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All Journal Communication in Biomathematical Sciences Al-Sharf: Jurnal Ekonomi Islam
Zikri, Afdol
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Economics, Econometrics & Finance Social Sciences

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Data-Driven Generating Operator in SEIRV Model for COVID-19 Transmission Nadia; Zikri, Afdol; Rizqina, Sila; Sukandar, Kamal Khairudin; Fakhruddin, Muhammad; Tay, Chai Jian; Nuraini, Nuning
Communication in Biomathematical Sciences Vol. 6 No. 1 (2023)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2023.6.1.6

Abstract

The COVID-19 (SARS-CoV-2) vaccine has been extensively implemented through large-scale programs in numerous countries as a preventive measure against the resurgence of COVID-19 cases. In line with this vaccination effort, the Indonesian government has successfully inoculated over 74% of its population. Nevertheless, a significant decline in the duration of vaccine-induced immunity has raised concerns regarding the necessity of additional inoculations, such as booster shots. Prior to proceeding with further inoculation measures, it is imperative for the government to assess the existing level of herd immunity, specifically determining whether it has reached the desired threshold of 70%. To shed light on this matter, our objective is to ascertain the herd immunity level following the initial and subsequent vaccination programs, while also proposing an optimal timeframe for conducting additional inoculations. This study utilizes COVID-19 data from Jakarta and employs the SEIRV model, which integrates time-dependent parameters and incorporates an additional compartment to represent the vaccinated population. By formulating a dynamic generator based on the cumulative cases function, we are able to comprehensively evaluate the analytical and numerical aspects of all state dynamics. Simulation results reveal that the number of individuals protected by the vaccine increases following the vaccination program; however, this number subsequently declines due to the waning effect of the vaccine. Our estimates indicate that the vaccination program in Jakarta has achieved herd immunity levels exceeding 70% from October 2021 to February 2022, thus underscoring the necessity of rolling out further inoculations no later than February 2022.
Analysis of the Impact of the Use of Rice Harvesting Machines (Jarwo) on Community Welfare from an Islamic Economic Perspective (Case Study: Nagari Tanjung Betung Timur, Rao Selatan District, Pasaman Regency) Zikri, Afdol; Joni, Yefri; Rahman, Ali; Rahmi, Rahmi
Al-Sharf: Jurnal Ekonomi Islam Vol 7, No 1 (2026)
Publisher : Yayasan Rahmat Islamiyah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56114/al-sharf.v7i1.12670

Abstract

Penelitian ini dilatarbelakangi oleh transformasi teknologi pertanian di Nagari Tanjung Betung Timur melalui penggunaan mesin pemanen padi (jarwo) yang secara fundamental mengubah praktik pertanian tradisional. Jumlah buruh tani berkurang drastis dari 871 orang menjadi 24 operator untuk 12 unit mesin, sekaligus menggeser pola interaksi sosial dari gotong royong menuju aktivitas individualistis. Penelitian ini menggunakan pendekatan kualitatif dengan wawancara mendalam terhadap petani pemilik lahan, buruh tani, operator mesin, dan tokoh masyarakat. Hasil penelitian menunjukkan adanya dampak kontradiktif: efisiensi ekonomi bagi petani pemilik lahan dengan penurunan biaya panen dari Rp4.200.000 menjadi Rp2.880.000 per 10.404 m², serta peningkatan pendapatan pemilik mesin hingga Rp3–4 juta per hari. Namun, 97,2% buruh tani mengalami penurunan kesejahteraan akibat hilangnya mata pencaharian. Meskipun demikian, 60% keluarga buruh berhasil beradaptasi dengan menemukan sumber pendapatan alternatif. Dari perspektif ekonomi Islam, penerapan teknologi ini memerlukan evaluasi agar prinsip keadilan dan kesejahteraan dapat tercapai bagi seluruh lapisan masyarakat, khususnya kelompok yang rentan.
Co-Authors Joni, Yefri Nadia Nuning Nuraini Rahman, Ali Rahmi Rahmi Rizqina, Sila Sukandar, Kamal Khairudin Syamsiar, Syamsiar Tay, Chai Jian