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All Journal Jurnal Inovasi Teknologi Pendidikan Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Pengabdian Magister Pendidikan IPA GERVASI: Jurnal Pengabdian kepada Masyarakat DIKDAS MATAPPA: Jurnal Ilmu Pendidikan Dasar Alamtara: Jurnal Komunikasi dan Penyiaran Islam Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Mnemonic At-Tanzir : Jurnal Ilmiah Prodi Komunikasi Penyiaran Islam Ilomata International Journal of Social Science jeti International Journal of Electronics and Communications Systems Indonesian Journal of Educational Development (IJED) Jurnal Begawe Teknologi Informasi Rumoh: Journal of Architecture Jurnal Teknik Sipil Macca Progressive Physics Journal COMPETITIVE: Journal of Education Journal of Data Science and Software Engineering JURNAL PENGABDIAN MASYARAKAT YAMASI Aceh Journal of Electrical Engineering and Technology Millatuna: Jurnal Studi Islam ARUS JURNAL SAINS DAN TEKNOLOGI WATHAN: Jurnal Ilmu Sosial dan Humaniora Jurnal MediaTIK Macca: Science-Edu Journal Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics International Journal Of Synergi In Law, Criminal And Justice Journal of Shoutheast Asian Islam and Society (JSEAIS) Al-Hayat: Journal of Islamic Education Jurnal Kolaborasi Akademika Media for Empowerment, Mobilization, and Innovation in Research & Community SainsTech Innovation Journal Tilawah: Journal of Al-Qur'an Studies Jurnal Ilmiah Mandalika Education Scientific Contributions Oil and Gas J-MILE: Journal of Management and Industrial Engineering
Muliadi
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Religion Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Murâbahah Li Al-Âmir Bi Al-Syirâ’ in the Perspective of Scholars: An Analysis of Contemporary World Fatwa Herman, Marlinda; Muliadi
Journal of Southeast Asian Islam and Society Vol. 4 No. 1 (2025): JSEAIS
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/8hsmr108

Abstract

In classical fiqh, murâbahah is a simple sale and purchase contract that requires the seller to tell the truth about the cost and profit. This concept was later transformed in Islamic banking into murâbahah li al-âmir bi al-syira’, which introduced a credit sales system as a form of financing. This study reveals some contemporary world fatwas regarding the murâbahah li al-âmir bi al-syirâ’ contract with a qualitative-descriptive approach through library research. The results of the study show that there is ikhtilaf among contemporary scholars regarding the permissibility of the practice of this contract, with some critics calling the dominance of Murâbahah in Islamic banking products a ‘deviation from Islamic principles’ and encouraging Islamic banking to switch to a financing model based on profit loss sharing. However, some scholars in Islamic countries have issued fatwas accepting this contract with some stipulations that should not be violated by Islamic banks, otherwise, the validity of this contract should be doubted.
Penyeimbangan Kelas SMOTE dan Seleksi Fitur Ensemble Filter pada Support Vector Machine untuk Klasifikasi Penyakit Liver Nugraha, Muhammad Amir; Mazdadi, Muhammad Itqan; Farmadi, Andi; Muliadi; Saragih, Triando Hamonangan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 6: Desember 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023107234

Abstract

Liver merupakan salah satu organ penting dalam tubuh manusia yang berperan dalam proses metabolisme tubuh. Mengutip artikel dari situs American Liver Foundation, pada tahun 2020 sebanyak 51.642 orang dewasa di Amerika Serikat meninggal akibat penyakit liver. Data hasil tes fungsi liver dari laboratorium dapat digunakan untuk mendiagnosis penyakit liver. Klasifikasi penyakit liver pada pasien perlu dilakukan dengan baik karena hasilnya dapat membantu dalam diagnosis awal apakah seorang pasien mengidap penyakit liver. Berdasarkan penelitian sebelumnya, metode Support Vector Machine (SVM) paling baik dalam mengklasifikasikan pasien penyakit liver. Namun, SVM memiliki kelemahan ketika diterapkan pada dataset dengan kelas yang tidak seimbang dan tidak bekerja secara akurat ketika terlalu banyak fitur yang tidak relevan digunakan. Untuk menyeimbangkan kelas pada dataset, digunakan metode Synthetic Minority Oversampling Technique (SMOTE). Sedangkan untuk seleksi fitur dilakukan menggunakan metode Ensemble Filter, terdiri dari metode Information Gain, Gain Ratio, dan Relief-F untuk menangani fitur-fitur tidak relevan. Berdasarkan hasil pengujian, penerapan SMOTE dan Ensemble Filter pada metode klasifikasi SVM memberikan hasil terbaik dengan nilai accuracy sebesar 85% dan AUC sebesar 0,850. Pengujian tersebut dapat membuktikan jika SMOTE pada penyeimbangan kelas dan Ensemble Filter pada seleksi fitur dapat meningkatkan performa klasifikasi dari metode SVM.    Abstract   The liver is one of the important organs in the human body that plays a role in the body's metabolic processes. Quoting an article from the American Liver Foundation website, in 2020, as many as 51,642 adults in the United States died from liver disease. Liver function test data from the laboratory can be used to diagnose liver disease. Classification of liver disease in patients needs to be done well because the results can help in the initial diagnosis of whether a patient has liver disease. Based on previous research, the Support Vector Machine (SVM) method best classifies liver disease patients. However, SVM has weaknesses when applied to datasets with unbalanced classes and does not work accurately when too many irrelevant features are used. To class-balance the dataset, the Synthetic Minority Oversampling Technique (SMOTE) method is used. Meanwhile, feature selection is performed using the Ensemble Filter method, which consists of Information Gain, Gain Ratio, and Relief-F methods to handle irrelevant features. Based on the test results, the application of SMOTE and Ensemble Filter in SVM classification gives the best results with an accuracy value of 85% and an AUC of 0.850. The test can prove if SMOTE on class balancing and Ensemble Filter on feature selection can improve the classification performance of the SVM method.
Settlement Spatial Planning Reconstruction Site Umah Pitu Ruang Cahayani, An’gun; Muliadi; Waulandari, Elysa; Jamaludin, Masdar
Rumoh Journal of Architecture Vol. 13 No. 1 (2023): Rumoh: Journal of Architecture
Publisher : Department of Architecture, Faculty of Engineering, University of Muhammadiyah Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37598/rumoh.v13i1.301

Abstract

The spatial arrangement patterns of rural areas are generally closely related to the natural environment and surrounding ecological, spiritual, and theological values. Kampung Genuren, the location chosen for the reconstruction of the Umah Pitu Ruang, is characterized by the presence of agricultural and plantation lands within its residential area. Moreover, Kampung Genuren is one of the traditional villages that still adheres to the Gayo cultural system, with a well-preserved rural atmosphere—both in terms of the local community’s activities and the environmental conditions. These characteristics make Kampung Genuren an appropriate site for the Umah Pitu Ruang reconstruction. The community's cultural practices and land use patterns help reveal various potential characteristics of the spatial settlement pattern in Kampung Genuren. These elements form the analytical foundation for identifying both opportunities and challenges that may arise at the study site, particularly in relation to the location and process of the Umah Pitu Ruang reconstruction, which is the main objective of this research. Based on field findings, the researcher conducted a site study using a descriptive qualitative method. The analysis of existing conditions was supported by map-based analysis through several stages to obtain primary data, which then served as a reference for identifying the spatial pattern characteristics of Kampung Genuren. The research was conducted over approximately three months. The initial stage involved collecting secondary data, followed by the acquisition of primary data through several journal references. These data were then processed and described using field documentation results, and visualized in map form using software applications such as ArcGIS, Google Earth, satellite imagery, and other supporting tools. The research concludes that several supporting facilities in the form of nearly extinct traditional buildings will be provided as a means to revive and preserve Gayo culture through the reconstruction of Umah Pitu Ruang.
PENERAPAN MODEL PROBLEM BASED LEARNING UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA PESERTA DIDIK Mashfufah; Gugus Rahmadi; Muliadi
Jurnal Ilmiah Mandalika Education (MADU) Vol. 1 No. 2 (2023): OKTOBER
Publisher : Lembaga PKBM Tunas Harapan Varoso

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/madu.v1i2.61

Abstract

Matematika adalah ilmu eksak yang berperan sebagai media untuk menstimulasi cara berpikir peserta didik agar lebih terstruktur dan logis. Faktanya, pembelajaran matematika terbilang sulit dan hasil belajar peserta didik pun terbilang rendah. Hal ini memerlukan solusi berupa penggunaan model problem based learning agar mampu meningkatkan hasil belajar matematika terutama di SMPN 5 Masbagik. Diketahui bahwa model pembelajaran berdampak pada hasil belajar. Jenis penelitian ini adalah penelitian tindakan kelas yang terdiri dari 2 siklus dengan tiap siklus terdiri dari 4 tahapan (perencanaan, tindakan, pengamatan, dan refleksi). Jumlah sampel pada penelitian ini sebanyak 25 orang. Instrumen pengumpulan data berupa tes pilihan ganda dan dianalisis dengan deskriptif kuantitatif. Hasil penelitian menunjukkan bahwa terjadi peninngkatan hasil belajar peserta didik pada mata pelajaran matematika setelah melaksanakan pembelajaran dengan model problem based learning selama 2 siklus.
The Application of Greimas' Narrative in the Story of the Prophet Yunus: A Structural Semiotic Study of the Quranic Narrative Wahyu Muhammad Abdul Wahid; Muliadi; Wildan Taufiq
Tilawah: Journal of Al-Qur'an Studies Vol. 1 No. 4 (2025)
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/tilawah.v1i4.13

Abstract

This article examines the story of Prophet Yunus in the Qur'an using A. J. Greimas' structural narrative theory, especially the actant model and narrative functional scheme. This study aims to explore the narrative structure of the story within the framework of structural semiotics in order to show the pattern of meaning transformation and character dynamics in the prophetic journey of Prophet Yunus. The methodology used is a qualitative-descriptive approach with an analysis of related Qur'anic texts, especially in Surah As-Saffat [37]:139–148, Q.S. Al-Anbiya’ [21] : 87-88, Yunus [10]:98, and Al-Qalam [68]:48–50. The results of the analysis show that the narrative structure of the story of Yunus represents six actant positions and three main functional stages that form spiritual and narrative transformation. This study contributes to strengthening the structural approach in the study of narrative interpretation and opens up interdisciplinary space between Qur'anic studies and modern narrative theory.
Parental role in supporting inclusive education for children with autism Muliadi; Tsaputra, Antoni; Rahmahtrisilvia; Nurhastuti; Amani, Risca
Indonesian Journal of Educational Development (IJED) Vol. 6 No. 3 (2025): November 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59672/ijed.v6i3.5351

Abstract

This research examines the role of parents in supporting the education of children with autism in special schools in Langsa City, Aceh. With the increasing number of children with autism spectrum disorders, attention to their educational needs has become very important. This research aims to identify the various roles played by parents and analyze the impact of their support on the social and academic development of the child. Qualitative descriptive methods were employed to assess the impact of parental involvement in the educational process on children's learning outcomes and social interactions. Data was collected using purposive sampling techniques. Data collection techniques used observation, interviews, and document studies, with the instruments used being observation guidelines and interview guidelines. The research results show that parents function as the primary supporters, who not only provide motivation but also play a crucial role in communication with teachers and in monitoring their child's development. Parental support has been proven to enhance children's self-confidence and social skills, thereby creating a more inclusive learning environment. Involving parents in the planning and evaluation of educational programs can significantly improve children's learning outcomes.
Identifikasi Struktur Bawah Permukaan Daerah Potensi Panas Bumi Di Daerah Tulehu Menggunakan Metode Gravitasi Indra Reza Kurniawan; Radhitya Perdhana; Muliadi
Progressive Physics Journal Vol. 6 No. 2 (2025): Progressive Physics Journal
Publisher : Program Studi Fisika, Jurusan Fisika, FMIPA, Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/w66fps36

Abstract

Indonesia has great geothermal potential, Indonesia is located in the path of volcanoes or the ring of fire can also be called the ring of fire. Maluku Province, especially the Ambon and Seram islands, has geothermal energy potential that can be developed as an alternative renewable source. One of the geothermal potentials located in the Maluku islands is WKP Tulehu which has a fairly high temperature reaching 134.09°C–251°C. One method that can be used to identify the subsurface layer of geothermal areas is the gravity method using GGMPlus gravity data. The 2013 Global Gravity Model Plus (GGMPlus) secondary gravity data is a global gravity model data that has ultra–high resolution with grid spacing between data points ~220 m in the north–south direction. The results of the identification of geological structures using gravity methods using regional anomaly values with a range of 80.7–101.3 mgal. The depth of the regional anomaly in the study area is estimated to be 1.862 km deep. There are 7 faults found in the 4 research cross sections. These faults are located in cross section A–A' at a distance of 8.30 km, cross section B–B' at a distance of 1.9 km and 5.1 km, cross section C–C' at a distance of 2.450 km and at a distance of 11.6 km, and cross section D–D' 2.248 km and 4.5 km.
Analysis of the mental readiness of technology and engineering students before industrial work practice Muliadi; Eddy Sutadji; Isnandar Isnandar; Widiyanti Widiyanti
Jurnal Inovasi Teknologi Pendidikan Vol. 12 No. 4 (2025): December (On Progress)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jitp.v12i4.85420

Abstract

Industrial Work Practice is an important stage for Vocational High School students in applying the technical skills acquired during the learning process to the world of work. Internal readiness is a determining factor for students' success in facing industry challenges. This study aims to analyse the internal readiness of students at Lingsar State Vocational High School 1, majoring in technology and engineering, before participating in pre-school, and to identify factors that affect this readiness. The method used is a quantitative descriptive method; data are collected through interviews. Moreover, questionnaires showed that 84 students had high self-confidence, while 50 felt anxious due to a lack of technical skills, and 38 admitted they lacked sufficient industry experience. A total of 95 students assessed that practitioners' roles are critical in shaping their internal readiness, indicating that educators' mentoring has a significant influence on their readiness. Statistical analysis shows that perseverance and environmental support factors contribute to students' internal readiness. Soft skill training programs, work culture simulations and strengthening psychosocial support, to ensure students have optimal internal readiness before entering the workforce.
Grey Wolf Optimization-Based Global MPPT for Solar-Assisted Hybrid Energy Systems in Oil and Gas Production Facilities Zulfadli, Teuku; Muliadi; Yassir; Zamzami; Salahuddin
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2056

Abstract

Partial shading in photovoltaic (PV) modules produces multiple power peaks that reduce system efficiency if the global maximum power point is not properly tracked. This condition commonly occurs in oil and gas production facilities due to shadows from industrial structures, requiring MPPT methods with reliable global tracking capability. This study evaluates the Grey Wolf Optimization (GWO) algorithm for global MPPT under eight partial shading scenarios (12.5%–100%) using MATLAB/Simulink simulation. The results show that GWO successfully tracks the global maximum power point under single-, double-, and triple-peak conditions. Under 12.5% shading, the system produces 277.0 W with an efficiency of 99.78%; under 25% shading, it produces 266.7 W with an efficiency of 99.85%; and under 37.5% shading, it produces 204.2 W with an efficiency of 99.90%. Across all scenarios, the algorithm achieves efficiencies above 99% with an average efficiency of 99.61%, which is higher than the 97.20% reported in previous studies. This efficiency improvement of approximately 2–4% increases the contribution of solar energy in PV–diesel hybrid systems and potentially reduces fuel consumption while improving power supply reliability for critical loads in oil and gas production facilities. Unlike conventional metaheuristic approaches such as PSO-MPPT, Flower Pollination Algorithm (FPA), and Differential Evolution (DE), which are sensitive to parameter tuning or prone to premature convergence, the proposed GWO implementation employs a hierarchical three-agent update mechanism (α, β, δ) that enhances global exploration capability across complex multi-peak P–V characteristics. This distinguishes the present study from prior GWO-based MPPT work that relied solely on the alpha agent for position update.
Application of Artificial Intelligence Algorithms to Improve the Accuracy of Agricultural Weather Predictions Maghfirah, Geubrina; Nurhanif; Yanti, Yeni; Muliadi
J-MILE: Journal of Management and Industrial Engineering Vol 2 No 1 (2026): April 2026
Publisher : J-MILE adalah jurnal akademik yang ditinjau sejawat (peer-reviewed) yang diterbitkan oleh CV Knowlexa Indonesia, terbit dua kali setahun (biannually) pada bulan April dan Oktober. Jurnal ini menampilkan penelitian teoretis dan empiris di bidang manaj

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Climate change, marked by increasing uncertainty in weather patterns, poses significant challenges to agricultural productivity in Indonesia. Accurate weather forecasting is therefore essential to support sustainable agrarian efficiency, parti-cularly in determining planting schedules, irrigation management, and mitigating crop failure risk. This study aims to apply artificial intelligence (AI) algorithms to improve weather prediction accuracy by comparing the performance of Long Short-Term Memory (LSTM), Random Forest (RF), and conventional methods, including ARIMA and Least Squares Method (LSM). The dataset used consists of historical meteorological parameters, including temperature, humidity, rainfall, and wind speed. The research process involved data collection, preprocessing, model development, and evaluation using RMSE, MAE, and R². The results reveal that LSTM outperforms the other models with an R² of 0.92, RMSE of 0.15, and MAE of 0.11, while RF achieved an R² of 0.85. In contrast, ARIMA and LSM showed lower performance with R² values below 0.80, highlighting the limitations of conventional approaches in capturing non-linear weather patterns. These findings confirm that the application of AI algorithms, particularly LSTM, provides more accurate weather forecasting, which directly contributes to sustainable agricultural practices by improving efficiency and resilience to climate variability.
Co-Authors A.A. Ketut Agung Cahyawan W Abdul Fattah Nasution Abdul Karim Abdul Latif Achmad Rizal Adean Mayasri Adrianda, Irsan Agitha, Nadiyasari Akbar Prayoga Aldy Ramadhan Amani, Risca Amin, Kasma Amna, Nurlaila Andi Farmadi Andi Farmandi Andi Ihwan Andriani, Cut Yessi Anjar Pranggawan Azhari Arlina Asyadi, Teuku Murisal Awal Nusantara Bayu Hadi Sudrajat Cahaya Maharani Sitompul Cahayani, An’gun Chalida Alfany Dedi Iskandar Desti Suci Safitri Dewi Fatmarani Surianto Difa Fitria Dini Rosyida Dira Ayu Annisa Dodon Turianto Nugrahadi Duyo, Rizal A Dwi Kartini Dwi Kartini, Dwi Eddy Sutadji Emma Andini Eriyani, Nindy Sri Erlianita, Noor Fadhli, Cut Fadillah, M. Surya Fahrul Rozi Fatma Indriani Fauzan Fridawati, Titit Friska Abadi Gugus Rahmadi Gunawan, Khairol Hafid, Abd Halimah Hasan Basri M. Nur Hasibuan, Helviana Hasita Dwi Putri Hendrawan Herman, Marlinda Hermiati, Arya Syifa Herri Muliadi Huynh, Phuoc-Hai Indah Nahdiat Isrori Indra Reza Kurniawan Irhami Irwan Budiman Irwan Budiman Isnandar Itqan Mazdadi, Muhammad Jahada Haluti, Islamiyati Jamaludin, Masdar Joko Sampurno Khairun Nisa Marpaung Kholipatul Hasanah Kurnia Prima Putra Linda Kurnia Mustafa M. Fauzi Rifqi M. Teguh Jaka Satya Samudra Jati Suara Maghfirah, Geubrina Mallikatul Hanin Marzuki Mashfufah Maulani Mochammad Imron Awalludin Muh. Ishak Jumarang Muhamad Fawwaz Akbar Muhammad Muhammad Denny Ersyadi Rahman Muhammad Itqan Mazdadi Muhammad Latief Saputra Muhammad Marwin Muhammad Nadim Mubaarok Muhammad Reza Faisal, Muhammad Reza Muhammad Taufiq Rahman, Muhammad Taufiq Muhardi Mulyantika, Dea Ambar Musa, Ratna Mustika Muzafar Nafis Satul Khasanah Nanda Wafiya Nirwana, Hafsah Nugraha, Muhammad Amir Nurhanif Nurhastuti Nurhidayat Nursalim, Danni Pajri Perdhana, Radhitya Pirjatullah Prastya, Septyan Eka Qaaf, Muhammad Alfath Radhitya Perdhana Radityo Adi Nugroho Rahmahtrisilvia Rahman Hadi Rahman Ramadani, Syahruni Ramadhan, Rafsanjani Ramadhani, Maudy Reza Faisal, Mohammad Ridwan, M. Arif Rina Sasmita Alfani Risdawati, Irsyam Riza Adriat Rudy Herteno Salahuddin Salam, Fitria Nur Dina Saragih, Sry Ningsih Saragih, Triando Hamonangan Satria Putra, Yoga Siena, Laifansan Sindi Hikmala Situngkir, Andreas Henfri Sri Indah Setiyaningsih MSM Sudarto Syamsuddin Syamsuddin Sylva Rahmah Hafiz Syukri Taufiq, Wildan Tengku Riza Zarzani N Teuku Zulfadli Tsaputra, Antoni Ulfa Khairina Wahyu Caesarendra Wahyu Muhammad Abdul Wahid Wasik, Abdul Waulandari, Elysa Widia Rahayu Widiyanti Widiyanti Wisnu Bekti Nugraha Yanti, Yeni Yassir Yulia Azmi Khotimah Yulisnaeni, Sri Yunida, Rahmi Yuris Sutanto Zaenuddin, Agus Rizal Zamzam, Yra Fatria zamzami Zulfian Zulfian