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The modeling of earthquake disaster mitigation in Bulukumba Regency: A stakeholder approach Ahmad, Despry Nur Annisa; Tarigan, Suria Darma; Tjahjono, Boedi; Sitanggang, Imas Sukaesih; Sakti, Harry Hardian
Journal of Degraded and Mining Lands Management Vol. 12 No. 4 (2025)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2025.124.8247

Bulukumba Regency, located along the Walanae Fault and within a seismic gap zone, indicates the potential for future earthquake recurrence. However, the regional and community capacity to address earthquake hazards remains weak, as evidenced by the lack of regulations accommodating earthquake studies in Bulukumba. This study aimed to design an earthquake mitigation model based on a stakeholder approach in Bulukumba Regency. The methodology employed MACTOR (Matrix of Alternatives for Choice and Trade-Offs), utilizing survey and questionnaire data. The output is a framework for policymakers in earthquake mitigation activities. The results suggested two effective alternative models: (i) a stakeholder formulation model based on role capacity and (ii) a time segmentation model for stakeholder involvement in earthquake mitigation. Based on these two models, it is essential to establish strong coordination and collaboration among these actors in order to minimize the impact of disasters on both the community and the environment.

Exploration of Data Handling Techniques to Improve PM2.5 Prediction Using Machine Learning Unik, Mitra; Sitanggang, Imas Sukaesih; Syaufina, Lailan; Jaya, I Nengah Surati
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.v5i1.25687

Particulate matter (PM₂.₅) is one of the most dangerous air pollutants because it can penetrate the respiratory system and cause serious health problems. Amidst the limitations of a real-time and comprehensive air quality monitoring system, a data-driven predictive approach is needed that can accurately project PM₂.₅ concentrations. This study aims to develop a PM₂ concentration prediction model using the Random Forest Regressor (RFR) algorithm optimised through a series of data pre-processing techniques. The pre-processing techniques include outlier detection with four methods (Isolation Forest, Autoencoder ANN, OCSVM, IQR) and missing value handling using three approaches (Spline Cubic Interpolation, Nearest Point Interpolation, Data Removal). The daily data used covered 12 environmental variables (including rainfall, temperature, relative humidity, AOD, and NDVI) from the period of March 2022 to March 2023, with PM₂.₅ as the target. The RFR model was built with 100 decision trees and 10-fold cross-validation to improve accuracy. Results showed the combination of IQR (outlier detection) and data deletion (missing values) produced the best performance with RMSE 0.082, MAE 0.027, and R² 0.886. The most influential variables were temperature (TEMP), relative humidity (RHU), and evapotranspiration (ET). This research contributes to the development of an accurate air quality prediction model, supporting the mitigation of PM₂.₅ pollution impacts on public health

PENGARUH MEDIA SOSIAL TERHADAP SITASI PUBLIKASI INTERNASIONAL KARYA ILMIAH INDONESIA BIDANG PERTANIAN DENGAN PENDEKATAN ALTMETRICS Ibrahim, Cecep; Sukaesih Sitanggang, Imas; Sukoco, Heru
BACA: Jurnal Dokumentasi dan Informasi Vol. 40 No. 1 (2019): BACA: Jurnal Dokumentasi dan Informasi (Juni)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.baca.v40i1.456

The purpose of this study was to measure the impact of Indonesia research especially in agriculture published in international Scopus journals using Altmetrics. This research method consisted of problem identification, data collection, data preprocessing, Altmetrics approach analysis, and final analysis. The data of this study were obtained from Scopus.com citation metadata by writing the Agriculture keyword and Indonesian affiliation that the limited year from 2015-2017. Altmetrics data is obtained from Altmetric.com; Altmetrics Explorer for Librarian by extracting DOIs from each publication of scientific work. Then the data is analyzed by the Altmetrics approach, namely Facebook Coverage and Mention Rate. This study performed an analysis based on Altmetrics data share to know the popularity Indonesian research in Scopus journal and analyzed the correlation between Citation data Indonesian research in Scopus journal and Altmetrics data share of Altmetric.com. This study analyzed the impact of 4484 Indonesia research articles published by Scopus journals in the field of agriculture through Altmetrics and compared it with bibliometrics. The result showed that Coverage and Mention Rate of social media only were below 30% which was not too significant in the content discussed, view & reader and mention on social media.

SOIL MOISTURE PREDICTION MODEL IN PEATLAND USING RANDOM FOREST REGRESSOR Taihuttu, Helda Yunita; Sitanggang, Imas Sukaesih; Syaufina, Lailan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2505-2516

Soil moisture is one of the factors that has recently become the focus of research because it is strongly correlated with forest and land fires, where low soil moisture will increase drought and the incidence of forest and land fires. For this reason, this study aims to create a prediction model for soil moisture as an early prevention of fires in peatlands using the Random Forest Regressor (RFR) algorithm. RFR is used because of its ability to predict values and its resistance to overfitting and outliers. A dataset covering soil moisture, precipitation, temperature, maturity, and peat thickness was collected from August 2019 to December 2023. The data includes soil moisture, precipitation, temperature, maturity, and peat thickness. The data were divided into 80% for modeling and 20% for testing. Model performance was optimized through random search CV, resulting in significant prediction accuracy R-squared: 0.914, MAE: 0.0081, MSE: 0.0007, RMSE: 0 .0271, and MAPE: 0.969. These findings demonstrate the effectiveness of RFR in soil moisture prediction and pave the way for more appropriate and timelier implementation of fire mitigation strategies.

Estimation Model of Nutritional Content Based on Broiler Feed Images Using Convolutional Neural Network and Random Forest Mufti, Abdul; Sitanggang, Imas Sukaesih; Neyman, Shelvie Nidya; Abdullah, Luki
Scientific Journal of Informatics Vol. 12 No. 3: August 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i3.28682

Purpose: This research aims to develop an intelligent model to estimate the nutritional content of broiler chicken feed based on feed images to assist farmers in selecting the best broiler feed and quickly verifying its quality to meet requirements. Methods: The methodology of this research includes literature study, data collection, data preprocessing, image classification, model evaluation, integration of CNN and random forest models, and estimation of nutritional content based on feed images. We collected 99 samples of broiler chicken feed from online stores in various regions of Indonesia, particularly Java. Next, we took pictures with a smartphone and analyzed the nutritional content using near-infrared spectroscopy. Preprocess the data by enhancing the dataset (color space and data augmentation). We use Convolutional Neural Network (CNN) for the classification of broiler feed images. The performance of the CNN model is evaluated using a confusion matrix. We integrate CNN and Random Forest Regressor (RFR) to estimate nutritional content from the features of broiler feed images. Result: The performance evaluation shows that the CNN (VGG-16) model is 0.9744% accurate and the RFR model has the highest R2 value of 0.8018. The benefits of this research include faster, more efficient, and automated feed quality measurement compared to traditional methods; maintaining feed quality standards; and avoiding health risks for livestock. Novelty: This research introduces an intelligent model to estimates the nutritional content of broiler feed images by integrating a CNN model with an RFR.

Transformasi Kerangka Hukum Lingkungan Indonesia melalui Next Generation Framework: Evaluasi Normatif-Praktis Tata Kelola Terpadu Mohammad, Farid; Sutjahjo, Surjono Hadi; Effendi, Hefni; Sitanggang, Imas Sukaesih; Sasongko, Dwi P
Bina Hukum Lingkungan Vol. 10 No. 1 (2025): Bina Hukum Lingkungan, Volume 10, Nomor 1, Oktober 2025
Publisher : Asosiasi Pembina Hukum Lingkungan Indonesia (PHLI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24970/bhl.v10i1.473

ABSTRAK Hukum lingkungan di Indonesia telah mengalami berbagai transformasi selama empat dekade terakhir, terutama dalam bidang kebijakan dan peraturan Analisis Dampak Lingkungan (AMDAL). Namun, perubahan ini sering mencerminkan pergeseran yang meningkat ke arah kekakuan administrasi, yang mengorbankan tujuan substantif keberlanjutan dan kualitas layanan publik. Studi ini menerapkan Next Generation Framework (NGF), alat evaluatif komprehensif yang dikembangkan oleh Fonseca dan Gibson (2020) untuk melakukan meta-evaluasi terhadap lima peraturan lingkungan utama Indonesia yang dikeluarkan antara tahun 1986 dan 2021. Melalui analisis konten kualitatif dan penilaian berbasis ahli dari 50 elemen praktik baik di sepuluh kategori NGF, penelitian ini mengungkapkan kesenjangan kelembagaan kritis dalam rasionalitas hukum, integrasi keberlanjutan, mekanisme partisipatif, dan fleksibilitas adaptif. Temuan menunjukkan bahwa sementara peraturan terbaru menekankan perampingan prosedural dan integrasi digital, mereka secara bersamaan mengabaikan landasan normatif seperti keadilan lingkungan jangka panjang, hak-hak adat, dan tata kelola yang responsif. Penelitian ini menempatkan NGF dalam kerangka hukum normatif-praktis, memposisikannya sebagai alat diagnostik yang berharga untuk reformasi kelembagaan. Pada akhirnya, studi ini mengusulkan reorientasi desain hukum dalam tata kelola lingkungan yang menyelaraskan maksud normatif, praktik administrasi, dan responsif sosial-ekologis dalam pemberian layanan publik. Kata kunci: evaluasi hukum normatif; kelembagaan; environmental impact assessment; next generation framework; tata kelola lingkungan. ABSTRACT Environmental law in Indonesia has undergone multiple transformations over the last four decades, particularly in the realm of Environmental Impact Assessment (EIA) policies and regulations. However, these changes often reflect an increasing shift toward administrative rigidity, compromising the substantive goals of sustainability and public service quality. This study applies the Next Generation Framework (NGF, a comprehensive evaluative tool developed by Fonseca and Gibson (2020) to conduct a meta-evaluation of five key Indonesian environmental regulations issued between 1986 and 2021. Through qualitative content analysis and expert-based scoring of 50 good practice elements across ten NGF categories, this study reveals critical institutional gaps in legal rationality, sustainability integration, participatory mechanisms, and adaptive flexibility. Findings show that while recent regulations emphasize procedural streamlining and digital integration, they simultaneously neglect normative foundations such as long-term environmental justice, indigenous rights, and responsive governance. The research situates NGF within a normative-practical legal framework, positioning it as a valuable diagnostic tool for institutional reform. Ultimately, the study proposes a reorientation of legal design in environmental governance one that harmonizes normative intent, administrative practice, and socio-ecological responsiveness in public service delivery. Keywords: environmental impact assessment; environmental governance; institutional reform; next generation framework; normative legal evaluation

Transformasi Kerangka Hukum Lingkungan Indonesia melalui Next Generation Framework: Evaluasi Normatif-Praktis Tata Kelola Terpadu Mohammad, Farid; Sutjahjo, Surjono Hadi; Effendi, Hefni; Sitanggang, Imas Sukaesih; Sasongko, Dwi P
Bina Hukum Lingkungan Vol. 10 No. 1 (2025): Bina Hukum Lingkungan, Volume 10, Nomor 1, Oktober 2025
Publisher : Asosiasi Pembina Hukum Lingkungan Indonesia (PHLI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24970/bhl.v10i1.473

ABSTRAK Hukum lingkungan di Indonesia telah mengalami berbagai transformasi selama empat dekade terakhir, terutama dalam bidang kebijakan dan peraturan Analisis Dampak Lingkungan (AMDAL). Namun, perubahan ini sering mencerminkan pergeseran yang meningkat ke arah kekakuan administrasi, yang mengorbankan tujuan substantif keberlanjutan dan kualitas layanan publik. Studi ini menerapkan Next Generation Framework (NGF), alat evaluatif komprehensif yang dikembangkan oleh Fonseca dan Gibson (2020) untuk melakukan meta-evaluasi terhadap lima peraturan lingkungan utama Indonesia yang dikeluarkan antara tahun 1986 dan 2021. Melalui analisis konten kualitatif dan penilaian berbasis ahli dari 50 elemen praktik baik di sepuluh kategori NGF, penelitian ini mengungkapkan kesenjangan kelembagaan kritis dalam rasionalitas hukum, integrasi keberlanjutan, mekanisme partisipatif, dan fleksibilitas adaptif. Temuan menunjukkan bahwa sementara peraturan terbaru menekankan perampingan prosedural dan integrasi digital, mereka secara bersamaan mengabaikan landasan normatif seperti keadilan lingkungan jangka panjang, hak-hak adat, dan tata kelola yang responsif. Penelitian ini menempatkan NGF dalam kerangka hukum normatif-praktis, memposisikannya sebagai alat diagnostik yang berharga untuk reformasi kelembagaan. Pada akhirnya, studi ini mengusulkan reorientasi desain hukum dalam tata kelola lingkungan yang menyelaraskan maksud normatif, praktik administrasi, dan responsif sosial-ekologis dalam pemberian layanan publik. Kata kunci: evaluasi hukum normatif; kelembagaan; environmental impact assessment; next generation framework; tata kelola lingkungan. ABSTRACT Environmental law in Indonesia has undergone multiple transformations over the last four decades, particularly in the realm of Environmental Impact Assessment (EIA) policies and regulations. However, these changes often reflect an increasing shift toward administrative rigidity, compromising the substantive goals of sustainability and public service quality. This study applies the Next Generation Framework (NGF, a comprehensive evaluative tool developed by Fonseca and Gibson (2020) to conduct a meta-evaluation of five key Indonesian environmental regulations issued between 1986 and 2021. Through qualitative content analysis and expert-based scoring of 50 good practice elements across ten NGF categories, this study reveals critical institutional gaps in legal rationality, sustainability integration, participatory mechanisms, and adaptive flexibility. Findings show that while recent regulations emphasize procedural streamlining and digital integration, they simultaneously neglect normative foundations such as long-term environmental justice, indigenous rights, and responsive governance. The research situates NGF within a normative-practical legal framework, positioning it as a valuable diagnostic tool for institutional reform. Ultimately, the study proposes a reorientation of legal design in environmental governance one that harmonizes normative intent, administrative practice, and socio-ecological responsiveness in public service delivery. Keywords: environmental impact assessment; environmental governance; institutional reform; next generation framework; normative legal evaluation

Analisis Dampak Kabut Asap dari Kebakaran Hutan dan Lahan dengan Pendekatan Text Mining Efendi, Zuliar; Sitanggang, Imas Sukaesih; Syaufina, Lailan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 5: Oktober 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023107248

Kebakaran hutan dan lahan (karhutla) berdampak buruk bagi lingkungan serta ekosistem. Kabut asap merupakan salah satu akibat yang ditimbulkan dari kebakaran hutan dan lahan. Keresahan dari munculnya kabut asap dan kebakaran hutan menjadi trending topic pada media sosial Twitter. Analisis Twitter perlu dilakukan untuk melihat kesesuaian hashtag yang digunakan dengan topik yang dibahas yaitu kabut asap. Data Twitter dapat dianalisis menggunakan text mining. Penelitian ini bertujuan untuk melihat hubungan antara percakapan di media sosial Twitter dengan kejadian kabut asap yang muncul dari kebakaran hutan dan lahan. Metode yang digunakan adalah teknik text mining yaitu menggunakan algoritme clustering. Data yang digunakan adalah data tweet terkait kabut asap di Provinsi Riau pada jarak 11 – 17 September 2019 dan juga data hotspot atau titik panas serta citra Sentinel2. Data tweet dikelompokkan dengan beberapa percobaan pada jarak antar cluster yaitu single linkage, complete linkage, average linkage, dan ward. Hasil clustering menunjukkan bahwa validitas cluster tertinggi memiliki silhouette index sebesar, 0,3360 dengan jarak antar cluster menggunakan ward. Hasil cluster menunjukkan bahwa terdapat tiga cluster yang dominan pembahasannya terkait kabut asap. Data Twitter pada ketiga cluster tersebut memiliki ciri istilah atau term yang berkaitan dengan kabut asap antara lain "kabut", "asap", dan "udara". terdapat di wilayah Pekanbaru serta wilayah Bengkalis, Provinsi Riau. Hasil dapat menjadi salah satu cara pengendalian karhutla yaitu deteksi dini dengan menggunakan media sosial Twitter. Abstract Forest and land fires have a harmful impact on the environment and ecosystem. Haze is one of the consequences that arise from forest fires and the environment. Anxiety about haze and forest fires is a trending topic on social media Twitter. Twitter analysis needs to be done to see the compatibility of the hashtags used with the haze topic. The Twitter data can be analyzed using text mining. This study aims to see the relation between conversations on social media Twitter and the occurrence of haze that arises from forest and land fires. The method used is a text mining technique that uses a clustering algorithm. The data used are tweet data related to haze in Riau Province in the range 11-17 September 2019 as well as hotspot data and Sentinel-2 imagery. Tweet data were clustered by several experiments on the distance between clusters, namely single linkage, complete linkage, average linkage, and ward. Clustering results show that the highest cluster validity has a silhouette index of 0.3360 with the distance between clusters using wards. The cluster results show that there are three clusters that are dominant in the discussion related to haze. The Twitter data for the three clusters has the characteristics of terms related to smog, including "kabut", "asap", and "udara". The impact felt by the people of Riau Province through social media Twitter related to the haze is the impact on health and air quality. Cluster tweets that discuss the topic of forest and land fires and haze are in the Pekanbaru and Bengkalis regions, Riau Province. The results can be one of the karhutla controls is early detection by using social media Twitter.

Scalability Testing of Land Forest Fire Patrol Information Systems Khusaeri, Ahmad; Sitanggang, Imas Sukaesih; Rahmawan, Hendra
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.977

The Patrol Information System for the Prevention of Forest Land Fires (SIPP Karhutla) in Indonesia is a tool for assisting patrol activities for controlling forest and land fires in Indonesia. The addition of Karhutla SIPP users causes the need for system scalability testing. This study aims to perform non-functional testing that focuses on scalability testing. The steps in scalability testing include creating schemas, conducting tests, and analyzing results. There are five schemes with a total sample of 700 samples. Testing was carried out using the JMeter automation testing tool assisted by Blazemeter in creating scripts. The scalability test parameter has three parameters: average CPU usage, memory usage, and network usage. The test results show that the CPU capacity used can handle up to 700 users, while with a memory capacity of 8GB it can handle up to 420 users. All users is the user menu that has the highest value for each test parameter The average value of CPU usage is 44.8%, the average memory usage is 69.48% and the average network usage is 2.8 Mb/s. In minimizing server performance, the tile cache map method can be applied to the system and can increase the memory capacity used.

Rancangan Sistem Penilaian Kinerja Perpustakaan Berbasis Indikator Kinerja Iso 11620:2008 Pada Layanan Terbuka Perpustakaan Nasional RI Wakhid, Abdul; Sitanggang, Imas Sukaesih; Saleh, Abdul Rahman
Jurnal Pustakawan Indonesia Vol. 14 No. 2 (2015): Jurnal Pustakawan Indonesia
Publisher : Perpustakaan IPB

Library performance measurement is one of a strategy to evaluate utilization of library resources. The objective of this study was to identify indicators needed to measure the performance and to design an counting system measurement at Open Service at National Library of Indonesia. The measurement indicators were based on ISO 11620:2008 consisting of 45 indicators. It was selected 10 indicators: 1) percentage of required titles in the collection (RTC); 2) shelving accuracy (SA); 3) staff per capita (LS); 4) collection turnover (CT); 5) loans per capita (LPC); 6) in-library use per capita (IUC); 7) library visits per capita (LVC); 8) percentage of target population reached (PTPR); 9) user satisfaction (AUS); 10) user services staff as a percentage of total staff (USSPTS). The indicators were selected through four stages: 1) selecting indicators related to activities in the Indonesia National Library and removing indicators related to activities that are not conducted in the institution; 2) removing indicators related to cost; 3) identifying and selecting indicators related to vision and mission by the questionnaire; 4) analizing the results of the questionnaire and setting the indicators that have an average value of the results greater than 0 as an selected indicator. The results of managements attitude that required the a performance counting system. System design was developed based on the system requirements and management’s needs. The system that was able to process data into information of performance. The system was integrated with the integrated national library system (INLIS) and the data that were not available in INLIS were manually input. Steps of system developing were defining use case, description use case, activity diagram, class diagram, sequence diagram, object role/relational mapping and entity relationship diagram. Keywords: Information System, ISO 11620, Library, Performance Indicators

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