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PEMBIMBINGAN DAN EVALUASI KEGIATAN PENGENALAN LAPANGAN PERSEKOLAHAN (PLP) DI SMA 1 REJOTANGAN: MENTORING AND EVALUATION OF INTRODUCTION TO SCHOOL FIELD ACTIVITIES (PLP) AT SENIOR HIGH SCHOOL 1 REJOTANGAN Noraniza Bahrotul Ilmi; Imelda Ajeng Nur Shinta; Muhammad Wahyu Kusnaeni
MESTAKA: Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 6 (2023): Desember 2023
Publisher : Pakis Journal Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58184/mestaka.v2i6.310

The introduction of school field activities (PLP) is carried out as an effort to form qualified prospective educators. Introduction to school field (PLP) is one of the compulsory courses that must be taken by undergraduate education students. Through PLP, students are expected to improve their pedagogical, social, personality, and professional competencies. PLP is divided into two stages, namely PLP 1 and PLP 2. Activities carried out in PLP 1 include observing school culture and management. Observation of learning activities, making learning tools, and teaching practice are carried out in PLP II. This article discusses the implementation of the school field introduction II (PLP II). The results of the introduction to the field of schooling II are described using a qualitative descriptive method. The evaluation is analysed based on the assessment of the supervising teacher. Based on the evaluation results, students participating in the Bhinneka PGRI University PLP have successfully fulfilled the indicators set in the implementation of PLP activities.

Penentuan Portofolio Saham Optimal Menggunakan Metode Markowitz Sebagai Dasar Keputusan Investasi Nisardi, Muhammad Rifki; Husain, Hartina; Kusnaeni, Kusnaeni; Resky, Aprizal
Square : Journal of Mathematics and Mathematics Education Vol 6, No 1 (2024)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2024.6.1.20441

A stock portfolio is a combination of two or more securities invested over a specific period and under certain conditions. This study analyzes the combination of stocks that can be formed into an optimal portfolio using the Markowitz method. The Markowitz method is employed to maximize returns and minimize the risks associated with a portfolio. This method uses a mathematical formulation that allows for adjustments based on risk tolerance levels and expected returns to achieve an optimal portfolio. The data used in this study comprises the monthly closing prices of stocks from five selected companies, namely ICBP, BBCA, TLKM, BBNI, and INCO, for the period from June 2019 to December 2022. The findings indicate a recommended portfolio with the lowest risk, known as the Minimum Variance Portfolio (MVP). The MVP comprises the following proportions: ICBP 36.10%, BBCA 36.28%, TLKM 17.84%, INCO 8.39%, and BBNI 1.39%. This combination of stock proportions yields an expected return of 8.58% and a portfolio risk of 21.52%.Keywords: Markowitz method, Minimum Variance Portfolio, Portfolio Optimization.

FUNCTION GROUP SELECTION OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) SIGNIFICANT TO ANTIOXIDANTS USING OVERLAPPING GROUP LASSO kusnaeni, kusnaeni; Soleh, Agus M; Afendi, Farit M; Sartono, Bagus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Functional groups of sembung leaf metabolites can be detected using FTIR spectrometry by looking at the spectrum's shape from specific peaks that indicate the type of functional group of a compound. There were 35 observations and 1866 explanatory variables (wavelength) in this study. The number of explanatory variables more than the number of observations is high-dimensional data. One method that can be used to analyze high-dimensional data is penalized regression. The overlapping group lasso method is a development of the group-based penalized regression method that can solve the problem of selecting variable groups and members of overlapping groups of variables. The results of selecting the variable groups using the overlapping group lasso method found that the functional groups that were significant for the antioxidants of sembung leaves were C=C Unstructured, CN amide, Polyphenol, Sio2.

IMPLEMENTATION OF FEATURE IMPORTANCE XGBOOST ALGORITHM TO DETERMINE THE ACTIVE COMPOUNDS OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) Kusnaeni, Kusnaeni; Adhalia, Nurul Fuady; Zulfattah, Abdul Khaliq
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp675-686

Sembung is a medicinal plant native to Indonesia that grows optimally in tropical climates. The secondary metabolite compounds found in the leaves of sembung are biopharmaceutical active ingredients. Fourier Transform Infrared (FTIR) spectroscopy can identify the functional compounds in sembung leaves by analyzing unique peaks in the spectrum, which correspond to specific functional groups of the compounds. In this research, 35 observations were made with 1,866 explanatory variables (wavelengths). Data in which the number of explanatory variables surpasses the number of observations is known as high-dimensional data. One method that can handle high-dimensional problems is to select important variables that affect the objective variable. The XGBoost algorithm can calculate the feature importance score that affects the goal variable so that it does not have to include all variables in the modeling, this can overcome problems in high-dimensional data. The results of the calculation of feature importance found Lignin Skeletal Band, CH, and CH2 aliphatic Stretching Group, C=C, C=N, C–H in ring structure, DNA and RNA backbones, NH2 Aminoacidic Group, C=O Ester Fatty Acid that the active compounds contained in the leaves of sembung.

Deepfake Image Classification Using ResNet50 Feature Extraction and XGBoost Learning Model Kusnaeni, Kusnaeni; Adriani, Ika Reskiana; Hafid, Mega Sartika; Andy B, Afif Budi; Rizal, Muhammad Edy
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.8387

Deepfake is an artificial intelligence-based media manipulation technology that realistically fabricates a person's face, voice, and movements in both video and audio formats. The increasing use of deepfakes in the creation of various forms of deceptive content, including pornography, fake news, and fraud, has led to an urgent need for effective detection methods. One of the main challenges in detecting deepfakes is the high quality and realism of synthetic media, which renders conventional detection techniques less effective. Therefore, machine learning techniques capable of recognizing subtle patterns in visual data that are imperceptible to the human eye are required. This study aims to develop a deepfake image detection system using a hybrid machine learning approach that combines ResNet50 for feature extraction and XGBoost for classification. The pre-trained ResNet50 model, originally trained on the large-scale ImageNet dataset, is utilized to extract visual representations from images in the form of feature vectors. These features are then classified using XGBoost to distinguish between authentic and AI-generated images based on subtle patterns embedded within the extracted features. The results demonstrate that this hybrid approach achieves an accuracy of 94.6% in detecting deepfake images by leveraging the deep representation power of CNNs and the advanced classification capabilities of XGBoost. This method is not only computationally efficient but also highly relevant for integration into adaptive digital security systems.

Penentuan Portofolio Saham Optimal Menggunakan Metode Markowitz Sebagai Dasar Keputusan Investasi Nisardi, Muhammad Rifki; Husain, Hartina; Kusnaeni, Kusnaeni; Resky, Aprizal
Square : Journal of Mathematics and Mathematics Education Vol. 6 No. 1 (2024)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2024.6.1.20441

A stock portfolio is a combination of two or more securities invested over a specific period and under certain conditions. This study analyzes the combination of stocks that can be formed into an optimal portfolio using the Markowitz method. The Markowitz method is employed to maximize returns and minimize the risks associated with a portfolio. This method uses a mathematical formulation that allows for adjustments based on risk tolerance levels and expected returns to achieve an optimal portfolio. The data used in this study comprises the monthly closing prices of stocks from five selected companies, namely ICBP, BBCA, TLKM, BBNI, and INCO, for the period from June 2019 to December 2022. The findings indicate a recommended portfolio with the lowest risk, known as the Minimum Variance Portfolio (MVP). The MVP comprises the following proportions: ICBP 36.10%, BBCA 36.28%, TLKM 17.84%, INCO 8.39%, and BBNI 1.39%. This combination of stock proportions yields an expected return of 8.58% and a portfolio risk of 21.52%.Keywords: Markowitz method, Minimum Variance Portfolio, Portfolio Optimization.

PELATIHAN PENGGUNAAN APLIKASI GEOGEBRA UNTUK PENGEMBANGAN MEDIA PEMBELAJARAN MATEMATIKA BAGI GURU SMA DI KOTA PAREPARE Adhalia H, Nurul Fuady; Zaitun, Zaitun; Nisardi, Muh Rifki; Resky, Aprizal; Kusnaeni, Kusnaeni; Husain, Hartina; Tungga, Rifaldy Atlant
Jurnal Abdi Insani Vol 11 No 1 (2024): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v11i1.1299

The The use of technology in the mathematics learning process by high school teachers in the city of Parepare is still lacking. Even though there are many learning media that can be utilized. The Geogebra application is a technological medium that has great potential in integrating mathematical concepts visually and interactively. The aim of implementing this PKM is to provide training to mathematics teachers who are members of MGMP Parepare to develop mathematics learning media at the high school level. The training method used is providing training assistance on the Geogebra application which consists of two stages. The preparation stages consist of observing, coordinating with partners, preparing the service implementation team and preparing the service implementation team regarding the training module. The implementation stages consist of giving a pre-test, providing an explanation regarding the Geogebra application, providing simulation assistance in making mathematics learning media using Geogebra, and providing a post-test. The results obtained from the training showed that 18 out of 20 people or around 90% of teachers were able to understand and apply the knowledge gained in training activities through a post-test given at the end of the activity. Thus, the implementation of the Geogebra Application training activities was considered successful because it had achieved the specified targets.

EDUKASI LITERASI KEUANGAN DIGITAL BAGI GENERASI Z DI SMK DDI PAREPARE Husain, Hartina; Zaitun, Zaitun; Nisardi, Muhammad Rifki; Resky, Aprizal; Kusnaeni, Kusnaeni; M.R, Andi Oxy Rayhan; Herlambang, Dwicki; Nurlia, Nurlia
Jurnal Abdi Insani Vol 11 No 3 (2024): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v11i3.1744

Generation Z who are used to technology have digital financial literacy problems. They lack basic financial understanding, are prone to deceptive online offers, and are vulnerable to cyber fraud. This can result in difficulty achieving financial goals and being in debt. It is important to increase Gen Z's digital financial literacy through education, campaigns and developing educational applications so that they become a financially independent generation. This is the background for implementing this service, where the aim of this service activity is to introduce and integrate digital financial literacy education from an early age, we can help the younger generation to become more financially independent and skilled in managing their money in this digital era. It is hoped that this digital financial literacy education will be able to increase the understanding of generation Z, or in this case, students at SMK DDI Parepare, in increasing awareness about the importance of managing finances. The methods that will be used include webinars, discussions, questions and answers to student participants (i) at SMK DDI Parepare. This training was proven to be effective in increasing the knowledge of generation Z at DDI Parepare Vocational School regarding digital financial literacy, this was shown by the results of the pretest posttest difference test).

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