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All Journal Jurnal sistem informasi, Teknologi informasi dan komputer JURNAL MEDIA INFORMATIKA BUDIDARMA KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Building of Informatics, Technology and Science TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Bulletin of Computer Science Research Jurnal Janitra Informatika dan Sistem Informasi BEES: Bulletin of Electrical and Electronics Engineering Bulletin of Data Science JOMLAI: Journal of Machine Learning and Artificial Intelligence Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)

Winanjaya, Riki

STIKOM Tunas Bangsa Pematangsiantar, Indonesia

Author-ID : 3338698

Aerospace Engineering Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 27 Documents Claim Missing Document

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Implementation of the Weighted Moving Average Method for Forecasting the Production of Manila Duck meat in Indonesia Diana Pratiwi; Riki Winanjaya; Irawan Irawan
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Manila duck is a waterfowl originating from South America, through the Philippines this type of duck entered Indonesia and has a large distribution in various regions of Indonesia the production on manila duck meat and from 2019-2020 has decreased due to the covid-19 pandemic which resulted in economic difficulties. And the lack of demand from restaurants and households so that the amount of production decrease. However, in 2020-2021 production will increase due to the relaxation from the previous pandemic and the demand and marketing has increased to that the number of production has increased from the previous year. The Weighted Moving Average method is a method used to determine the latest trend with a moving average value. The purpose of this study was to analyses the amount of production of manila duck meat in solving the problem. The result obtained with the smallest error percentage are at F128 in the province of North Maluku with MAPE value of 0,003 or equal to 0,3% with a bias of -0,25, MAD 0,25, MSE 0,06, with a forecasting value of 83,29 which is close to the original data, namely 83,04 so that the forecast value for 2022 is 83,24 tons.

Forecasting of Rubber Production in North Sumatra with Backpropagation Algorithm Josua Fernando Simanjuntak; Riki Winanjaya; Wendi Robiansyah
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Rubber is a commodity to produce tires, balloons, and other rubber-based products. Indonesia is the second largest rubber producer and distributor in the world. But, rubber production level tends to fluctuate. Therefore, an analysis is needed to predict rubber production in the future thus rubber plantations, especially folk-owned, can take steps to prevent if declines in production are found. One way that can be done to predict is by utilizing Artificial Neural Network with Backpropagation method, since it provides accurate results. In this research, 10 network architecture models were tested and the best architecture achieved was 10-10-11-1 with accuracy of 96%. With that architecture, predictions are done and resulted in estimated rubber production in North Sumatra for 2021-2025.

Artificial Neural Network Method in Predicting the Amount of Manila Duck Meat Production by Province in Indonesia Joko Pamungkas; Riki Winanjaya; Wendi Robiansyah
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Duck meat is a source of animal protein that many Indonesians need because it can increase nutritional needs to improve people's quality of life. One of the types of ducks used in this study is the Manila duck, this type of duck was chosen because it is very easy to maintain and the price is also relatively affordable. Based on data on the production of Manila ducks in Indonesia from several provinces, the annual production amount is unstable. Therefore, it is important to make predictions about this matter as information for the government. The data sample used in this study is manila duck production data taken from the Indonesian Central Statistics Agency in 2017-2020. This research uses backpropagation algorithm. Based on the results of the analysis, the best architectural model is 3-6-1 which will later be used to predict the amount of manila duck meat production in 2022 because it has the highest accuracy rate compared to other models, which is 74%. MSE Testing is 0,00412. Based on this model, predictions of the amount of manila duck meat production will be made based on provinces in Indonesia. From the prediction results, it can be seen that there are 25 provinces that are estimated to experience an increase in production in 2022 or around 73,5% (25 provinces) of a total of 34 provinces in Indonesia. Meanwhile, 9 other provinces experienced a decline or around 26,5%.

Implementation of the Mamdani Fuzzy Method in Handling Room Availability in 2022 at Hotel Inna Parapat Nugroho, Muhammad Rizky Tri; Winanjaya, Riki; Susiani, Susiani
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 2 (2023): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i2.2368

This study aims to implement the Fuzzy Mamdani Method in handling room availability in 2022 at Hotel Inna Parapat. The Fuzzy Mamdani method is a mathematical approach to dealing with uncertainty and ambiguity in decision-making. This study collected and analyzed data regarding the number of hotel rooms, occupancy rates, and room demand during 2022 at Hotel Inna Parapat. Then, the Fuzzy Mamdani model was developed to predict room availability based on predetermined variables. The study results show that implementing the Fuzzy Mamdani Method can provide a more accurate prediction regarding room availability at Hotel Inna Parapat. The Mamdani Fuzzy Model can handle uncertainty and ambiguity in the data and provides membership values that provide a more precise picture of the actual situation. With the Fuzzy Mamdani model, Hotel Inna Parapat management can be more effective in optimizing room utilization, improving customer service, and anticipating high room demand in 2022. Implementing the Fuzzy Mamdani Method is important to handling room availability in 2022 at Inna Hotel Parapat. This approach is expected to help hotels and the hospitality industry make smarter, data-based decisions to deal with changing demands and dynamic business situations.

Co-Authors Agus Perdana Windarto Agus Tiranda Sipayung Diana Pratiwi Fadillah Alwi Pambudi Febrivani, Elischa Fitri Anggraini, Fitri Fitri Rizki GS , Achmad Daengs GS, Acmad Daengs Harliana Harliana Hartama, Dedy Hendry Qurniawan Hendry Qurniawan Indra Riyana Rahadjeng Irawan Irawan Irfan Sudahri Damanik Jaya Tata Hardinata Joko Pamungkas Josua Fernando Simanjuntak M Safii Mhd Wendico Herdian Muhammad Fauzan Muhammad Safii Nugroho, Muhammad Rizky Tri Nurhayati Nurhayati Okprana, Harly Putri Mai Sarah Tarigan Putri Mai Sarah Tarigan Qurniawan, Hendry Rajes Wasimson Sinaga Reza Fauzy Rizki, Fitri Rizky Khairunnisa Sormin S Saifullah S Susianti Safii, M Saifullah Saifullah Saifullah Sanri Sunervia Yunika Damanik Sari, Hanifah Urbach Simanjorang, Fernandi Susiani Susiani Susiani Susiani, Susiani Syahputra, Muhammad Syahputra, Muhammad Riza Tarigan, Putri Mai Sarah Wanto, Anjar Wendi Robiansyah Yuni Radana Sembiring Yusuf Maulana Zulia Almaida Siregar

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