UIN (Universitas Islam Negeri) Sunan Kalijaga, Yogyakarta: E-Journal Fakultas Sains dan Teknologi
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Synthesis Synthesis of SnO₂ Nanoparticles by Microwave-Assisted Hydrothermal Method for the Photodegradation of Congo Red Dye
No full textTextile dyes are widely used in manufacturing processes and are often discharged as untreated wastewater, leading to environmental contamination. Congo Red is one of the most commonly found azo dyes in textile effluents and is highly resistant to conventional treatments. Photodegradation offers an environmentally friendly alternative by utilizing semiconductor-based photocatalysts. In this study, tin oxide nanoparticles were synthesized via a microwave-assisted hydrothermal method with different heating durations to determine the optimum reaction time. The nanoparticles were characterized using X-ray diffraction and applied for Congo Red removal through adsorption followed by photocatalytic degradation, with persulfate ions used as electron scavengers. The results indicate that the microwave-assisted method successfully produced tin oxide nanoparticles with optimal performance at a synthesis duration of four hours. The material exhibited a tetragonal structure with a crystallite size of 8.1 nm and an optical band gap of 3.04 eV. Congo Red removal through adsorption reached 11.11%, while photocatalytic treatment achieved 74.67%, and further increased to 98.64% with the addition of persulfate. These findings demonstrate the potential of microwave-assited hydrothermal derived tin oxide nanoparticles for efficient dye removal in wastewater treatment
Improving Osteosarcoma Detection through SMOTE-Driven Machine Learning Approaches
No full textOsteosarcoma is an aggressive and highly malignant bone cancer primarily affecting adolescents and young adults, with males being more commonly affected. Although deep learning models such as YOLO (95.73% accuracy) and VGG19 (95.25% accuracy), have demonstrated effectiveness in osteosarcoma detection, their large model sizes and extensive computational requirements limit their feasibility in resource-constrained environments. This study proposes a lightweight AI approach that optimizes osteosarcoma detection while maintaining high diagnostic accuracy, leveraging machine learning models under 5MB, manually or semi-automatically extracted features, and SMOTE for data balancing. Experimental results show that Random Forest, SVM, and XGBoost achieve accuracies of 94.70%, 94.23%, and 94.39%, respectively, closely matching the performance of YOLO and VGG19 while maintaining computational efficiency. Furthermore, the inference time for SVM is under one second (0.97s), demonstrating the speed advantage of lightweight models. These findings highlight the potential of small-size (lightweight) machine learning models to deliver high diagnostic accuracy with minimal computational requirements, providing a scalable and practical solution for early osteosarcoma detection in resource-limited settings. By balancing simplicity, efficiency, and high performance, this study establishes a new benchmark for achieving state-of-the-art results with lightweight models and paving the way for improved healthcare accessibility in underserved regions
Perancangan Jaminan Kualitas Kehalalan Produk Makanan Berdasarkan Metode Failure Mode Effect Analysis (FMEA) (Studi Kasus: UMKM Cilok ABC)
No full textCilok is a type of traditional snack from West Java made from tapioca flour. Based on observations, the cilok production process includes activities that have the risk of reducing the halal assurance of the product. Therefore, this study aims to identify any reduction in halal assurance using the Failure Mode and Effect Analysis (FMEA) method to ensure halal compliance by business operators. Based on the results of identification by identifying halal assurance by determining the Risk Priority Number (RPN) based on a scale on severity (severity), level of occurrence (occurrence) and level of occurrence (detection), revealed eleven risks of reduced halal assurance. The next step is to propose improvements to implement halal assurance measures, following the given recommendations to maintain the product’s halal status
Islamic Scientific Education Based on Taurat, Zabur, Injil, Quran, and Hadith
No full textThe aim of this research is Allah\u27s messages at QS Al Maidah 46, 66 – 68, and QS Ar Araf 170. At all that surah we know if moslem must used Taurat, Injil, Al Qur’an for law and human daily activity included education. Why Allah said like this it’s because grandchild of Prophet Ibrahim A.S had three imam, they are Rabi imam for Turat and Zabur, Paus Imam for Injil, Imam Makkah Imam for Al Qur’an. Purpose for this research is we can get complete knowledge for our theory and research product that no one can interrupted out knowledge especially at Isaiah and Moslem zone. This research used interview and secondary data from all Allah holly books and scientific journal since April 2019 until April 2024 with descriptive qualitative analyze. Result from this research are Isaiah and Moslem only had one God, and it’s Allah and Jesus is Allah\u27s Prophet (Taurat Tanakh Tafsir Razaq, Zabur 1:1, Injil Genesisn 1:1, QS Al Ikhlas, HR Ibnu Mas’ud).The truth of human evolution theory is human come from Prophet Adam A.S and Eve, theory Darwinian comes from sabbath day (Taurat Kuzari 2 :20, Injil Imamat 26 : 2, Mathius 12:5, Ashabun Nuzul QS. Al Baqoroh 76, HR Abdirrahman Abdiilah bin Ibnu Mas’ud). Hawila location it’s Saudi Arabia (Taurat Samuel 15:7, Injil Genesis 2: 10 – 16, QS Al Baqoroh 35, HR Abu Daud, Tirmizi, Nasa’I : 4744).Complete Tarikh about Prophet Ibrahim A.S family, Prophet Ibrahim A.S had two wives, Sara and Hajar but if we used all holy books kitab Allah we know if Prophet Ibrahim had four wives, Sara mother of Europa, Hajar mother of Middle East Asia, Ketura mother of East Asia and ASEAN, Hajun mother of South Asia (Taurat Tanakh, Pirkei Avot 3:2, 5:21, Bamidbar Rabbah 13:2, Bereshit Rabbah 60:16, 61:1, Aggadat Bereshit 19:2, 3: 1-2, Injil Genesis 23:1, Genesis 16:1, Genesis 25:1, QS. Hujurat ; 11, QS. Ibrahim 37, QS Hud : 71, Kitab Al Qashah An Anbiya, HR Bukhari : 3112).Syaria Law Pirkei Avot 1:1, Zabur 1:2, 19:8, 119:1, Galatia5:18, Lukas 17:5, Mathius 5: 17 – 20, QS Ali Imran 3 – 4, QS Al Maidah 46,48,68, QS Ar Araf 170. Keluarga Nabi Adam A.S Sehendrin 38a: 9 – 18, Zabur 31 : 20, Genesis 1 – end, Exodus 1 – end, Barnabas lonsdale 117 – 120, QS Hijr 26, QS Al Maidah 27 – 32, HR Bukhari 3083. Money and monetary Miscnah Masser Sheni 2 : 5 – 9, Lukas 15 : 8 – 10, Mathius 20 : 1 – 16, QS Ali Imran 75, QS Yusuf 20, HR Bukhari. Daging halal Beitzah 32b: 11 – 12, Imamat 11:4, 47, Yesaya 16: 17, Ulangan 14 : 8, QS Al An’am 146. Last Prophet and Qiyamah Injil Barnabas lonsdale – laura halaman 117 – 120, QS An Nur : 146 : HR Syekh Taharsi so the conclusion is relation between knowledge and Taurat, Zabur, Injil, Al Qur’an, and Hadist, Isaiah and Moslem zone never can interrupted and all Imam father Rabi, Paus, Imam Makkah will accepted
Algoritma Random Forest dan Synthetic Minority Oversampling Technique (SMOTE) untuk Deteksi Diabetes
No full textDiabetes is one of the challenges in global health. Indonesia ranks 5th in the world with the highest rate of diabetes. This research uses the Random Forest algorithm for diabetes detection. The purpose of this study is to detect diabetes using the Random Forest algorithm, which provides accurate and efficient results in the early diagnosis of diabetic patients. The data used is secondary data, specifically the “Diabetes Dataset,” which consists of 952 data points and has 17 features. The test scenario in this study divides the data into three parts, namely scenario 1 (90:10 ratio), scenario 2 (70:30 ratio), and scenario 3 (50:50 ratio). In each scenario, a comparison is made between using SMOTE and not using it. The best performance results are obtained in scenario 1, which uses SMOTE, producing 97% accuracy, 100% precision, 94% recall, and an F1-score of 97%
Analisis Ketertarikan Pengguna Microsoft Excel Online untuk Pengolahan Data Silsilah Keluarga Menggunakan TAM dan TPB
No full textThe use of web-based applications such as Microsoft Excel Online has increased, including for recording family genealogy data. This study aims to analyze the factors influencing the intention and behavior of using this application based on the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and their combined framework. The constructs examined include perceived ease of use, perceived usefulness, attitude, subjective norm, perceived behavioral control, intention, and behavior. This quantitative study collected primary data through questionnaires distributed to family members using Microsoft Excel Online. Data analysis was conducted using SEM-PLS (Structural Equation Modeling-Partial Least Squares) with the assistance of SmartPLS version 4.1.0.2. The results indicate that perceived ease of use and perceived usefulness positively and significantly affect attitude, while attitude, subjective norm, and perceived behavioral control positively influence behavioral intention. Furthermore, behavioral intention has a positive effect on actual usage behavior. These findings suggest that Microsoft Excel Online is reliable for recording family genealogy data and supports technology acceptance among users
Android Malware Threats: A Strengthened Reverse Engineering Approach to Forensic Analysis
No full textThe widespread adoption of Android devices has rendered them a primary target for malware attacks, resulting in substantial financial losses and significant breaches of user privacy. Malware can exploit system vulnerabilities to execute unauthorized premium SMS transactions, exfiltrate sensitive data, and install additional malicious applications. Conventional detection methodologies, such as static and dynamic analysis, often prove inadequate in identifying deeply embedded malicious behaviors. This study introduces a systematic reverse engineering framework for analysing suspicious Android applications. In contrast to traditional approaches, the proposed methodology comprises six distinct stages: initialization, decompilation, static analysis, code reversal, behavioral analysis, and reporting. This structured process facilitates a comprehensive examination of an application’s internal mechanisms, enabling the identification of concealed malware functionalities. The findings of this study demonstrate that the proposed method attains an overall effectiveness of 84.3%, surpassing conventional static and dynamic analysis techniques. Furthermore, this research generates a detailed list of files containing specific malware indicators, thereby enhancing the effectiveness of future malware detection and prevention systems. These results underscore the efficacy of reverse engineering as a critical tool for understanding and mitigating sophisticated Android malware threats
Optimizing K-Means Algorithm Using the Purity Method for Clustering Oil Palm Producing Regions
No full textThe K-Means algorithm is a fundamental tool in machine learning, widely utilized for data clustering tasks. This research aims to enhance the performance of the K-Means algorithm by integrating the Purity method, with a specific focus on clustering regions renowned for oil palm production in North Aceh. Oil palm cultivation is a vital agricultural sector in North Aceh, contributing significantly to the local economy and employment. This study examines two clustering techniques: the conventional K-Means algorithm and an optimized version, Purity K-Means. Integrating the Purity method enhances the efficiency of K-Means by reducing the number of required convergence iterations. The data used for clustering analysis is sourced from the Department of Agriculture and Food in North Aceh Regency and pertains to oil palm production in 2023. The findings indicate that the Purity K-Means approach notably reduces the iteration count and improves cluster quality. The average Davies-Bouldin Index (DBI) for standard K-Means is 0.45, whereas the Purity K-Means method lowers it to 0.30. Furthermore, applying the Purity method reduced the number of K-Means iterations from 15 to just 3. These results highlight an enhancement in clustering performance and overall efficiency
Analisis Forensik Metadata Lokasi Android Dengan Autopsy dan Evaluai Akurasi Haversine
No full textDi balik setiap foto yang diambil dengan ponsel Android tersembunyi jejak digital yang tak kasat mata yaitu metadata lokasi. Informasi ini bukan sekadar angka koordinat, melainkan kunci penting dalam menelusuri perjalanan seseorang dalam investigasi forensik digital. Penelitian ini bertujuan untuk menganalisis metadata lokasi dari citra Android menggunakan perangkat lunak forensik open-source Autopsy, serta mengevaluasi akurasi data lokasi tersebut dengan rumus Haversine. Metode yang digunakan meliputi ekstraksi metadata EXIF dari file gambar, pengumpulan koordinat lokasi sebenarnya sebagai ground truth, dan penghitungan jarak kesalahan posisi. Hasil menunjukkan bahwa Autopsy mampu mengidentifikasi metadata lokasi dengan rata-rata tingkat akurasi sebesar 0.30 meter, yang menjadikannya alat yang dapat diandalkan dalam mendukung proses investigasi forensik digital.
Kata kunci: Forensik Digital, Metadata Lokasi, Android, EXIF, Autopsy
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FORENSIC ANALYSIS OF ANDROID LOCATION METADATA USING AUTOPSY AND HAVERSINE ACCURACY EVALUATION
Behind every photo taken with an Android phone lies an invisible digital trace, location metadata. This information is more than just a set of coordinates; it can serve as a crucial key in uncovering an individual\u27s movements during a digital forensic investigation. This study aims to analyze the location metadata embedded in Android images using the open-source forensic tool Autopsy, and to evaluate the accuracy of the retrieved location data using the Haversine formula. The methodology involves extracting EXIF metadata from image files, collecting the actual location coordinates as ground truth, and calculating the positional error distance. The results show that Autopsy is capable of identifying location metadata with an average accuracy of 0.30 meters, making it a reliable tool to support digital forensic investigations.
Keywords: Digital Forensics, Location Metadata, Android, EXIF, Autops
Earthquake Hazard Analysis in Probolinggo Region as a Mitigation Effort Using Probabilistic Seismic Hazard Analysis Method: Analisis Bahaya Gempa Bumi Di Wilayah Probolinggo Sebagai Upaya Mitigasi Menggunakan Metode Probabilistic Seismic Hazard Analysis
No full textProbolinggo is one of the areas traversed by an active fault, namely the Probolinggo Fault. As an area that is prone to earthquake disasters, Probolinggo needs to have an earthquake hazard modeling as a mitigation effort to minimize the impact of an earthquake that occurs in the future. Earthquake hazard modeling is a multidisciplinary science that aims to predict earthquakes, and the ground shaking they produce. One method that can be used is Probabilistic Seismic Hazard Analysis (PSHA). This study aims to analyze the earthquake hazard in Probolinggo area using the PSHA method as an effort to mitigate earthquake prone areas. The data used is historical earthquake data from the Agency for Meteorology, Climatology, and Geophysics (BMKG) for the 1973-2020 period with a magnitude of Mw ≥ 5, a depth of 0-300 km, and a radius of 300 km from the study area. The earthquake source model used includes megathrust, faults, and background earthquake sources. Three sets of Ground Motion Prediction Equation (GMPE) were used for each earthquake source. PSHA was performed for the condition of a 2% probability of being exceeded in 50 years. The average shear wave velocity to a depth of 30 m (Vs30) from the United States Geological Survey (USGS) were used to model the peak ground acceleration on the surface. The results showed that the peak ground acceleration (PGA) at bedrock ranged from 0.27 to 0.71 g. PGA at the surface (PGAM) ranges from 0.27 to 0.83 g. The distribution of the amplification value in Probolinggo area is 1.02 to 1.12. The earthquake hazard analysis obtained shows that the northern part of the Probolinggo area has a higher earthquake hazard than the southern part. The results of the study can be used as consideration in regional development based on earthquake risk reduction