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All Journal JMPM (Jurnal Material dan Proses Manufaktur) International Journal of Artificial Intelligence Research Jurnal Sistem dan Manajemen Industri Journal of Applied Data Sciences Journal of Industrial Engineering and Halal Industries
Widodo, Imam Djati
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Identifying Improvement Strategic from User Application Reviews Group Using K-Means Clustering and TF-IDF Weighting Istiqomah, Khairunnisa Nurul; Widodo, Imam Djati; Mufid, Nisrina Faiza; Qurtubi, Qurtubi
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1062

Abstract

PT ABC is one of the companies that provide online ticket-purchasing facilities amidst the rise of the digitalization era. So, companies need to see how application users complain as a form of evaluation and improvement. The rating results given by application users show a score of 3.3 from 172,000 reviews. The review results that will be examined are user reviews from January 2022 to April 1, 2023, which is more or less the last year of user comments. This research aims to form a review group using K-Means Clustering, the Elbow method, TF-IDF weighting, and analysis of review improvement strategies. The Elbow method is used to determine the optimal number of clusters so as not just to use assumptions. The success of the Elbow method in processing categorical data can be supported by assigning weights based on word frequency sequences using TF-IDF. The research analysis results show the formation of 4 clusters, with two tending to have negative sentiment, one neutral sentiment, and one positive sentiment. Mapping is carried out on each cluster to find out the characteristics of each cluster and possible causes of reviews, as well as providing solutions and strategies as a form of improvement. The problem of negative reviews appearing in each review group is different. It can be corrected with the proposed strategies, such as improving the appearance of features at the registration, ordering, and payment stages, adding payment methods, and carrying out regular system maintenance.
The Identification and Elimination of Waste Activities in The Gray Yarn Processing Company Arifa, Dhinar Elma; Widodo, Imam Djati; Fausa, Erlangga
Journal of Industrial Engineering and Halal Industries Vol. 5 No. 2 (2024): Journal of Industrial Engineering and Halal Industries (JIEHIS)
Publisher : Industrial Engineering Department, Faculty of Science and Engineering, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiehis.4913

Abstract

This study aims to identify the types of waste and recommend improvements to minimize waste that occurs in the gray yarn processing company. Value Stream Mapping (VSM) is used to analyze the flow of materials and information throughout the production process. The main objective is to identify and eliminate waste, thereby improving efficiency and productivity in manufacturing operations. The biggest types of waste in the grey yarn processing production process of the preparation department are Unnecessary motion and Overprocessing waste types at 30% each, Unnecessary Inventory at 20%, and transportation at 20%. The recommendations given can reduce the overall leadtime from 58967 seconds to 58771 seconds.
Analisis Pengendalian Risiko Keselamatan dan Kesehatan Kerja (K3) dengan Metode Failure Mode and Effect Analysis (FMEA) pada PT. ABC Saputra, Bisma Rahmad; Widodo, Imam Djati
JMPM (Jurnal Material dan Proses Manufaktur) Vol. 7 No. 2 (2023): Desember
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jmpm.v7i2.19405

Abstract

PT. ABC is engaged in metal casting such as drinking water pipe connections and quality drainage components. Existing manufacturing processes involve direct interaction of workers with equipment in production situations that have sufficiently high safety risks. The research aims to identify the type or source of hazard, determine the value of high risk, and appropriate risk control measures. Using the Failure Mode and Effect Analysis (FMEA) method to identify failures from facilities, systems or equipment that have an impact on work accidents. The results of the study found 48 hazards with identifying the risk of work accidents with categories are very low (7), low (48), medium (17), high (10) and there is no risk of work accidents with very high categories. Work accidents that have a high risk in the metal casting process at PT. ABC is at the die-making, smelting and pouring, roughing, and finishing work stations. Potential risks to work safety include dust from mixing, being crushed by solid iron, exposed to sparks, exposed to molten liquids, electrocuted, and exposed to odors from paint. Risk control measures are proposed in the metal casting process at PT. ABC is carried out with engineering control and the use of PPE according to the source of danger.
Stochastic Queuing System Model Design Based on Stakeholder Aspirations Widodo, Imam Djati; Parkhan, Ali; Qurtubi, Qurtubi
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.314

Abstract

A good queuing system will provide satisfaction and trust for consumers and operational cost efficiency for service providers. This study aims to obtain the optimal number of service facilities by considering the aspirations of stakeholders, namely customers and service providers. Using aspiration theory, this research contributes to obtaining a dynamic solution to the number of service facilities with reference to service operating costs that can be determined with certainty and waiting costs that vary based on customer profiles. The study began by designing sampling for arrival time and service time data based on simple random sampling. The probability distributions of arrival time and service time are determined based on the data collection results of the sampling design. Based on the queuing profile and distribution of the two data, a suitable queuing model is built. Poisson distribution-based multi-channel queue model is constructed ((M/M/c):(GD/∞/∞)), and an optimization analysis is carried out on the number of service facilities provided by considering the aspirations of the two stakeholders. The results showed that based on stakeholder aspirations, optimal conditions were achieved at the number of servers c = 2 if the waiting cost (C2): IDR 0/hour≤ C2 ≤ IDR 11,076/hour, and the number of servers c = 3 if the waiting cost (C2): IDR 11,076/hour ≤ C2 ≤ IDR 120,690/hour.  Given that there are two conditional alternatives, the company can decide subjectively to take preventive and adaptive actions proactively according to the customer's appreciation of the waiting time in the company. Flexibility in opening service facilities will require the availability of workers and facilities to be provided. Multi-skilled workers will significantly help the flexibility of the system being built. Future research certainly needs to conduct a more in-depth study related to monthly fluctuations in arrival and service times within that period.
Intelligent optimisation for multi-objectives flexible manufacturing cells formation Purnomo, Muhammad Ridwan Andi; Widodo, Imam Djati; Zukhri, Zainudin
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7974

Abstract

The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids and exceptional parts. This objective frequently leads to extreme solutions, such as the persistently significant workload disparity among the manu­facturing cells. It will have a detrimental psychological impact on operators who work in each formed manufacturing cell. The complexity of the problem increases when there is a requirement to finish all parts before the midday break, at which point the formed manufacturing cells can proceed with the following production batch after the break. This research examines the formation of manufacturing cells using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) and particle swarm optimisation (PSO). The discussed manufacturing system has flexible machines, allowing each part to have multiple production routing options. The optimisation process involved addressing four simultaneous objectives: enhancing the efficiency and efficacy of the manufacturing cells, minimizing the deviation of manufacturing cells working time with the allocated working hours, which is prior to the midday break, and ensuring a balanced workload for the formed manufacturing cells. The optimisation results demonstrate that the G.A. outperforms the PSO method and is capable of providing manufacturing cell formation solutions with an efficiency level of 0.86, efficacy level as high as 0.64, achieving a minimum lateness of only 24 minutes from the completion target before midday break and a maximum difference in workload as low as 49 minutes.
Co-Authors Ali Parkhan Arifa, Dhinar Elma Fausa, Erlangga Istiqomah, Khairunnisa Nurul Mufid, Nisrina Faiza Muhammad Ridwan Andi Purnomo Qurtubi Qurtubi, Qurtubi Saputra, Bisma Rahmad Zainudin Zukhri