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All Journal Fountain of Informatics Journal Squalen Bulletin of Marine and Fisheries Postharvest and Biotechnology Building of Informatics, Technology and Science Journal of Innovation and Future Technology (IFTECH) Advances in Police Science Research Journal KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika
Abdillah, Rifqi
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Upaya Unit Patroli Satuan Sabhara Dalam Mencegah Kasus Pencurian Kendaraan Bermotor Di Wilayah Hukum Polres Cilacap Abdillah, Rifqi
Advances in Police Science Research Journal Vol. 1 No. 3 (2017): March, Advances in Police Science Research Journal
Publisher : Indonesian National Police Academy

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Abstract

Penelitian ini dilatarbelakangi karena adanya beberapa kasus curanmor yang terjadi di Kabupaten Cilacap, bahkan keadaan ini menjadikan masyarakat resah dan tidak aman. Sehingga penulis melakukan penelitian yang bertujuan untuk mengetahui seperti apa Upaya pencegahan yang dilakukan unit patroli Satuan Sabhara dalam mencegah kasus pencurian kendaraan bermotor di wilayah Polres Cilacap. Beberapa teori dan konsep pemikiran yang digunakan oleh penulis pada penulisan skripsi adalah sebagai berikut: Teori Manajemen, Teori Aktivitas Rutin, Konsep Upaya, Konsep Sabhara, Konsep Patroli, Konsep Pencurian Kendaraan Bermotor. Metode penelitian menggunakan pendekatan (field research yaitu penelitian yang dilakukan dengan cara riset ke lapangan untuk memproleh perbandingan antara teori dan praktek. Pendekatan kualitatif diskriptif yang bersumber dari data primer dan sekunder melalui tehnik pengumpulan data, wawancara dan observasi. Berdasarkan hasil penelitian yang telah dilakukan, maka diberikan hasil bahwa upaya unit patroli Satuan Sabhara dalam mencegah kasus curanmor diwilayah hukum Polres Cilacap masih belum dapat dikatakan berhasil disebabkan oleh kondisi sumber daya manusia yang kurang sehingga tidak dapat memaksimalkan saran prasarana serta anggaran yang ada, sehingga berdampak juga pada pelaksanaannya, Dan beberapa faktor baik secara internal dan eksternal, faktor internal adalah kekurang pahaman dan kesadaran bagi tiap-tiap anggota untuk melaksanakan tugas dan tanggung jawabnya. Faktor eksternal adalah masyarakat dapat dibilang apatis terhadap kewaspadaan terhadap barang kepemilikannya. Saran yang dapat diberikan penulis yaitu peningkatan sumber daya manusia sesuia dengan sarana prasarana dan anggaran yang ada. Lakukan koordinasi dengan satuan fungsi lain dan instanti lain diharapkan dapat membantu dalam mencegah dan menekan angka pencurian kendaraaan bermotor di wilayah hukum Polres Cilacap.
Algorithmic Advancements in Heuristic Search for Enhanced Sudoku Puzzle Solving Across Difficulty Levels Pratama, Moch Deny; Abdillah, Rifqi; Herumurti, Darlis; Hidayati, Shintami Chusnul
Building of Informatics, Technology and Science (BITS) Vol 5 No 4 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i4.4622

Abstract

Computer technology, particularly artificial intelligence, has found diverse applications in the rapidly evolving era of the industrial revolution, notably in gaming, delving into artificial intelligence and explicitly applying game-solving techniques to Sudoku puzzles. Sudoku, a popular game requiring logical precision, serves as an ideal platform for exploring algorithms such as depth-first search, breadth-first search, and heuristic search. This research identifies memory-intensive demands in breadth-first search and the potential issue of infinite traversal in depth-first search. To address these challenges, the study proposes implementing the heuristic search algorithm, which prioritizes promising paths based on estimations of proximity to the goal state made by a heuristic function. The primary objective is to enhance Sudoku puzzle-solving by comparing the performance of the heuristic search algorithm with traditional breadth-first and depth-first search methods, with a particular focus on improving efficiency and reducing memory usage, including time and steps. The results indicate that the heuristic search algorithm outperforms traditional methods, demonstrating faster completion times and reduced memory requirements, thereby contributing to the advancement of Sudoku-solving algorithms. The study evaluates their performance across different difficulty levels, utilizing data from sudoku.com and extremesudoku.info. Notably, the heuristic search algorithm emerges as a superior method, outperforming other algorithms in terms of completion steps and time efficiency. The implementation and analysis involved three types of Sudoku puzzle-solving methods, revealing that the heuristic search algorithm significantly outperforms other algorithms, optimizing its performance in solving Sudoku puzzles. The average time required to complete Sudoku puzzles from data sourced from Sudoku.com was 0.02, 0.05, and 0.61 seconds for each level, respectively. In contrast, according to extremesudoku.info, it took 0.31 seconds for the highest difficulty level. Furthermore, the average total steps needed on sudoku.com ranged from 43 to 1201 steps for each level, spanning from easy to hard. On extremesudoku.info, 509 steps were required for the highest difficulty level. These results affirm the reliability of heuristic search, consistently demonstrating encouraging outcomes and outperforming other algorithms across diverse conditions. This strategic selection facilitates a comprehensive analysis of Sudoku problem-solving algorithms, allowing for the exploration of algorithmic performance and providing a comprehensive range of Sudoku puzzles, thereby ensuring the study's robustness and validity
Water Quality Identification Using Ensemble Machine Learning and Hybrid Resampling SMOTE-ENN Algorithm Pratama, Moch Deny; Abdillah, Rifqi; Haq, Dina Zatusiva
Fountain of Informatics Journal Vol. 9 No. 2 (2024): November 2024
Publisher : Universitas Darussalam Gontor

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Abstract

Abstract Water is essential for all living organisms, yet only a small fraction is fresh and suitable for consumption. The limited availability of freshwater sources, worsened by pollution, overuse, and climate change, underscores the urgent need for sustainable water management. Traditional water quality identification methods are labour-intensive, slow, and costly. Water quality identification often struggles with data quality, imbalanced datasets, and model interpretability. These challenges lead to inaccuracies, especially in detecting minority classes, which is crucial for identifying pollution. This research explores machine learning (ML) techniques to address the limitations of water quality classification by integrating ensemble learning using LightGBM and hybrid Resampling using SMOTE-ENN. Ensemble learning techniques improve accuracy and robustness by aggregating the strengths of multiple models, effectively handling imbalanced data and reducing overfitting. Hybrid Resampling techniques enhance model sensitivity by generating synthetic minority-class samples and refining datasets through noise reduction. Together, these integrations provide a more reliable framework for water quality identification, enabling timely and accurate. This innovative method offers a robust solution for addressing data imbalance and overfitting, ensuring more effective detection of polluted conditions. This study highlights the importance of advanced ML techniques in improving water quality tasks and underscores LightGBM's effectiveness in handling imbalanced data post-SMOTE-ENN application. This method is known for its superior performance, achieving the highest performance evaluation metrics in water quality classification with accuracy, F1-Score, and increasing the recall value by 3% with values ​​of 94.50%, 94.76% and 93.00%, respectively. Keywords: Water Quality, Machine Learning, Imbalanced Data, LightGBM, SMOTE-ENN, Ensemble Learning, Hybrid Resampling.   Abstrak Air sangat penting bagi semua organisme hidup, namun hanya sebagian kecil yang segar dan layak untuk dikonsumsi. Terbatasnya ketersediaan sumber air bersih, yang diperburuk oleh polusi, penggunaan berlebihan, dan perubahan iklim, menggarisbawahi kebutuhan mendesak akan pengelolaan air berkelanjutan. Metode identifikasi kualitas air tradisional memerlukan banyak tenaga kerja, lambat, dan mahal. Identifikasi kualitas air sering kali bermasalah dengan kualitas data, kumpulan data yang tidak seimbang, dan kemampuan interpretasi model. Tantangan-tantangan ini menyebabkan ketidakakuratan, terutama dalam mendeteksi kelompok minoritas, yang sangat penting dalam mengidentifikasi polusi. Penelitian ini mengeksplorasi teknik pembelajaran mesin (ML) untuk mengatasi keterbatasan klasifikasi kualitas air dengan mengintegrasikan pembelajaran ensembel menggunakan LightGBM dan pengambilan sampel hybrid menggunakan SMOTE-ENN. Teknik pembelajaran ensemble meningkatkan akurasi dan ketahanan dengan menggabungkan kekuatan beberapa model, menangani data yang tidak seimbang secara efektif, dan mengurangi overfitting. Teknik pengambilan sampel hibrid meningkatkan sensitivitas model dengan menghasilkan sampel kelas minoritas sintetik dan menyempurnakan kumpulan data melalui pengurangan noise. Bersama-sama, integrasi ini memberikan kerangka kerja yang lebih andal untuk identifikasi kualitas air, sehingga memungkinkan dilakukannya identifikasi secara tepat waktu dan akurat. Metode inovatif ini menawarkan solusi yang kuat untuk mengatasi ketidakseimbangan dan overfitting data, sehingga memastikan deteksi kondisi tercemar dengan lebih efektif. Studi ini menyoroti pentingnya teknik ML tingkat lanjut dalam meningkatkan tugas kualitas air dan menggarisbawahi efektivitas LightGBM dalam menangani data yang tidak seimbang pasca penerapan SMOTE-ENN. Metode ini dikenal dengan kinerjanya yang unggul, mencapai metrik evaluasi kinerja tertinggi dalam klasifikasi kualitas air dengan akurasi, F1-Score, dan meningkatkan nilai recall sebesar 3% dengan nilai masing-masing 94,50%, 94,76% dan 93,00%. Kata kunci: Kualitas Air, Pembelajaran Mesin, Data Ketidakseimbangan, LightGBM, SMOTE-ENN, Pembelajaran Ensemble, Pengambilan Sampel Hibrid.
Antimicrobial ointment based on Bacillus subtilis subsp. subtilis HSFI-9 isolated from Sea Cucumber of Kodek Bay Lombok Indonesia Rakhmawatie, Maya Dian; Diatri, Devita; Samiroh, Samiroh; Abdillah, Rifqi; Arfiyanti, Mega Pandu; Ethica, Stalis Norma; Zilda, Dewi Seswita
Squalen, Buletin Pascapanen dan Bioteknologi Kelautan dan Perikanan Vol 20, No 1 (2025): May 2025
Publisher : :Agency for Marine and Fisheries Research and Human Resources, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/squalen.925

Abstract

The ethyl acetate extract of Bacillus subtilis subsp. subtilis HSFI-9, a bacteria isolated from intestinal fermentation of sea cucumbers (Holothuria scabra) is known to have antimicrobial properties. This research aimed to determine the activity of HSFI-9 extract ointment against Staphylococcus aureus and Candida albicans. Extract ointment is a topical preparation for skin infections made from a mixture of Vaseline Alba and Adeps lanae bases. The extract ointment was prepared into four concentrations of 0.003%, 0.03%, 0.3%, and 1% w/v using HSFI-9 as active ingredient.  Antimicrobial assay was carried out in vitro using the disc diffusion method. The extract ointment was evaluated based on organoleptic, homogeneity, spreadability, adhesion characteristics, and pH tests. The optimal concentration of the extract ointment to inhibit the growth of S. aureus  0.3% (inhibition zone of 11.67±1.26 mm) and against C. albicans is 0.03% (inhibition zone of 10.16±1.50 mm). The activity of the extract ointment was categorized as strong although not as strong as the antibiotic control ointment Mupirocin 2% or Ketoconazole 2%. The extract ointment organoleptic indicated a characteristic odor of ethyl acetate, was yellowish-white ointment, and had a homogeneous and smooth consistency. The extract ointment also had properties such as good spreadability but poor adhesion and tended to have an acidic pH ( 4.5). The HSFI-9 extract can be declared feasible for the development of topical antimicrobials. The ointment still needs to be optimized, especially regarding improving the adhesion characteristic and pH to be safe for the skin and mucosa.
Analisis Transformasi Digital Pelayanan Kesehatan Publik melalui Implementasi Aplikasi SiKuat di Puskesmas Kota Sidoarjo Purwita, Anggraeni Widya; Izzati, Berlian Maulidya; Cinthya, Monica; Elfaiz, Ersha Aisyah; Abdillah, Rifqi
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 6, No 1 (2025)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2025.v6i1.7784

Abstract

Digital transformation is an important part of improving the quality of health services, especially through the implementation of information systems. SiKuat is an information system developed to support the efficiency of the Puskesmas. The purpose of this study is to analyze the implementation process of SiKuat using the Diffusion of Innovation theory as an analytical framework with a qualitative approach with a case study. From the results of interviews, observations, and document analysis, it shows that SiKuat has a relative advantage in accelerating and efficient service time, as well as observability whose benefits are easily observed directly by users, especially during queues and waiting times for services. However, obstacles occur in the aspect of system compatibility with the flow and work procedures that are customary, and the complexity and trial capabilities there is no trial phase before SiKuat is fully implemented during operations because the system is relatively complicated. Without increasing training, adjustment systems, and gradual implementation of strategies, the implementation of SiKuat is at risk of being limited to the initial user group. Strengthening the five innovation attributes in a balanced manner is needed to expand the institutional diffusion system to the early majority phase.
PENENTUAN DOSIS KOAGULAN PADA PENGOLAHAN AIR MINUM: PENDEKATAN FUZZY BERBASIS DATA DAN PENENTUAN FUZZY SET BERBASIS Z-SCORE Cinthya, Monica; Vinarti, Retno Aulia; Septiyanti, Nisa Dwi; Putra, Cendra Devayana; Rahman, Erik; Abdillah, Rifqi
Journal of Innovation And Future Technology (IFTECH) Vol. 7 No. 2 (2025): Vol 7 No 2 (Agustus 2025): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/0ffxq425

Abstract

direct use of raw water has serious health risks. Therefore, various water treatment processes are needed to make the raw water safe for use in domestic purposes. One important stage in such processing processes is coagulation and flocculation, where chemicals (coagulants) are used to remove colloidal particles and form larger floc that can be easily precipitated through sedimentation and filtration. Determination of the optimal coagulant dosage is essential to achieve the desired water quality. However, jer-test problems, the non-linear nature of water, and the complexity of coagulation theory can make it difficult to determine the optimal dose. Therefore, in this study, a system is proposed that uses a data-based fuzzy approach and fuzzy set determination using z-score to study data patterns and relationships between parameters in the coagulation process. The proposed method utilizes a fuzzy approach to address the non-linear nature of water and the complexity of coagulation theory. The system uses the collected data patterns to develop fuzzy models that can predict optimal coagulant doses based on specific conditions. This approach allows the system to learn from existing data and identify patterns of relationships that may be hidden between relevant parameters. The results showed that the proposed system achieved an RMSE value of 0.7639589866827494, while the MSE value was 0.5836333333333333333. This suggests that the system can provide a fairly accurate prediction of the dose of coagulant required in the coagulation process.
Co-Authors Arfiyanti, Mega Pandu Berlian Maulidya Izzati Cinthya, Monica Darlis Herumurti Dewi Seswita Zilda Diatri, Devita Elfaiz, Ersha Aisyah Haq, Dina Zatusiva Hidayati, Shintami Chusnul Maya Dian Rakhmawatie Nisa Dwi Septiyanti Pratama, Moch Deny Purwita, Anggraeni Widya Putra, Cendra Devayana Rahman, Erik Retno Aulia Vinarti Samiroh Samiroh, Samiroh Stalis Norma Ethica