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INDONESIA
J@TI (TEKNIK INDUSTRI)
Published by Universitas Diponegoro
ISSN : -     EISSN : 25021516     DOI : -
Core Subject : Engineering,
Industrial & Manufacturing Engineering
J@ti Undip: Jurnal Teknik Industri [e-ISSN 2502-1516] merupakan jurnal nasional yang mengangkat tulisan-tulisan penelitian dalam disiplin ilmu teknik industri. Pertama kali terbit sejak tahun 2006 hingga saat ini dengan frekuensi terbit tiga (3) kali dalam setahun. Setiap edisi terbitan berisi 8 artikel jurnal. Terbit setiap Januari, Mei, dan September.
Arjuna Subject : -
Articles 465 Documents
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PENGARUH ERGONOMI LINGKUNGAN KERJA TERHADAP KESELAMATAN OPERATOR MESIN DI PERUSAHAAN ELEKTRONIK XYZ Maisyaroh, Rizki; Irawan, Hery
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.1.1.66-75

Abstract

Keselamatan kerja operator mesin masih menjadi permasalahan penting dalam industri, khususnya terkait dengan kondisi ergonomi lingkungan kerja. Lingkungan kerja yang tidak ergonomis dapat meningkatkan risiko kecelakaan kerja dan keluhan kesehatan musculoskeletal. Penelitian ini bertujuan untuk menganalisis pengaruh aspek ergonomi lingkungan kerja terhadap keselamatan operator mesin, yang mencakup postur kerja, jarak pandang, kebisingan, getaran, dan penggunaan alat pelindung. Metode yang digunakan adalah observasional deskriptif dengan pendekatan kuantitatif, melalui kuesioner dan lembar observasi checklist penilaian ergonomi dan keselamatan pada 10 operator mesin selama periode observasi tertentu. Hasil penelitian menunjukkan bahwa ergonomi lingkungan kerja berpengaruh positif terhadap keselamatan operator mesin, sebagian besar aspek ergonomi berada pada kategori cukup baik, namun masih ditemukan aspek-aspek yang perlu ditingkatkan seperti tanda kelelahan otot dan kepatuhan prosedur. Penilaian keselamatan kerja juga menunjukkan adanya insiden ringan dan keluhan kesehatan ringan yang masih terjadi. Penelitian ini menyimpulkan bahwa ergonomi lingkungan kerja memiliki pengaruh signifikan terhadap tingkat keselamatan operator mesin, sehingga perlu perhatian dan perbaikan secara berkelanjutan untuk meminimalkan risiko kecelakaan dan meningkatkan produktivitas.  Abstract[The Influence of Work Environmental Ergonomics on Machine Operator Safety In XYZ Electronics Company] Machine operator safety remains a critical issue in industrial environments, especially regarding the ergonomics of the workplace. Poor ergonomic conditions can increase the risk of work-related accidents and musculoskeletal health complaints. This study aims to analyze the effect of workplace ergonomic aspects on the safety of machine operators, focusing on body posture, viewing distance, noise levels, vibration intensity, and the use of protective equipment. The method used is a descriptive observational approach with quantitative analysis, employing ergonomic and safety assessment checklists on 10 machine operators over a specific observation period. The results show that most ergonomic aspects are in a fairly good category; however, issues such as muscle fatigue symptoms and compliance with procedures still require improvement. Safety assessments also revealed minor incidents and mild health complaints among the workers. This study concludes that workplace ergonomics significantly affect operator safety, highlighting the need for continuous improvements to reduce accident risks and enhance productivity.Keywords: ergonomics; occupational safety; machine operator; work environment; workplace accidents
THE INFLUENCE OF AVAILABILITY AND PROMOTION ON CUSTOMER RETENTION WITH THE CUSTOMER SATISFACTION AS A MEDIATING VARIABLE – A LITERATURE REVIEW ON THE PERSONAL CARE INDUSTRY Tjoeanda, Christopher Andrew; Hartono, Markus
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.1.1.17-27

Abstract

The personal care industry relies on product innovation, distribution, and promotional strategies as key factors for business success. Product availability and effective promotion play crucial roles in customer satisfaction and retention. However, limited research discusses how these two aspects interact and affect business sustainability in the personal care industry. To address this gap, this literature examines how prior studies have conceptualized and examined the relationships among product availability, promotion, customer satisfaction, and customer retention within the personal care industry. Relevant studies from marketing and distribution were systematically reviewed, using publications collected from ScienceDirect. We initially gathered 3,491 articles related to personal care, restricted to the last ten years, classified as research articles, and aligned with keywords such as marketing, promotion, advertising, discounting, branding, product completeness, and product availability. From this process, ten key journal articles were selected for further analysis. The findings reveal that product availability enhances customer satisfaction and encourages repeat purchases, while promotional strategies foster positive product perceptions and strengthen brand awareness. Together, these strategies provide a cohesive approach that significantly impacts customer retention. Overall, this study highlights the importance of combining product availability and promotional efforts to improve customer experience and support long-term success in the personal care industry. However, this study is limited to a conceptual framework and does not yet test the proposed relationships empirically. Future research is recommended to validate this structural model through application in real-world cases within the personal care industry, which would provide stronger practical insights and implications for both academics and practitioners.
STUDI KOMPARATIF MODEL MACHINE LEARNING DALAM MEMPREDIKSI KETERLAMBATAN PEGAWAI: LOGISTIC REGRESSION, SVM, DAN RANDOM FOREST Palupi, Inggrid Nindia Aprila; Mardianto, M Fariz Fadillah; Yuadi, Imam; Mariyadi, Budiyan
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.21.1.76-87

Abstract

Keterlambatan karyawan adalah salah satu jenis pelanggaran terhadap disiplin kerja yang dapat berdampak pada produktivitas dan efektivitas organisasi. Penelitian ini bertujuan untuk mengembangkan serta membandingkan performa dari tiga algoritma machine learning Regresi Logistik, SVM, dan Random Forest dalam memprediksi keterlambatan pegawai dengan menggunakan data keterlambatan dan karakteristik individu. Dataset yang digunakan terdiri dari 1902 data, yang dibagi 80% data training dan 20% data testing dengan enam variabel, mencakup usia, lama bekerja, status pernikahan, jarak tempat tinggal ke kantor, jenis kendaraan yang digunakan, dan gaya hidup. Hasil analisis menunjukkan bahwa Random Forest memberikan kinerja prediktif yang paling baik dalam mengenali pegawai yang memiliki potensi untuk terlambat, dengan nilai akurasi tertinggi sebesar 0.82, presisi sebesar 0.93, recall sebesar 0.84, dan F1-score sebesar 0.88. Model ini terbukti dapat menunjukkan kemampuan klasifikasi yang andal dan seimbang. Analisis feature importance mengidentifikasi usia dan masa kerja sebagai faktor paling berpengaruh terhadap prediksi keterlambatan. Temuan ini tidak hanya memberikan wawasan baru dalam pengelolaan kedisiplinan pegawai, tetapi juga membuka peluang implementasi sistem peringatan dini yang dapat diintegrasikan ke dalam sistem kehadiran digital organisasi. Penelitian ini merekomendasikan perluasan variabel untuk studi lanjutan dan pemanfaatan hasil model sebagai dasar penyusunan kebijakan SDM yang lebih adaptif dan berbasis data. Abstract[Comparative Study of Machine Learning Models in Predicting Employee Delay: Logistic Regression, SVM, and Random Forest] Employee tardiness is one type of violation of work discipline that can impact organizational productivity and effectiveness. This study aims to develop and compare the performance of three machine learning algorithms Logistic Regression, SVM, and Random Forest in predicting employee tardiness using tardiness data and individual characteristics. The dataset used consists of 1902 data, which is divided into 80% training data and 20% with six variables, including age, length of service, last education level, marital status, distance from residence to office, type of vehicle used, and lifestyle. The results of the analysis show that Random Forest provides the best predictive performance in identifying employees who have the potential to be late, with the highest accuracy value of 0.82, precision of 0.93, recall of 0.84, and F1-score of 0.88. This model is proven to be able to demonstrate reliable and balanced classification capabilities. Feature importance analysis identifies age and length of service as the most influential factors in predicting tardiness. These findings not only provide new insights into employee discipline management but also open up opportunities for the implementation of an early warning system that can be integrated into the organization's digital attendance system. This study recommends expanding the variables for further studies and utilizing the model results as a basis for formulating more adaptive and data-based HR policies.Keywords: sustainability industry; developing strategy; MCDM
PENGEMBANGAN KERANGKA EVALUASI APLIKASI EDUKASI ANAK USIA DINI: INTEGRASI INDIKATOR KOGNITIF, INTERAKTIVITAS, DAN SOSIAL KONTEKSTUAL Yuviananda, Lukita; Dewi, Ratna Sari
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.1.1.28-37

Abstract

Perkembangan teknologi digital telah mendorong munculnya berbagai aplikasi edukatif untuk anak usia dini (2 hingga 6 tahun). Namun, hingga saat ini sebagian besar aplikasi tersebut belum dirancang secara optimal sesuai dengan prinsip perkembangan anak, terutama dalam hal seperti beban kognitif, interaktivitas, dan sosial kontekstual. Penelitian ini bertujuan untuk mengidentifikasi dan mengelompokkan indikator krusial yang seharusnya dimiliki oleh aplikasi pendidikan anak usia dini, guna mendukung proses pembelajaran yang efektif, menyenangkan dan sesuai dengan tahap perkembangan mereka. Metode yang digunakan yaitu menggabungkan literatur review, aplikasi aktual dan kuesioner berbasis expert judgement, dengan melibatkan tiga kelompok yaitu pengembang aplikasi pendidikan, guru taman kanak-kanak, dan orang tua murid. Sebanyak 55 indikator dievaluasi, dikaji serta dianalisis menggunakan pendekatan Relative Importance Index (RII). Hasilnya menunjukkan bahwa terdapat 28 indikator dinilai penting oleh para ahli, yang kemudian hasil tersebut diklasifikasikan ke dalam tiga dimensi utama yaitu (1) faktor kognitif dan pembelajaran, (2) faktor interaktivitas dan teknologi, serta (3) faktor sosial dan kontekstual. Temuan ini menghasilkan sebuah kerangka evaluasi multidimensi yang dapat dijadikan sebagai acuan dalam perancangan dan penilaian aplikasi pendidikan anak usia dini yang lebih efektif dan sesuai dengan tahapan perkembangan anak usia dini.  Abstract[Development of an Evaluation Framework for Early Childhood Educational Application: Integrating Cognitive, Interactivity and Social Contextual Aspect] The advancement of digital technology has led to the emergence of various educational applications for early childhood (age 2 to 6). However, most of these applications have not been optimally designed in accordance with child development principles, particularly regarding cognitive load, interactivity, and socio contextual aspects. This study aims to identify and categorize the key indicators that should be incorporated into early childhood educational applications to support effective, enjoyable, and developmentally appropriate learning experiences. The method combines a literature review, analysis of existing applications, and an expert judgement based questionnaire involving three groups such as educational application  developers, kindergarten teachers, and parents. A total of 55 indicators were evaluated and analyzed using the Relative Importance Index (RII) approach. The findings reveal that 30 indicators were rated as important by the experts, which were then classified into three main dimensions such as (1) cognitive and learning factors, (2) interactivity and technology factors, and (3) social and contextual factors. These results form a multidimensional evaluation framework that can serve as a reference for designing and assessing early childhood educational applications that are more effective and aligned with children’s developmental stages.Keywords: cognitive load; early childhood educational application; interactivity; multidimensional evaluation; social context
PERANCANGAN MEKANISME PENILAIAN DAN EVALUASI KINERJA SUPPLIER PADA PUSAT PENJUALAN DAN DISTRIBUSI X DENGAN PENDEKATAN FUZZY MULTI-CRITERIA DECISION MAKING (FMCDM) DAN ISM-FUZZY MICMAC Prihartono, Budhi; Darmawan, Rachel Aliya; Kamilah, Mursyida; Rizkiana, Aldila
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.1.1.47-57

Abstract

Pusat penjualan dan distribusi X mengalami penurunan penjualan yang besar pada tahun 2021–2023. Hal ini disebabkan oleh disrupsi eksternal, seperti pandemi global dan perubahan teknologi. Analisis internal menunjukkan kelemahan supplier, terutama dalam ketepatan pengiriman, kualitas produk, dan penanganan klaim. Ketiadaan mekanisme evaluasi supplier yang formal dan terstruktur berisiko menghambat pemulihan kondisi dan menurunkan daya saing operasional jangka panjang. Penelitian ini bertujuan membuat mekanisme penilaian dan evaluasi kinerja supplier yang strategis dan selaras dengan tujuan bisnis, dengan mengacu pada standar internasional seperti ISO 9001 dan Framework of Standards to Secure and Facilitate Global Trade (SAFE FoS). Metode penelitian menggunakan pendekatan kualitatif dan kuantitatif, termasuk gap analysis untuk merumuskan tujuan strategis dan mengembangkan kriteria yang divalidasi melalui literatur dan wawancara pemangku kepentingan. Pembobotan kriteria dilakukan dengan Fuzzy Multi-Criteria Decision Making (FMCDM), lalu pemetaan hierarkis menggunakan ISM–Fuzzy MICMAC. Hasil penelitian berupa structured scorecard, indikator, dan protokol evaluasi yang diformalkan dalam prosedur standar untuk supplier baru maupun yang sudah ada. Sistem ini memungkinkan pemantauan berkelanjutan dan penilaian objektif, sehingga meningkatkan manajemen risiko pengadaan dan mendukung efisiensi operasional pusat penjualan dan distribusi X. Abstract[Design of Supplier Performance Assessment and Evaluation Mechanism at Sales and Distribution Center X Using Fuzzy Multi-Criteria Decision Making (FMCDM) and ISM-Fuzzy MICMAC Approach]Sales and distribution center X sales decline from 2021 to 2023 due to the external disruptions, like the global pandemic and changes in technology demand. Internal analysis showed weak supplier performance, especially in on-time delivery, product quality, and claim handling. No formal and clear supplier evaluation system risks slowing recovery and cutting long-term competitiveness. This study aims to make a strategic supplier assessment and evaluation system that matches business goals and follows global standards like ISO 9001 and the Framework of Standards to Secure and Facilitate Global Trade (SAFE FoS). The study uses both qualitative and quantitative methods, including gap analysis to set goals and build criteria, checked by literature and interviews with stakeholders. Criteria are weighted with Fuzzy Multi-Criteria Decision Making (FMCDM) and hierarchical mapping with ISM–Fuzzy MICMAC. The research output includes a structured scorecard, indicators, and standard evaluation steps that helps ongoing monitoring, fair assessment, and higher operational efficiency.Keywords: Fuzzy Multi-Criteria Decision Making (FMCDM); Interpretive Structural Modeling (ISM); Matrice d'Impacts Croisés Appliquée à un Classement (MICMAC); supplier performance; performance assessment indicators

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