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All Journal Sinergi Scientific Journal of Informatics Jurnal Manajemen & Supervisi Pendidikan Jurnal Penelitian Sains JMM (Jurnal Masyarakat Mandiri) Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Jurnal Pengabdian Masyarakat Teknik JENIUS: Jurnal Terapan Teknik Industri Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Jurnal Jaring SainTek INVENTORY : Industrial Vocational E-Journal On Agroindustry Klabat Accounting Review
Muhendra, Rifki
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Transportation Other

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Evaluasi Kinerja Tenaga Kependidikan Berbasis SMARTER dan Strategi Optimalisasi Pelayanan di Perguruan Tinggi Muhendra, Rifki
Jurnal Jaring SainTek Vol. 7 No. 1 (2025): April 2025
Publisher : Fakultas Teknik, Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/aej3hb85

Abstract

Evaluasi kinerja tenaga kependidikan merupakan aspek penting dalam meningkatkan kualitas layanan akademik dan administratif di institusi pendidikan tinggi. Penelitian ini bertujuan untuk mengevaluasi kinerja tenaga kependidikan di Fakultas Teknik Universitas XYZ menggunakan metode SMARTER (Simple Multi-Attribute Rating Technique Exploiting Rank). Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei, di mana data dikumpulkan melalui kuesioner berbasis skala Likert. Hasil analisis menunjukkan bahwa tenaga kependidikan memiliki keunggulan dalam komunikasi dan kerja sama tim, namun masih perlu perbaikan dalam aspek produktivitas, efisiensi kerja, serta inisiatif dan pengembangan diri. Selain itu, diusulkan strategi peningkatan kinerja tenaga kependidikan mencakup pelatihan keterampilan komunikasi, program pengembangan diri, penerapan sistem umpan balik, serta optimalisasi proses kerja. Studi lebih lanjut dapat dilakukan dengan memperluas cakupan penelitian atau mengombinasikan metode lain untuk memperkaya hasil analisis.
Prediksi Kualitas Penyolderan pada Mesin Solder Wave Menggunakan Metode FIS dan ANFIS Model Sugeno Solihin, Solihin; Muhendra, Rifki; Prasmoro, Alloysius Vendhi; Al Munawir, Al Munawir
Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Vol 11, No 1 (2025): April
Publisher : universitas teuku umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jmkn.v11i1.11803

Abstract

This study aims to predict the quality of the soldering process using a wave soldering machine by utilizing the Sugeno model Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) methods. Soldering is a critical stage in PCB (Printed Circuit Board) production, where its quality is influenced by parameters such as solder temperature, conveyor speed, and flux volume. Traditional approaches such as visual inspection are considered less effective because they are prone to human error. Therefore, this study proposes the use of Sugeno FIS and ANFIS to model the non-linear relationship between process parameters and soldering quality, which is measured through Defect Per Opportunity (DPO). Data were obtained from the actual production process and processed using MATLAB. Sugeno FIS was applied with fuzzification, rule making, and defuzzification, while ANFIS combines neural networks with fuzzy logic for data-driven optimization. The results showed that both models were able to predict DPO with high accuracy, indicated by very small Root Mean Squared Error (RMSE) values (0.00179 for FIS Sugeno and 1.31597 × 10⁻⁶ for ANFIS). ANFIS excels in capturing non-linear complexity, especially in conveyor speed variations. Simulations using SIMULINK prove the effectiveness of this model in real-time prediction. These findings provide an innovative solution for the electronics industry to improve soldering quality automatically. Keywords -   Wave soldering, FIS Sugeno, ANFIS, quality prediction, DPO.
Pengembangan model peramalan dan estimasi upah pekerja Indonesia menggunakan metode curve fitting Muhendra, Rifki
Jurnal Penelitian Sains Vol 27, No 2 (2025)
Publisher : Faculty of Mathtmatics and Natural Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56064/jps.v27i2.1108

Abstract

Penelitian ini bertujuan untuk mengembangkan model peramalan dan estimasi upah pekerja di Indonesia dengan mempertimbangkan faktor pendidikan, jenis kelamin, dan wilayah. Data sekunder yang digunakan berasal dari Badan Pusat Statistik (BPS) untuk periode 2015 hingga 2021. Metode curve fitting diterapkan dengan pendekatan regresi linier dan polinomial untuk membangun model prediksi. Akurasi model dievaluasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan bahwa tingkat pendidikan memiliki korelasi positif yang kuat terhadap upah, di mana pekerja dengan pendidikan lebih tinggi cenderung memperoleh pendapatan yang lebih besar. Terdapat kesenjangan upah berbasis gender, meskipun perbedaannya menunjukkan tren penyempitan dari waktu ke waktu. Faktor wilayah juga berperan penting, di mana pekerja di daerah perkotaan umumnya memperoleh upah yang lebih tinggi dibandingkan pekerja di daerah pedesaan. Model regresi polinomial menunjukkan akurasi prediksi yang lebih baik dibandingkan model regresi linier. Temuan ini menekankan pentingnya investasi di bidang pendidikan serta perlunya perhatian terhadap kesenjangan upah berbasis wilayah dan gender. Model berbasis curve fitting ini memberikan pendekatan berbasis data untuk mendukung perumusan kebijakan upah yang lebih efektif dan berkeadilan di Indonesia.
Analyzing Bankruptcy Risk and Economic Correlation in a Re-gional Bank: A Study on Bank Nagari Muhendra, Rifki
Klabat Accounting Review Vol. 6 No. 2 (2025): Klabat Accounting Review
Publisher : UNKLAB Business School

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60090/kar.v6i2.1323.94-103

Abstract

Bankruptcy can cause uncertainty in financial markets and weaken the confidence of economic actors which leads to a slowdown in economic growth. The purpose of this study is to determine the health of regional banking through analysis and in-depth study in the late COVID-19 pandemic and early New Normal periods. The object of research is Bank Nagari. The research method used is a descriptive method sourced from public financial data. The results of this analysis show that Bank Nagari is in a state of bankruptcy. However, Bank Nagari remains in growth and shows an increase in operating profit. The correlation between bankruptcy value and GRDP was also further analyzed. The results show a value of 0.156 which means that the two variables do not have a significant relationship with each other in the period used. Bankruptcy can be one of the components that can affect the economic growth and stability of a country. Therefore, effective banking supervision and management is essential to maintain banking sector stability and promote healthy economic growth.
Optimasi Optical Distribution Cabinet (ODC) pada Jalur Optical Distribution Point (ODP) Menggunakan Metode Pemrograman Linear Spalanzani, Widya; Raihan, Dwi Rizky Puti; Zulkarnaen, Iskandar; Muhendra, Rifki
INVENTORY: Industrial Vocational E-Journal On Agroindustry Vol. 6 No. 2 (2025)
Publisher : Politeknik ATI Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52759/inventory.v6i2.73

Abstract

PT Telkom Access is a global internet service provider that plays a crucial role in developing fiber optic–based telecommunication infrastructure. One of its operational areas, located on Jl. Duri, Gambir District, Central Jakarta, faces issues related to the inefficient distribution route of the 1:4 Optical Distribution Point (ODP) serving twenty customer homes. This condition has led to 198 customer complaints in 2023 and high installation costs for the Optical Distribution Cabinet (ODC) to ODP distribution network, amounting to Rp 78,205,400. This study aims to optimize the installation cost of the Fiber to the Home (FTTH) network using a Linear Programming approach with the aid of LINGO software, as well as to design a more efficient ODC scheme on a new ODP configuration. The approach involves a comparative analysis between 1:4 and 1:8 ODP configurations, considering both technical and economic aspects of fiber optic network distribution. The results show that using an ODP 1:8 configuration with a 1:8 passive splitter in the new FTTH line produces a total installation cost of Rp 49,085,400, which is approximately Rp 29,120,000 lower than the 1:4 ODP configuration, resulting in cost optimization of 59.37%. In addition to cost savings, the ODP 1:8 configuration reduces network maintenance complexity and enhances distribution efficiency without compromising service quality. Based on these findings, this research recommends the adoption of the ODP 1:8 configuration as the optimal solution to improve cost efficiency, network maintainability, and sustainable infrastructure development in fiber optic network implementation. This strategy is expected to strengthen PT Telkom Access’s competitiveness and support sustainable global internet service performance.
A predictive safety and maintenance framework for railway locomotives: integrating HAZOP, FMEA, and IoT-based risk mitigation Muhendra, Rifki; Fadhlurrohman, Zain; Adi, Farhan Indra Pratama; Sinaga, Zulkani; Turseno, Andi
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2026.1.014

Abstract

Safety and maintenance efficiency are critical challenges in the railway industry, particularly in the use of lifting jacks for locomotive maintenance. This study proposes a predictive maintenance framework that integrates the Hazard and Operability Study (HAZOP), Failure Mode and Effects Analysis (FMEA), and Internet of Things (IoT) technology to detect potential failures in real time. A case study was conducted at a locomotive maintenance depot in Indonesia, where several occupational accidents had been recorded due to lifting jack malfunctions. Based on HAZOP and FMEA analyses components such as stoppers and drive motors were identified as having high Risk Priority Numbers (RPN), each reaching 512, indicating significant failure risks. The proposed IoT system employs HCSR-04 and MPU6050 sensors to accurately monitor the height and inclination of the equipment. Evaluation results show that the system effectively detects anomalies with minimal data deviation and a low data loss rate during a 10-day testing period. The implementation of this system significantly reduces workplace accident risks, improves maintenance efficiency, and supports digital transformation within the industrial environment. These findings demonstrate that the integration of HAZOP, FMEA, and IoT is effective for risk mitigation and can be replicated in other railway components. Moreover, this research opens new avenues for developing AI-based predictive systems and implementing digital twins as part of future smart maintenance strategies.
Co-Authors Adi, Farhan Indra Pratama Aisyah Amin, Aisyah Al Munawir Alloysius Vendhi Prasmoro, Alloysius Vendhi Alrasyid, Muhamad Aji Maulana Amin, Abu Ridho Al Andi Nuraliyah Aryafangger, Thomas Romyansen Davi, Faradilla Aulia Fadhlurrohman, Zain Ferdiansyah, Ikhsan Hamdani, Haris Hendrik Hidayat Iskandar Zulkarnaen Kumalasari, Ratih Nugroho, Ricko Puspo Oki Widhi Nugroho P, Diovan Dharma Paduloh Paduloh Perdiansyah Prakoso, Endah Ningrat Jati Putra, Achmad Mandala Raihan, Dwi Rizky Puti Rifda Ilahy Rosihan Sinaga, Zulkani Solihin Solihin Solihin, Solihin Solihin Spalanzani, Widya Turseno, Andi Widyantoro, Murwan