Penerapan Metode MOORA pada Sistem Pemilihan Bibit Cabai (Kasus: Desa Bandar Siantar Kecamatan Gunung Malela)

Red chili is one of the plants that is often used as a complement to spices in Indonesian society and makes chili plants one of their main crops. Some farmers often find it difficult to determine which chili seeds are good and resistant to viruses. In addition, farmers are also difficult to determine good chili seeds at affordable prices. The difficulty of determining which chili seeds are good often makes some farmers fail harvests and suffer considerable losses. This research was conducted in the village of Bandar Siantar, Gunung Malela District. Data is obtained by interviewing and observing directly to chili farmers. This study uses a decision support system technique with the Multi-Objective Optimization method on the basis of Ratio Analysis (MOORA) which can help farmers to determine good chili seeds. The assessment criteria used were the price of seeds (C1), Harvest Period (C2), Fruit Length (C3), Fruit Weight (C4), Chili Disease (C5), Number of Branches (C6) with 8 alternatives, namely: Lado (A1), Taro (A2), Belinda (A3), TM (A4), Kripsy (A5), Tebing (A6), Indra Pura (A7) and Keling (A8). The results of applying the MOORA method in choosing chili seeds are the type of Lado (A1) chili with a value (Yi (max) = 0.2080) becomes the first recommendation, TM (A4) with a value (Yi (max) = 0.2071) being ranked second and Indra Pura (A7) with a value (Yi (max) = 0.1974) becomes third place. This research is expected to help farmers in determining good chili seeds so that they can help the economy of the farmers and avoid crop failure, especially in the village of Bandar Siantar, Gunung Malela District.Cabai merah adalah salah satu tanaman utama dari salah satu tanaman petani di Indonesia. Permasalahan yang timbul adalah sulit untuk menentukan biji cabai mana yang baik dan tahan terhadap virus. Selain itu, petani juga kesulitan menentukan benih yang baik dengan harga terjangkau. Sulitnya menentukan benih putih yang baik membuat sebagian petani gagal panen dan menderita kerugian yang cukup besar. Penelitian ini dilakukan di Desa Bandar Siantar, Kabupaten Gunung Malela. Data diperoleh dengan mewawancarai dan mengamati langsung ke petani cabai. Penelitian ini menggunakan teknik sistem pendukung keputusan dengan metode Multi-Objective Optimization berdasarkan Analisis Rasio (MOORA) yang dapat membantu petani untuk merekomendasikan benih cabai yang baik. Kriteria penilaian yang digunakan sebanyak 6 yakni: Harga bibit (C1), Masa Panen (C2), Panjang Buah (C3), Berat Buah (C4), Penyakit Cabai (C5), Banyaknya Cabang (C6) dan 8 alternatif, yaitu: Lado (A1), Taro (A2) ), Belinda (A3), TM (A4), Kripsy (A5), Tebing (A6), Indra Pura (A7) dan Keling (A8). Hasil penelitian menunjukkan jenis Lado (A1) dengan nilai (Yi (maks) = 0,2080) menjadi rekomendasi pertama, TM (A4) dengan nilai (Yi (maks) = 0,2071) berada di peringkat kedua dan Indra Pura (A7) dengan nilai (Yi (maks) = 0,1974) menjadi tempat ketiga. Penelitian ini diharapkan dapat membantu para petani untuk menghindari kegagalan panen, mereka dapat membantu para petani untuk menghindari kegagalan panen, terutama di desa Bandar Siantar, Kabupaten Gunung Malela

Menentukan Kepuasan Masyarakat dalam Membuat Surat Izin Mendirikan Bangunan pada Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu menggunakan Algoritma K-Nearest Neighbor

This research aims to classify the public satisfaction on the creation of building permits in the Office of Investment and integrated service of one door Pematangsiantar. Data is obtained from the results of a community questionnaire from 2019, with a sample of 80 data in society. The attributes used as many as 9, namely terms, procedures, service time, cost/tariff, service products, implementing competence, implementing conduct, infrastructure and handling complaints. The method used in this research is the K-Nearest Neighbor (KNN) algorithm and was processed using the RapidMiner Studio 8.1 software to determine the public satisfaction of the creation of building permits. The data used is divided into two, which are training data used 50 data and data testing used as much as 30 data. With this research is expected to help the Department of Investment and Integrated services one door Pematangsiantar to evaluate the service system provided to the public to meet the expectations of the community in the manufacture of building permits

Prediction of Mortlity Rate in Indonesia due to Covid-19 Using the Naïve Bayes Algorithm

One of the functions of this research is to obtain the latest information regarding the level of accuracy and death rates due to the Covid-19 pandemic. One of the tasks of planning a response to a pandemic is to access data related to the number of deaths due to Covid-19. The research that the author is carrying out will predict the death rate due to the COVID-19 pandemic in Indonesia. This study collects all data sourced from the website address https://sinta.ristekbrin.go.id/covid/datasets. By using Indonesia's death rate data due to covid-19 from March 2020 to July 2021. The calculation process and prediction workflow will use the Naïve Bayes Algorithm to be able to measure accuracy and predict the death rate due to the coronavirus in 2022. Prediction testing data figures with a total of 20 the area is in the highest class with a death rate of 120,568 cases obtained based on the calculation of the Naive Bayes algorithm, for an accuracy performance of 100% by testing using Rapidminer tools. It is hoped that the results of this prediction can be used by the government to overcome and set plans for good improvements to the community during the coronavirus pandemic

Analisis Penilaian Kualitas Jenis Pelayanan Tebaik dengan Metode Analytic Network Process (ANP) di Kantor Dinas Kependudukan dan Pencatatan Sipil Kota Pematangsiantar

This study aims to determine the best service quality at the Pematangsiantar City Population and Civil Registration Office, which includes services for making Identity Cards (KTP), Family Cards (KK), birth certificates, marriage certificates and receipt making. The method used in this research is the Analytic Network Process (ANP) method. The data collection technique used is a questionnaire technique that is distributed directly to the people who come to take care of the needs of personal and family data files. The parameters used consist of the facilities provided, employee behavior, services, and provisions. Determining community satisfaction with a service can be seen from the quality of the type of service. The results of this study were obtained in rank-1 with a normal value of 0.49126400, rank-2 family cards with a value of 0.18988000, rank-3 birth certificates with a value of 0.16073800, marriage certificates rank-4 with a value of 0.09707200 and Finally, rank-5 receipt services with a value of 0.06104600 With this research it is hoped that it can help the Pematangsiantar City Population and Civil Registration Service to evaluate the services provided to the community in order to meet community expectations in terms of managing the needs of personal and family data files and knowing the types of best services

Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat

Based on data on the results of oil palm production in PTPN IV Marihat displays several locations with fruit yields that vary in number. For this reason, grouping of potential fruit-producing locations is needed to know which locations produce large or small numbers of palm fruit. The production sharing is usually done based on the location or block of harvesting oil palm fruit. Therefore, a method is needed to facilitate the grouping of fruit producing locations. With the K-Means clustering approach, the division of location groups can be done based on harvested area (Ha), production realization (kg) and harvest year. In this research, clustering of potential fruit-producing areas was carried out using the K-Means algorithm. By using K-Means aims to facilitate the grouping of a block with a lot of fruit production, and low. The result of this research is that C1 (highest) is 14 Harvest Block data, and C2 (lowest) is 11 Harvest Block data

Levenberg-Marquardt Algorithm Combined with Bipolar Sigmoid Function to Measure Open Unemployment Rate in Indonesia

The purpose of this research is to see how much open unemployment rate according to the highest education completed in the country of Indonesia for subsequent years through predictions used on the basis of existing data, which later as input for the government so that the government can make better policies to suppress the unemployment rate. This research uses artificial neural network application using a combination of Levenberg-Marquardt Algorithm with bipolar sigmoid function. Open unemployment data according to the highest education is sourced from the National Labor Force Survey of the Republic of Indonesia, 2013-2017 in each semester. The data processing consists of two stages where the first phase of pattern recognition and the second stage is predicted. Pattern recognition and prediction use different data from the same process that uses data training and data testing. Data Training year 2013-2015 with a target of 2016, while data testing year 2014-2016 with the target year 2017. Architectural model used there are five, among others 6-2-5-2, 6-5-6-2, 6- 5-8-2, 6-5-10-2 and 6-8-12-2. From the 5 models, it can be concluded that the best model is 6-5-10-2 with the epoch of 13 iterations, MSE in February 0.0109696004, MSE in August 0.0233797200. While the accuracy rate in February and August is the same, that is equal to 88%