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All Journal Tekinfo | Scientific Journal of Industrial and Information Engineering Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Isnaini Nurisusilawati
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Computer Science & IT Industrial & Manufacturing Engineering

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Analisis Sentimen Masyarakat terhadap Kampanye Sosial Pengurangan Food Waste di Indonesia Ratna Dwi Lestari; Isnaini Nurisusilawati
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 2 (2024): Juni: Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v2i2.105

Abstract

The remaining food waste in Indonesia reaches around 46.35 million tons, with economic losses reaching 23 million to 48 million tons per year. This condition has led to various campaigns to reduce food waste from people concerned about the problem of food waste. However, the increase in food waste campaigns has yet to be accompanied by a decrease in the volume of food waste in Indonesia. This research aims to determine public sentiment toward food waste campaigns on Instagram social media and determine the accuracy of the methods used in data classification. The method used is the Naïve Bayes Classifier method. The results obtained were from a total of 118 data regarding the food waste campaign; 79% data showed that the public had a positive sentiment, and 21% other data had a negative sentiment. The accuracy results of using sentiment analysis were 78.94%; this shows that the performance of the Naïve Bayes method in classifying data is quite good.
Analisis Perbandingan Metode Peramalan Pada Produksi Air di PDAM XYZ Anggratha Khemal Pasyah; Isnaini Nurisusilawati; Fauzan Romadlon
Tekinfo: Jurnal Ilmiah Teknik Industri dan Informasi Vol 13 No 2 (2025)
Publisher : Program Studi Teknik Industri Universitas Setia Budi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31001/tekinfo.v13i2.2306

Abstract

Good production planning can meet the demand and availability of raw materials, as well as proper production planning and scheduling, production control, inventory control, and evaluation. PDAM XYZ produces clean water for the Banyumas Regency area. Water demand at PDAM XYZ is starting to exceed the production capacity limit, so a capacity addition plan is needed to meet the customer's clean water demand. The addition of capacity can be calculated by calculating demand forecasting. Thus, this study aims to determine the best forecasting method for making water demand forecasting calculations at PDAM XYZ and the estimated amount of water demand at PDAM XYZ in the next five years. The forecasting methods used are least square and regression. The accuracy values compared are MAD, MSE, RMSE, MAPE, and Tracking signal. The results of the comparison state that the regression method is better with a MAD value of 129938.4, MSE of 28536740000, RMSE of 168928.2, and MAPE of 0.05. So, in planning the addition of production capacity, the regression method can be used to forecast calculations as a reference for determining the additional production capacity. The forecasting results using the regression method show a value of 4,352,051 m3. Based on these results, it is expected that PDAM XYZ will be able to map the amount of clean water demand so that customer water needs can be met.
Co-Authors Anggratha Khemal Pasyah Ratna Dwi Lestari