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ANALISIS KEBIJAKAN PERSEDIAAN AIR BERSIH DI KABUPATEN PONOROGO DENGAN PENDEKATAN SISTEM DINAMIS Nugraha, Isna; Donoriyanto, Dwi Sukma
Tekmapro Vol. 18 No. 2 (2023): TEKMAPRO
Publisher : Program Studi Teknik Industri Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/tekmapro.v18i2.333

Abstract

Air bersih merupakan kebutuhan pokok manusia yang vital untuk kelangsungan hidup dan kesejahteraan. Kabupaten Ponorogo sebagai salah satu daerah di Indonesia turut menghadapi tantangan dalam memastikan ketersediaan air bersih bagi penduduknya. Permasalahan kebijakan dalam pengelolaan persediaan air bersih di Kabupaten Ponorogo tidak dapat dipandang sebelah mata, melainkan memerlukan pemahaman mendalam dengan pendekatan yang holistik dan dinamis. Penelitian ini bertujuan untuk melakukan analisis mendalam terhadap kebijakan persediaan air bersih di Kabupaten Ponorogo dengan menggunakan pendekatan sistem dinamis. Melalui pendekatan ini, diharapkan dapat diidentifikasi poin-poin kritis dalam sistem yang memerlukan perhatian lebih, serta merumuskan kebijakan yang berkelanjutan dan mampu mengatasi tantangan yang terus berkembang dalam mengelola persediaan air bersih. Dari hasil penelitian didapat bahwa penambahan sumber air atau pengeboran sumber dapat meningkatkan persediaan air bersih di untuk memenuhi kebutuhan masyarakat Ponorogo. Selain itu dengan mererapkan kebijakan hemat air yaitu dengan mengurangi kebutuhan air per orang juga dapat meningkatkan persediaan air yang ada. Sebelum adanya kebijakan penambahan sumber air atau pengeboran sumber yaitu sebesar 3,29 juta m3. Sedangkan sesudah ditambah 8 sumber air maka naik sebesar 4,30 juta m3.
ANALISIS KETERSEDIAAN BERAS DI SURABAYA DENGAN PENDEKATAN SISTEM DINAMIS Donoriyanto, Dwi Sukma; Nugraha, Isna; Ardlianti , Rana Atikah
Tekmapro Vol. 18 No. 2 (2023): TEKMAPRO
Publisher : Program Studi Teknik Industri Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/tekmapro.v18i2.334

Abstract

Kota Surabaya salah satu kota di Provinsi Jawa Timur dengan tingkat jumlah penduduk setiap tahun yang terus meningkat yang menyebabkan kebutuhan untuk konsumsi panganan pokok beras semakin banyak dan berdampak pada ketersediaan beras yang semakin menipis serta krisis beras di kemudian hari. Serta lahan pertanian yang terus berkurang setiap tahunnya dimana dipergunakan untuk perumahan maupun industri. Dengan permasalahan diatas penelitian ini bertujuan untuk menganalisis kebijakan ketersediaan beras di surabaya pada masa mendatang guna memberikan alternatif kebijakan untuk meningkatkan ketersediaan beras. Penyelesaian pada penelitian ini adalah menggunakan metode pendekatan sistem dinamis, dengan langkah awal pembuatan model causal loop diagram, lalu stock flow diagram hingga simulasi dengan bantuan software vensim. Hasil yang didapatkan adalah dengan adanya kebijakan jumlah ketersediaan beras meningkat sebanyak 205.840 ton/tahun dan jumlah produksi beras sebanyak 287.216 ton/tahun. Dari hasil diatas bisa disimpulkan dengan adanya kebijakan untuk peningkatan produktivitas dapat meningkatkan hasil produksi beras dan ketersediaan beras begitu juga dengan kebijakan pengurangan lahan mutasi dapat berpengaruh juga dalam meningkatnnya ketersediaan beras dan produksi beras.
Analisis Kualitas Defect Produk Pupuk Dolomit dengan Metode New Seven Tools dan Failure Mode and Effect Analysis (FMEA) di PT. XYZ Prakosa, Albertus Adriyanto Satrio; Rochmoeljati, Rr.; Nugraha, Isna
Tekmapro Vol. 19 No. 2 (2024): TEKMAPRO
Publisher : Program Studi Teknik Industri Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/tekmapro.v19i2.414

Abstract

PT. XYZ merupakan perusahaan yang bergerak dalam industri pupuk dan bahan tambang dolomit. Standar mutu komposisi hara yang terdapat pada pupuk yang dimiliki oleh PT. XYZ antara lain kadar magnesium oksida (MgO) sebesar 18-22%, kadar kalsium oksida (CaO) sebesar 29-30%, kadar air (H2O) <1%, kehalusan (mesh 100) lolos 95%. Permasalahan yang masih sering terjadi di PT. XYZ adalah pupuk yang dihasilkan tidak sesuai dengan standar yang telah ditentukan. Penelitian ini bertujuan untuk mengetahui faktor-faktor penyebab kecacatan serta usulan perbaikan yang dapat dilakukan untuk mengurangi defect. New Seven Tools merupakan alat-alat bantu yang digunakan dalam eksplorasi kualitatif meliputi beberapa tahapan yaitu Affinity Diagram, Interrelationship Diagram, Tree Diagram, Matrix Diagram, Matrix Data Analysis, Activity Network Diagram, dan Process Decision Program Chart (PDPC). Failure Mode and Effect Analysis (FMEA) adalah suatu prosedur terstruktur untuk mengidentifikasi dan mencegah sebanyak mungkin mode kegagalan (failure mode) dengan menghitung Risk Priority Number (Severity x Occurrance x Detection). Berdasarkan hasil penelitian dapat diketahui faktor-faktor yang menjadi penyebab kecacatan antara lain faktor manusia, material, metode, mesin, dan lingkungan, serta diketahui kecacatan kehalusan dengan nilai Risk Priority Number (RPN) tertinggi yakni 567 yang berarti menjadi prioritas untuk dilakukan usulan perbaikan.
Analysis of the Influence of Raw Material Types for Clothing on the Level of Consumer Interest Aged 18-22 Years in Brand XYZ Nugraha, Isna; Kirana, Intania Widyantari; Khofiyah, Nida An; Ramadhan, Gilang
Tekmapro Vol. 20 No. 2 (2025): TEKMAPRO
Publisher : Program Studi Teknik Industri Universitas Pembangunan Nasional Veteran Jawa Timur

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

Abstract

Brand XYZ is a global apparel company that emphasizes comfort, durability, and design aesthetics in its product offerings. This study aims to examine the influence of clothing material type on purchase interest among consumers aged 18–22 years. A quantitative research approach was applied, using data collected from 50 respondents via a structured questionnaire on a 5-point Likert scale. Statistical analyses were performed using SPSS, including the Kolmogorov–Smirnov test for normality, a linearity test, Pearson correlation analysis, and simple linear regression. The results show that the data met the normality assumption (p = 0.859) and revealed a strong positive correlation between clothing material type and purchase interest (r = 0.810, p < 0.001). The regression model was found to be significant (F = 91.728, p < 0.001) with the equation Y=1.932+0.859XY = 1.932 + 0.859XY=1.932+0.859X and an R2R^2R2 value of 0.656, indicating that 65.6% of the variance in purchase interest can be explained by the clothing material type. The findings highlight the critical role of material selection in influencing consumer behavior. Practical recommendations for Brand XYZ include diversifying high-quality material options, improving transparency in fabric information, and implementing targeted consumer education campaigns to enhance brand loyalty and purchase intention.
Minimasi Biaya Persediaan Ikan Kakap Merah PT. MMU Metode Economic Order Quantity (EOQ) Arifin, Defitria Sabrina Firdaus; Nugraha, Isna
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 1 (2024): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i1.23540

Abstract

PT. MMU is an industry engaged in processing marine fish. The aim of this research is to minimize the cost of snapper supplies so that the production process becomes more efficient. The analysis begins with data on demand for red snapper in 2023. The movement of recorded demand shows fairly stable fluctuations, although there are some significant declines in certain months, data on ordering costs and storage costs, including raw material prices, ordering frequency, costs forklift, and ice cube costs, have been obtained to account for the total cost of raw material inventory. Data on fish demand, ordering costs, storage costs, and inventory factors were analyzed, resulting in an optimal order quantity of 298.98 kg per order with an order frequency of 6 times a year. Cost analysis shows potential savings of Rp. 3,078,677.43, safety stock of 127 kg and re order point of 42 kg. This research provides insight into the efficiency of inventory management at PT. MMU and its important implications for stock control in the fishing industry
Penerapan Data Mining Produksi Padi di Pulau Sumatera Menggunakan Analisis Regresi Linear Nababan, Yohanes; Nugraha, Isna
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 1 (2024): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i1.23545

Abstract

Indonesia, primarily an agrarian nation, relies heavily on farming as a livelihood, particularly in rice production. Rice is a crucial commodity, especially in Sumatra. Understanding the influential factors such as rainfall, humidity, average temperature, and harvest area is vital for effective rice production. This research applies the CRISP-DM method: Business Understanding, Data Understanding, Data Preparation, and Modeling. Multiple linear regression analysis is employed using Python programming in Google Colab to assess the impact of these factors on rice production. Results indicate that rainfall, humidity, and average temperature insignificantly affect rice production, while harvest area significantly influences it. The regression model is expressed as Y = 12.3X1 + 1637.1X2 – 159677.3X3 + 5.1X4. This model provides valuable insights for farmers to prioritize influential factors in future rice production
Analisis segmentasi pelanggan dengan model RFM (Recency, Frequency, Monetary) dan K-Means Clustering (Studi kasus: PT XYZ) Sitorus, Ema Rosary; Nugraha, Isna
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 8 No. 1 (2025): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v8i1.39447

Abstract

Customer segmentation is a crucial process in understanding consumer behavior patterns to support strategic decision making in marketing. The main challenge companies face is accurately segmenting customers based on transaction data. The purpose of this research is to determine and segment customers using the K-Means clustering algorithm based on the RFM (Recency, Frequency, Monetary) model on AMDK sales transaction data at PT XYZ. The research method involves analysis of 111 customer data processed using Orange Data Mining software, with validation of the results using Silhouette Score which is useful in determining the ideal number of clusters. This research produces four customer clusters, with Cluster 4 reflecting customers with the highest level of loyalty, characterized by dominant Frequency and Monetary values, while Cluster 3 describes customers with low loyalty potential. The results of this research provide a scientific basis for the development of more focused and efficient data-based marketing strategies.
IoT-Based Water Quality Monitoring System to Enhance Sustainability and Business Performance in Koi Fish Cultivation Sugiarto; Nugraha, Isna; Fahrudin, Tresna Maulana; Rizqina, Azza; Agvenia, Keisya
Journal of Advances in Information and Industrial Technology Vol. 7 No. 2 (2025): Nov
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i2.730

Abstract

Water quality is a critical factor that determines the survival and productivity of koi fish cultivation. Fluctuations in key parameters, such as pH, dissolved oxygen (DO), total dissolved solids (TDS), and turbidity, can induce stress and lead to mass fish mortality, resulting in substantial financial losses for farmers. This study proposes an IoT-based water quality monitoring system designed to enhance both environmental sustainability and business performance in koi aquaculture. The system integrates four sensors (pH, DO, TDS, and turbidity) connected to an ESP32 microcontroller, which transmits real-time data via Wi-Fi to cloud platforms (Firebase and Blynk). A dedicated dashboard provides continuous monitoring, historical trend visualization, and real-time alerts when parameter thresholds are exceeded. The prototype was validated in an operational koi pond and achieved an average accuracy of 96.5%. User testing involving 10 koi farmers showed an 89% satisfaction rate, demonstrating the system's practicality and usability. Economically, the solution reduced manual monitoring costs by 40%, water replacement volume by 25%, and increased fish survival rates by 12%. These results indicate that IoT implementation in aquaculture not only improves environmental control but also increases operational efficiency and overall profitability, contributing to sustainable, data-driven aquaculture practices.