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All Journal Innovative: Journal Of Social Science Research
Manullang, Maria Ayuni Isabella
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Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Public Health Other

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Analisis Survival terhadap Faktor Keberlangsungan Usaha Pedagang Sayur di Pasar Raya MMTC PANCING, MEDAN Siboro, Alio Hutaperi; Simanjuntak, Christina N; Manullang, Maria Ayuni Isabella; Manullang, Sudianto; Farhana, Nurul Ain
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i6.16004

Abstract

Penelitian ini bertujuan untuk menganalisis keberlangsungan usaha pedagang sayur di Pasar Raya MMTC Pancing, Medan dengan menggunakan pendekatan metode analisis survival. Dengan fokus pada faktor-faktor yang mempengaruhi durasi keberlangsungan usaha, penelitian ini menggunakan metode Kaplan-Meier untuk mengestimasi probabilitas bertahan para pedagang. Data yang dikumpulkan meliputi modal awal, rata-rata keuntungan dan kerugian, dan lama usaha pedagang berjualan di pasar raya MMTC dengan jumlah 30 sampel. Hasil penelitian menunjukkan bahwa keuntungan memiliki pengaruh signifikan terhadap keberlangsungan usaha, sedangkan modal dan kerugian tidak memberikan pengaruh yang signifikan. Pada tahun pertama, probabilitas survival adalah 93%, yang menurun menjadi 71% pada tahun keempat. Penelitian ini menyarankan agar studi lanjutan menggunakan sampel yang lebih besar dengan periode pengamatan yang lebih panjang untuk mendapatkan hasil yang lebih mendalam.
Penerapan Rantai Markov Dalam Peramalan Cuaca (Studi Kasus: Cuaca Harian Di Deli Serdang) Siboro, Alio Hutaperi; N Simanjuntak, Christina; Manullang, Maria Ayuni Isabella; Simanjuntak, Natalia Anggriani; Sitanggang, Santa Falare; Simbolon, Taing Pebrieni; Manullang, Sudianto; Nasution, Alvi Sahrin
Innovative: Journal Of Social Science Research Vol. 5 No. 3 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i3.19426

Abstract

Weather is the state of the air (about temperature, sunlight, humidity, wind speed, and so on) in a certain place with a limited period of time (KBBI). Daily weather forecasting holds significant importance in daily activities, especially in helping people and various industrial sectors adapt their activities to upcoming weather conditions. The objective of this research is to apply the Markov Chain model in daily weather forecasting in Deli Serdang. This study uses daily weather data in Deli Serdang district from March 1, 2025 to April 30, 2025. The data was sourced from the Meteorology, Climatology, and Geophysics Agency (BMKG). The research variables used are weather conditions, namely, sunny , cloudy , light rain , and rain Weather predictions for the next seven days can be carried out gradually by taking into account previous weather conditions. The results of the forecasting obtained show that the chances of each weather condition occurring in the following days can be clearly mapped, thus providing a more realistic probabilistic picture than conventional deterministic methods.
Co-Authors Manullang, Sudianto N Simanjuntak, Christina Nasution, Alvi Sahrin Nurul Ain Farhana Siboro, Alio Hutaperi Simanjuntak, Christina N Simanjuntak, Natalia Anggriani Simbolon, Taing Pebrieni Sitanggang, Santa Falare