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All Journal TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Jurnal Teknologi dan Komunikasi Pemerintahan
Pohan, Muhammad Aria Rajasa
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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Perbandingan Performa Logika Fuzzy Tipe-1 Dan Logika Fuzzy Tipe-2 Pada Sistem Pasteurisasi Susu Berbasis Mikrokontroler Taufiqurrahman, Dhiyaa Rifqi; Pohan, Muhammad Aria Rajasa
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol. 11 No. 1 (2023): TELEKONTRAN vol 11 no 1 April 2023
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/telekontran.v11i1.9686

Abstract

Milk is a perishable food product, to extend its shelf life, a heating technique called pasteurization can be applied. The purpose of pasteurization is to kill pathogenic bacteria that can be harmful to human health and minimize the growth of other spoilage microorganisms. This study aims to design a milk pasteurization system that can regulate temperature stably in the HTST pasteurization method using type-1 fuzzy logic and type-2 fuzzy logic. Type-2 fuzzy logic is a further development of type-1 fuzzy logic, with an additional dimension of membership function, allowing type-2 fuzzy logic systems to represent more flexible fuzzy sets and better represent uncertainty than type-1 fuzzy logic. Two tests were conducted to compare the performance of the two systems, one with no disturbance (noise) and other with disturbance. The result showed that in the test with no disturbance, type-2 fuzzy logic performed better than type-1 fuzzy logic in terms of maximum overshoot, while type-1 fuzzy logic performed better in terms of rise time. However, in the test with disturbance, type-2 fuzzy logic outperformed type-1 fuzzy logic at achieving rise time and settling time and was able to maintain or approach the temperature setpoint for a longer period than type-1 fuzzy logic.
Penerapan Jaringan Syaraf Tiruan untuk Meningkatkan Akurasi Sensor Arus PZEM-004T Putra, Reydho Trihandika; Pohan, Muhammad Aria Rajasa
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol. 12 No. 2 (2024): TELEKONTRAN vol 12 no 2 Oktober 2024
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/telekontran.v12i2.9687

Abstract

The PZEM-004T sensor is used for monitoring the electrical current consumed by electronic devices. However, the data generated by these sensors is still inaccurate and requires optimization. In this study, the Artificial Neural Network (ANN) method was used to optimize the PZEM-004T sensor system using ammeter data as a learning target. The ANN architecture used is 1-10-1. Matlab simulation results show that the architecture is very effective with an error difference of 0.0027. Then, ANN parameters such as weights and bias were applied to the system and succeeded in increasing accuracy with an average error difference of 0.0075. Even though there is a difference between the error values in the Matlab simulation and the Arduino implementation, the error values can still be minimized and the system can be used in several applications. Thus, the use of the PZEM-004T sensor optimization system with 1-10-1 architecture and ANN parameters on Arduino can be an effective solution in increasing the accuracy of electric current measurements.
Kajian Literatur Pemanfaatan Kecerdasan Buatan dalam Merespons Prioritas Pembangunan Kota Bandung Pohan, Muhammad Aria Rajasa
Jurnal Teknologi dan Komunikasi Pemerintahan Vol 5 No 2 (2023): Jurnal Teknologi dan Komunikasi Pemerintahan
Publisher : Program Studi Teknologi Rekayasa Informasi Pemerintahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33701/jtkp.v5i2.3620

Abstract

Kota Bandung menghadapi beragam tantangan dalam mewujudkan prioritas pembangunan yang meliputi optimalisasi infrastruktur, pelestarian lingkungan, pemerataan ekonomi, pembentukan masyarakat humanis, peningkatan pendidikan dan kesehatan, serta penguatan tata kelola pemerintahan. Kompleksitas permasalahan ini mendorong pencarian solusi inovatif, salah satunya adalah dengan menggunakan teknologi kecerdasan artificial atau sering disebut sebagai AI. Tujuan dari artikel ini adalah untuk mengkaji literatur terkait dengan pemanfaatan AI untuk memberikan solusi inovatif dalam merespons prioritas pembangunan kota Bandung. Penelitian ini dilakukan dengan pendekatan studi literatur dengan mengambil sumber-sumber utama dari jurnal ilmiah, laporan pemerintah, dan publikasi terkait AI dan pembangunan kota. Analisis literatur menunjukkan bahwa AI dapat digunakan untuk membantu agar pembangunan prioritas kota Bandung dapat diselesaikan secara lebih optimal. Implementasi AI dalam berbagai aspek pembangunan dapat memberikan manfaat yang signifikan, seperti pengambilan keputusan yang lebih akurat, penghematan waktu dan sumber daya, serta penyediaan layanan yang lebih baik kepada masyarakat. Namun, pemerintah juga harus memperhatikan tantangan dalam mengimplementasikan teknologi AI seperti privasi data, keandalan algoritma, integrasi teknologi dengan kebijakan pemerintah, dan juga partisipasi masyarakat. Maka sangat penting untuk melakukan kolaborasi lintas sektor dan kemitraan dalam mengoptimalkan potensi AI untuk meraih pembangunan yang berkelanjutan. Diharapkan, artikel ini dapat bermanfaat bagi para pembuat kebijakan, praktisi, dan akademisi yang tertarik pada pembangunan kota berkelanjutan. Kontribusi AI dalam merespons prioritas pembangunan kota Bandung dapat membuka jalan agar dapat diperoleh pengambilan keputusan dan solusi yang lebih inovatif dan lebih baik. Kata Kunci: Kecerdasan Buatan, Pemerintah Kota Bandung, Solusi Perkotaan, Mobilitas, Lingkungan, Pelayanan Publik.
A Time-Adaptive Ensemble Framework for Multi-Year University Ranking Prediction Integrating Outlier-Aware Scoring and Hybrid Feature Selection Pohan, Muhammad Aria Rajasa; Muiz, Bagus Abdul
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 7 No. 1 (2026): INJIISCOM: VOLUME 7, ISSUE 1, JUNE 2026 (ONLINE FIRST)
Publisher : Universitas Komputer Indonesia

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

Abstract

University ranking prediction requires adaptive models to capture temporal dynamics and handle data anomalies. This study develops a time-adaptive ensemble framework integrating outlier-aware scoring and hybrid feature selection. We collected data from Times Higher Education from 2011 to 2024, applying windowed outlier detection with clipping and masking, and using ANOVA F-tests, permutation importance, and SHAP values to select dynamic feature subsets. The framework trains linear moving-average, temporal Random Forest, and LSTM models, then ensembles their forecasts using dynamically optimized weights. Experimental results on rolling forecasts (2016–2024) demonstrate a mean rank deviation of 1.2 positions, Top-1000 classification accuracy of 0.96, and reduced MAE and RMSE compared to single-model baselines. SHAP-based analyses reveal evolving feature importance across time windows, highlighting the impact of changing indicators. The findings indicate that integrating outlier handling, dynamic feature selection, and ensemble learning enhances prediction robustness and interpretability. This framework can support strategic decision-making, policy formulation, and resource allocation in higher education
Co-Authors Muiz, Bagus Abdul Putra, Reydho Trihandika Taufiqurrahman, Dhiyaa Rifqi