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All Journal Unistek: Jurnal Pendidikan dan Aplikasi Industri Science and Education Journal Jurnal Penelitian Teknologi Informasi dan Sains
Mochamad Eko Nugroho
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Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Social Sciences

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Peningkatan Akurasi Stock Opname Material Local Parts Menggunakan CCM, FMEA, dan FTA: Sebuah Studi tentang Pengendalian Persediaan dan Ketepatan Penghitungan Stok Cinta Cinta; Mochamad Eko Nugroho; Lifia Citra Ramadhanti
UNISTEK Vol. 13 No. 2 (2026): Agustus 2026 - Februari 2027
Publisher : UNIVERSITAS ISLAM SYEKH YUSUF TANGERANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33592/unistek.v13i2.8917

Abstract

Inventory is an important asset that supports the continuity of production processes in manufacturing companies. One of the common problems is the discrepancy between physical inventory and system records during stock opname activities, which may cause financial losses and reduce inventory accuracy. This study aims to identify the causes of stock opname discrepancies and improve inventory accuracy of Local Parts materials at PT Inoi Mobile Indonesia (IMI). The methods applied in this research include Failure Mode and Effect Analysis (FMEA), Cycle Counting Method Method (CCM) with ABC classification, and Fault Tree Analysis (FTA) based on the 5W+1H approach. Data were collected through observation, interviews, and company stock opname records. The results indicate that the main causes of inventory discrepancies are recording errors, operator negligence, and weak implementation of standard procedures. FMEA analysis shows that non-real-time material issuing has the highest Risk Priority Number (RPN), making it the primary improvement priority. ABC analysis reveals that category A materials contribute the highest cost impact on the company. Furthermore, FTA systematically identifies the root causes of stock discrepancies. The integration of these methods is proven to improve inventory accuracy and effectively reduce stock opname discrepancies.
Peningkatan Produktivitas Proses Mixing Mie Instan PT XYZ melalui Efisiensi Material Handling dengan Pendekatan Root Cause Analysis (RCA) dan Work Measurement Harry Praditia; Rakay Edhiargo Toyosito; Mochamad Eko Nugroho
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 3 (2026): September: JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i3.4790

Abstract

This study aims to improve the productivity of the mixing process at PT XYZ by optimizing the efficiency of the material handling system. Based on production data from October 2025 to March 2026, the average utilization of the mixing machine reached 91.87%, exceeding the company's KPI target of 90% but still leaving an 8.13% gap toward the 100% design capacity. The analysis of downtime data revealed that idling minor stop caused by delays in material supply was the largest contributor, accounting for 60% (180 hours) of the total 300 hours of downtime. To identify the root cause, this study applied a Root Cause Analysis (RCA) approach using a fishbone diagram and the 5 Whys method, while Work Measurement was conducted using the stopwatch time study technique to establish the standard time for material handling activities. The findings indicate that inefficiency was caused by four main factors: the absence of standard work time, non-standardized work methods, poor coordination between operators, and the long distance between the warehouse and the mixing machine. The recommended improvements include implementing a material handling SOP, applying a scheduled material staging system, and using standard time as a reference for operators. The simulation shows that these proposals can reduce waiting time by 90 hours and increase machine utilization to 94.37%. Therefore, productivity improvement can be achieved without investment in new machinery.
Integrasi Metode Six Sigma, Root Cause Analysis (RCA) dan Statistical Process Control (SPC) dalam Meminimalisir Jumlah Reject Packing PT XYZ Mochamad Eko Nugroho; Awan Irawan; Abby Yazid Bustommy
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 3 (2026): September: JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i3.4820

Abstract

Industri makanan merupakan salah satu sektor yang berkontribusi besar terhadap Produk Domestik Bruto (PDB) Indonesia, dan PT XYZ menjadi salah satu pabrik terbesar yang memproduksi produk makanan dan minuman dalam grupnya. Aktivitas produksi masih menghadapi permasalahan berupa tingginya jumlah reject pada proses packing yang berdampak pada penurunan efisiensi dan peningkatan biaya operasional. Penelitian ini bertujuan menganalisis penyebab reject packing serta merumuskan dan mengevaluasi solusi perbaikan melalui integrasi metode Statistical Process Control (SPC), Root Cause Analysis (RCA), dan Six Sigma. Data reject periode April–September 2025 dianalisis menggunakan SPC, perhitungan DPMO dan level sigma, diagram Fishbone, serta rekomendasi perbaikan dengan metode 5W+1H. Hasil penelitian menunjukkan bahwa reject tertinggi terjadi pada primary packaging dengan jumlah 514.874 unit, terutama pada mesin A1 dan A2 di Area Produksi A, dengan level sigma masing-masing 3,241 dan 3,499. Faktor penyebab utama berasal dari aspek manusia, mesin, metode, dan material. Setelah penerapan usulan perbaikan, tingkat reject primary packaging menurun dari 4,27% menjadi 0,55% atau berkurang sebesar 3,72 poin persentase. Temuan ini menunjukkan bahwa integrasi SPC, RCA, dan Six Sigma efektif dalam mengurangi reject packing serta meningkatkan kualitas dan efisiensi produksi di PT XYZ.
Pengendalian Persediaan Perangkat Jaringan dengan menggunakan Root Cause Analysis (RCA), Trend Projection, Part Period Balancing (PPB), Reorder Point (ROP) di Industri Internet Service Provider Lifia Citra Ramadhanti; Nurarofah; Mochamad Eko Nugroho
Science and Education Journal (SICEDU) Vol 5 No 3 (2026): Science and Education Journal 2026
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/sicedu.v5i3.1126

Abstract

The inventory control system at ISP company has not been optimally implemented, resulting in frequent stock-outs, high emergency purchasing frequency, and increased inventory costs due to the absence of a systematic approach for determining inventory requirements, optimal order quantities, and reorder timing. This study aims to identify the root causes of stock-outs using Root Cause Analysis (RCA), forecast inventory demand using the Trend Projection method, determine the optimal order quantity using Part Period Balancing (PPB), and establish the appropriate Reorder Point using the Reorder Point (ROP) method. This research employed a quantitative descriptive approach using inventory, demand, and purchasing data from January to December 2025 for seven fast-moving inventory items, namely ONT, Pathcore, Cable Clamps, Connector Pins, Adhesive Tape, Adapters, and Fiber Optic Cables. The results indicate that the primary causes of stock-outs are related to human factors, methods, materials, and the working environment. The Trend Projection method successfully generated demand forecasts that can serve as the basis for future inventory planning. The implementation of the PPB method produced more optimal order quantities by balancing ordering and holding costs, while the ROP method determined appropriate Reorder Points to ensure replenishment before inventory reached critical levels. Therefore, the integration of RCA, Trend Projection, PPB, and ROP proved effective in improving inventory control, reducing the risk of stock-outs, minimizing inventory costs, and supporting warehouse operational efficiency at PT AST.
Co-Authors Abby Yazid Bustommy Awan Irawan Cinta Cinta Harry Praditia Lifia Citra Ramadhanti LIFIA CITRA RAMADHANTI Nurarofah Rakay Edhiargo Toyosito