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All Journal Jurnal Pendidikan Terbuka Dan Jarak Jauh Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika International Journal of Quantitative Research and Modeling Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) SAGA: Journal of Technology and Information Systems JCOSIS (Journal Computer Science and Information Systems)
Lintang Patria
Universitas Terbuka
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Physics Social Sciences

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Fuzzy Time Series Application in Predicting the Number of Confirmation Cases of Covid-19 Patients in Indonesia Lintang Patria
International Journal of Quantitative Research and Modeling Vol 2, No 4 (2021)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v2i4.194

Abstract

Forecasting is a statistical method that can use historical data patterns to predict future events. This article discusses the prediction of the number of new confirmed cases of Covid-19 patients in Indonesia. The data used is from January 1, 2021 to August 7, 2021. The methods used are Fuzzy Time Series (FTS) Chen (2014) and Cheng et al. (2008). FTS is a forecasting method that uses rules and logic on fuzzy sets. The level of prediction accuracy is then calculated based on the Mean Absolute Percentage Error (MAPE) value. The MAPE values of these two methods are then compared to know which method is more suitable in this case study. The results showed that FTS Chen produced an accuracy of 12.75% and FTS Cheng produced an accuracy of 14.27%. The results of this study indicate that FTS Chen and FTS Cheng produce good accuracy and can be used to predict new confirmed cases of Covid 19 sufferers in Indonesia.
Forecasting of the Cases of Covid-19 Patients in Indonesia using Fuzzy Time Series Lintang Patria
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 2 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i2.5446

Abstract

The main objective of this study is forecasting of the cases of covid-19 patients in indonesia using fuzzy time series. The data used is from February 1, 2022 to February 28, 2022. The methods used are Fuzzy Time Series (FTS) Chen and FTS Cheng, using first order and second order. FTS is a forecasting method that uses rules and logic on fuzzy sets. The level of prediction accuracy is then calculated based on the Mean Absolute Percentage Error (MAPE) value. The MAPE values of these two methods are then compared to know which method is more suitable in this case study. The results showed that Fisrt Order FTS Chen produced an accuracy of 4,21% and Fisrt Order FTS Cheng produced an accuracy of 4,22%. Second Order FTS Chen and Second Order FTS Chen produced/1the same MAPE, 1,23%./1The results of this study indicate that Second Order FTS Chen and FTS Cheng produce good accuracy and can be used to predict new confirmed cases of Covid 19 sufferers in Indonesia.
Faktor-Faktor yang Mempengaruhi Resistensi Mahasiswa Fakultas Sains dan Teknologi Universitas Terbuka Lintang Patria; Sri Utami; Deddy A Suhardi; Heny Kurniawati; Dian Nursantika
Jurnal Pendidikan Terbuka Dan Jarak Jauh Vol. 23 No. 2 (2022)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/ptjj.v23i2.3944.2022

Abstract

Pandemi Covid-19 berdampak signifikan terhadap pembelajaran mahasiswa di perguruan tinggi. Adanya Covid-19 yang berdampak pada berbagai bidang kehidupan dapat mempengaruhi ketahanan mahasiswa untuk kuliah di UT. Selama ini strategi pembelajaran, faktor sosiodemografi, layanan tutorial, kemampuan akademik dan kepuasan mahasiswa terhadap layanan UT telah mempengaruhi resiliensi mahasiswa. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi daya tahan mahasiswa Universitas Terbuka selama masa pandemi COVID-19. Analisis data dilakukan dengan menggunakan Confirmatory Factor Analysis (CFA). Hasil penelitian ini menyatakan bahwa kondisi sosial ekonomi pada masa pandemi Covid 19 dan strategi pembelajaran berpengaruh signifikan terhadap resistensi registrasi mahasiswa. Tingkat resistensi (mahasiswa registrasi ulang) dipengaruhi oleh kemampuan mengatasi kendala sosial ekonomi pada masa pandemi (Sosvid, 0,49), kemampuan akademik (0,38), kondisi layanan UT (-0,16), layanan tutorial-praktikum (-0,20), dan strategi pembelajaran (-0,44). Keluaran dari penelitian ini adalah rekomendasi perbaikan dan inovasi layanan FST UT selama pandemi.
Determining the Best Web Designer Using the SMARTER Method (Case Study: Website Development Service Provider) Patria, Lintang; Sitompul, Bernad J. D.; Marbun, Nasib
SAGA: Journal of Technology and Information System Vol. 2 No. 3 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i3.286

Abstract

This research aims to solve the problem of determining the best Web Designer objectively for website development service business activists. In this research, the author offers SMARTER as a decision support system method to produce a ranking of the best Web Designer alternatives to be selected by decision makers. The alternatives selected as the best Web Designer in this study consist of 5 candidates (AX1, AX2, AX3, AX4, and AX5). The criteria used in the process of determining the best Web Designer in this study are communication, ability to design websites, discipline, and loyalty. The results of the application of the SMARTER method in this study recommend alternative AX3 to the decision maker to be selected as the best web designer who is entitled to a reward
Fuzzy Time Series Application in Predicting the Number of Confirmation Cases of Covid-19 Patients in Indonesia Lintang Patria
International Journal of Quantitative Research and Modeling Vol. 2 No. 4 (2021): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v2i4.194

Abstract

Forecasting is a statistical method that can use historical data patterns to predict future events. This article discusses the prediction of the number of new confirmed cases of Covid-19 patients in Indonesia. The data used is from January 1, 2021 to August 7, 2021. The methods used are Fuzzy Time Series (FTS) Chen (2014) and Cheng et al. (2008). FTS is a forecasting method that uses rules and logic on fuzzy sets. The level of prediction accuracy is then calculated based on the Mean Absolute Percentage Error (MAPE) value. The MAPE values of these two methods are then compared to know which method is more suitable in this case study. The results showed that FTS Chen produced an accuracy of 12.75% and FTS Cheng produced an accuracy of 14.27%. The results of this study indicate that FTS Chen and FTS Cheng produce good accuracy and can be used to predict new confirmed cases of Covid 19 sufferers in Indonesia.
Edukasi Ibu Hamil (Bumil) dan Pemberian Makanan Tambahan Balita di Posyandu Melati Bahagia Ariyanti Hartari; Heny Kurniawati; Lintang Patria; Heri Kurniawan
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 2 (2026): Oktober 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i2.1610

Abstract

Ibu hamil dan balita termasuk dalam kelompok yang rentan terhadap masalah gizi, sehingga perlu mendapatkan perhatian khusus untuk mencegah dampak jangka panjang akibat kekurangan gizi. Tujuan pelaksanaan kegiatan penyuluhan gizi ibu hamil dan pemberian makanan tambahan balita adalah meningkatkan pengetahuan ibu hamil tentang asupan gizi dan kesehatan ibu hamil untuk mencegah kejadian stunting dan tumbuh kembang bayi, serta pemberian variasi makanan tambahan kepada balita yang hadir ke posyandu. Penyuluhan gizi ibu hamil dilakukan melalui metode ceramah dan diskusi/tanya jawab dengan bantuan media leaflet. Pemberian makanan tambahan dilakukan secara langsung kepada balita yang hadir dan informasi nilai gizi disampaikan melalui label yang disertakan pada kemasan PMT. Parameter tumbuh kembang bayi dan balita di Posyandu Melati Bahagia yang berhubungan postitif yaitu umur dan berat badan serta umur dan tinggi/panjang bayi dan balita. Hubungan umur, berat badan, dan tinggi badan bayi dan balita di posyandu Melati Bahagia berada di kuadran positif dan memiliki hubungan positif. Kondisi ini menunjukkan parameter tumbuh kembang bayi dan balita di lingkungan posyandu Melati Bahagia berada pada status baik. Pemberian PMT Balita berupa 1 cup macaroni skutel seberat 150g memberikan energi sebesar 188,29 Kcal dengan kandungan nutrisi 7,54% protein, 7,06% lemak, dan 23,66% karbohidrat disambut dengan antusias baik oleh ibu, balita, dan kader posyandu. Penyuluhan gizi ibu hamil di posyandu Melati Bahagia dilakukan secara langsung menggunakan leaflet berisi pesan gizi seimbang, kenaikan berat badan ibu hamil sebagai parameter atau indikator kesehatan dan kesejahteraan ibu hamil dan janin, mendapatkan respon yang antusias dari bumil dan kader posyandu.
Analisis Pemanfaatan Artificial Intelligence sebagai Pendukung Transformasi Digital Pendidikan pada Mahasiswa di Program Studi Sistem Informasi Universitas Terbuka Deny Budiyanto; Lintang Patria; Tia Andriani
JCOSIS (Journal Computer Science and Information Systems) Vol. 3 No. 2 (2026): October
Publisher : Institute for Research and Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61567/jcosis.v3i2.319

Abstract

Tujuan: Penelitian ini bertujuan menganalisis pengaruh Artificial Intelligence (AI) terhadap proses belajar mahasiswa serta menguji peran sistem informasi sebagai variabel mediasi pada mahasiswa Program Studi Sistem Informasi Universitas Terbuka. Metode/Design/Pendekatan: Penelitian ini menggunakan pendekatan kuantitatif dengan metode Partial Least Squares–Structural Equation Modeling (PLS-SEM) melalui SmartPLS. Data diperoleh melalui kuesioner skala Likert lima poin yang disebarkan kepada 75 mahasiswa. Model penelitian melibatkan AI sebagai variabel independen, sistem informasi sebagai mediator, dan proses belajar sebagai variabel dependen. Hasil/Temuan: Hasil menunjukkan bahwa AI berpengaruh positif terhadap sistem informasi (0,492), proses belajar (0,377), dan sistem informasi berpengaruh positif terhadap proses belajar (0,369). Pengujian mediasi menunjukkan pengaruh tidak langsung sebesar 0,183 (p = 0,005), yang membuktikan peran mediasi parsial sistem informasi. Kebaruan/Originalitas/Nilai: Kebaruan penelitian terletak pada pengujian sistem informasi sebagai variabel mediasi dalam hubungan AI dan proses belajar mahasiswa pada pendidikan tinggi jarak jauh. Hasil penelitian memberikan kontribusi empiris bagi pengembangan integrasi AI dan sistem informasi untuk mendukung pembelajaran digital.
Co-Authors Ariyanti Hartari Deddy Ahmad Suhardi Deny Budiyanto Dian Nursantika Heny Kurniawati Heri Kurniawan Nasib Marbun Sitompul, Bernad J. D. Sri Utami Tia Andriani