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Damen (Rice Straw) Waste and Eggshell as Liquid Organic Fertilizer: An Effort for New Business Opportunities Muthoharoh, Luluk; Sari, Reni Permata; Pamungkas, Muhammad Putra; Komarudin, Agus
Smart Society Vol 2, No 1 (2022): June 2022
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (152.444 KB) | DOI: 10.58524/smartsociety.v2i1.81

Abstract

The dissemination activity of exploring damen (rice straw) waste as liquid organic fertilizer is a form of Tridharma of higher education for community service practiced by four lecturers. This activity has several main goals: increasing public awareness, particularly among residents of RT 20 Sadar Sriwijaya Village, Bandar Sribhawono District, about the importance of utilizing damen waste to be used as liquid organic fertilizer, rather than being thrown away or simply burned after the harvesting process is complete. Socialization activities are carried out in two ways: material delivery and practice daily. Based on the socialization, it was discovered that the participants achieved the socialization's objectives with good criteria in general. As a result, the public knowledge, particularly among residents of RT 20 Sadar Sriwijaya Village, Bandar Sribhawono District, East Lampung Regency, on the use of damen waste and chicken eggshell waste is still low, so socialization is required to raise awareness of the use of agricultural waste as fertilizer
Natural Resources Data Visualization Training Using Google Data Studio in Triharjo Village, Merbau Mataram District, South Lampung Regency Muthoharoh, Luluk; S, Mika Alvionita; Irawati, Febri Dwi; Setiawan, Tirta; Nadeak, Christyan Tamaro
Smart Society Vol 3, No 2 (2023): December 2023
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/smartsociety.v3i2.287

Abstract

Visualization is becoming as the most frequent tool for examining and extracting information from datasets by novice and professional researchers alike. Many data processing applications help to present and report data. One of the digital tools that is quite widely used is Google Data Studio. This Community Service activity aims to provide data visualization training to Triharjo Village, one of the villages that still does not use digitalization to access village data online. Natural Resources Data Visualization Training Using Google Data Studio in Triharjo Village, Merbau Mataram District, South Lampung Regency has been successfully implemented and attended by 10 (ten) participants consisting of village officials. This activity is very necessary to facilitate the monitoring of agricultural products from Triharjo Village on the dashboard via the village website. The target in community service has also been achieved and serves to provide problem solving for problems that occur with partners, namely in the form of: 1. Can introduce the Tiharjo village community to the importance of digitizing performance dashboards. 2. Can teach how to use Google Data Studio tools which can be used to help the process of creating Dashboards. With this training, it is hoped that it can help manage natural resource data which will help village officials and village communities, teachers and students in providing information services related to data visualization.
Foreign Institutional Ownership and Dividend Policy Muthoharoh, Luluk; Setianto, Rahmat Heru
Southeast Asian Business Review Vol. 1 No. 1 (2023)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/sabr.v1i1.48977

Abstract

Increasing institutional investors in manufacturing companies encourage companies to be more wise in making financial decisions, including dividend policy. Dividend policy related to profits earned by the company will be distributed to shareholders in the form of dividends or saved as retained earnings for reinvestment purposes. This study aims to examine the effect of foreign institutional ownership on dividend policy. This research was conducted on manufacturing companies listed on the Indonesia Stock Exchange (IDX) during 2013-2017, with a total of 466 observations. The Generalized Method of Moment (GMM) logistic regression and dynamic panel data estimation model was used in this study, with the dependent variable being dividend policy and the independent variable being ownership of foreign institutions. The study shows that foreign institutional ownership has a positive effect on dividend policy.
Tour Recommendation System Based On User Interest and Surrounding Facilities in North Sumatera Using Simple Multi-Attribute Rating Technique With Dijkstra's Algorithm Muthoharoh, Luluk; Ahmad Luky Ramdani; Ira Safitri; Muhammad Dhoni Apriyadi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 6, ISSUE 1, April 2025
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol6.iss1.art3

Abstract

In this study, we collected data on tourist attractions, tourist attractions utilities, on the island of Sumatra, especially in Toba and Samosir districts in North Sumatra Province. In this process, information was collected on 100 tourist destinations with the highest popularity based on Google Maps Review. To determine the interest of tourists, the SMART method is used to obtain the value of tourist interest in each tourist spot based on the weight determined on each criterion. Meanwhile, entropy is used to determine the value of facilities available at tourist attractions. The value represents the interest of tourists and the facilities available around the tourist attractions. The results of this research show that in the aspect of running time Dijkstra's algorithm is fast algorithms
Indonesian Consumer Price Index Forecasting Using Autoregressive Integrated Moving Average Ishak, Shahnaz Salsabila; Abednego, Michael; Sari, Dian Maya; Sabila, Viyonisa Syafa; Khoirunnisa, Khoirunnisa; Alvionita, Mika; Muthoharoh, Luluk
International Journal of Electronics and Communications Systems Vol. 3 No. 1 (2023): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v3i1.18252

Abstract

The Consumer Price Index is one of the indicators used to confirm financial success in inflation management. This study aims to help determine the CPI prediction value in Indonesia for the next twelve periods in a month using the ARIMA (Autoregressive Integrated Moving Average) method using the data from January 2015 to March 2022. The results obtained show that the best model that can be used for forecasting is the ARIMA model (2,1,2) with drift with Akaike's Information Criterion (AIC) values of 2190.84. The results of Indonesia's accurate CPI forecasting can be used to assess inflation management for policymaking in the context of controlling inflation.It can be concluded that Based on the analysis, the optimal ARIMA model for forecasting Indonesia's CPI is ARIMA (2,1,2) with drift, aiding in evaluating inflation management for policymaking
Analysis of Google Stock Prices from 2020 to 2023 using the GARCH Method Athaulloh, M Farhan; Mubarok, Husni Na’fa; Sharov, Sergii; Hati, Berliyana Kesuma; Muthoharoh, Luluk; Alvionita, Mika
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v3i2.20899

Abstract

This research focuses on Google's share price movements, considering their significant impact on the financial market, using Google's share price data from 2020 to 2023. The aim is to analyze error variance and forecast and provide valuable information to stockbrokers and investors. The ARMA model has shortcomings in dealing with volatility, so the GARCH model is used to overcome it. Research methods include financial data analysis, preprocessing, and modeling with GARCH. The rolling forecast method describes changes in price patterns over time. Evaluation using MAPE validates the prediction accuracy of the ARIMA model. The best model chosen with the most negligible AIC value criteria was the ARIMA(3,0,2)GARCH(1,1) model. The forecasting results show accurate stock price predictions with an average MAPE value of 20.7 percent. This research provides an essential basis for brokers and investors in making investment decisions based on a deep understanding of the dynamics of Google's share price movements in the above time frame.
GARCH Model IBM Stock Forecasting of Price Volatility Zamzami, Balqis Dwian Fitri; Sihombing, Ericson Chandra; Kartika, Veni Zahara; Biran, Christian Arvianus Nathanael; Muthoharoh, Luluk; Sitinjak, Mika Alvionita
International Journal of Electronics and Communications Systems Vol. 4 No. 1 (2024): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v4i1.22866

Abstract

Risk and volatility are two related factors in research regarding capital markets. Many factors influence the movement of shares and indices. Volatility is common and affects risk assessment. Stock price volatility is an important aspect of understanding market behavior, with high volatility reflecting rapid and unstable price fluctuations. This research investigates the GARCH model in assessing volatility on the IBM Stock Exchange. The method employed was the symmetric GARCH model. It focuses on univariate analysis using the GARCH econometric model. The GARCH model allows modeling stock price variance over time based on the assumption that the variance was influenced by past stock price variance. The stages of this research were (1) data collection, (2) data pre-processing, and (3) forecasting model implementation. The best model obtained was ARMA(4,2)-GARCH(5,6) with an AIC value of 4.1017. A lower AIC value indicates that the model explains the data better or more optimally. A diagnostic test found that the model was adequate because the residual distribution followed a straight line, which means it was normally distributed.
Text Mining Customer Feedback: An Agglomerative Clustering Approach to Service Optimization Muthoharoh, Luluk
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.27188

Abstract

The increasing volume of customer support tickets in the e-commerce industry creates significant challenges in terms of efficiently managing unstructured text data. Traditional manual categorization methods are no longer efficient or scalable in managing well with growing data. This study proposes a text mining framework that integrates Natural Language Processing (NLP) techniques with Agglomerative Hierarchical Clustering (AHC) to automatically group customer support tickets based on their textual content similarity. The framework includes preprocessing (cleaning, tokenization, stopword removal, and lemmatization), followed by feature extraction using Term Frequency–Inverse Document Frequency (TF-IDF), and dimensionality reduction using Principal Component Analysis (PCA). The clustered data is then visualized through dendrograms and evaluated using silhouette scores to determine the optimal number of clusters. Using a real-world dataset of 8.469 support tickets, the framework identified an optimal two-cluster configuration, distinguishing between general inquiries and specific error-related complaints. Unlike previous studies by using K-Means or DBSCAN, this framework leverage the hierarchical structure to capture nuanced textual similarities without requiring cluster number in the beginning. It also introduces integrated for evaluation and visualization pipeline tailored for operational customer use. However, because AHC has high computational complexity, this approach is more suitable for daily clustering batches than for real-time processing. Alternatives such as Mini-Batch K-Means also need to be considered for more efficient implementation. This study contributes to the development of an automated triage system and strategies for improving customer experience in digital platforms
Empowering the Future: AI-Based Website Development Training to Boost High School Students' Creativity and Digital Skills Muthoharoh, Luluk; Yuliana, Yuliana; Rassiyanti, Linda; Lailani, Ade; Sofia, Ayu; Yulita, Tiara; Sasongko, Dharu Cahyoaji; Maharani, Khairunnisa; Rahman, Aditya
Smart Society Vol 5, No 1 (2025): June (2025)
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/smartsociety.v5i1.658

Abstract

In the rapidly evolving digital era, Artificial Intelligence (AI) has become one of the key technologies playing a significant role in various fields, including website development. AI-based website development training is a strategic step to enhance the skills and creativity of the younger generation in the era of digitalization. This activity was conducted at SMA Al Huda, South Lampung, with the aim of equipping students with an understanding of basic concepts, steps for creating websites, and how AI can be utilized to enhance creativity in the digital world. The methods used included interactive presentations, demonstrations, hands-on practice, and discussions. The activity also assessed students' knowledge before and after the training through an interactive quiz using Quizizz. The results of the study showed a significant improvement in students' understanding of AI-based website development. In conclusion, this training program was effective in enhancing students' skills and creativity in the digitalization world, particularly in creating AI-based websites
Digital-Based Physics Pocket Book Design with Short Counting Methods for Junior High School Students Yanti, Fitri April; Kristiawan, Muhammad; Riastuti, Reny Dwi; Muthoharoh, Luluk; Noperi, Hendri
Jurnal Pendidikan MIPA Vol 23, No 3 (2022): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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

Abstract

This study aims to design a digital-based physics pocket book with a short calculation method for junior high school students. This type of research and development is used in this study. At the design stage, we selected the ADDIE model. The design phase includes: the analysis phase, the stage design, the stage of development. Research data obtained by reviewing the curriculum, interviews, and validation questionnaires. Class VII, VIII, IX students, as many as 9 people, became the subject of a limited trial in this study. Data analysis was carried out by reviewing curriculum content, descriptive interview results, and quantitative analysis for validation. The results showed that the design of a digital-based physics pocket book with a short calculation method was valid and could be used by Junior high school students.Keywords: digital book, pocket book, short count method, physics learning.DOI: http://dx.doi.org/10.23960/jpmipa/v23i3.pp1030-1039