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All Journal SAINSMAT Panrannuangku Jurnal Pengabdian Masyarakat SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M)
Meliyana R, Sitti Masyitah
Unknown Affiliation
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Library & Information Science Mathematics Physics Social Sciences Other

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 1 
The Community Empowerment in Managing Inorganic Recycled Waste in Tallo Subdistrict, Makassar city Meliyana R, Sitti Masyitah; Hafid, Hardianti; Ahmar, Ansari Saleh; Talib, Ahmad; Rahman, Abdul
Panrannuangku Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/panrannuangku2108

Abstract

Community service activities are a continuous effort to enhance the awareness and abilities of the residents in the Pannampu Village, Tallo Subdistrict, Makassar City, in the management of inorganic recycling waste. The purpose of these activities is to identify the potential of inorganic waste within the local community, provide education on sustainable waste management practices, and teach recycling skills to encourage active community participation in waste separation, support better waste management initiatives, and create creative recycling products, namely economically valuable handicrafts. The results of these activities depict an increase in community awareness regarding the importance of sustainable waste management practices, with a positive impact on the local environment. This community service initiative provides concrete evidence that collaboration between academics and the local community can create significant changes in the management of inorganic recycling waste and promote active community participation in maintaining a cleaner environment.
Pengenalan Manfaat dan Pengolahan Moringa olifera pada Anak di BTN Kasumberang Kabupaten Gowa Puspitasari, Dewi; Meliyana R, Sitti Masyitah; Jayadilaga, Yadi; Rhesa, Muhammad; Saleh, Andi Rahmat
Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Vol. 2 No. 1 (2023): Volume 02 Nomor 01 (April 2023)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jhp2m.v2i1.171

Abstract

The community service carried out aims to provide experience for children to know Moringa-based foods. Children are given an introduction to like to consume vegetables. The community service carried out was training in making moringa fried rice using the demonstration method. A total of 12 panelists participated to assess the level of preference for Moringa fried rice which included color, taste, aroma and texture that the panelists liked. It can be concluded that the results of the dedication show that Moringa fried rice is accepted/liked by the panelists and can be used as an alternative for daily consumption of highly nutritious children
Epidemiological Mapping Of Tuberculosis In South Sulawesi Using Local Indicators Of Spatial Association (LISA) And K-Means Clustering Mar'ah, Zakiyah; Hafid, Hardianti; Meliyana R, Sitti Masyitah
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 1 (2025): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat141665022025

Abstract

Spatial statistics is a statistical approach that links data to the location of events. The most basic way to test whether data can be analyzed using spatial statistics is to find the spatial dependence. Local spatial dependence is tested using Local Indicators of Spatial Association (LISA). This research aims to use a form of LISA, Local Moran, to cluster and map epidemiological data, the number of tuberculosis (TB) cases in South Sulawesi. The novelty of this research is that the mapping of TB infectious disease in South Sulawesi was carried out using Local Moran, as well as clustering area using K-Means. The distribution pattern of TB cases in South Sulawesi tended to be clustered and the areas that had significant spatial dependency were Makassar, Maros and Takalar. The positive Moran value in Makassar shows that the characteristics of TB cases in Makassar tended to be similar to its neighbor. Meanwhile, the negative Moran values in Maros and Takalar indicates that the characteristics of TB cases in both areas were not similar to their neighbors. The result of K-Means shows that the areas with the highest number of TB cases in South Sulawesi were Bone, Gowa and Makassar.
Epidemiological Mapping Of Tuberculosis In South Sulawesi Using Local Indicators Of Spatial Association (LISA) And K-Means Clustering Mar'ah, Zakiyah; Hafid, Hardianti; Meliyana R, Sitti Masyitah
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 1 (2025): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat141665022025

Abstract

Spatial statistics is a statistical approach that links data to the location of events. The most basic way to test whether data can be analyzed using spatial statistics is to find the spatial dependence. Local spatial dependence is tested using Local Indicators of Spatial Association (LISA). This research aims to use a form of LISA, Local Moran, to cluster and map epidemiological data, the number of tuberculosis (TB) cases in South Sulawesi. The novelty of this research is that the mapping of TB infectious disease in South Sulawesi was carried out using Local Moran, as well as clustering area using K-Means. The distribution pattern of TB cases in South Sulawesi tended to be clustered and the areas that had significant spatial dependency were Makassar, Maros and Takalar. The positive Moran value in Makassar shows that the characteristics of TB cases in Makassar tended to be similar to its neighbor. Meanwhile, the negative Moran values in Maros and Takalar indicates that the characteristics of TB cases in both areas were not similar to their neighbors. The result of K-Means shows that the areas with the highest number of TB cases in South Sulawesi were Bone, Gowa and Makassar.
Analisis Sentimen Ulasan Game Simulator Indonesia di Google Play Store Menggunakan Algoritma Naive Bayes Meliyana R, sitti Masyitah; Sudarmin; Sabrina Effendy, Yuni
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 2 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm336

Abstract

Sentiment analysis is the process of text data to understand the opinion contained in a sentence. The commonly used algorithm in this analysis is the Naïve Bayes Classifier. Naive Bayes Classifier (NBC) is a classification that uses statistical and probabilistic methods to group texts into several categories of sentiments such as positive and negative. The Indonesian simulator game analyzed is Angkot d Game. This algorithm is used to understand users' perceptions of the game and to identify the factors that affect user sentiment. The results show that the Naive Bayes Classifier has a high level of accuracy in classifying the sentiments of simulator game reviews. The findings of this analysis are also expected to provide insights to game developers about user preferences and complaints, allowing them to adjust features or aspects of the game to better meet user needs. This enables game developers to make significant changes to the games they develop, potentially increasing revenue in the Indonesian gaming industry and focusing more on games created by local developers. Keywords: Simulator Game, Sentiment analysis, Naive Bayes Classifier.
Co-Authors Abdul Rahman Ahmad Talib Ahmar, Ansari Saleh Dewi Puspitasari Hardianti Hafid Jayadilaga, Yadi Mar'ah, Zakiyah Rhesa, Muhammad Sabrina Effendy, Yuni Saleh, Andi Rahmat Sudarmin