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All Journal Sosio e-kons Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Sugeng Haryono
Indraprasta Pgri University

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Analisis Kontribusi Pariwisata terhadap Pertumbuhan Ekonomi dan Dampaknya terhadap IPM di Pulau Jawa Sugeng Haryono; Nurlaela Nurlaela
Sosio e-Kons Vol. 18 No. 1 (2026): Sosio e-Kons
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/sosioekons.v18i1.2721

Abstract

Pariwisata dipulau di pulau jawa sangat luas dan banyak apakah dengan pariwisata mampu perekonomian masyarakat di pulau jawa, maka dari itu Tujuan Penelitian ini bertujuan untuk menganalisis sejauh mana sektor pariwisata berpengaruh terhadap pertumbuhan ekonomi dan Indeks Pembangunan Manusia (IPM) di Pulau Jawa periode 2020–2024. Variabel yang digunakan mencakup jumlah kunjungan wisatawan domestik dan mancanegara, tingkat hunian kamar hotel, dan kontribusi sektor akomodasi serta makan-minum terhadap Produk Domestik Regional Bruto (PDRB). Formulasi Model Penelitian ini menggunakan analisis regresi linier berganda dan regresi linier sederhana, Regresi linier berganda. Sektor pariwisata memiliki kontribusi signifikan terhadap pertumbuhan ekonomi di Pulau Jawa. Peningkatan jumlah kunjungan wisatawan, pendapatan dari sektor pariwisata, serta perkembangan infrastruktur wisata terbukti mampu mendorong peningkatan Produk Domestik Regional Bruto (PDRB) di berbagai provinsi di Pulau Jawa. Pertumbuhan ekonomi yang didorong oleh sektor pariwisata berdampak positif terhadap peningkatan Indeks Pembangunan Manusia (IPM).  
Sistem Pakar Untuk Identifikasi Kerusakan Sepeda Motor Menggunakan Metode Forward Chaining pada Bengkel AKC Workshop Erlan Ramadhan; Wanti Rahayu; Sugeng Haryono
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.824

Abstract

Rapid advancements in information technology have driven significant transformations across various sectors, including the automotive industry. One of the challenges faced by motorcycle repair shops is the diagnostic process, which is still performed manually and relies on the technician’s intuition, often leading to inefficiencies and potential errors in identifying issues. This study aims to develop an expert system based on the forward chaining method to facilitate a faster and more accurate initial diagnosis of motorcycle malfunctions. A case study was conducted at AKC Workshop, which faced similar challenges. This expert system was developed using a rule-based approach to mimic an expert’s thought process in diagnosing faults. Based on the test results, when the motorcycle exhibited symptoms G9, G10, G11, and G16, the system successfully identified the fault with a 100% match rate on rule 2 (R2), indicating that the motorcycle had a battery issue (weak battery). These results demonstrate that the developed expert system is capable of providing accurate diagnoses and has the potential to improve the efficiency and accuracy of services at motorcycle repair shops
Co-Authors Erlan Ramadhan Nurlaela Nurlaela Wanti Rahayu