Article Per Year (5 Year)
p-Index From 2020 - 2025
1.116
P-Index
This Author published in this journals
All Journal Jurnal Optimasi Sistem Industri PENA SAINS Journal of Industrial Engineering Management ARIKA Abdimas Langkanae Jurnal Pengabdian Pada Masyarakat METHABDI
Arminas, Arminas
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Perancangan Alat Pengeruk Buah Markisa Berbasis Ergonomi pada UKM Markisa Aurora Makassar Arminas, Arminas
ARIKA Vol 17 No 2 (2023)
Publisher : Industrial Engineering Study Program, Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/arika.2023.17.2.59

Abstract

UKM Markisa Aurora Makassar merupakan salah satu UKM (Usaha Kecil Menengah) yang berada di Kota Makassar yang bergerak dalam pembuatan sirup markisa. Pengambilan bulir adalah salah satu proses produksi dalam membuat sirup markisa, dimana pada pengambilan bulir ini dilakukan kegiatan pengerukan buah dari cangkangnya. Namun dalam identifikasi di industri rumah tangga pembuatan sirup markisa, terlihat bahwa pada tahap pengambilan bulir dilakukan dengan mengeruk buah markisa menggunakan alat yang masih sederhana yaitu sendok makan sebagai alat untuk mengeluarkan isi buah dan juga kegiatan dilakukan dengan posisi membungkuk dan duduk melantai dalam waktu yang cukup lama sehingga cepat merasakan lelah. Dari permasalahan tersebut penulis melakukan identifikasi terhadap postur kerja bagian pengambilan bulir dan merancang mesin pengeruk markisa. Metode yang digunakan adalah menggunakan kuisioner NBM dan metode RULA (Rapid Upper Limb Assessment) untuk mendapatkan level tindakan terhadap postur operator untuk memperbaiki gerakan tubuh. Hasil penelitian menunjukkan bahwa postur kerja pada kegiatan pengambilan bulir dengan cara mengeruk isi buah dari skor RULA yaitu 6 dengan action level 3 artinya investigasi dan perubahan postur kerja harus dilakukan secepatnya.
Pengukuran Beban Kerja pada Divisi Assembling dan Packaging di PT. Jati Jaya Perkasa Mandiri Kabupaten Maros Basri, Muhammad; Arminas, Arminas; Pangeran, Aulid Rahmat
ARIKA Vol 17 No 2 (2023)
Publisher : Industrial Engineering Study Program, Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/arika.2023.17.2.100

Abstract

Meningkatnya perkembangan dalam dunia industri saat ini, perusahaan dituntut mampu bersaing dan berkompetisi untuk meningkatan produktivitas. Untuk menunjang peningkatan produktivitas, pekerja harus melakukan aktivitas seoptimal mungkin. Pada PT. Jati Jaya Perkasa Mandiri Maros tidak demikian karena pada divisi Assembling dan Packaging sering terjadi Idle Time. salah satunya terjadi pada proses finger joint, adanya penumpukan kayu karena proses pengerjaan yang lama dan hanya dikerjakan oleh 1 pekerja, Sehingga pada proses pengeleman terkadang menunggu kayu yang siap untuk dilem. Hal tersebut menunjukkan bahwa terjadi ketidakseimbangan beban kerja pada pekerja. Oleh karena itu perlu adanya suatu perhitungan beban kerja untuk menyeimbangkan beban kerja pekerja optimal. Penelitian ini bertujuan untuk menentukan waktu baku dan nilai beban kerja pada Divisi Assembling dan Packaging di PT. Jati Jaya Perkasa Mandiri Maros. Pada penelitian ini menentukan waktu baku dan penentuan jumlah pekerja pada divisi Assembling dan Packaging dengan menggunakan Stopwatch Time Study. Selanjutnya dilakukan analisa beban kerja setiap pekerja. Apabila terdapat beban kerja terendah atau melebihi 100%, maka dilakukan perubahan jumlah pekerja pada workstation tersebut. Dari hasil penelitian ini didapatkan bahwa beban kerja pada divisi Assembling dan Packaging masih belum optimal. Berikut nilai beban kerja pada operator 1,2 dan 3 Workstation Assembling, operator 4 dan 5 Workstation Pengeleman, operator 6,7,8 Workstation Pressing, operator 9,10,11 Workstation Sanding dan operator 12,13,14 dan 15 Workstation Packaging dalam menjalankan kerjanya masing-masing adalah 48,31%, 195,90%, 58,95%, 106,29%, 88,05%, 47,08%, 105,95%, 55,07% dan 51,76%. Maka dari itu dilakukan keseimbangan beban kerja, pada Workstation Assembling dilakukan pemindahan 1 operator dari EK 1a ke 1b sehingga beban kerja pada 1b tidak akan melebihi nilai 100%. Pada Workstation Pengeleman dilakukan penambahan operator sehingga nilai beban kerja yang diterima berkurang. Sedangkan pada Workstation Sanding dilakukan pengurangan 1 pekerja, sehinga beban kerja yang diterima bisa optimal.
MACHINE LEARNING MODELS FOR PREDICTING STRESS VALUE IN THE TENSILE STRENGTH OF BIOFILMS FROM STARCH AND HAIR WASTE Utami, Hermin Hardyanti; Fitrah, Muhammad Aqdar; Yusriadi, Yusriadi; Ardiansah, Ardiansah; Arminas, Arminas; Lestari, Mega Fia; Towolioe, Sherly
JURNAL PENA SAINS Vol 11, No 2 (2024): Jurnal Pena Sains
Publisher : Program Studi Pendidikan IPA, Fakultas Ilmu Pendidikan, Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/jps.v11i2.26227

Abstract

Biofilms, structured communities of microorganisms, have emerged as a subject of significant interest across various industries due to their unique biodegradable and sustainable characteristics. Hair waste is an incredibly rich source of keratin, and this abundance makes it a promising candidate as a fundamental building block for the development of biodegradable plastics. This study focuses on sustainable biofilms derived from biodegradable materials, specifically a unique combination of starch and hair waste. Machine Learning models, implemented in RapidMiner, were utilized to predict the tensile strength of these biofilms, with the goal of enhancing quality control in their production. Neural Networks and Deep Learning methods were employed to compare their predictive capabilities, assessing both their strengths and limitations. Through rigorous data collection, feature identification, and detailed data analysis, critical factors influencing the quality of the biofilms were identified. The results revealed the remarkable predictive accuracy of the Neural Net model, particularly for Ratio 40, while the performance of the Deep Learning model varied across different ratios. The lower RMSE of the Neural Net model indicated a more precise alignment between the predicted and actual values, distinguishing it as the superior model. This research contributes to the advancement of sustainable biofilm development, offering eco-friendly solutions through the use of unconventional materials. Both models offer valuable predictive capabilities, and the choice between them may depend on the specific requirements and contexts of the application. In conclusion, the performance of the Neural Net and Deep Learning models in predicting stress in tensile strength varies across different ratios.
THE MAINTENANCE INTERVAL OF PREBREAKER CRITICAL COMPONENTS USING RELIABILITY-CENTERED MAINTENANCE IN PT XYZ Haming, Puadi; Arminas, Arminas; Fajri, Nofias; Efendi, Dodi
Journal of Industrial Engineering Management Vol 8, No 1 (2023): Journal of Industrial Engineering and Management Vol 8 No 1
Publisher : Center for Study and Journal Management FTI UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33536/jiem.v8i1.1268

Abstract

PT XYZ is a crumb rubber company that produces SIR 10 and rubber smoke sheets (RSS). As the biggest crumb rubber-produced company in Indonesia PT XYZ makes the production process sustainable. The often problem in this company is machine breakdown that occurs downtime value to be high. The highest downtime value from October 2020 until March 2021 was the Prebreaker Machine whose total downtime value was 1875 minutes. The Reliability Centered Maintenance (RCM) method is used for decreasing downtime value. The RCM is integrated with Failure Mode Effect Analysis (FMEA) for analyzing The Highest Risk Priority Number (RPN). The research results that the optimal maintenance time of the Prebreaker Machine is 51 hours which means the Prebreaker Machine is maintained after operation for 51 hours.
Analisis Postur Kerja Aktivitas Pengangkatan Karung di PT. Indofood CBP Sukses Makmur Tbk. Cabang Makassar Arminas, Arminas
Jurnal Optimasi Sistem Industri Vol. 16 No. 1 (2017): Published in May 2017
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v16.n1.p58-67.2017

Abstract

PT. Indofood CBP Sukses Makmur Tbk is a company that works in the field of food processing industry which produces instant noodles, Indomie. At this company, human resource management gives a significant effect on the production sustainability and development. The observation that conducted in PT. Indofood CBP indicates that loading and delivering process are still using the manual procedure which uses human power with loading capacity around 25 kg. The observation focus on two working movement elements used by the screw machine workers consists of bending over when lifting and pouring the wheat flour sack resulted in worker’s frequent complaints related to the waist and backbone problems. The objective of this research is to discover the risk arising from lifting and delivering techniques used by the screw machine workers in PT. Indofood Sukses Makmur Tbk., then analyze the worker’s workload based on the observation result. Rapid Entire Body Assessment (REBA) method was used to analyze the data and it is concluded that lifting and pouring procedures used by the screw machinery workers in PT. Indofood CBP have a high risk of injury since the REBA scores of both activities is 5 or on the third level. This score means that immediate improvement on the working system is needed.
Penerapan Teknologi Tepat Guna Mesin Perajang Pisang Untuk Meningkatkan Produktivitas Olahan Pisang UMKM di Kabupaten Bantaeng Muhammad Aqdar Fitrah; Syaiful, Syaiful; Arminas, Arminas; Mahlina Ekawati
Abdimas Langkanae Vol. 5 No. 2 (2025): September-Desember 2025
Publisher : Pustaka Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53769/jpm.v5i2.581

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan nilai tambah, kualitas, daya saing produk UMKM, keberlanjutan usaha dan  memperluas jangkuan pasarnya. Produktivitas UMKM olahan pisang melalui suatu penerapan teknologi tepat guna berupa mesin perajang pisang. Permasalahan utama pada UMKM mitra adalah rendahnya kapasitas produksi dan ketidakkonsistenan ukuran irisan pisang akibat proses perajangan yang masih dilakukan secara manual. Melalui program ini dilakukan suatu perancangan, pembuatan, pelatihan penggunaan, serta pendampingan operasional mesin perajang pisang. Hasil kegiatan menunjukkan adanya peningkatan signifikan pada kapasitas produksi, efisiensi waktu, dan kualitas produk. Selain itu, UMKM mitra memperoleh pengetahuan dalam membangun fondasi keterampilan dan wawasan terhadap usahanya, agar mampu bertransformasi menjadi usaha yang lebih profesional, inovatif, dan kompetitif.
Edukasi Keamanan AWS: Mengamankan Akun, Data, dan Kepatuhan Cloud dengan AWS IAM Hamdani, Ibnu Mansyur; Syahadi, Adi; Julyaningsih, A. Hermina; Arminas, Arminas
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 1 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Cloud computing service security is a crucial aspect in managing data and information technology infrastructure. Amazon Web Services (AWS) provides security features such as AWS Identity and Access Management (IAM) to control access to resources. However, the lack of user understanding in implementing this system increases the risk of data leaks and cyber attacks. This community service activity aims to improve digital security literacy, especially in the use of AWS IAM. The training was held online on February 2, 2025 via Zoom and was attended by 24 participants from a total of 30 registrants. The methods used include theory and direct practice using an AWS Academy account. Evaluation was carried out through pre-tests and post-tests as well as a Google Form survey. The results showed an increase in understanding with an average pre-test score of 60 increasing to 85 in the post-test. In addition, 92% of participants stated that the material presented was relevant, 88% felt the training was practically useful, and 90% were more confident in managing their AWS accounts. These results show that education about AWS security is essential to reduce the risk of misconfiguration and improve the security of cloud-based systems.
Co-Authors A. Hermina Julyaningsih Aqdar Fitrah, Muhammad Ardiansah, Ardiansah Efendi, Dodi Ekawati, Mahlina Fajri, Nofias Hamdani, Ibnu Mansyur Haming, Puadi Mega Fia Lestari Muhammad Aqdar Fitrah Muhammad Basri Pangeran, Aulid Rahmat Syahadi, Adi Syaiful . Towolioe, Sherly Utami, Hermin Hardyanti Yusriadi Yusriadi