Abstract:Abstract: Various specifications and prices for a laptop make potential buyers confused about choosing it. Information technology with its technological developments has produced a system that can provide alternative decisions…
isions for decision-making problems.This study aims to develop a system that can select the best laptop from several alternatives. There are 5 parameters used in determining the priority of alternative laptops. They are hard disk drive, RAM, processor, operating system and price.The alternative of the decision making system also consists of 5 alternatives.The method used in the MultiAttribute Decision Making (MADM) research is a combination of 2 methods. These methods are SAW and TOPSIS methods.The SAW method is used to optimize the parameter weighting process and the specific TOPSIS method to complete the alternative ranking process.This hybrid method can produce a more precise MADM process because it uses two methods, each of which has characteristics in accordance with the process specifications.
Keywords: laptop; multi attribute decision making; SAW; TOPSIS
Abstrak: Spesifikasi dan variasi harga yang beragam dari sebuah laptop membuat calon pembeli menjadi kebingungan dan ragu dalam memutuskan jenis atau tipe laptop mana yang akan dibeli. Teknologi informasi beserta dengan perkembangan teknologinya dapat menghasilkan suatu system untuk membantu memberikan alternative keputusan untuk suatu permasalahan pengambilan keputusan. Pengembangan sistem yang dapat memilih laptop yang tepat dari beberapa alternatif yang ditawarkan merupakan tujuan dari penelitian ini. Ada 5 parameter yang digunakan dalam menentukan prioritas alternatif laptop, yaitu hard disk drive, RAM, prosesor, sistem operasi dan harga. Laptop yang ditawarkan sebagai alternatif juga sebanyak 5 jenis. Metode yang digunakan padaMulti Attribute Decision Making (MADM) adalah kombinasi dari 2 metode, yaitu metode SAW dan TOPSIS. Metode SAW digunakan untuk mengoptimalkan proses pembobotan parameter dan metode TOPSIS spesifik untuk menyelesaikan proses perangkingan alternatif. Metode hybrid ini dapat menghasilkan suatu proses MADM yang lebih tepat karena menggunakan dua metode yang masing-masing mempunyai karakteristik sesuai dengan proses yang dilakukannya.
Kata kunci: laptop; multi-attribute decision making; SAW; TOPSIS
Abstract:Abstract: chili is a plant that many of us have encountered in Indonesia, usually used as a cooking spice and flavor enhancer in food. Chili includes members of the genus Capsicum. The high number of chili enthusiasts has…
s made the need for chili higher in Indonesia while chili is used in various fields such as medicine, cooking spices, and the food industry. Based on data from the Central Statistics Agency (BPS) in July the first 2019, retail red chili prices are set at Rp 62,099 per kilogram. This price increased by 21.76 percent when compared to the average price of chili in June 2019. In recent months the price of chili has increased very high, this is due to the reduced yields of chili farmers. Increasing the supply of chili is reduced and can not meet market needs. To control the soaring chili prices, the government is making important imports from India. The problem experienced by local farmers is the selection of superior chili seeds. The process of selecting chili seeds carried out so far by farmers is still by manual and traditional methods. Because this adds to the knowledge that is qualified to choose superior chili seeds based on certain criteria and which choices of chili seeds are suitable for cultivation. The process of cultivating chili seeds becomes more complete with maximum results. The technology used is using the Fuzzy Multi-Criteria Decision Making Method in determining superior chili seeds. From this method, it is expected to provide a solution to the chili farmers about the alternative selection of superior chili seeds.
Keywords: Chili Seeds; Decision Support System; Fuzzy Multi Criteria Decision Making
Abstrak: cabai merupakan tanaman yang banyak kita jumpai di Indonesia, biasanya digunakan sebagai bumbu masakan dan penguat rasa pada makanan. Cabai termasuk anggota genus Capsium. Banyaknya peminat cabai membuat kebutuhan akan cabai semakin tinggi di Indonesia cabai digunakan dalam berbagai bidang seperti obat-obatan, bumbu masakan dan industri makanan. Berdasarkan data Badan Pusat Statistik (BPS) pada bulan juli pecan pertama 2019, harga cabai merah eceran tercatat Rp 62.099 per kilogram. Harga tersebut mengalami kenaikan sebesar 21,76 persen jika dibandingkan rata-rata harga cabai pada juni 2019. Beberapa bulan terakhir ini harga cabai mengalami lonjakan yang sangat tinggi hal tersebut karena berkurangnya hasil panen para petani cabai. Sehingga pasokan cabai berkurang dan tidak bisa memenuhi kebutuhan pasar. Dalam rangka mengendalikan harga cabai yang melonjak tinggi pemerintah melakukan impor cabai dari India. Masalah yang dialami oleh para petani lokal yaitu pemilihan bibit cabai unggul. Proses pemilihan bibit cabai yang dilakukan selama ini oleh petani masih dengan cara manual dan tradisional. Hal tersebut mereka lakukan Karena kurangnya pengetahuan yang mumpuni untuk memilih bibit cabai unggul berdasarkan kriteria-kriteria tertentu dan beberapa pilihan alternatif bibit cabai mana yang cocok untuk dibudidayakan. Sehingga dengan demikian proses pembudidayaan bibit cabai menjadi lebih singkat waktunya dengan hasil yang maksimal. Teknologi yang digunakan yaitu menggunakan metode Fuzzy Multi Criteria Decision Making dalam menetukan bibit cabai unggul. Dari metode tersebut diharapkan dapat memberikan solusi kepada para petani cabai mengenai alternatif pemilihan bibit cabai unggul.
Kata Kunci: Bibit Cabai; Fuzzy Multi Criteria Decision Making; sistem pendukung keputusan
Abstract:This research aims to investigate the impact of transfer pricing, thin capitalization, and capital intensity on tax avoidance within the consumer goods industry. The study focuses on how these key financial strategies are…
e employed by companies to reduce their tax liabilities while navigating complex global tax environments. Transfer pricing allows companies to shift profits across jurisdictions by manipulating the prices of intra-company transactions, while thin capitalization—the practice of using excessive debt relative to equity—enables companies to maximize interest deductions and lower taxable income. Capital intensity, defined as the ratio of capital assets to sales, also plays a crucial role, as firms with significant physical assets can benefit from tax deductions through depreciation, further reducing taxable obligations. The sample used in this study was selected using purposive sampling, resulting in 23 companies that have complete financial reports and meet the specified criteria. By analyzing financial data and company reports, this research provides insights into sector-specific tax strategies and discusses the ethical implications, sustainability, and regulatory challenges associated with these practices in the consumer goods sector. The analysis shows that transfer pricing negatively and significantly affects tax avoidance, indicating that more aggressive transfer pricing practices may actually reduce tax avoidance activities. In contrast, thin capitalization and capital intensity do not show a significant impact on tax avoidance.
Abstract:This study was conducted to empirically examine the influence of intellectual capital and profitability on stock prices in banking sector companies in Indonesia. The independent variable of this research is intellectual…
capital which is presented by VAICTM (Value Added Intellectual Coefficient) which was developed by Pulic (1998). Then the dependent variable is stock price, and profitability, which is presented by ROA, as a moderating variable. The sample of this study was selected using the purposive sampling method, and there were 24 (twenty-four) banking companies (listed on the BEI) that met the criteria so that the sample of this study amounted to 120 samples. The study was analyzed using multiple regression analysis. The results of this study found that overall, VACA, VAHU, and STVA had a significant positive effect on stock prices. But only VACA and VAHU variables were able to be moderated by ROA.