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All Journal OPERATION EXCELLENCE: Journal of Applied Industrial Engineering Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat (ABDIRA) International Journal of Innovation in Mechanical Engineering and Advanced Materials JIPITI: Jurnal Pengabdian kepada Masyarakat
Chairat, Arief Suardi Nur
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Aerospace Engineering Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Nursing Social Sciences Other

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Optimization of soybean distribution costs with the transportation method: a case in SME’s Chairat, Arief Suardi Nur; Caswito, Ade; Octavia, Lia Nur; Asnul, Nur Shania; Fauziah, Annisa; Bahasoan, Alisya Sulifianti
Operations Excellence: Journal of Applied Industrial Engineering Vol. 16, No. 1, (2024): OE March 2024
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2024.v16.i1.098

Abstract

The distribution of soybean raw materials is not only related to aspects of quality and smooth production of tofu making but can also influence cost efficiency to increase competitiveness. In this situation, the number of soybeans shipped, transportation costs per unit, and the choice of transportation service used are transportation model issues. This research aims to determine the cheapest cost of sending soybean raw materials from four agent locations to three tofu factory locations with a choice of two transportation services that can be adopted. The case studied is a case of unbalanced transportation with supply greater than demand. The method used is the application of a transportation model, with the Northwest Corner method to determine the initial base solution and the Modified Distribution method to optimize distribution costs for soybean raw materials in the context of tofu production supply. Based on data processing, the results showed that the first and second transportation services offered services with a total shipping cost of IDR 691,750 and IDR 605,250. Observation of these differences leads to the conclusion that the second transportation service offers the most optimal value for money. The research results provide additional knowledge for tofu makers in optimizing costs and delivery routes for soybean raw materials, supporting production continuity, and increasing competitiveness in an ever-changing market.
Implementasi Strategi Digital Marketing dalam Meningkatkan Daya Saing UMKM Caswito, Ade; Aulia, Annisa Risqina Putri; Aisal, Naufal Yurfana; Lisdiana, Lisdiana; Chairat, Arief Suardi Nur; Ridwan, Muhammad
JIPITI: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 3 (2025): Agustus 2025 - JIPITI: Jurnal Pengabdian kepada Masyarakat
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Kegiatan pengabdian kepada masyarakat dilakukan pada UMKM bertujuan untuk mengimplementasikan strategi digital marketing dalam mengoptimalkan UMKM, yang bergerak dalam produksi produk lokal. Digital marketing, melalui sosial medial, SEO, dan iklan digital, diharapkan dapat meningkatkan jangkauan pasar UMKM. Metode yang digunakan adalah pengabdian kepada masyarakat (pengmas), dalam memberikan  kepada seluruh pengelola atau pelaku UMKM. Hasil pada pengabdian kepada masyarakat ini menunjukkan bahwa penerapan strategi digital marketing berhasil meningkatkan visibilitas merk dan menarik pelanggan, yang berdampak pada peningkatan penjualan. Kesimpulannya, strategi digital marketing efektif dalam mengoptimalkan kinerja UMKM dan meningkatkan kontribusinya terhadap perekonomian lokal, dengan saran untuk melanjutkan pengembangan dan penerapan teknologi digital di masa depan.
Impact of Extended Intervals on Diesel Engine Performance with 15W-40 DH1 Lubricant Oil Suprihatiningsih, Wiwit; Priyanto, Arief; Nurato, Nurato; Chairat, Arief Suardi Nur; Prumanto, Denny
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 6, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v6i2.25014

Abstract

Engine lubricant oil is crucial for minimizing friction between moving components within an engine, directly influencing the engine's reliability and lifespan. Determining the appropriate oil replacement intervals is essential, as extending these intervals necessitates more rigorous monitoring of both oil quality and engine condition. This study investigated the performance of SAKAI 15W-40 DH1 engine oil in the SAKAI Vibrating Roller SV526 over varying operational periods: 125 hours, 250 hours, 375 hours, and 500 hours. The research involved analyzing oil samples for viscosity, metal additives, total base number (TBN), and contaminants using Fourier Transform Infrared Spectroscopy (FTIR). Additionally, key engine performance indicators, including fuel consumption, valve clearance, and compression pressure, were measured. The findings revealed a gradual decrease in oil viscosity from 13.48 cSt to 11.56 cSt, approaching the minimum acceptable threshold of 11.45 cSt. Concurrently, the Fe content in the oil increased to 11 ppm, indicating wear, while the valve clearance in cylinder number three expanded to 0.48 mm, and compression pressure dropped from 31 kg/cm² to 28 kg/cm². Despite these changes, the oil remained within the standard operational limits, and the engine continued to perform adequately. However, based on the observed trends, extending the oil replacement interval to 500 hours cannot be conclusively recommended, as the oil's condition and engine performance may begin to decline beyond this point.
Pengenalan Energi Baru Terbarukan melalui Media Pembelajaran Interaktif pada Tingkat Pendidikan Dasar Chairat, Arief Suardi Nur; Ridwan, Muhammad; Prayudi, Prayudi; Sany, Nasril; Dody, Dody; Kusumastuti, Dyah Pratiwi; Vaza, Hery; Asnul, Nur Shania
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 6, No 1 (2026): Abdira
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v6i1.1216

Abstract

Global warming has become a major concern due to its impacts on the environment and human life. One way to reduce these impacts is by increasing the use of renewable energy. Introducing the concept of renewable energy at the elementary school level is expected to foster students’ awareness and understanding of the importance of using clean energy. This Community Service (PkM) program aims to enhance the knowledge and understanding of students and teachers at SD Islam Al Azhar 5, West Jakarta, regarding solar-based renewable energy through an interactive learning approach. The activities were carried out in several stages, including survey, socialization, training, evaluation, and sustainability. The socialization session was delivered through material presentations supported by engaging visual media, while the training involved assembling toys powered by solar energy. The results showed strong enthusiasm, improved understanding of renewable energy among students and teachers, and enhanced teacher skills in implementing interactive learning. This program also encouraged greater awareness of the importance of adopting renewable energy in daily life.
Comparative Sentiment Analysis of YouTube Comments on Indonesia's Electric Vehicle Incentive Policy Using TF-IDF and IndoBERTweet Models Chairat, Arief Suardi Nur; Rizal, Randi; Himawan, Hidayatulah
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5499

Abstract

Indonesia’s battery electric vehicle (KBLBB) incentives aim to accelerate low-carbon mobility, yet public reactions regarding affordability, charging infrastructure readiness, and subsidy equity remain highly heterogeneous. This research systematically compares classical machine learning and transformer-based models for classifying sentiment in 1,516 YouTube comments discussing the incentive policy and broader EV ecosystem. Comments are collected via web scraping and processed through filtering, case folding, normalization, tokenization, stopword removal, stemming, lexicon-based sentiment labelling, TF-IDF bigram vectorization, random oversampling, and hyperparameter optimization with GridSearch. Support Vector Machine and Random Forest serve as baseline models, while Logistic Regression with TF-IDF bigram and IndoBERTweet represent advanced approaches that exploit richer feature representations. Results show that the baseline models achieve around 65–66% accuracy, Logistic Regression improves performance to 88%, and IndoBERTweet attains the highest accuracy of 94% with balanced precision, recall, and F1-score across sentiment classes. Sentiment distribution indicates that 63.3% of comments are negative, dominated by concerns over limited charging networks, high upfront costs, and perceived unfairness of public subsidies, while 36.7% of comments highlight support for cleaner transportation, technological innovation, and national industrial competitiveness. These findings demonstrate that transformer-based contextual embeddings substantially enhance sentiment classification for noisy Indonesian social media text and provide a scalable informatics tool for continuous monitoring of EV policy reception. The resulting empirical evidence can inform more targeted refinements of incentive design, infrastructure planning, and communication strategies, thereby supporting inclusive, data-driven, and sustainable KBLBB adoption across diverse demographic groups and evolving policy scenarios nationwide over time.
Co-Authors Aisal, Naufal Yurfana Annisa Fauziah, Annisa Asnul, Nur Shania Aulia, Annisa Risqina Putri Bahasoan, Alisya Sulifianti Caswito, Ade Dody, Dody Hidayatulah Himawan Kusumastuti, Dyah Pratiwi Lisdiana Lisdiana Muhammad Ridwan Nasril Sany Nurato Nurato, Nurato Octavia, Lia Nur Prayudi Prayudi Priyanto, Arief Prumanto, Denny Rizal, Randi Vaza, Hery Wiwit Suprihatiningsih