination of potential fishing zones is one of the essential efforts in the potential fishing zone mapping system for tuna fishing. By means of this novel data-driven study to construct the information and to identify the potential tuna fishing zones is done. We also showed that utilizing the Direct-NMFSC can spot and identify the potential tuna fishing zones presented in red cluster that covers both the spatial and temporal information.
Teacher and student readiness using E-learning and M-learning Ramadiani Ramadiani; Azainil Azainil; Achmad Nizar Hidayanto; Dyna Marissa Khairina; Muhammad Labib Jundillah
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.792 KB) | DOI: 10.11591/eei.v9i3.2006

Abstract

This research is about the readiness of teachers and students to develop E-learning and M-learning for the learning process. Before developing and implementing an E-learning and M-learning system, it is important to ensure the user's readiness for the technology. Users' perceptions will affect their willingness and readiness to use the system. This study aims to investigate the teachers and students perceptions about E-learning and M-learning, ensuring their readiness to involve in developing online learning process. The study was conducted by survey methods, questionnaires and direct interviews with prospective users in the schools, students, teachers and principals. Research respondents were from Junior High School and Senior High Schools in Samarinda. The questionnaires will be carried out in two stages, before and after the development of E-learning and M-learning systems. The findings obtained from this study indicate that research partner schools are ready and able to participate in developing E-learning and M-learning systems.
E-Learning Success Model: An Extention of DeLone & McLean IS' Success Model Henki Bayu Seta; Theresia Wati; Anita Muliawati; Achmad Nizar Hidayanto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.505

Abstract

Learning by using e-learning system at this time become an important part of university to carrying out the education. Learning by e-learning system is very supportive to conventional learning, so it is necessary to measure the success of e-learning implementation. In this article, the research model was developed by integrating. DeLone& McLean IS concept of success model and adoption model of e-learning success. The variables that used in this research is technical system quality, service quality, content and information quality, use, user perceived satisfaction, and individual impact. Data collection is by conducting surveys to e-learning users which is lecturers and students. To test the model that has been developed, conducted a survey on UPN "Veteran" Jakarta with the total number of respondents as many as 180 respondents and obtained 157 respondents who fill the questionnaire correctly. This research, shows both the use and satisfaction of e-learning system have an impact for individual performance. This research also found that educational system quality and technical quality are the main factors that encourage user satisfaction with e-learning system, while the use of e-learning system that influenced by content & information quality, also user perceived satisfaction for e-learning system.
Perception of beneficiaries towards adoption of e-money in the distribution of social assistance in Indonesia Sartika Djamaluddin; Achmad Nizar Hidayanto; Sita Wardhani
Economic Journal of Emerging Markets Volume 8 Issue 1, 2016
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ejem.vol8.iss1.art2

Abstract

Wide access to formal finance for poor households through distribution of social assistance via electronic money (E-money) is believed to accelerate eradication of poverty. We would like to find out the beneficiaries response to this payment method. This aims of this study is to investigate the perception of beneficiaries towards distribution of social assistance through e-money. We surveyed 230 beneficiaries in Jakarta, Cirebon and Pasuruan. The result of research indicates that the perception of PKH beneficiaries related to the cost, benefits and security of e-money is relatively good. However, from the aspect of ease of use and the respondents’ desire to use e-money, the perception is quite low. 
Factors Affecting Switching Intention from Cash on Delivery to E-Payment Services in C2C E-Commerce Transactions: COVID-19, Transaction, and Technology Perspectives Betty Purwandari; Syahrul Alam Suriazdin; Achmad Nizar Hidayanto; Suryana Setiawan; Kongkiti Phusavat; Mutia Maulida
Emerging Science Journal Vol 6 (2022): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2022-SPER-010

Abstract

During the COVID-19 pandemic, the application of e-payment has rapidly increased. However, e-payment has not been able to achieve a trustworthy level in e-commerce transactions. Thus, cash payment methods with Cash On Delivery (COD) services still dominate C2C e-commerce payment transactions in Indonesia. This study aims to investigate factors that affect users' switching intentions from COD to e-payment services. The research model was adopted by using the Push-Pull-Mooring framework, integrating perceived COVID-19 risk, technology acceptance, and transaction effort. Empirical research was conducted using data from 546 COD and e-payment users in Indonesia, with Structural Equation Modelling (SEM) being used to validate the model and analyze the hypotheses. The results indicate that switching intention from COD to e-payment is significantly influenced by pull factors in e-payment, which are economic benefits, performance expectancy, effort expectancy, and critical mass. There are also two mooring factors that significantly influence the switching intention from COD to e-payment, which are trust and perceived security and privacy. This study makes a significant contribution to the literature in terms of validating a theoretical framework that emphasizes factors that influence user switching intentions from COD to e-payment in the context of the COVID-19 pandemic. This research can be a reference for Indonesian payment system regulators and e-payment service providers in formulating regulations and strategies to accelerate the spread of digital transactions in Indonesia. Doi: 10.28991/esj-2022-SPER-010 Full Text: PDF
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