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All Journal International Journal of Electrical and Computer Engineering Perfecting a Video Game with Game Metrics AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat CARADDE: Jurnal Pengabdian Kepada Masyarakat IJAIT (International Journal of Applied Information Technology) Indonesian Community Journal Literasi: Jurnal Pengabdian Masyarakat dan Inovasi eProceedings of Applied Science
Dedy Rahman Wijaya
Universitas Telkom
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Public Health Social Sciences Other

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Simple Machine Learning Architecture as a Service Tora Fahrudin; Dedy Rahman Wijaya
IJAIT (International Journal of Applied Information Technology) Vol 07 No 01 (May 2023)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v7i01.5991

Abstract

Machine learning (ML) development starting in the 1950s, has shown significant progress. Various fields have used machine learning as an information system element that is useful in assisting data processing, personalization, prediction, and performing anomaly detection of occurring transactions. Along with developments, cloud-based machine learning technology is becoming the choice for ease of implementation and connectivity with various other technology platforms. This paper proposes a machine learning architecture as a service (MLaaS) implemented in a case study of a gender prediction model based on height and weight. The results show that the MLaaS architecture is straightforward to implement and fits the needs of various access environments and the ease of updating models centrally. Our gender prediction model achieved 91.78% in the precision, recall, and F1-score, 91.8% in specificity and NPV, and 91.79% in accuracy.
Poverty Level Prediction Based on E-Commerce Data Using Naïve Bayes Algorithm and Similarity-Based Feature Selection Pramuko Aji; Dedy Rahman Wijaya; Elis Hernawati; Sherla Yualinda; Sherli Yualinda; Muhammad Akbar Haikal Frasanta; Rathimala Kannan
IJAIT (International Journal of Applied Information Technology) Vol 7 No 02 (2023): Vol 07 No 02 (November 2023)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v7i02.5374

Abstract

The poverty rate is an important measure of any country because it indicates how well the economy develops and how well the economic prosperity distributes among citizens. The Central Statistics Agency, or BPS, measures the poverty rates in Indonesia using the concept of the ability to meet demands (basic needs approach). Using this approach, spending becomes a measure of poverty, defined as an economic incapacity to satisfy food and non-food requirements. Thus, the poor are individuals whose monthly per capita spending is less than the poverty threshold. In this study, the machine learning method using Naive Bayes with similarity-based feature selection and e-commerce data has been proposed to predict the poverty level in Indonesia. We proposed the method to be used as a complement to the results of the costly surveys and censuses conducted by BPS. Our experiments show that the classifier shows little relevance between the predicted and the original values or actual poverty prediction based on BPS data. A limited number of features does not necessarily result in poor accuracy, however great accuracy is not always achieved if a lot of features are being used.
Co-Authors , Inne Gartina Aldilla Iradianty Astri Wulandari Astri Wulandari Bayu Rima Aditya Bethani Suryawardani Dendi Gusnadi Elis Hernawati Elis Hernawati Fathya Ariyani Guntur Prabawa Kusuma Heru Nugroho Inne Gartina Irfan Moch Fazri Marcelino, Dandy Muhammad Akbar Haikal Frasanta Muhammad Nezar Mahardika Pramuko Aji Rathimala Kannan Riyanarto Sarno Sherla Yualinda Sherli Yualinda Siska Komala Sari Siska Komala Sari Sri Rahayu Suryana Suryana Suryatiningsih Tedi Gunawan Tora Fahrudin Wawa Wikusna