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All Journal Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics EDUMATIC: Jurnal Pendidikan Informatika JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Nofiyati, Nofiyati
Jenderal Soedirman University
Computer Science & IT Education Electrical & Electronics Engineering

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Rancang Bangun Sistem Informasi Bank Sampah di Desa Paguyangan Lasmedi Afuan; Nofiyati Nofiyati; Nasichatul Umayah
Jurnal Pendidikan Informatika (EDUMATIC) Vol 5, No 1 (2021): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v5i1.3171

Abstract

Garbage is the residual material resulting from a production process, both industry and households. Based on Brebes district's statistical data, the Paguyangan sub-district is in fourth place with an average of 249.62 m3 of garbage per day. Paguyangan is one of the villages in the Paguyangan sub-district. Paguyangan has a garbage problem where people still have the habit of throwing garbage in the river and yards around the house. Based on this, the Paguyangan Village Hall plans to build a garbage bank to overcome the problem. A garbage bank managed activities such as recording savings transactions. This study conducted a web-based design of the Garbage Bank Information System (SIBS). SIBS is an information system used to help process garbage transactions at a garbage bank. The purpose of this SIBS is to facilitate officers and customers in processing services at the garbage bank. The methodology used in system development is the Waterfall method. SIBS development uses PHP as a programming language and MySql as the DBMS. The result of this research is a garbage bank information system. SIBS can be used in the management of garbage management transactions. Testing the system using Blackbox Testing and MOS. SIBS is easy to operate from the test results obtained.
Naive Bayes modification for intrusion detection system classification with zero probability Yogiek Indra Kurniawan; Fakhrur Razi; Nofiyati Nofiyati; Bangun Wijayanto; Muhammad Luthfi Hidayat
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2833

Abstract

One of the methods used in detecting the intrusion detection system is by implementing Naïve Bayes algorithm. However, Naïve Bayes has a problem when one of the probabilities is 0, it will cause inaccurate prediction, or even no prediction was found. This paper proposed two modifications for Naïve Bayes algorithm. The first modification eliminated the variable that has 0 probability and the second modification changed the multiplication operations to addition operations. This modification is only applied when the Naïve Bayes algorithm does not find any prediction results caused by zero probabilities. The results of this research show that the value of precision, recall, and accuracy in the modification made tends to increase and better than the original Naïve Bayes algorithm. The highest precision, recall, and accuracy are obtained from modification by changing the multiplication operation to the addition. Increasing precision can reach 4%, increasing recall reaches 2% and increasing accuracy reaches 2%.
Rancang Bangun Sistem Informasi Pengelolaan Pendadaran Menggunakan Framework Laravel lasmedi afuan; Nofiyati Nofiyati; Ahmad Fauzi Ridlwan
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 10, No 1 (2022)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (991.984 KB) | DOI: 10.26418/justin.v10i1.45678

Abstract

Salah satu kegiatan yang harus diikuti oleh mahasiswa tingkat akhir untuk memperoleh gelar sarjana S1 adalah Pendadaran. Pendadaran di Fakultas Teknik Universitas Jenderal Soedirman (UNSOED) terdiri dari beberapa proses yaitu pendaftaran, penjadwalan pendadaran, dan pengelolaan nilai. Permasalahan yang terjadi dalam pengelolaan proses pendadaran di Fakultas Teknik UNSOED adalah pengelolaan pendadaran pada proses–proses tersebut dilakukan dengan mencatat data dalam buku dan papan tulis. Hal ini menyebabkan proses pengelolaan pendadaran menjadi kurang efektif dan efisien, kekurangan tersebut akan mempersulit kinerja dari staff bapendik, dan dalam hal ini tentunya akan menghambat bagi dosen penguji dan mahasiswa. Untuk mengatasi permasalahan tersebut, penelitian ini telah mengembangkan sebuah sistem informasi pengelolaan pendadaran (SIPENDAR) di Fakultas Teknik UNSOED. Ada beberapa tahapan yang dilakukan dalam pengembangan SIPENDAR yaitu pengumpulan data, analisis dan perancangan, tahapan pengembangan SIPENDAR, dan pengujian sistem informasi. Pengembangan SIPENDAR menggunakan framework Laravel dan menggunakan MySQL sebagai Database Management System. Pengujian dilakukan menggunakan pengujian blackbox dan Mean Opinion Score. Dari hasil pengembangan dan pengujian dapat disimpulkan bahwa SIPENDAR dapat digunakan untuk mempermudah dalam proses pengelolaan pendadaran di Fakultas Teknik UNSOED.
Seq2Seq encoder–decoder with adaptive metaheuristic for scheduling optimization Arief Kelik Nugroho; Nurul Hidayat; Nofiyati Nofiyati
International Journal of Advances in Intelligent Informatics Vol 12, No 3 (2026): August 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v12i3.2224

Abstract

The Job Shop Scheduling Problem (JSSP) is a combinatorial optimization problem that is NP-hard and highly complex, particularly in modern manufacturing environments associated with industry. Conventional metaheuristic methods such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are capable of generating solutions in a relatively short time; however, they often face limitations in solution quality due to premature convergence and limited adaptability to dynamic problem conditions. In contrast, deep learning approaches such as Sequence-to-Sequence (Seq2Seq) offer strong representational capabilities for modeling operation sequences, although they still encounter challenges related to training stability and generalization. This study proposes a hybrid approach that integrates a Seq2Seq encoder–decoder architecture with an adaptive metaheuristic mechanism to enhance scheduling optimization performance. The Seq2Seq model is utilized to learn underlying patterns in operation sequences, while the adaptive mechanism dynamically adjusts search parameters based on makespan evaluation. The experiments are conducted using datasets from the OR-Library, specifically the 10×10 and 15×15 scenarios, to evaluate the performance and scalability of the proposed method. The experimental results demonstrate that the Seq2Seq + adaptive metaheuristic approach consistently produces lower makespan values compared to GA and PSO. For the 10×10 dataset, the proposed method achieves a makespan of 932, outperforming GA (1095) and PSO (1047). Similarly, for the 15×15 dataset, it attains a makespan of 1050, which is better than GA (1250) and PSO (1200). Although the proposed approach requires slightly longer computational time, the improvement in solution quality indicates that it effectively balances exploration and exploitation.
Co-Authors Ahmad Fauzi Ridlwan Arief Kelik Nugroho Bangun Wijayanto Fakhrur Razi Hidayat, Nurul Kurniawan, Yogiek Indra Lasmedi Afuan Muhammad Luthfi Hidayat Nasichatul Umayah