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All Journal Jurnal Ilmiah Teknik Industri Kreasi: Jurnal Inovasi dan Pengabdian Kepada Masyaraka
Hanura, Muhammad Ridzky
Unknown Affiliation
Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Pemanfaatan Limbah Ternak Sebagai Pupuk Organik untuk Meningkatkan Produktivitas Pertanian Suyana, Jaka; Novitasari, Aulia Rahma; Widyatmaka, Burhan; Dewanto, Hendrawan Kusumo; Karnela, Gina; Prastyaningrum, Suci; Pertiwi, Sekar Ayuni Diah; Putri, Nanda Belva Kemala; Prasetyo, Bayu; Dewa, Refansyah Basu; Hanura, Muhammad Ridzky
KREASI : Jurnal Inovasi dan Pengabdian kepada Masyarakat Vol. 3 No. 1 (2023): April
Publisher : BALE LITERASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58218/kreasi.v3i1.499

Abstract

Program Kuliah Kerja Nyata (KKN) merupakan salah satu poin dalam Tri Dharma Perguruan Tinggi yaitu pengabdian masyarakat. Salah satu desa yang menjadi tempat pengabdian para mahasiswa adalah Desa Kunden. Tingginya jumlah peternak di desa Kunden menghasilkan limbah organik yang menumpuk akibat tidak adanya pengelolaan yang baik dari limbah. Hal ini menyebabkan kurangnya nilai guna dari limbah organik tersebut, terutama limbah peternakan dapat diolah menjadi pupuk Trichokompos dan Pupuk Organik Cair yang mudah dibuat dan bernilai guna tinggi terutama untuk meningkatkan produktivitas pertanian Desa Kunden yang didominasi oleh lahan pertanian.
Causal Inference to Predict Delayed Arrival of Ordered Production Materials at PT. XYZ Hanura, Muhammad Ridzky; Priyandari, Yusuf; Hisjam, Muhammad
Jurnal Ilmiah Teknik Industri Vol. 22, No. 2, December 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i2.23020

Abstract

PT XYZ has a problem with the delayed arrival of ordered production materials. Although the company is aware of the delays based on data, the company does not yet know the causes or sources of problems that cause delays. On the other hand, not all factors can be controlled to reduce the delay in the arrival of production materials. The company intends to predict the change in delay time if control or intervention is carried out on certain factors by utilising data availability. The factor to be treated is requisition-to-order lead time A causal inference model is used using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between requisition-to-order lead time and the arrival time of the ordered material by considering other factors that also affect the delay. The results of the causal effect estimation are that by intervening or controlling the requisition-to-order lead time factor by one day, there is a decrease in the average delay in material arrival time by one day
Causal Inference to Predict Delayed Arrival of Ordered Production Materials at PT. XYZ Hanura, Muhammad Ridzky; Priyandari, Yusuf; Hisjam, Muhammad
Jurnal Ilmiah Teknik Industri Vol. 22, No. 2, December 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i2.23020

Abstract

PT XYZ has a problem with the delayed arrival of ordered production materials. Although the company is aware of the delays based on data, the company does not yet know the causes or sources of problems that cause delays. On the other hand, not all factors can be controlled to reduce the delay in the arrival of production materials. The company intends to predict the change in delay time if control or intervention is carried out on certain factors by utilising data availability. The factor to be treated is requisition-to-order lead time A causal inference model is used using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between requisition-to-order lead time and the arrival time of the ordered material by considering other factors that also affect the delay. The results of the causal effect estimation are that by intervening or controlling the requisition-to-order lead time factor by one day, there is a decrease in the average delay in material arrival time by one day
Co-Authors Bayu Prasetyo, Bayu Dewa, Refansyah Basu Dewanto, Hendrawan Kusumo Hisjam, Muhammad Jaka Suyana Karnela, Gina Novitasari, Aulia Rahma Pertiwi, Sekar Ayuni Diah Prastyaningrum, Suci Putri, Nanda Belva Kemala Widyatmaka, Burhan Yusuf Priyandari