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Pemanfaatan Limbah Organik Bekatul Menjadi Pupuk Cair Sebagai Solusi Pupuk Pengganti Untuk Pertanian Mufarrihah, Iftitaahul; Lazulfa, Indana; Andriani, Anita; F, Reza Augusta Jannatul
Dinamis: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 1 (2024): Juni 2024
Publisher : Universitas Hasyim Asy'ari Tebuireng Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/dinamis.v4i1.6068

Abstract

Limbah organik adalah limbah atau sampah yang berasal dari makhluk hidup, baik manusia, hewan maupun tumbuhan. Limbah organik dapat dimanfaatakan jika dikelola dengan prosedur yang benar. Limbah organik dapat mengalami dekomposisi (pelapukan) dan terurai menjadi bahan yang lebih kecil dan tidak berbau. Salah satu limbah organik yang sering ditemui adalah bekatul. Bekatul adalah limbah hasil peggilingan padi yang belum banyak dimanfaaatkan. Salah satu usaha untuk memanfaatkan bekatul adalah dengan merubahnya menjadi pupuk cair sehingga dapat dimanfaatkan sebagai alternatif pengganti pupuk kimia. Tujuan dari pengolahan limbah ini adalah untuk mengurangi limbah bekatul yang ada di lapangan dan meningkatkan nilai ekonomi pada bekatul itu sendiri. Hasil dari kegiatan ini adalah pupuk cair hasil pengolahan limbah bekatul yang nantinya dapat digunakan sebagai pupuk pengganti untuk tanaman yang ada di ladang masyarakat.
Hidroponik: Pemanfaatan Pertanian di Lahan Terbatas Sebagai Alternatif Ketahanan Pangan Mufarrihah, Iftitaahul; Andriani, Anita; Lazulfa, Indana; Firdaus, Reza Augusta Jannatul
Dinamis: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2025): Januari-Juni 2025
Publisher : Universitas Hasyim Asy'ari Tebuireng Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/dinamis.v5i1.9248

Abstract

Kurangnya pemanfaatan lahan pekarangan dan rendahnya keterlibatan ibu rumah tangga dalam kegiatan produktif menyebabkan potensi ekonomi dan ketahanan pangan di desa Banjaragung belum optimal. Pengabdian ini bertujuan untuk mengenalkan sistem pertanian hidroponik sebagai alternatif pemanfaatan lahan sempit yang bernilai ekonomi. Kegiatan dilaksanakan menggunakan metode Asset-Based Community Development (ABCD) yang berfokus pada pengembangan potensi lokal dan pemberdayaan masyarakat melalui pendekatan aset yang telah dimiliki. Hasil kegiatan menunjukkan bahwa peserta, terutama ibu rumah tangga, mampu memahami teknik pertanian hidroponik Deep Flow Technique (DFT), serta menunjukkan minat tinggi untuk menerapkannya di lingkungan rumah masing-masing. Pengabdian ini berhasil membangun instalasi hidroponik sederhana sebagai media praktik dan sarana edukasi lanjutan. Implikasi dari pengabdian ini antara lain meningkatnya kesadaran warga terhadap pentingnya teknologi hidroponik sebagai solusi pertanian modern, peningkatan akses terhadap sayuran sehat bebas pestisida, serta terbukanya peluang ekonomi kreatif berbasis hidroponik yang mendukung kemandirian pangan rumah tangga secara berkelanjutan.
METODE RESAMPLED EFFICIENT FRONTIER MEAN – VARIANCE SIMULASI MONTECARLO UNTUK PEMILIHAN BOBOT PORTOFOLIO Andriani, Anita
Inovate Vol 2 No 1 (2017): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v2i1.213

Abstract

Optimisasi portofolio pertama kali dikemukakan oleh Markowitz dan dikenal dengan nama Optimisasi Portofolio Mean – Variance (MVEP). Dalam optimisasi MVEP, estimasi parameter mean dan matriks kovarians menghasilkan bobot portofolio yang berfluktuasi dari waktu ke waktu dan memberikan hasil portofolio yang kurang baik untuk jangka waktu yang lama. Untuk menyelesaikan ketidakstabilan MVEP adalah dengan menggunakan metode resampled efficient frontier (REF). Dalam penelitian ini metode REF Risk Taker lebih menjanjikan daripada metode MVEP. Kata kunci: Optimisasi, Portofolio, MVEP, Resampled Portfolio optimization was first proposed by Markowitz and known as Optimization Portfolio Mean - Variance (MVEP). In MVEP optimization, parameter estimation of mean and covariance matrices gives poor portfolio results for long periods of time and fluctuate. One of method to solve MVEP is resampled efficient frontier (REF). In this article, REF Risk Taker method is give the best result than MVEP. Keywords: Optimization, Portfolio, MVEP, Resampled
PEMANFAATAN SOFTWARE R UNTUK ANALISIS REGRESI LINEAR Andriani, Anita
Inovate Vol 2 No 2 (2018): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v2i2.217

Abstract

R adalah suatu sistem untuk analisis data yang termasuk dalam kelompok open source software atau disebut juga dengan freeware. Penggunaan software R sampai saat ini masih kalah popular bila dibandingkan dengan software – software statistika lain yang berbayar, seperti SPSS, MINITAB, SAS atau Eviews. Keterbatasan referensi dan penunjang, khusunya dalam bahasa Indonesia, adalah salah alasan pengguna statistika lebih memilih paket – paket statistika komersil daripada software R yang gratis dan memberikan hasil analisis yang tidak kalah powerful dan sistem grafik yang menarik. Diantara banyaknya teknik – teknik statistika yang dapat diselesaikan software R, salah satu yang paling diminati adalah analisis regresi linear. Pada artikel ini akan dibahas tentang pemodelan regresi linear berganda menggunakan software R sebagai salah satu alternatif software SPSS atau software berbayar lainnya. Versi R yang digunakan adalah Command Line Interface (CLI). Analisa regresi pada artikel ini meliputi pembentukan model regresi linear berganda dan analisis plot residual untuk melihat kecocokan model yang telah dibentuk. Kata kunci: software R, analisis regresi linear, open source R is a system used for data analysis which belongs to open source software group or known by freeware. The use of R software is less popular than other paid statistics software, such as SPSS, MINITAB, SAS or Eviews. The limitation of references, especially in bahasa, is one of the reasons why users prefer to commercial statistical packages than R which is free and provide no less robust analysis results and interesting graphics systems. One of the most desirable statisticial techniques in R is linear regression analysis. This article will discuss about multiple linear regression modeling using software R as an alternative SPSS software using R-CLI (Command Line Interface). Multiple linear regression analysis and residual plot analysis will be formed for fitting model. Keywords: R software, linear regression analysis, open source
SISTEM PERAMALAN PENJUALAN TAS PADA TOKO FIRDAUS BAG BERBASIS WEB MENGGUNAKAN METODE MOVING AVERAGE Uswatun Khasanah, Siti; Dwi Indriyanti, Aries; Andriani, Anita
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.693

Abstract

Sales of bags every year experience a rapid growth, especially for types of school bags, therefore many ofthe bag shops that not only sell one type of school bag, but a variety of school bags, such as those that areoffered in Paradise Stores. Firdaus bag shop sells 17 types of school bags such as, ripper bags, alto bags,character bags etc. The number of bag sales reaches more than 100 pcs per month from all types of bags,but in making sales reports and reporting data the shop owner still uses a manual system. Asking the storeowner to have difficulty adding or subtracting bag data preparation data. The purpose of this research isto study the bag selling system in the web-based paradise Bag Store. The data in this study use 17 types ofbags with the method used in this study is the method of moving average or moving average. Movingaverage is one of the forecasting methods that uses time series data. The period used is period 6.Forecasting errors can be calculated using the MAD and MAPE formulas. The results of this study are abag sales system in the following month. The bag sales data used are January to December 2018 withmoving averages. The result of applying the moving average method is forecasting in January 2019.Forecasting the most bag sales in January 2019 is the sale of large ripper bags with a total of 127 pcs.Forecasting The level of accuracy is generated using MAD and MAPE. MAD for alto palo bags is 5.83while MAPE for alto palo bags is 58.02%.Keywords: Sales, Moving Average, Forecasting Error
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) REKOMENDASI SISWA BERPRESTASI UNTUK DIAJUKAN KE KELAS UNGGULAN Wahyu Saputro, Angga; Rahman Prehanto, Dedy; Andriani, Anita
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.734

Abstract

Madrasah tsanawiyah negeri is an islamic school which have the same level as junior high school.Sometimes it requires outstanding students to be recommended to a special class, which not only considersacademic score, but also non-academic of each student. To avoid subjective decision, it need DecisionSupport System (DSS) in providing student recommendations.One of DSS methods to solving a problem is TOPSIS. TOPSIS is based on the concept that the chosenalternative should have the shortest distance from the positive ideal solution as well as the longest distancefrom the negative ideal solutionThis study focuses on providing recommendation of outstanding students at MTsN TambakberasJombang. Observations data are collected from students grade 7 and processed using TOPSIS method. Thecriteria variables are academic score, nonacademic score, extra score, attitude score, attendance score,communication skill, and expertness. The result of preference score is generated by system then comparedwith result of manual. The comparison obtained an accuracy of 99.75%. Then, based on blackbox testingit can be concluded that the system is feasible to be used in this study case.Keywords: DSS, TOPSIS, Recommended Student, Outstanding Class.
SISTEM PEMILIHAN RUMAH KOS TERBAIK DI SEKITAR UNHASY DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) BERBASIS WEB Hidayatullah, Arif; Kadek Dwi Nuryana, I; Andriani, Anita
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.741

Abstract

Boarding house is temporary house rent by a settled foreigner or someone who stays a way from home. Someof unhasy students from outside the city find some difficulties to get information about the boarding house, they haveto come and compare it. It makes them confused to select the best boarding house. Therefore, it is necesssary to presenta system on selecting a boarding house in order to help the students. The system implements MAUT method with several criteria related to finding the best boarding house. Thesuperiority of the MAUT method is able to process data from multiple criteria which have different attributes. Asanother DSS method, MAUT is only able to solve the problem of semi-structured and non-structured.The system work by searching the result of total evaluation on every boarding house based on the determinedcriteria and alternative clasification. As the result, the system shows the best boarding house to be recomended. the comparison between system and manual calculation gets 100 % accuration. This proves that the MAUT method hasbeen successfully applied to the system, and able to give recomendation the best boarding house based on the specificcriteria above.Keyword : boarding house, decision supporting system, MAUT, Information System
Memprediksi Jumlah Produksi Roti Dengan Menerapkan Metode Monte Carlo Nur Rohmah, Fitri; Arwin Dermawan, Dodik; Andriani, Anita
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3120

Abstract

The process of predicting the amount of production is useful for reducing the level of producer losses due to inaccuracy in determining the amount of production, so that the stock of goods which usually experience accumulation or even out of stock is expected no longer. The purpose of this research itself is to design a system using Monte Carlo as a method to predict the amount of bread production. In the Monte Carlo method there is one step in the process using random numbers. The method used to generate random numbers this time is using the Linear Congruent Method (LCM). Hasil method. The results of this research is an application to facilitate the admin of the production sector to predict the amount of bread production for the next day. The prediction of the amount of production for this type of comb bread yields 1461 seeds of bread. The results of testing the accuracy of the Monte Carlo method in predicting the amount of bread production using MAPE, resulting in a fairly small error value of 9.43%. So this research is quite appropriate to be used as a method of predicting the amount of bread production. Keywords: Prediction, Production, Monte Carlo, LCM
Implementasi Algoritma FP Growth Untuk Menganalisa Pola Pembelian Barang (studi kasus : Koperasi) Sabila K.S., Nella; Sujatmiko, Bambang; Andriani, Anita
Inovate Vol 6 No 2 (2022): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i2.3173

Abstract

Analyzing piles of sales transaction data turns out to be able to produce information, one of which can take a recommendation and layout decisions of goods such as arranging goods according to association patterns, doing discount or cheap redemption prices on products that are less desirable based on the results of the association pattern, and information on goods that are not in demand. less desirable according to association rules. The association pattern has several solutions, one of which is using the fp growth algorithm. The purpose of using the fp growth algorithm is to find out frequent itemset data sets, in this study the authors apply the fp growth algorithm and association rules to cooperative data for the 1 day period of 2019. The results of this study are to produce applications that can make it easier for cooperatives to take A decision uses 20 sample data to look for association rules and FP growth, which can analyze consumer habits in making purchases, with an average percentage of support values of 9.09% and a confidence value of 100% Keywords: Data Mining, Fp Growth, Association rules, recommendations
Implementasi Algoritma Apriori Untuk Menentukan Strategi Pemasaran Bilqis Ismail Putri, Tiara; Sujatmiko, Bambang; Andriani, Anita
Inovate Vol 7 No 1 (2022): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v7i1.3680

Abstract

Store X is retail that provide a variety of toys for girls and boys. Every day the sales transaction data Store X will definitely increase and accumulate. So that data does not accumulate it is good can be used to know the habits of the buyer or of buyer behavior of goods purchased. How to search the goods sold simultaneously can use the data mining methods, which is a technique to analyze large-sized data by finding relationships among the data or the search combination and rule. The search for a combination is done with the process of merging (join) and pruning (prune) items called apriori algorithm. This research resulted in a website-based system by testing data sales transactions as many as 30 data a memorandum of the transaction with a minimum support of 35% and minimum confidence of 75%. So as to form one rule, namely, if buy a Meja Belajar K then will buy a Kreatif Block Tas with the value of the support 36.67% and the value of the confidence 78.57%. Keywords : Association, Apriori Algorithm, The Transaction Data, Sales