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All Journal Journal of Applied Science, Engineering, Technology, and Education Mattawang: Jurnal Pengabdian Masyarakat Quantitative Economics and Management Studies ARRUS Journal of Mathematics and Applied Science ARRUS Journal of Engineering and Technology VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Rais, Zulkifli
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Improving the Life Skills of Students of SMK Negeri 1 Barru through Training in Making Liquid Organic Fertilizers: Peningkatan Life Skill Siswa SMK Negeri 1 Barru melalui Pelatihan Pembuatan Pupuk Organik Cair Rasjid, Yusniar; Rais, Zulkifli; Purnamasari, A. Bida; Rusdianto
Mattawang: Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.088 KB) | DOI: 10.35877/454RI.mattawang307

Abstract

The purpose of this activity is to seek to develop skills and abilities in the manufacture of liquid organic fertilizers as an effort to reduce environmental pollution caused by household waste and industrial waste. Lack of skills in making organic liquid fertilizer from household waste for students is the driving force for the implementation of this training activity. For this reason, this activity will provide training on how to make liquid organic fertilizer from household waste and rotten fruits. The results achieved were in the form of knowledge and skills on how to make organic liquid fertilizer from household waste and rotten fruits by involving students at school. This can be seen from the results of the participants' independent work in producing the final product in the form of liquid organic fertilizer. These students' skills can be seen from the results of independent work in forming attractive and beautiful horticulture plants. The results of the activity are also in the form of enthusiasm and enthusiasm of the students/training participants which can be seen from the presence of the participants and interest in the practice of making organic liquid fertilizer from waste. Abstrak: Tujuan kegiatan ini yaitu hendak mengupayakan pengembangan keterampilan dan kemampuan dalam pembuatan pupuk organik cair sebagai upaya mengurangi pencemaran lingkungan akibat limbah rumah tangga dan limbah industri. Kurangnya keterampilan dalam membuat pupuk cair organik dari limbah rumah tangga bagi siswa menjadi pendorong pelaksanaan kegiatan pelatihan ini. Untuk itu, kegiatan ini akan memberikan pelatihan cara pembuatan pupuk organik cair dari limbah yang berasal dari rumah tangga dan buah-buahan yang busuk. Hasil yang dicapai berupa pengetahuan dan keterampilan cara membuat pupuk cair organik dari limbah rumah tangga dan buah-buahan busuk dengan melibatkan siswa-siswa di sekolah. Hal tersebut tampak dari hasil kerja mandiri peserta dalam menghasilkan produk akhir berupa pupuk organik cair. Keterampilan siswa tersebut tampak dari hasil kerja mandiri dalam membentuk tanaman vertikultur yang menarik dan indah. Hasil kegiatan juga berupa antusiasme dan semangat siswa/ peserta pelatihan yang tampak dari kehadiran peserta dan ketertarikan dalam praktek pembuatan pupuk cair organik dari limbah.
K-Means Cluster Analysis for Grouping Districts in South Sulawesi Province Based on Village Potential Azrahwati; Nusrang, Muhammad; Aidid, Muhammad Kasim; Rais, Zulkifli
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 2 (2022)
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/mathscience739

Abstract

Cluster analysis is an analysis in multivariable statistics that is used to group objects that have the same characteristics. One of the methods in cluster analysis used to group relatively large amounts of data is the K-Means method. In this study, the K-Means method was applied to classify sub-districts in South Sulawesi Province based on village potential. The variables used are the number of: Elementary School/Equivalent degree, Junior High School/Equivalent degree, Senior High School/Vocational School/Equivalent degree, Community Health Center/Pustu, Families without electricity, Villages/Urbans according to market presence, Villages/Towns that are passed by public transportation and Villages/Kelurahan that have lighting main road. The results of this study are that 3 groups are formed where the first cluster consists of 107 sub-districts that have high village potential, the second cluster consists of 16 sub-districts that have medium village potential and the third cluster consists of 184 sub-districts that have low village potential.
Empowering the Manimbahoi Village Community through Digital Marketing Training: Pemberdayaan Masyarakat Desa Manimbahoi melalui Pelatihan Digital Marketing Ahmar, Ansari Saleh; Rais, Zulkifli; Bakri, Rizal; Asmar, Asmar
Mattawang: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2024)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3049

Abstract

This training was held in the Manimbahoi Village Meeting Room, Parigi District, Gowa Regency, South Sulawesi Province on August 31, 2023. Participants in this training were young people from Karang Taruna, with the aim that the community, especially young people in Manimbahoi Village, could understand the importance of digital marketing as an effort to market Manimbahoi coffee products not only in the Parigi District area but also to the National area. This community service activity went smoothly and as expected. The results of this service show that there has been an increase in the abilities and knowledge of the village community from not knowing to knowing about digital marketing for coffee marketing. Abstrak Pelatihan ini dilaksanakan di Ruang Pertemuan Desa Manimbahoi, Kecamatan Parigi, Kabupaten Gowa, Provinsi Sulawesi Selatan pada tanggal 31 Agustus 2023. Peserta dari pelatihan ini adalah pemuda karang taruna, dengan tujuan warga masyarakat khususnya pemuda di Desa Manimbahoi dapat memahami tentang pentingnya digital marketing sebagai upaya untuk memasarkan produk kopi Manimbahoi bukan hanya di daerah Kecamatan Parigi tetapi bisa ke kawasan Nasional. Kegiatan pengabdian ini berjalan lancar dan sesuai dengan yang diharapkan. Hasil dari pengabdian ini, terlihat bahwa terjadi peningkatan kemampuan dan pengetahuan masyarakat desa dari tidak tahu menjadi tahu tentang digital marketing untuk pemasaran kopi.
Application of Ensemble K-Modes and SWFM for Grouping Sulawesi Tengah Regions by Underdeveloped Indicators Rais, Zulkifli; Aidid, Muhammad Kasim; Amira, Husnul
ARRUS Journal of Engineering and Technology Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech4014

Abstract

This research aims to determine the best final clustering results and clustering statistics for regencies/cities in Central Sulawesi based on underdeveloped region indicators. The study uses categorical and numerical data variables, consisting of 10 numerical variables and 3 categorical variables. The methods used in this research are the mixed data Ensemble K-Modes and the Similarity Weight and Filter Method (SWFM). The best mixed data clustering method shows that the Ensemble K-Modes method produces better clustering results than the SWFM method, as Ensemble K-Modes has a higher accuracy score of 0,8462
Algoritma K-Prototype dalam Pengelompokan Kabupaten/Kota di Provinsi Sulawesi Selatan Berdasarkan Indikator Kesejahteraan Rakyat Tahun 2020 Rais, Zulkifli; Annas, Suwardi; Muhammad Refaldy
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm20

Abstract

Clustering is something that is used to analyze data both in machine learning, data mining, pattern engineering, image analysis and bioinformatics. To produce the information needed for a data analysis using the clustering process, this is because the data has a large variety and amount. Researchers will use the K-Prototype method where this method becomes an efficient and effective algorithm in processing mixed-type data. The K-Prototype algorithm has problems in finding the best number of clusters. So, in this paper, researchers will conduct research by finding the best number of clusters in the K-Prototype method. There are many ways to determine this, one of which is the Elbow method. The determination of this method is seen from the SSE (Sum Square Error) graph of several number of clusters. The results of the clustering formed 2 clusters which were considered optimal based on the value of k that experienced the greatest decrease. The results showed that, cluster 1 is a cluster that has characteristics of people's welfare which is better than cluster 2.
Implementation of Binary Logistic Regression and Chi-Squared Automatic Interaction Detection (CHAID) to Recipients of the Prosper Family Card Program in Makassar City Rais, Zulkifli; Ruliana; Indrayasaro
Quantitative Economics and Management Studies Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3981

Abstract

The binary logistic regression analysis method is a classification method that forms a relationship between a dichotomous dependent variable and an independent variable, while the chi-squared automatic interaction detection (CHAID) analysis method is a decision tree classification method for studying the relationship between independent variables and variables. bound by using the chi-square test statistic as the main tool. This research aims to determine the magnitude of the resulting accuracy value and what factors influence recipients of the Prosperous Family Card program in Makassar City based on National Socio-Economic Survey data in 2022 using the binary logistic regression method and the chi-squared automatic interaction detection method (CHAID). The results of this research using the binary logistic regression method show that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with an accuracy value of 75.78%, while the chi-squared automatic interaction detection (CHAID) method also shows that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with the resulting accuracy value of 75%. Based on the accuracy values of the two methods, the binary logistic regression method is the appropriate method for classifying recipients of the Prosperous Family Card program in Makassar City
Backpropagation Neural Network Method For The Classification of Districts/Cities Based On Macro Socio-Economic Indicators In The Province Of South Sulawesi Rais, Zulkifli; Sudarmin; Syahputra, Akbar
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3982

Abstract

Classification is a way of grouping objects based on the characteristics possessed by the objects of classified. One of the developing classification methods is the backpropagation neural network. This study aims to look at the descriptive and classification results of the District/City Macro Socioeconomic Indicators in South Sulawesi Province. The data set comprises 24 observations with 9 variables, namely population density, poverty line, Gini ratio, open unemployment rate, life expectancy, average length of schooling, labor force participation rate, life growth rate, and GRDP at current prices. A model with a total of 9 hidden layers and a learning rate of 0.002 is obtained with an accuracy of 70%, precision of 70%, recall of 100%, and F1 score of 87%.
Classification Of Hypertension Using Methods Support Vector Machine Genetic Algorithm (SVM-GA) Fahmuddin S, Muhammad; Rais, Zulkifli; Yuniar, Eka Citra
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience3976

Abstract

Support Vector Machine (SVM) is a machine learning method for classifying data that has been successfully used to solve problems in various fields. The risk minimization principle used can produce an SVM model with good generalization capabilities. The problem with the SVM method is the difficulty in determining the optimal SVM hyperparameters. This research uses Genetic Algorithm (GA) to optimize SVM hyperparameters. GA optimization on SVM is used to classify hypertension. From the result of classification analysis using GA, it shows good accuracy value performance, namely 100% compared to using only SVM.
Implementation of Machine Learning Algorithm with Extreme Gradient Boosting (XGBoost) Method In Hypertension Level Classification Rais, Zulkifli; Fahmuddin S, Muhammad; Saida, Saida; Triutomo, Agung
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci4191

Abstract

The increasing number of hypertension patients and the threat of serious complications make hypertension one of the leading causes of death worldwide. Early prevention is currently considered one of the best solutions. Early prevention through early detection can be achieved by utilizing machine learning technology. XGBoost is a machine learning algorithm based on gradient boosting machines. XGBoost applies regularization techniques to reduce overfitting and has faster execution speed as well as better performance. The objective of this research is to classify hypertension levels using the XGBoost method and leveraging hyperparameter tuning for optimization. In this study, the hyperparameter optimization technique used is gridsearchCV. The evaluation results of the XGBoost classification method using the best combination of parameters show good performance, where the XGBoost model achieves an accuracy of 93.3%, Precision of 97%, Recall of 92%, F1-Score of 93%, and AUC value of 0.935. This implies that the classification of hypertension levels in patients at Pelamonia Makassar Hospital can be well or accurately classified using the XGBoost method.
Training on Structural Equation Modelling (SEM) Analysis for Lecturers at Patompo University: Pelatihan Analisis Structural Equation Modelling (SEM) Bagi Dosen Universitas Patompo Ruliana, Ruliana; Sudarmin, Sudarmin; Meliyana, Sitti Masyitah; Rais, Zulkifli
Mattawang: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3180

Abstract

This community service project aims to enhance the understanding and skills of lecturers at Universitas Patompo in using Structural Equation Modelling (SEM) for research data analysis. The activity took place on September 18, 2024, and was attended by 28 lecturers. The main issues faced by the participants were a lack of understanding of SEM techniques and limited skills in using statistical software for analysis. The solution offered was an intensive training session that included the introduction of statistical software and the application of SEM using the Jamovi software. In addition, a community action planning process was implemented, involving the lecturers in the organization of the training. The results of this project showed a significant improvement in the participants' understanding and skills in SEM analysis.
Co-Authors Ahmar, Ansari Saleh Aidid, Muhammad Kasim Amira, Husnul Asmar Asmar, Asmar Azrahwati Fahmuddin S, Muhammad Indrayasaro Muhammad Refaldy Nusrang, Muhammad Purnamasari, A. Bida Rizal Bakri Ruliana Ruliana Ruliana, Ruliana Rusdianto Saida, Saida Sitti Masyitah Meliyana R. Sudarmin Sudarmin Sudarmin Suwardi Annas Syahputra, Akbar Triutomo, Agung Yuniar, Eka Citra Yusniar Rasjid, Yusniar